Understanding Arctic surface temperature differences in reanalyses

NASA Astrophysics Data System (ADS)

Cullather, R. I.; Zhao, B.; Shuman, C. A.; Nowicki, S.

2017-12-01

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. For example, the 1980-2009 mean surface air temperature for the north polar cap (70°N-90°N) among global reanalyses span a range of 2.4 K, which approximates the average warming trend from these reanalyses over the 30-year period of 2.1 K. Understanding these differences requires evaluation over the three principal surface domains of the Arctic: glaciated land, the unglaciated terrestrial surface, and sea ice/ocean. An examination is conducted of contemporary global reanalyses of the ECMWF Interim project, NASA MERRA, MERRA-2, JRA-55, and NOAA CFSR using available in situ data and assessments of the surface energy budget. Overly-simplistic representations of the Greenland Ice Sheet surface are found to be associated with local warm air temperature biases in winter. A review of progress made in the development of the MERRA-2 land-ice representation is presented. Large uncertainty is also found in temperatures over the Arctic tundra and boreal forest zone. But a key focus of temperature differences for northern high latitudes is the Arctic Ocean. Near-surface air temperature differences over the Arctic Ocean are found to be related to discrepancies in sea ice and sea surface temperature boundary data, which are severely compromised in current reanalyses. Issues with the modeled representation of sea ice cover are an additional factor in reanalysis temperature trends. Differences in the representation of the surface energy budget among the various reanalyses are also reviewed.

Understanding Arctic Surface Temperature Differences in Reanalyses

NASA Technical Reports Server (NTRS)

Cullather, Richard; Zhao, Bin; Shuman, Christopher; Nowicki, Sophie

2017-01-01

Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. For example, the 1980-2009 mean surface air temperature for the north polar cap (70ÂdegN-90ÂdegN) among global reanalyses span a range of 2.4 K, which approximates the average warming trend from these reanalyses over the 30-year period of 2.1 K. Understanding these differences requires evaluation over the three principal surface domains of the Arctic: glaciated land, the unglaciated terrestrial surface, and sea ice/ocean. An examination is conducted of contemporary global reanalyses of the ECMWF Interim project, NASA MERRA, MERRA-2, JRA-55, and NOAA CFSR using available in situ data and assessments of the surface energy budget. Overly-simplistic representations of the Greenland Ice Sheet surface are found to be associated with local warm air temperature biases in winter. A review of progress made in the development of the MERRA-2 land-ice representation is presented. Large uncertainty is also found in temperatures over the Arctic tundra and boreal forest zone. But a key focus of temperature differences for northern high latitudes is the Arctic Ocean. Near-surface air temperature differences over the Arctic Ocean are found to be related to discrepancies in sea ice and sea surface temperature boundary data, which are severely compromised in current reanalyses. Issues with the modeled representation of sea ice cover are an additional factor in reanalysis temperature trends. Differences in the representation of the surface energy budget among the various reanalyses are also reviewed.

Updating representation of land surface-atmosphere feedbacks in airborne campaign modeling analysis

NASA Astrophysics Data System (ADS)

Huang, M.; Carmichael, G. R.; Crawford, J. H.; Chan, S.; Xu, X.; Fisher, J. A.

2017-12-01

An updated modeling system to support airborne field campaigns is being built at NASA Ames Pleiades, with focus on adjusting the representation of land surface-atmosphere feedbacks. The main updates, referring to previous experiences with ARCTAS-CARB and CalNex in the western US to study air pollution inflows, include: 1) migrating the WRF (Weather Research and Forecasting) coupled land surface model from Noah to improved/more complex models especially Noah-MP and Rapid Update Cycle; 2) enabling the WRF land initialization with suitably spun-up land model output; 3) incorporating satellite land cover, vegetation dynamics, and soil moisture data (i.e., assimilating Soil Moisture Active Passive data using the ensemble Kalman filter approach) into WRF. Examples are given of comparing the model fields with available aircraft observations during spring-summer 2016 field campaigns taken place at the eastern side of continents (KORUS-AQ in South Korea and ACT-America in the eastern US), the air pollution export regions. Under fair weather and stormy conditions, air pollution vertical distributions and column amounts, as well as the impact from land surface, are compared. These help identify challenges and opportunities for LEO/GEO satellite remote sensing and modeling of air quality in the northern hemisphere. Finally, we briefly show applications of this system on simulating Australian conditions, which would explore the needs for further development of the observing system in the southern hemisphere and inform the Clean Air and Urban Landscapes (https://www.nespurban.edu.au) modelers.

Using a GCM analogue model to investigate the potential for Amazonian forest dieback

NASA Astrophysics Data System (ADS)

Huntingford, C.; Harris, P. P.; Gedney, N.; Cox, P. M.; Betts, R. A.; Marengo, J. A.; Gash, J. H. C.

A combined GCM analogue model and GCM land surface representation is used to investigate the influences of climatology and land surface parameterisation on modelled Amazonian vegetation change. This modelling structure (called IMOGEN) captures the main features of the changes in surface climate as estimated by a GCM with enhanced atmospheric greenhouse gas concentrations. Advantage is taken of IMOGEN's computational speed which allows multiple simulations to be carried out to assess the robustness of the GCM results. The timing of forest dieback is found to be sensitive to the initial ``pre-industrial'' climate, as well as uncertainties in the representation of land-atmosphere CO2 exchange. Changing from a Q10 form for plant dark and maintanence respiration (as used in the coupled GCM runs) to a respiration proportional to maximum photosynthesis, reduces the biomass lost from Amazonia in the 21st century. Replacing the GCM control climate (which has about 25% too little rain in the annual mean over Amazonia) with an observed climatology increases the CO2 concentration at which rainfall drops to critical levels, and thereby further delays the dieback. On the other hand, calibration of the canopy photosynthesis model against Amazonian flux data tends to lead to earlier forest dieback. Further advances are required in both GCM rainfall simulation and land-surface process representation before a clearer picture will emerge on the timing of possible Amazonian forest dieback. However, it seems likely that these advances will overall lead to projections of later forest dieback as GCM control climates become more realistic.

The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models

NASA Astrophysics Data System (ADS)

Yang, Z.

2011-12-01

I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling.

Validation of Land-Surface Mosaic Heterogeneity in the GEOS DAS

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Molod, Andrea; Houser, Paul R.; Schubert, Siegfried

1999-01-01

The Mosaic Land-surface Model (LSM) has been included into the current GEOS Data Assimilation System (DAS). The LSM uses a more advanced representation of physical processes than previous versions of the GEOS DAS, including the representation of sub-grid heterogeneity of the land-surface through the Mosaic approach. As a first approximation, Mosaic assumes that all similar surface types within a grid-cell can be lumped together as a single'tile'. Within one GCM grid-cell, there might be 1 - 5 different tiles or surface types. All tiles are subjected to the grid-scale forcing (radiation, air temperature and specific humidity, and precipitation), and the sub-grid variability is a function of the tile characteristics. In this paper, we validate the LSM sub-grid scale variability (tiles) using a variety of surface observing stations from the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) Program. One of the primary goals of SGP ARM is to study the variability of atmospheric radiation within a G,CM grid-cell. Enough surface data has been collected by ARM to extend this goal to sub-grid variability of the land-surface energy and water budgets. The time period of this study is the Summer of 1998 (June I - September 1). The ARM site data consists of surface meteorology, energy flux (eddy correlation and bowen ratio), soil water observations spread over an area similar to the size of a G-CM grid-cell. Various ARM stations are described as wheat and alfalfa crops, pasture and range land. The LSM tiles considered at the grid-space (2 x 2.5) nearest the ARM site include, grassland, deciduous forests, bare soil and dwarf trees. Surface energy and water balances for each tile type are compared with observations. Furthermore, we will discuss the land-surface sub-grid variability of both the ARM observations and the DAS.

Variable strategy model of the human operator

NASA Astrophysics Data System (ADS)

Phillips, John Michael

Human operators often employ discontinuous or "bang-bang" control strategies when performing large-amplitude acquisition tasks. The current study applies Variable Structure Control (VSC) techniques to model human operator behavior during acquisition tasks. The result is a coupled, multi-input model replicating the discontinuous control strategy. In the VSC formulation, a switching surface is the mathematical representation of the operator's control strategy. The performance of the Variable Strategy Model (VSM) is evaluated by considering several examples, including the longitudinal control of an aircraft during the visual landing task. The aircraft landing task becomes an acquisition maneuver whenever large initial offsets occur. Several different strategies are explored in the VSM formulation for the aircraft landing task. First, a switching surface is constructed from literal interpretations of pilot training literature. This approach yields a mathematical representation of how a pilot is trained to fly a generic aircraft. This switching surface is shown to bound the trajectory response of a group of pilots performing an offset landing task in an aircraft simulator study. Next, front-side and back-side landing strategies are compared. A back-side landing strategy is found to be capable of landing an aircraft flying on either the front side or back side of the power curve. However, the front-side landing strategy is found to be insufficient for landing an aircraft flying on the back side. Finally, a more refined landing strategy is developed that takes into the account the specific aircraft's dynamic characteristics. The refined strategy is translated back into terminology similar to the existing pilot training literature.

A novel representation of groundwater dynamics in large-scale land surface modelling

NASA Astrophysics Data System (ADS)

Rahman, Mostaquimur; Rosolem, Rafael; Kollet, Stefan

2017-04-01

Land surface processes are connected to groundwater dynamics via shallow soil moisture. For example, groundwater affects evapotranspiration (by influencing the variability of soil moisture) and runoff generation mechanisms. However, contemporary Land Surface Models (LSM) generally consider isolated soil columns and free drainage lower boundary condition for simulating hydrology. This is mainly due to the fact that incorporating detailed groundwater dynamics in LSMs usually requires considerable computing resources, especially for large-scale applications (e.g., continental to global). Yet, these simplifications undermine the potential effect of groundwater dynamics on land surface mass and energy fluxes. In this study, we present a novel approach of representing high-resolution groundwater dynamics in LSMs that is computationally efficient for large-scale applications. This new parameterization is incorporated in the Joint UK Land Environment Simulator (JULES) and tested at the continental-scale.

Simulating the Effects of Irrigation over the U.S. in a Land Surface Model Based on Satellite Derived Agricultural Data

NASA Technical Reports Server (NTRS)

Ozdogan, Mutlu; Rodell, Matthew; Beaudoing, Hiroko Kato; Toll, David L.

2009-01-01

A novel method is introduced for integrating satellite derived irrigation data and high-resolution crop type information into a land surface model (LSM). The objective is to improve the simulation of land surface states and fluxes through better representation of agricultural land use. Ultimately, this scheme could enable numerical weather prediction (NWP) models to capture land-atmosphere feedbacks in managed lands more accurately and thus improve forecast skill. Here we show that application of the new irrigation scheme over the continental US significantly influences the surface water and energy balances by modulating the partitioning of water between the surface and the atmosphere. In our experiment, irrigation caused a 12% increase in evapotranspiration (QLE) and an equivalent reduction in the sensible heat flux (QH) averaged over all irrigated areas in the continental US during the 2003 growing season. Local effects were more extreme: irrigation shifted more than 100 W/m from QH to QLE in many locations in California, eastern Idaho, southern Washington, and southern Colorado during peak crop growth. In these cases, the changes in ground heat flux (QG), net radiation (RNET), evapotranspiration (ET), runoff (R), and soil moisture (SM) were more than 3 W/m(sup 2), 20 W/m(sup 2), 5 mm/day, 0.3 mm/day, and 100 mm, respectively. These results are highly relevant to continental- to global-scale water and energy cycle studies that, to date, have struggled to quantify the effects of agricultural management practices such as irrigation. Based on the results presented here, we expect that better representation of managed lands will lead to improved weather and climate forecasting skill when the new irrigation scheme is incorporated into NWP models such as NOAA's Global Forecast System (GFS).

Representing agriculture in Earth System Models: Approaches and priorities for development

NASA Astrophysics Data System (ADS)

McDermid, S. S.; Mearns, L. O.; Ruane, A. C.

2017-09-01

Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land-use and intensive in management, owing to 20th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture-climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate-crop models that capture dynamic feedbacks. We highlight the robust agriculture-climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land-use-climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Last, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate-surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.

Intercomparison and Uncertainty Assessment of Nine Evapotranspiration Estimates Over South America

NASA Astrophysics Data System (ADS)

Sörensson, Anna A.; Ruscica, Romina C.

2018-04-01

This study examines the uncertainties and the representations of anomalies of a set of evapotranspiration products over climatologically distinct regions of South America. The products, coming from land surface models, reanalysis, and remote sensing, are chosen from sources that are readily available to the community of users. The results show that the spatial patterns of maximum uncertainty differ among metrics, with dry regions showing maximum relative uncertainties of annual mean evapotranspiration, while energy-limited regions present maximum uncertainties in the representation of the annual cycle and monsoon regions in the representation of anomalous conditions. Furthermore, it is found that land surface models driven by observed atmospheric fields detect meteorological and agricultural droughts in dry regions unequivocally. The remote sensing products employed do not distinguish all agricultural droughts and this could be attributed to the forcing net radiation. The study also highlights important characteristics of individual data sets and recommends users to include assessments of sensitivity to evapotranspiration data sets in their studies, depending on region and nature of study to be conducted.

Land surface sensitivity of monsoon depressions formed over Bay of Bengal using improved high-resolution land state

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.; Mohanty, U. C.; Rai, D.; Baisya, H.; Pandey, P. C.

2017-12-01

Monsoon depressions (MDs) constitute a large fraction of the total rainfall during the Indian summer monsoon season. In this study, the impact of high-resolution land state is addressed by assessing the evolution of inland moving depressions formed over the Bay of Bengal using a mesoscale modeling system. Improved land state is generated using High Resolution Land Data Assimilation System employing Noah-MP land-surface model. Verification of soil moisture using Soil Moisture and Ocean Salinity (SMOS) and soil temperature using tower observations demonstrate promising results. Incorporating high-resolution land state yielded least root mean squared errors with higher correlation coefficient in the surface and mid tropospheric parameters. Rainfall forecasts reveal that simulations are spatially and quantitatively in accordance with observations and provide better skill scores. The improved land surface characteristics have brought about the realistic evolution of surface, mid-tropospheric parameters, vorticity and moist static energy that facilitates the accurate MDs dynamics in the model. Composite moisture budget analysis reveals that the surface evaporation is negligible compared to moisture flux convergence of water vapor, which supplies moisture into the MDs over land. The temporal relationship between rainfall and moisture convergence show high correlation, suggesting a realistic representation of land state help restructure the moisture inflow into the system through rainfall-moisture convergence feedback.

Effects of Topography-based Subgrid Structures on Land Surface Modeling

NASA Astrophysics Data System (ADS)

Tesfa, T. K.; Ruby, L.; Brunke, M.; Thornton, P. E.; Zeng, X.; Ghan, S. J.

2017-12-01

Topography has major control on land surface processes through its influence on atmospheric forcing, soil and vegetation properties, network topology and drainage area. Consequently, accurate climate and land surface simulations in mountainous regions cannot be achieved without considering the effects of topographic spatial heterogeneity. To test a computationally less expensive hyper-resolution land surface modeling approach, we developed topography-based landunits within a hierarchical subgrid spatial structure to improve representation of land surface processes in the ACME Land Model (ALM) with minimal increase in computational demand, while improving the ability to capture the spatial heterogeneity of atmospheric forcing and land cover influenced by topography. This study focuses on evaluation of the impacts of the new spatial structures on modeling land surface processes. As a first step, we compare ALM simulations with and without subgrid topography and driven by grid cell mean atmospheric forcing to isolate the impacts of the subgrid topography on the simulated land surface states and fluxes. Recognizing that subgrid topography also has important effects on atmospheric processes that control temperature, radiation, and precipitation, methods are being developed to downscale atmospheric forcings. Hence in the second step, the impacts of the subgrid topographic structure on land surface modeling will be evaluated by including spatial downscaling of the atmospheric forcings. Preliminary results on the atmospheric downscaling and the effects of the new spatial structures on the ALM simulations will be presented.

Simulating crop phenology in the Community Land Model and its impact on energy and carbon fluxes

USDA-ARS?s Scientific Manuscript database

A reasonable representation of crop phenology and biophysical processes in land surface models is necessary to accurately simulate energy, water and carbon budgets at the field, regional, and global scales. However, the evaluation of crop models that can be coupled to earth system models is relative...

High Resolution Land Surface Modeling with the next generation Land Data Assimilation Systems

NASA Astrophysics Data System (ADS)

Kumar, S. V.; Eylander, J.; Peters-Lidard, C.

2005-12-01

Knowledge of land surface processes is important to many real-world applications such as agricultural production, water resources management, and flood predication. The Air Force Weather Agency (AFWA) has provided the USDA and other customers global soil moisture and temperature data for the past 30 years using the agrometeorological data assimilation model (now called AGRMET), merging atmospheric data. Further, accurate initialization of land surface conditions has been shown to greatly influence and improve weather forecast model and seasonal-to-interannual climate predictions. The AFWA AGRMET model exploits real time precipitation observations and analyses, global forecast model and satellite data to generate global estimates of soil moisture, soil temperature and other land surface states at 48km spatial resolution. However, to truly address the land surface initialization and climate prediction problem, and to mitigate the errors introduced by the differences in spatial scales of models, representations of land surface conditions need to be developed at the same fine scales such as that of cloud resolving models. NASA's Goddard Space Flight Center has developed an offline land data assimilation system known as the Land Information System (LIS) capable of modeling land atmosphere interactions at spatial resolutions as fine as 1km. LIS provides a software architecture that integrates the use of the state of the art land surface models, data assimilation techniques, and high performance computing and data management tools. LIS also employs many high resolution surface parameters such as the NASA Earth Observing System (EOS)-era products. In this study we describe the development of a next generation high resolution land surface modeling and data assimilation system, combining the capabilities of LIS and AGRMET. We investigate the influence of high resolution land surface data and observations on the land surface conditions by comparing with the operational AGRMET outputs.

Characterization of Air and Ground Temperature Relationships within the CMIP5 Historical and Future Climate Simulations

NASA Astrophysics Data System (ADS)

García-García, A.; Cuesta-Valero, F. J.; Beltrami, H.; Smerdon, J. E.

2017-12-01

The relationships between air and ground surface temperatures across North America are examined in the historical and future projection simulations from 32 General Circulation Models (GCMs) included in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The covariability between surface air (2 m) and ground surface temperatures (10 cm) is affected by simulated snow cover, vegetation cover and precipitation through changes in soil moisture at the surface. At high latitudes, the differences between air and ground surface temperatures, for all CMIP5 simulations, are related to the insulating effect of snow cover and soil freezing phenomena. At low latitudes, the differences between the two temperatures, for the majority of simulations, are inversely proportional to leaf area index and precipitation, likely due to induced-changes in latent and sensible heat fluxes at the ground surface. Our results show that the transport of energy across the air-ground interface differs from observations and among GCM simulations, by amounts that depend on the components of the land-surface models that they include. The large variability among GCMs and the marked dependency of the results on the choice of the land-surface model, illustrate the need for improving the representation of processes controlling the coupling of the lower atmosphere and the land surface in GCMs as a means of reducing the variability in their representation of weather and climate phenomena, with potentially important implications for positive climate feedbacks such as permafrost and soil carbon stability.

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

Treesearch

Andrew D. Richardson; Ryan S. Anderson; M. Altaf Arain; Alan G. Barr; Gil Bohrer; Guangsheng Chen; Jing M. Chen; Philippe Ciais; Kenneth J. David; Ankur R. Desai; Michael C. Dietze; Danilo Dragoni; Steven R. Garrity; Christopher M. Gough; Robert Grant; David Hollinger; Hank A. Margolis; Harry McCaughey; Mirco Migliavacca; Russel K. Monson; J. William Munger; Benjamin Poulter; Brett M. Raczka; Daniel M. Ricciuto; Alok K. Sahoo; Kevin Schaefer; Hanqin Tian; Rodrigo Vargas; Hans Verbeeck; Jingfeng Xiao; Yongkang Xue

2012-01-01

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO

Seasonal-to-Interannual Precipitation Variability and Predictability in a Coupled Land-Atmosphere System

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, M. J.; Heiser, M.

1998-01-01

In an earlier GCM study, we showed that interactive land surface processes generally contribute more to continental precipitation variance than do variable sea surface temperatures (SSTs). A new study extends this result through an analysis of 16-member ensembles of multi-decade GCM simulations. We can now show that in many regions, although land processes determine the amplitude of the interannual precipitation anomalies, variable SSTs nevertheless control their timing. The GCM data can be processed into indices that describe geographical variations in (1) the potential for seasonal-to-interannual prediction, and (2) the extent to which the predictability relies on the proper representation of land-atmosphere feedback.

Assessment of Irrigation Physics in a Land Surface Modeling Framework Using Non-Traditional and Human-Practice Datasets

NASA Technical Reports Server (NTRS)

Lawston, Patricia M.; Santanello, Joseph A.; Rodell, Matthew; Franz, Trenton E.

2017-01-01

Irrigation increases soil moisture, which in turn controls water and energy fluxes from the land surface to the10 planetary boundary layer and determines plant stress and productivity. Therefore, developing a realistic representation of irrigation is critical to understanding land-atmosphere interactions in agricultural areas. Irrigation parameterizations are becoming more common in land surface models and are growing in sophistication, but there is difficulty in assessing the realism of these schemes, due to limited observations (e.g., soil moisture, evapotranspiration) and scant reporting of irrigation timing and quantity. This study uses the Noah land surface model run at high resolution within NASAs Land15 Information System to assess the physics of a sprinkler irrigation simulation scheme and model sensitivity to choice of irrigation intensity and greenness fraction datasets over a small, high resolution domain in Nebraska. Differences between experiments are small at the interannual scale but become more apparent at seasonal and daily time scales. In addition, this study uses point and gridded soil moisture observations from fixed and roving Cosmic Ray Neutron Probes and co-located human practice data to evaluate the realism of irrigation amounts and soil moisture impacts simulated by the model. Results20 show that field-scale heterogeneity resulting from the individual actions of farmers is not captured by the model and the amount of irrigation applied by the model exceeds that applied at the two irrigated fields. However, the seasonal timing of irrigation and soil moisture contrasts between irrigated and non-irrigated areas are simulated well by the model. Overall, the results underscore the necessity of both high-quality meteorological forcing data and proper representation of irrigation foraccurate simulation of water and energy states and fluxes over cropland.

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

Modelling evapotranspiration during precipitation deficits: Identifying critical processes in a land surface model

DOE PAGES

Ukkola, Anna M.; Pitman, Andy J.; Decker, Mark; ...

2016-06-21

Surface fluxes from land surface models (LSMs) have traditionally been evaluated against monthly, seasonal or annual mean states. The limited ability of LSMs to reproduce observed evaporative fluxes under water-stressed conditions has been previously noted, but very few studies have systematically evaluated these models during rainfall deficits. We evaluated latent heat fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLE) LSM across 20 flux tower sites at sub-annual to inter-annual timescales, in particular focusing on model performance during seasonal-scale rainfall deficits. The importance of key model processes in capturing the latent heat flux was explored by employing alternative representations of hydrology, leafmore » area index, soil properties and stomatal conductance. We found that the representation of hydrological processes was critical for capturing observed declines in latent heat during rainfall deficits. By contrast, the effects of soil properties, LAI and stomatal conductance were highly site-specific. Whilst the standard model performs reasonably well at annual scales as measured by common metrics, it grossly underestimates latent heat during rainfall deficits. A new version of CABLE, with a more physically consistent representation of hydrology, captures the variation in the latent heat flux during seasonal-scale rainfall deficits better than earlier versions, but remaining biases point to future research needs. Lastly, our results highlight the importance of evaluating LSMs under water-stressed conditions and across multiple plant functional types and climate regimes.« less

A simple hydrologically based model of land surface water and energy fluxes for general circulation models

NASA Technical Reports Server (NTRS)

Liang, XU; Lettenmaier, Dennis P.; Wood, Eric F.; Burges, Stephen J.

1994-01-01

A generalization of the single soil layer variable infiltration capacity (VIC) land surface hydrological model previously implemented in the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model (GCM) is described. The new model is comprised of a two-layer characterization of the soil column, and uses an aerodynamic representation of the latent and sensible heat fluxes at the land surface. The infiltration algorithm for the upper layer is essentially the same as for the single layer VIC model, while the lower layer drainage formulation is of the form previously implemented in the Max-Planck-Institut GCM. The model partitions the area of interest (e.g., grid cell) into multiple land surface cover types; for each land cover type the fraction of roots in the upper and lower zone is specified. Evapotranspiration consists of three components: canopy evaporation, evaporation from bare soils, and transpiration, which is represented using a canopy and architectural resistance formulation. Once the latent heat flux has been computed, the surface energy balance is iterated to solve for the land surface temperature at each time step. The model was tested using long-term hydrologic and climatological data for Kings Creek, Kansas to estimate and validate the hydrological parameters, and surface flux data from three First International Satellite Land Surface Climatology Project Field Experiment (FIFE) intensive field campaigns in the summer-fall of 1987 to validate the surface energy fluxes.

L-band Microwave Remote Sensing and Land Data Assimilation Improve the Representation of Prestorm Soil Moisture Conditions for Hydrologic Forecasting

NASA Technical Reports Server (NTRS)

Crow, W. T.; Chen, F.; Reichle, R. H.; Liu, Q.

2017-01-01

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events.

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting.

PubMed

Crow, W T; Chen, F; Reichle, R H; Liu, Q

2017-06-16

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events.

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting

PubMed Central

Crow, W.T.; Chen, F.; Reichle, R.H.; Liu, Q.

2018-01-01

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i.e., total stream flow divided by total rainfall accumulation in depth units) and pre-storm surface soil moisture estimates from a range of surface soil moisture data products. Results demonstrate that both satellite-based, L-band microwave radiometry and the application of land data assimilation techniques have significantly improved the utility of surface soil moisture data sets for forecasting stream flow response to future rainfall events. PMID:29657342

Large-Eddy Atmosphere-Land-Surface Modelling over Heterogeneous Surfaces: Model Development and Comparison with Measurements

NASA Astrophysics Data System (ADS)

Shao, Yaping; Liu, Shaofeng; Schween, Jan H.; Crewell, Susanne

2013-08-01

A model is developed for the large-eddy simulation (LES) of heterogeneous atmosphere and land-surface processes. This couples a LES model with a land-surface scheme. New developments are made to the land-surface scheme to ensure the adequate representation of atmosphere-land-surface transfers on the large-eddy scale. These include, (1) a multi-layer canopy scheme; (2) a method for flux estimates consistent with the large-eddy subgrid closure; and (3) an appropriate soil-layer configuration. The model is then applied to a heterogeneous region with 60-m horizontal resolution and the results are compared with ground-based and airborne measurements. The simulated sensible and latent heat fluxes are found to agree well with the eddy-correlation measurements. Good agreement is also found in the modelled and observed net radiation, ground heat flux, soil temperature and moisture. Based on the model results, we study the patterns of the sensible and latent heat fluxes, how such patterns come into existence, and how large eddies propagate and destroy land-surface signals in the atmosphere. Near the surface, the flux and land-use patterns are found to be closely correlated. In the lower boundary layer, small eddies bearing land-surface signals organize and develop into larger eddies, which carry the signals to considerably higher levels. As a result, the instantaneous flux patterns appear to be unrelated to the land-use patterns, but on average, the correlation between them is significant and persistent up to about 650 m. For a given land-surface type, the scatter of the fluxes amounts to several hundred W { m }^{-2}, due to (1) large-eddy randomness; (2) rapid large-eddy and surface feedback; and (3) local advection related to surface heterogeneity.

Incorporating dynamic root growth enhances the performance of Noah-MP at two contrasting winter wheat field sites

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Ingwersen, Joachim; Wizemann, Hans-Dieter; Warrach-Sagi, Kirsten; Attinger, Sabine; Streck, Thilo; Wulmeyer, Volker

2014-05-01

Interactions between the soil, the vegetation, and the atmospheric boundary layer require close attention when predicting water fluxes in the hydrogeosystem, agricultural systems, weather and climate. However, land-surface schemes used in large scale models continue to show deficits in consistently simulating fluxes of water and energy from the subsurface through vegetation layers to the atmosphere. In this study, the multi-physics version of the Noah land-surface model (Noah-MP) was used to identify the processes, which are most crucial for a simultaneous simulation of water and heat fluxes between land-surface and the lower atmosphere. Comprehensive field data sets of latent and sensible heat fluxes, ground heat flux, soil moisture, and leaf area index from two contrasting field sites in South-West Germany are used to assess the accuracy of simulations. It is shown that an adequate representation of vegetation-related processes is the most important control for a consistent simulation of energy and water fluxes in the soil-plant-atmosphere system. In particular, using a newly implemented sub-module to simulate root growth dynamics has enhanced the performance of Noah-MP at both field sites. We conclude that further advances in the representation of leaf area dynamics and root/soil moisture interactions are the most promising starting points for improving the simulation of feedbacks between the sub-soil, land-surface and atmosphere in fully-coupled hydrological and atmospheric models.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Dong, Xiquan; Kennedy, Aaron D.

2011-01-01

The degree of coupling between the land surface and PBL in NWP models remains largely undiagnosed due to the complex interactions and feedbacks present across a range of scales. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with observations during the summers of 2006/7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which enables a suite of PBL and land surface model (LSM) options along provides a flexible and high-resolution representation and initialization of land surface physics and states. This coupling is one component of a larger project to develop a NASA-Unified WRF (NU-WRF) system. A range of diagnostics exploring the feedbacks between soil moisture and precipitation are examined for the dry/wet extremes, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture.

The impact of anthropogenic land use and land cover change on regional climate extremes.

PubMed

Findell, Kirsten L; Berg, Alexis; Gentine, Pierre; Krasting, John P; Lintner, Benjamin R; Malyshev, Sergey; Santanello, Joseph A; Shevliakova, Elena

2017-10-20

Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.

Effect of water table dynamics on land surface hydrologic memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui; Famiglietti, James S.

2010-11-01

The representation of groundwater dynamics in land surface models has received considerable attention in recent years. Most studies have found that soil moisture increases after adding a groundwater component because of the additional supply of water to the root zone. However, the effect of groundwater on land surface hydrologic memory (persistence) has not been explored thoroughly. In this study we investigate the effect of water table dynamics on National Center for Atmospheric Research Community Land Model hydrologic simulations in terms of land surface hydrologic memory. Unlike soil water or evapotranspiration, results show that land surface hydrologic memory does not always increase after adding a groundwater component. In regions where the water table level is intermediate, land surface hydrologic memory can even decrease, which occurs when soil moisture and capillary rise from groundwater are not in phase with each other. Further, we explore the hypothesis that in addition to atmospheric forcing, groundwater variations may also play an important role in affecting land surface hydrologic memory. Analyses show that feedbacks of groundwater on land surface hydrologic memory can be positive, negative, or neutral, depending on water table dynamics. In regions where the water table is shallow, the damping process of soil moisture variations by groundwater is not significant, and soil moisture variations are mostly controlled by random noise from atmospheric forcing. In contrast, in regions where the water table is very deep, capillary fluxes from groundwater are small, having limited potential to affect soil moisture variations. Therefore, a positive feedback of groundwater to land surface hydrologic memory is observed in a transition zone between deep and shallow water tables, where capillary fluxes act as a buffer by reducing high-frequency soil moisture variations resulting in longer land surface hydrologic memory.

Project M: Scale Model of Lunar Landing Site of Apollo 17: Focus on Lighting Conditions and Analysis

NASA Technical Reports Server (NTRS)

Vanik, Christopher S.; Crain, Timothy P.

2010-01-01

This document captures the research and development of a scale model representation of the Apollo 17 landing site on the moon as part of the NASA INSPIRE program. Several key elements in this model were surface slope characteristics, crater sizes and locations, prominent rocks, and lighting conditions. This model supports development of Autonomous Landing and Hazard Avoidance Technology (ALHAT) and Project M for the GN&C Autonomous Flight Systems Branch. It will help project engineers visualize the landing site, and is housed in the building 16 Navigation Systems Technology Lab. The lead mentor was Dr. Timothy P. Crain. The purpose of this project was to develop an accurate scale representation of the Apollo 17 landing site on the moon. This was done on an 8'2.5"X10'1.375" reduced friction granite table, which can be restored to its previous condition if needed. The first step in this project was to research the best way to model and recreate the Apollo 17 landing site for the mockup. The project required a thorough plan, budget, and schedule, which was presented to the EG6 Branch for build approval. The final phase was to build the model. The project also required thorough research on the Apollo 17 landing site and the topography of the moon. This research was done on the internet and in person with Dean Eppler, a space scientist, from JSC KX. This data was used to analyze and calculate the scale of the mockup and the ratio of the sizes of the craters, ridges, etc. The final goal was to effectively communicate project status and demonstrate the multiple advantages of using our model. The conclusion of this project was that the mockup was completed as accurately as possible, and it successfully enables the Project M specialists to visualize and plan their goal on an accurate three dimensional surface representation.

Constraining the JULES land-surface model for different land-use types using citizen-science generated hydrological data

NASA Astrophysics Data System (ADS)

Chou, H. K.; Ochoa-Tocachi, B. F.; Buytaert, W.

2017-12-01

Community land surface models such as JULES are increasingly used for hydrological assessment because of their state-of-the-art representation of land-surface processes. However, a major weakness of JULES and other land surface models is the limited number of land surface parameterizations that is available. Therefore, this study explores the use of data from a network of catchments under homogeneous land-use to generate parameter "libraries" to extent the land surface parameterizations of JULES. The network (called iMHEA) is part of a grassroots initiative to characterise the hydrological response of different Andean ecosystems, and collects data on streamflow, precipitation, and several weather variables at a high temporal resolution. The tropical Andes are a useful case study because of the complexity of meteorological and geographical conditions combined with extremely heterogeneous land-use that result in a wide range of hydrological responses. We then calibrated JULES for each land-use represented in the iMHEA dataset. For the individual land-use types, the results show improved simulations of streamflow when using the calibrated parameters with respect to default values. In particular, the partitioning between surface and subsurface flows can be improved. But also, on a regional scale, hydrological modelling was greatly benefitted from constraining parameters using such distributed citizen-science generated streamflow data. This study demonstrates the modelling and prediction on regional hydrology by integrating citizen science and land surface model. In the context of hydrological study, the limitation of data scarcity could be solved indeed by using this framework. Improved predictions of such impacts could be leveraged by catchment managers to guide watershed interventions, to evaluate their effectiveness, and to minimize risks.

The role of land surface fluxes in Saudi-KAU AGCM: Temperature climatology over the Arabian Peninsula for the period 1981-2010

NASA Astrophysics Data System (ADS)

Ashfaqur Rahman, M.; Almazroui, Mansour; Nazrul Islam, M.; O'Brien, Enda; Yousef, Ahmed Elsayed

2018-02-01

A new version of the Community Land Model (CLM) was introduced to the Saudi King Abdulaziz University Atmospheric Global Climate Model (Saudi-KAU AGCM) for better land surface component representation, and so to enhance climate simulation. CLM replaced the original land surface model (LSM) in Saudi-KAU AGCM, with the aim of simulating more accurate land surface fluxes globally, but especially over the Arabian Peninsula. To evaluate the performance of Saudi-KAU AGCM, simulations were completed with CLM and LSM for the period 1981-2010. In comparison with LSM, CLM generates surface air temperature values that are closer to National Centre for Environmental Prediction (NCEP) observations. The global annual averages of land surface air temperature are 9.51, 9.52, and 9.57 °C for NCEP, CLM, and LSM respectively, although the same atmospheric radiative and surface forcing from Saudi-KAU AGCM are provided to both LSM and CLM at every time step. The better temperature simulations when using CLM can be attributed to the more comprehensive plant functional type and hierarchical tile approach to the land cover type in CLM, along with better parameterization of upward land surface fluxes compared to LSM. At global scale, CLM exhibits smaller annual and seasonal mean biases of temperature with respect to NCEP data. Moreover, at regional scale, CLM demonstrates reasonable seasonal and annual mean temperature over the Arabian Peninsula as compared to the Climatic Research Unit (CRU) data. Finally, CLM generated better matches to single point-wise observations of surface air temperature and surface fluxes for some case studies.

Closing the loop: integrating human impacts on water resources to advanced land surface models

NASA Astrophysics Data System (ADS)

Zaitchik, B. F.; Nie, W.; Rodell, M.; Kumar, S.; Li, B.

2016-12-01

Advanced Land Surface Models (LSMs), including those used in the North American Land Data Assimilation System (NLDAS), offer a physically consistent and spatially and temporally complete analysis of the distributed water balance. These models are constrained both by physically-based process representation and by observations ingested as meteorological forcing or as data assimilation updates. As such, they have become important tools for hydrological monitoring and long-term climate analysis. The representation of water management, however, is extremely limited in these models. Recent advances have brought prognostic irrigation routines into models used in NLDAS, while assimilation of Gravity Recovery and Climate Experiment (GRACE) derived estimates of terrestrial water storage anomaly has made it possible to nudge models towards observed states in water storage below the root zone. But with few exceptions these LSMs do not account for the source of irrigation water, leading to a disconnect between the simulated water balance and the observed human impact on water resources. This inconsistency is unacceptable for long-term studies of climate change and human impact on water resources in North America. Here we define the modeling challenge, review instances of models that have begun to account for water withdrawals (e.g., CLM), and present ongoing efforts to improve representation of human impacts on water storage across models through integration of irrigation routines, water withdrawal information, and GRACE Data Assimilation in NLDAS LSMs.

Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; 4 Blyth, Eleanor; de Roo, Ad; Doell. Petra; Ek, Mike; Famiglietti, James;

Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water

NASA Astrophysics Data System (ADS)

Wood, Eric F.; Roundy, Joshua K.; Troy, Tara J.; van Beek, L. P. H.; Bierkens, Marc F. P.; Blyth, Eleanor; de Roo, Ad; DöLl, Petra; Ek, Mike; Famiglietti, James; Gochis, David; van de Giesen, Nick; Houser, Paul; Jaffé, Peter R.; Kollet, Stefan; Lehner, Bernhard; Lettenmaier, Dennis P.; Peters-Lidard, Christa; Sivapalan, Murugesu; Sheffield, Justin; Wade, Andrew; Whitehead, Paul

2011-05-01

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (˜10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a "grand challenge" to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

LS3MIP (v1.0) Contribution to CMIP6: The Land Surface, Snow and Soil Moisture Model Intercomparison Project Aims, Setup and Expected Outcome.

NASA Technical Reports Server (NTRS)

Van Den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; Seneviratne, Sonia I.; Derksen, Chris; Oki, Taikan; Douville, Herve; Colin, Jeanne; Ducharne, Agnes; Cheruy, Frederique;

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE PAGES

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard; ...

2016-08-24

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

LS3MIP (v1.0) contribution to CMIP6: the Land Surface, Snow and Soilmoisture Model Intercomparison Project – aims, setup and expected outcome

DOE Office of Scientific and Technical Information (OSTI.GOV)

van den Hurk, Bart; Kim, Hyungjun; Krinner, Gerhard

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). Furthermore, the solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both stronglymore » affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. But, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).« less

Sensitivity of a model projection of near-surface permafrost degradation to soil column depth and representation of soil organic matter.

Treesearch

David M. Lawrence; Andrew G. Slater; Vladimir E. Romanovsky; Dmitry J. Nicolsky

2008-01-01

The sensitivity of a global land-surface model projection of near-surface permafrost degradation is assessed with respect to explicit accounting of the thermal and hydrologic properties of soil organic matter and to a deepening of the soil column from 3.5 to 50 or more m. Together these modifications result in substantial improvements in the simulation of near-surface...

Improved representations of coupled soil–canopy processes in the CABLE land surface model (Subversion revision 3432)

DOE PAGES

Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.; ...

2016-09-07

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil–canopy processes by introducing an alternative hydrology model with amore » physically accurate representation of coupled energy and water fluxes at the soil–air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Here, marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.« less

Improved representations of coupled soil–canopy processes in the CABLE land surface model (Subversion revision 3432)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil–canopy processes by introducing an alternative hydrology model with amore » physically accurate representation of coupled energy and water fluxes at the soil–air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Here, marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.« less

Improved representations of coupled soil-canopy processes in the CABLE land surface model (Subversion revision 3432)

NASA Astrophysics Data System (ADS)

Haverd, Vanessa; Cuntz, Matthias; Nieradzik, Lars P.; Harman, Ian N.

2016-09-01

CABLE is a global land surface model, which has been used extensively in offline and coupled simulations. While CABLE performs well in comparison with other land surface models, results are impacted by decoupling of transpiration and photosynthesis fluxes under drying soil conditions, often leading to implausibly high water use efficiencies. Here, we present a solution to this problem, ensuring that modelled transpiration is always consistent with modelled photosynthesis, while introducing a parsimonious single-parameter drought response function which is coupled to root water uptake. We further improve CABLE's simulation of coupled soil-canopy processes by introducing an alternative hydrology model with a physically accurate representation of coupled energy and water fluxes at the soil-air interface, including a more realistic formulation of transfer under atmospherically stable conditions within the canopy and in the presence of leaf litter. The effects of these model developments are assessed using data from 18 stations from the global eddy covariance FLUXNET database, selected to span a large climatic range. Marked improvements are demonstrated, with root mean squared errors for monthly latent heat fluxes and water use efficiencies being reduced by 40 %. Results highlight the important roles of deep soil moisture in mediating drought response and litter in dampening soil evaporation.

The Effect of Subsurface Parameterizations on Modeled Flows in the Catchment Land Surface Model, Fortuna 2.5

NASA Astrophysics Data System (ADS)

Roningen, J. M.; Eylander, J. B.

2014-12-01

Groundwater use and management is subject to economic, legal, technical, and informational constraints and incentives at a variety of spatial and temporal scales. Planned and de facto management practices influenced by tax structures, legal frameworks, and agricultural and trade policies that vary at the country scale may have medium- and long-term effects on the ability of a region to support current and projected agricultural and industrial development. USACE is working to explore and develop global-scale, physically-based frameworks to serve as a baseline for hydrologic policy comparisons and consequence assessment, and such frameworks must include a reasonable representation of groundwater systems. To this end, we demonstrate the effects of different subsurface parameterizations, scaling, and meteorological forcings on surface and subsurface components of the Catchment Land Surface Model Fortuna v2.5 (Koster et al. 2000). We use the Land Information System 7 (Kumar et al. 2006) to process model runs using meteorological components of the Air Force Weather Agency's AGRMET forcing data from 2006 through 2011. Seasonal patterns and trends are examined in areas of the Upper Nile basin, northern China, and the Mississippi Valley. We also discuss the relevance of the model's representation of the catchment deficit with respect to local hydrogeologic structures.

Using ARM Observations to Evaluate Climate Model Representation of Land-Atmosphere Coupling on the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Phillips, T. J.; Klein, S. A.; Ma, H. Y.; Tang, Q.

2016-12-01

Statistically significant coupling between summertime soil moisture and various atmospheric variables has been observed at the U.S. Southern Great Plains (SGP) facilities maintained by the U.S. DOE Atmospheric Radiation Measurement (ARM) program (Phillips and Klein, 2014 JGR). In the current study, we employ several independent measurements of shallow-depth soil moisture (SM) and of the surface evaporative fraction (EF) over multiple summers in order to estimate the range of SM-EF coupling strength at seven sites, and to approximate the SGP regional-scale coupling strength (and its uncertainty). We will use this estimate of regional-scale SM-EF coupling strength to evaluate its representation in version 5.1 of the global Community Atmosphere Model (CAM5.1) coupled to the CLM4 Land Model. Two experimental cases are considered for the 2003-2011 study period: 1) an Atmospheric Model Intercomparison Project (AMIP) run with historically observed sea surface temperatures specified, and 2) a more constrained hindcast run in which the CAM5.1 atmospheric state is initialized each day from the ERA Interim reanalysis, while the CLM4 initial conditions are obtained from an offline run of the land model using observed surface net radiation, precipitation, and wind as forcings. These twin experimental cases allow a distinction to be drawn between the land-atmosphere coupling in the free-running CAM5.1/CLM4 model and that in which the land and atmospheric states are constrained to remain closer to "reality". The constrained hindcast case, for example, should allow model errors in coupling strength to be related more closely to potential deficiencies in land-surface or atmospheric boundary-layer parameterizations. AcknowledgmentsThis work was funded by the U.S. Department of Energy Office of Science and was performed at the Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Uncertainty in Arctic hydrology projections and the permafrost-carbon feedback

NASA Astrophysics Data System (ADS)

Andresen, C. G.; Lawrence, D. M.; Wilson, C. J.; McGuire, D.

2017-12-01

Projected warming is expected to thaw permafrost soils and deepen the permafrost active layer. These changes will affect surface hydrological conditions. Since the soil hydrologic state exerts a strong influence on the rate and pathway of soil organic matter decomposition into CO2 or CH4, there is a strong need to examine and better understand model projections of hydrologic change and how differences in process representation affect projections of wetting and/or drying of changing permafrost landscapes. This study aims to advance understanding of where, when and why arctic will become wetter or drier. We assessed simulations from 8 "permafrost enabled" land models that were run in offline mode from 1960 to 2299 forced with the same projected climate for a high-emissions scenario. Climate models project increased precipitation (P) across most of the Arctic domain and the land models indicate that runoff and evapotranspiration (ET) will also both increase. In general, the water input to the soil (P-ET) also increases, but the models project a contradicting long-term drying of the surface soil. The surface drying in the models can generally be explained by filtration of moisture to deeper soil layers as the active layer deepens or by increased sub-surface drainage where permafrost in a grid cell thaws completely. Though, there is a qualitative agreement in this type of response across the models, the projections vary dramatically in magnitude. Variability among simulations is largely attributed to parameterization and structural differences across the participating models, particularly the diverse representations of evapotranspiration, water table and soil water storage and transmission. A limited set of results from single forcing experiments suggests that the warming effect in the sensitivity analysis was the principal driver of soil drying while CO2 and precipitation effects had a small wetting influence. When compared to observational data, simulations tend to underestimate discharge by a factor of 2 for the major arctic river basins. This analysis serves as a baseline to identify key process representation gaps and opportunities to improve representation of permafrost hydrology and associated projections of carbon and energy feedbacks in land models.

Logo for the 20th Anniversary of the Apollo 11 mission

NASA Technical Reports Server (NTRS)

1989-01-01

Logo for the 20th Anniversary of the Apollo 11 mission. Logo is described as the numeral 20. Inside the zero is a representation of an eagle landing on the lunar surface with the title 'Apollo 11' above it.

Logo for the 20th Anniversary of the Apollo 11 mission

NASA Image and Video Library

1989-02-06

Logo for the 20th Anniversary of the Apollo 11 mission. Logo is described as the numeral 20. Inside the zero is a representation of an eagle landing on the lunar surface with the title "Apollo 11" above it.

Development of an Operational Land Water Mask for MODIS Collection 6, and Influence on Downstream Data Products

NASA Technical Reports Server (NTRS)

Carroll, M. L.; DiMiceli, C. M.; Townshend, J. R. G.; Sohlberg, R. A.; Elders, A. I.; Devadiga, S.; Sayer, A. M.; Levy, R. C.

2016-01-01

Data from the Moderate Resolution Imaging Spectro-radiometer (MODIS)on-board the Earth Observing System Terra and Aqua satellites are processed using a land water mask to determine when an algorithm no longer needs to be run or when an algorithm needs to follow a different pathway. Entering the fourth reprocessing (Collection 6 (C6)) the MODIS team replaced the 1 km water mask with a 500 m water mask for improved representation of the continental surfaces. The new water mask represents more small water bodies for an overall increase in water surface from 1 to 2 of the continental surface. While this is still a small fraction of the overall global surface area the increase is more dramatic in certain areas such as the Arctic and Boreal regions where there are dramatic increases in water surface area in the new mask. MODIS products generated by the on-going C6 reprocessing using the new land water mask show significant impact in areas with high concentrations of change in the land water mask. Here differences between the Collection 5 (C5) and C6 water masks and the impact of these differences on the MOD04 aerosol product and the MOD11 land surface temperature product are shown.

Impact of Optimized land Surface Parameters on the Land-Atmosphere Coupling in WRF Simulations of Dry and Wet Extremes

NASA Technical Reports Server (NTRS)

Kumar, Sujay; Santanello, Joseph; Peters-Lidard, Christa; Harrison, Ken

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty module in NASA's Land Information System (LIS-OPT), whereby parameter sets are calibrated in the Noah land surface model and classified according to the land cover and soil type mapping of the observations and the full domain. The impact of the calibrated parameters on the a) spin up of land surface states used as initial conditions, and b) heat and moisture fluxes of the coupled (LIS-WRF) simulations are then assessed in terms of ambient weather, PBL budgets, and precipitation along with L-A coupling diagnostics. In addition, the sensitivity of this approach to the period of calibration (dry, wet, normal) is investigated. Finally, tradeoffs of computational tractability and scientific validity (e.g.,. relating to the representation of the spatial dependence of parameters) and the feasibility of calibrating to multiple observational datasets are also discussed.

Impacts of spectral nudging on the simulated surface air temperature in summer compared with the selection of shortwave radiation and land surface model physics parameterization in a high-resolution regional atmospheric model

NASA Astrophysics Data System (ADS)

Park, Jun; Hwang, Seung-On

2017-11-01

The impact of a spectral nudging technique for the dynamical downscaling of the summer surface air temperature in a high-resolution regional atmospheric model is assessed. The performance of this technique is measured by comparing 16 analysis-driven simulation sets of physical parameterization combinations of two shortwave radiation and four land surface model schemes of the model, which are known to be crucial for the simulation of the surface air temperature. It is found that the application of spectral nudging to the outermost domain has a greater impact on the regional climate than any combination of shortwave radiation and land surface model physics schemes. The optimal choice of two model physics parameterizations is helpful for obtaining more realistic spatiotemporal distributions of land surface variables such as the surface air temperature, precipitation, and surface fluxes. However, employing spectral nudging adds more value to the results; the improvement is greater than using sophisticated shortwave radiation and land surface model physical parameterizations. This result indicates that spectral nudging applied to the outermost domain provides a more accurate lateral boundary condition to the innermost domain when forced by analysis data by securing the consistency with large-scale forcing over a regional domain. This consequently indirectly helps two physical parameterizations to produce small-scale features closer to the observed values, leading to a better representation of the surface air temperature in a high-resolution downscaled climate.

A ripple-spreading genetic algorithm for the aircraft sequencing problem.

PubMed

Hu, Xiao-Bing; Di Paolo, Ezequiel A

2011-01-01

When genetic algorithms (GAs) are applied to combinatorial problems, permutation representations are usually adopted. As a result, such GAs are often confronted with feasibility and memory-efficiency problems. With the aircraft sequencing problem (ASP) as a study case, this paper reports on a novel binary-representation-based GA scheme for combinatorial problems. Unlike existing GAs for the ASP, which typically use permutation representations based on aircraft landing order, the new GA introduces a novel ripple-spreading model which transforms the original landing-order-based ASP solutions into value-based ones. In the new scheme, arriving aircraft are projected as points into an artificial space. A deterministic method inspired by the natural phenomenon of ripple-spreading on liquid surfaces is developed, which uses a few parameters as input to connect points on this space to form a landing sequence. A traditional GA, free of feasibility and memory-efficiency problems, can then be used to evolve the ripple-spreading related parameters in order to find an optimal sequence. Since the ripple-spreading model is the centerpiece of the new algorithm, it is called the ripple-spreading GA (RSGA). The advantages of the proposed RSGA are illustrated by extensive comparative studies for the case of the ASP.

Coupled atmosphere-biophysics-hydrology models for environmental modeling

USGS Publications Warehouse

Walko, R.L.; Band, L.E.; Baron, Jill S.; Kittel, T.G.F.; Lammers, R.; Lee, T.J.; Ojima, D.; Pielke, R.A.; Taylor, C.; Tague, C.; Tremback, C.J.; Vidale, P.L.

2000-01-01

The formulation and implementation of LEAF-2, the Land Ecosystem–Atmosphere Feedback model, which comprises the representation of land–surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision of a RAMS surface grid cell into multiple areas of distinct land-use types is allowed, with each subgrid area, or patch, containing its own LEAF-2 model, and each patch interacts with the overlying atmospheric column with a weight proportional to its fractional area in the grid cell. A description is also given of TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. Details of the incorporation of a modified form of TOPMODEL into LEAF-2 are presented. Sensitivity tests of the coupled system are presented that demonstrate the potential importance of the patch representation and of lateral water transport in idealized model simulations. Independent studies that have applied LEAF-2 and verified its performance against observational data are cited. Linkage of RAMS and TOPMODEL through LEAF-2 creates a modeling system that can be used to explore the coupled atmosphere–biophysical–hydrologic response to altered climate forcing at local watershed and regional basin scales.

Bridging the Gap between Policy-Driven Land Use Changes and Regional Climate Projections

NASA Astrophysics Data System (ADS)

Berckmans, J.; Hamdi, R.; Dendoncker, N.; Ceulemans, R.

2017-12-01

Land use land cover changes (LULCC) can impact the regional climate by two mechanisms: biogeochemical and biogeophysical. The biogeochemical mechanism of the LULCC alters the chemical composition of the atmosphere by greenhouse gas emissions. The biogeophysical mechanism forces changes in the heat and moisture transfer between the land and the atmosphere. The different representations of the future LULCC under influence of the biogeochemical mechanism are included in the IPCC Radiative Concentration Pathways (RCPs). In contrast, the RCPs do not incorporate the biogeophysical effects. Although considerable research has been devoted to the biogeophysical effects of LULCC on climate, less attention has been paid to assessing the full (both biogeochemical and biogeophysical) LULCC impact on the regional climate in modeling studies. Due to the large variety of small changes in the landscape of Western Europe, the small scale climate impact by the LULCC has been achieved using high-resolution scenarios. The "ALARM" project that was governed by the European Commission generated LULCC data on a resolution of 250x250 m for three time steps: 2020, 2050 and 2080. The CNRM-CM5.1 global climate model has been downscaled to perform simulations with ALARO-SURFEX for the near-term future. Both climate changes and land cover changes have been assessed based on RCP and ALARM scenarios. The use of the land surface model SURFEX with its tiling approach allowed us to accurately represent the small scale changes in the landscape. The largest landscape changes contain the abandonment of agricultural land and the increase in forestry and urban areas. Our results show that the conversions from rural areas to urban areas and arable land to forest in Western Europe considerable affect the near-surface temperature and to a lesser extent the precipitation. These results are related to modifications demonstrated in the surface energy budget. The LULCC have a significant impact compared to the near-term future climate changes. They provide valuable information for landscape planning to mitigate and adapt to climate change. The strength of this study is the use of policy-driven LULCC data combined with an accurate representation of the land by the climate model.

Representation of dissolved organic carbon in the JULES land surface model (vn4.4_JULES-DOCM)

NASA Astrophysics Data System (ADS)

Nakhavali, Mahdi; Friedlingstein, Pierre; Lauerwald, Ronny; Tang, Jing; Chadburn, Sarah; Camino-Serrano, Marta; Guenet, Bertrand; Harper, Anna; Walmsley, David; Peichl, Matthias; Gielen, Bert

2018-02-01

Current global models of the carbon (C) cycle consider only vertical gas exchanges between terrestrial or oceanic reservoirs and the atmosphere, thus not considering the lateral transport of carbon from the continents to the oceans. Therefore, those models implicitly consider all of the C which is not respired to the atmosphere to be stored on land and hence overestimate the land C sink capability. A model that represents the whole continuum from atmosphere to land and into the ocean would provide a better understanding of the Earth's C cycle and hence more reliable historical or future projections. A first and critical step in that direction is to include processes representing the production and export of dissolved organic carbon in soils. Here we present an original representation of dissolved organic C (DOC) processes in the Joint UK Land Environment Simulator (JULES-DOCM) that integrates a representation of DOC production in terrestrial ecosystems based on the incomplete decomposition of organic matter, DOC decomposition within the soil column, and DOC export to the river network via leaching. The model performance is evaluated in five specific sites for which observations of soil DOC concentration are available. Results show that the model is able to reproduce the DOC concentration and controlling processes, including leaching to the riverine system, which is fundamental for integrating terrestrial and aquatic ecosystems. Future work should include the fate of exported DOC in the river system as well as DIC and POC export from soil.

Towards a more efficient and robust representation of subsurface hydrological processes in Earth System Models

NASA Astrophysics Data System (ADS)

Rosolem, R.; Rahman, M.; Kollet, S. J.; Wagener, T.

2017-12-01

Understanding the impacts of land cover and climate changes on terrestrial hydrometeorology is important across a range of spatial and temporal scales. Earth System Models (ESMs) provide a robust platform for evaluating these impacts. However, current ESMs lack the representation of key hydrological processes (e.g., preferential water flow, and direct interactions with aquifers) in general. The typical "free drainage" conceptualization of land models can misrepresent the magnitude of those interactions, consequently affecting the exchange of energy and water at the surface as well as estimates of groundwater recharge. Recent studies show the benefits of explicitly simulating the interactions between subsurface and surface processes in similar models. However, such parameterizations are often computationally demanding resulting in limited application for large/global-scale studies. Here, we take a different approach in developing a novel parameterization for groundwater dynamics. Instead of directly adding another complex process to an established land model, we examine a set of comprehensive experimental scenarios using a very robust and establish three-dimensional hydrological model to develop a simpler parameterization that represents the aquifer to land surface interactions. The main goal of our developed parameterization is to simultaneously maximize the computational gain (i.e., "efficiency") while minimizing simulation errors in comparison to the full 3D model (i.e., "robustness") to allow for easy implementation in ESMs globally. Our study focuses primarily on understanding both the dynamics for groundwater recharge and discharge, respectively. Preliminary results show that our proposed approach significantly reduced the computational demand while model deviations from the full 3D model are considered to be small for these processes.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U. S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Peters-Lidard, Christa D.; Kennedy, Aaron D.; Kumar, Sujay; Dong, Xiquan

2011-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts of local land-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

Compensatory Root Water Uptake of Overlapping Root Systems

NASA Astrophysics Data System (ADS)

Agee, E.; Ivanov, V. Y.; He, L.; Bisht, G.; Shahbaz, P.; Fatichi, S.; Gough, C. M.; Couvreur, V.; Matheny, A. M.; Bohrer, G.

2015-12-01

Land-surface models use simplified representations of root water uptake based on biomass distributions and empirical functions that constrain water uptake during unfavorable soil moisture conditions. These models fail to capture the observed hydraulic plasticity that allows plants to regulate root hydraulic conductivity and zones of active uptake based on local gradients. Recent developments in root water uptake modeling have sought to increase its mechanistic representation by bridging the gap between physically based microscopic models and computationally feasible macroscopic approaches. It remains to be demonstrated whether bulk parameterization of microscale characteristics (e.g., root system morphology and root conductivity) can improve process representation at the ecosystem scale. We employ the Couvreur method of microscopic uptake to yield macroscopic representation in a coupled soil-root model. Using a modified version of the PFLOTRAN model, which represents the 3-D physics of variably saturated soil, we model a one-hectare temperate forest stand under natural and synthetic climatic forcing. Our results show that as shallow soil layers dry, uptake at the tree and stand level shift to deeper soil layers, allowing the transpiration stream demanded by the atmosphere. We assess the potential capacity of the model to capture compensatory root water uptake. Further, the hydraulic plasticity of the root system is demonstrated by the quick response of uptake to rainfall pulses. These initial results indicate a promising direction for land surface models in which significant three-dimensional information from large root systems can be feasibly integrated into the forest scale simulations of root water uptake.

Nutrient cycle benchmarks for earth system land model

NASA Astrophysics Data System (ADS)

Zhu, Q.; Riley, W. J.; Tang, J.; Zhao, L.

2017-12-01

Projecting future biosphere-climate feedbacks using Earth system models (ESMs) relies heavily on robust modeling of land surface carbon dynamics. More importantly, soil nutrient (particularly, nitrogen (N) and phosphorus (P)) dynamics strongly modulate carbon dynamics, such as plant sequestration of atmospheric CO2. Prevailing ESM land models all consider nitrogen as a potentially limiting nutrient, and several consider phosphorus. However, including nutrient cycle processes in ESM land models potentially introduces large uncertainties that could be identified and addressed by improved observational constraints. We describe the development of two nutrient cycle benchmarks for ESM land models: (1) nutrient partitioning between plants and soil microbes inferred from 15N and 33P tracers studies and (2) nutrient limitation effects on carbon cycle informed by long-term fertilization experiments. We used these benchmarks to evaluate critical hypotheses regarding nutrient cycling and their representation in ESMs. We found that a mechanistic representation of plant-microbe nutrient competition based on relevant functional traits best reproduced observed plant-microbe nutrient partitioning. We also found that for multiple-nutrient models (i.e., N and P), application of Liebig's law of the minimum is often inaccurate. Rather, the Multiple Nutrient Limitation (MNL) concept better reproduces observed carbon-nutrient interactions.

The NASA-Goddard Multi-Scale Modeling Framework - Land Information System: Global Land/atmosphere Interaction with Resolved Convection

NASA Technical Reports Server (NTRS)

Mohr, Karen Irene; Tao, Wei-Kuo; Chern, Jiun-Dar; Kumar, Sujay V.; Peters-Lidard, Christa D.

2013-01-01

The present generation of general circulation models (GCM) use parameterized cumulus schemes and run at hydrostatic grid resolutions. To improve the representation of cloud-scale moist processes and landeatmosphere interactions, a global, Multi-scale Modeling Framework (MMF) coupled to the Land Information System (LIS) has been developed at NASA-Goddard Space Flight Center. The MMFeLIS has three components, a finite-volume (fv) GCM (Goddard Earth Observing System Ver. 4, GEOS-4), a 2D cloud-resolving model (Goddard Cumulus Ensemble, GCE), and the LIS, representing the large-scale atmospheric circulation, cloud processes, and land surface processes, respectively. The non-hydrostatic GCE model replaces the single-column cumulus parameterization of fvGCM. The model grid is composed of an array of fvGCM gridcells each with a series of embedded GCE models. A horizontal coupling strategy, GCE4fvGCM4Coupler4LIS, offered significant computational efficiency, with the scalability and I/O capabilities of LIS permitting landeatmosphere interactions at cloud-scale. Global simulations of 2007e2008 and comparisons to observations and reanalysis products were conducted. Using two different versions of the same land surface model but the same initial conditions, divergence in regional, synoptic-scale surface pressure patterns emerged within two weeks. The sensitivity of largescale circulations to land surface model physics revealed significant functional value to using a scalable, multi-model land surface modeling system in global weather and climate prediction.

Assessment of surface turbulent fluxes using geostationary satellite surface skin temperatures and a mixed layer planetary boundary layer scheme

NASA Technical Reports Server (NTRS)

Diak, George R.; Stewart, Tod R.

1989-01-01

A method is presented for evaluating the fluxes of sensible and latent heating at the land surface, using satellite-measured surface temperature changes in a composite surface layer-mixed layer representation of the planetary boundary layer. The basic prognostic model is tested by comparison with synoptic station information at sites where surface evaporation climatology is well known. The remote sensing version of the model, using satellite-measured surface temperature changes, is then used to quantify the sharp spatial gradient in surface heating/evaporation across the central United States. An error analysis indicates that perhaps five levels of evaporation are recognizable by these methods and that the chief cause of error is the interaction of errors in the measurement of surface temperature change with errors in the assigment of surface roughness character. Finally, two new potential methods for remote sensing of the land-surface energy balance are suggested which will relay on space-borne instrumentation planned for the 1990s.

Integrating spatially explicit representations of landscape perceptions into land change research

USGS Publications Warehouse

Dorning, Monica; Van Berkel, Derek B.; Semmens, Darius J.

2017-01-01

Purpose of ReviewHuman perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research.Recent FindingsMapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models.SummaryChallenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.

Sensitivity of Land Surface Parameters on Thunderstorm Simulation through HRLDAS-WRF Coupling Mode

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Kumar, Krishan; Mohanty, U. C.; Kisore Osuri, Krishna

2016-07-01

Land surface characteristics play an important role in large scale, regional and mesoscale atmospheric process. Representation of land surface characteristics can be improved through coupling of mesoscale atmospheric models with land surface models. Mesoscale atmospheric models depend on Land Surface Models (LSM) to provide land surface variables such as fluxes of heat, moisture, and momentum for lower boundary layer evolution. Studies have shown that land surface properties such as soil moisture, soil temperature, soil roughness, vegetation cover, have considerable effect on lower boundary layer. Although, the necessity to initialize soil moisture accurately in NWP models is widely acknowledged, monitoring soil moisture at regional and global scale is a very tough task due to high spatial and temporal variability. As a result, the available observation network is unable to provide the required spatial and temporal data for the most part of the globe. Therefore, model for land surface initializations rely on updated land surface properties from LSM. The solution for NWP land-state initialization can be found by combining data assimilation techniques, satellite-derived soil data, and land surface models. Further, it requires an intermediate step to use observed rainfall, satellite derived surface insolation, and meteorological analyses to run an uncoupled (offline) integration of LSM, so that the evolution of modeled soil moisture can be forced by observed forcing conditions. Therefore, for accurate land-state initialization, high resolution land data assimilation system (HRLDAS) is used to provide the essential land surface parameters. Offline-coupling of HRLDAS-WRF has shown much improved results over Delhi, India for four thunder storm events. The evolution of land surface variables particularly soil moisture, soil temperature and surface fluxes have provided more realistic condition. Results have shown that most of domain part became wetter and warmer after assimilation of soil moisture and soil temperature at the initial condition which helped to improve the exchange fluxes at lower atmospheric level. Mixing ratio were increased along with elevated theta-e at lower level giving a signature of improvement in LDAS experiment leading to a suitable condition for convection. In the analysis, moisture convergence, mixing ratio and vertical velocities have improved significantly in terms of intensity and time lag. Surface variables like soil moisture, soil temperature, sensible heat flux and latent heat flux have progressed in a possible realistic pattern. Above discussion suggests that assimilation of soil moisture and soil temperature improves the overall simulations significantly.

Impact of physical permafrost processes on hydrological change

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Blome, Tanja; Beer, Christian; Ekici, Altug

2015-04-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) and Earth system models (ESMs) lacked the sufficient representation of permafrost physics in their land surface schemes. Within the European Union FP7 project PAGE21, the land surface scheme JSBACH of the Max-Planck-Institute for Meteorology ESM (MPI-ESM) has been equipped with the representation of relevant physical processes for permafrost studies. These processes include the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. In the present study, it will be analysed how these permafrost relevant processes impact projected hydrological changes over northern hemisphere high latitude land areas. For this analysis, the atmosphere-land part of MPI-ESM, ECHAM6-JSBACH, is driven by prescribed SST and sea ice in an AMIP2-type setup with and without the newly implemented permafrost processes. Observed SST and sea ice for 1979-1999 are used to consider induced changes in the simulated hydrological cycle. In addition, simulated SST and sea ice are taken from a MPI-ESM simulation conducted for CMIP5 following the RCP8.5 scenario. The corresponding simulations with ECHAM6-JSBACH are used to assess differences in projected hydrological changes induced by the permafrost relevant processes.

Towards a more detailed representation of the energy balance in a coupled land surface model

NASA Astrophysics Data System (ADS)

Ryder, J.; Polcher, J.; Luyssaert, S.

2012-04-01

Currently, the land-surface region sequesters 25% of global CO2 emissions. In addition to climate change, increasing atmospheric CO2 concentrations, fertilisation and nitrogen deposition, this sink is thought to be largely due to land management. When applied deliberately to enhance the terrestrial carbon sink strength, this land management may have unintended effects on the energy budget, potentially offsetting the radiative effect of carbon sequestration. As with other land surface models, the present release of ORCHIDEE (the land surface model of the IPSL Earth system model) has difficulties in reproducing consistently observed energy balances (Pitman et al., 2009; Jimenez et al., 2011; de Noblet-Ducoudré et al., 2011). Hence, the model must be improved to be better able to study the radiative effect of forest management and land use change. This observation serves as a starting point in this research - improving the level of detail in energy balance simulations of the surface layer. We here outline the structure of a new detailed and practical simulation of the energy budget that is currently under development within the surface model ORCHIDEE, and will be coupled to the atmospheric model LMDZ. The most detailed simulations of the surface layer energy budget are detailed iterative multi-layer canopy models, such as Ogeé et al. (2003), which are linked to specific measurement sites and do not interact with the atmosphere. In this current project, we aim to create a model that will implement the insights obtained in those previous studies and improve upon the present ORCHIDEE parameterisation, but will run stably and efficiently when coupled to an atmospheric model. This work involves a replacement of the existing allocation of 14 different types of vegetation within each surface tile (the 'Plant Functional Types') by a more granular scheme that can be modified to reflect changes in attributes such as vegetation density, leaf type, distribution (clumping factors), age and height of vegetation within the surface tile. There will be the implementation of more than one canopy vegetation layer to simulate the effects of scalar gradients within the canopy for determining, more accurately, the net sensible and latent heat fluxes that are passed to the atmosphere. The model will include representation of characteristics such as in-canopy transport, coupling with sensible heat flux from the soil, a multilayer radiation budget and stomatal resistance, and interaction with the bare soil flux within the canopy space (and also with snow pack). We present how the implicit coupling approach of Polcher et al. (1998) and Best et al. (2004) is to be extended to a multilayer scenario, present initial sensitivity studies and outline future testing scenarios and validation plans.

Soil frost-induced soil moisture precipitation feedback and effects on atmospheric states

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Blome, Tanja; Ekici, Altug; Beer, Christian

2016-04-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) and Earth system models (ESMs) lacked the sufficient representation of permafrost physics in their land surface schemes. Within the European Union FP7 project PAGE21, the land surface scheme JSBACH of the Max-Planck-Institute for Meteorology ESM (MPI-ESM) has been equipped with the representation of relevant physical processes for permafrost studies. These processes include the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. In the present study, it will be analysed how these permafrost relevant processes impact large-scale hydrology and climate over northern hemisphere high latitude land areas. For this analysis, the atmosphere-land part of MPI-ESM, ECHAM6-JSBACH, is driven by prescribed observed SST and sea ice in an AMIP2-type setup with and without the newly implemented permafrost processes. Results show a large improvement in the simulated discharge. On one hand this is related to an improved snowmelt peak of runoff due to frozen soil in spring. On the other hand a subsequent reduction of soil moisture leads to a positive land atmosphere feedback to precipitation over the high latitudes, which reduces the model's wet biases in precipitation and evapotranspiration during the summer. This is noteworthy as soil moisture - atmosphere feedbacks have previously not been in the research focus over the high latitudes. These results point out the importance of high latitude physical processes at the land surface for the regional climate.

Diagnosing the Nature of Land-Atmosphere Coupling During the 2006-7 Dry/Wet Extremes in the U.S. Southern Great Plains

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Dong, Xiquan; Kennedy, Aaron D.

2011-01-01

Land-atmosphere interactions play a critical role in determining the. diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling (LoCo) is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during the summers of 200617 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet extremes of this region, along with the sensitivity of PBL-LSM coupling to perturbations in soil moisture. As such, this methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which is serving as a testbed for LoCo experiments to evaluate coupling diagnostics within the community.

Toward improving the representation of the water cycle at High Northern Latitudes

NASA Astrophysics Data System (ADS)

Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke

2016-04-01

The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical weather prediction models. Analyses include information on root zone soil moisture. We provide evidence of the value of satellite soil measurements over Norway, including their fidelity, and their impact at improving the representation of the hydrological cycle over northern high latitudes. We indicate benefits from these results for multi-decadal soil moisture datasets such as that from the ESA CCI for soil moisture.

Assessing the Effects of Irrigation on Land Surface Processes Utilizing CLM.PF in Los Angeles, California

NASA Astrophysics Data System (ADS)

Reyes, B.; Vahmani, P.; Hogue, T. S.; Maxwell, R. M.

2013-05-01

Irrigation can significantly alter land surface properties including increases in evapotranspiration (ET) and latent heat flux and a decrease in land surface temperatures that have a wide range of effects on the hydrologic cycle. However, most irrigation in land surface modeling studies has generally been limited to large-scale cropland applications while ignoring the, relatively, much smaller use of irrigation in urban areas. Although this assumption may be valid in global studies, as we seek to apply models at higher resolutions and at more local scales, irrigation in urban areas can become a key factor in land-atmosphere interactions. Landscape irrigation can account for large portions of residential urban water use, especially in semi-arid environments (e.g. ~50% in Los Angeles, CA). Previous modeling efforts in urbanized semi-arid regions have shown that disregarding irrigation leads to inaccurate representation of the energy budget. The current research models a 49.5-km2 (19.11-mi2) domain near downtown Los Angeles in the Ballona Creek watershed at a high spatial and temporal resolution using a coupled hydrologic (ParFlow) and land surface model (CLM). Our goals are to (1) provide a sensitivity analysis for urban irrigation parameters including sensitivity to total volume and timing of irrigation, (2) assess the effects of irrigation on varying land cover types on the energy budget, and (3) evaluate if residential water use data is useful in providing estimates for irrigation in land surface modeling. Observed values of land surface parameters from remote sensing products (Land Surface Temperature and ET), water use data from the Los Angeles Department of Water and Power (LADWP), and modeling results from an irrigated version of the NOAH-Urban Canopy Model are being used for comparison and evaluation. Our analysis provides critical information on the degree to which urban irrigation should be represented in high-resolution, semi-arid urban land surface modeling of the region. This research also yields robust upper-boundary conditions for further analysis and modeling in Los Angeles.

Sensitivity of land surface modeling to parameters: An uncertainty quantification method applied to the Community Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Mei, R.; Mao, J.; Hoffman, F. M.; Kumar, J.

2015-12-01

Uncertainties in land parameters could have important impacts on simulated water and energy fluxes and land surface states, which will consequently affect atmospheric and biogeochemical processes. Therefore, quantification of such parameter uncertainties using a land surface model is the first step towards better understanding of predictive uncertainty in Earth system models. In this study, we applied a random-sampling, high-dimensional model representation (RS-HDMR) method to analyze the sensitivity of simulated photosynthesis, surface energy fluxes and surface hydrological components to selected land parameters in version 4.5 of the Community Land Model (CLM4.5). Because of the large computational expense of conducting ensembles of global gridded model simulations, we used the results of a previous cluster analysis to select one thousand representative land grid cells for simulation. Plant functional type (PFT)-specific uniform prior ranges for land parameters were determined using expert opinion and literature survey, and samples were generated with a quasi-Monte Carlo approach-Sobol sequence. Preliminary analysis of 1024 simulations suggested that four PFT-dependent parameters (including slope of the conductance-photosynthesis relationship, specific leaf area at canopy top, leaf C:N ratio and fraction of leaf N in RuBisco) are the dominant sensitive parameters for photosynthesis, surface energy and water fluxes across most PFTs, but with varying importance rankings. On the other hand, for surface ans sub-surface runoff, PFT-independent parameters, such as the depth-dependent decay factors for runoff, play more important roles than the previous four PFT-dependent parameters. Further analysis by conditioning the results on different seasons and years are being conducted to provide guidance on how climate variability and change might affect such sensitivity. This is the first step toward coupled simulations including biogeochemical processes, atmospheric processes or both to determine the full range of sensitivity of Earth system modeling to land-surface parameters. This can facilitate sampling strategies in measurement campaigns targeted at reduction of climate modeling uncertainties and can also provide guidance on land parameter calibration for simulation optimization.

Developing Land Surface Type Map with Biome Classification Scheme Using Suomi NPP/JPSS VIIRS Data

NASA Astrophysics Data System (ADS)

Zhang, Rui; Huang, Chengquan; Zhan, Xiwu; Jin, Huiran

2016-08-01

Accurate representation of actual terrestrial surface types at regional to global scales is an important element for a wide range of applications, such as land surface parameterization, modeling of biogeochemical cycles, and carbon cycle studies. In this study, in order to meet the requirement of the retrieval of global leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by the vegetation (fPAR) and other studies, a global map generated from Suomi National Polar- orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) surface reflectance data in six major biome classes based on their canopy structures, which include: Grass/Cereal Crops, Shrubs, Broadleaf Crops, Savannas, Broadleaf Forests, and Needleleaf Forests, was created. The primary biome classes were converted from an International Geosphere-Biosphere Program (IGBP) legend global surface type data that was created in previous study, and the separation of two crop types are based on a secondary classification.

Using WEED to simulate the global wetland distribution in a ESM

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2016-04-01

Lakes and wetlands are an important land surface feature. In terms of hydrology, they regulate river discharge, mitigate flood events and constitute a significant surface water storage. Considering physical processes, they link the surface water and energy balances by altering the separation of incoming energy into sensible and latent heat fluxes. Finally, they impact biogeochemical processes and may act as carbon sinks or sources. Most global hydrology and climate models regard wetland extent and properties as constant in time. However, to study interactions between wetlands and different states of climate, it is necessary to implement surface water bodies (thereafter referred to as wetlands) with dynamical behavior into these models. Besides an improved representation of geophysical feedbacks between wetlands, land surface and atmosphere, a dynamical wetland scheme could also provide estimates of soil wetness as input for biogeochemical models, which are used to compute methane production in wetlands. Recently, a model for the representation of wetland extent dynamics (WEED) was developed as part of the hydrology model (MPI-HM) of the Max-Planck-Institute for Meteorology (MPI-M). The WEED scheme computes wetland extent in agreement with the range of observations for the high northern latitudes. It simulates a realistic seasonal cycle which shows sensitivity to northern snow-melt as well as rainy seasons in the tropics. Furthermore, flood peaks in river discharge are mitigated. However, the WEED scheme overestimates wetland extent in the Tropics which might be related to the MPI-HM's simplified potential evapotranspiration computation. In order to overcome this limitation, the WEED scheme is implemented into the MPI-M's land surface model JSBACH. Thus, not only its effect on water fluxes can be investigated but also its impact on the energy cycle, which is not included in the MPI-HM. Furthermore, it will be possible to analyze the physical effects of wetlands in a coupled land-atmosphere simulation. First simulations with JSBACH-WEED show results similar to the MPI-HM simulations. As the next step, the scheme is modified to account for energy cycle relevant issues such as the dynamical alteration of surface albedo as well as the allocation of appropriate thermal properties to the wetlands. In our presentation, we will give an overview on the functionality of the WEED scheme and the effect of wetlands in coupled land-atmosphere simulations.

Exclusion of agricultural lands in spatial conservation prioritization strategies: consequences for biodiversity and ecosystem service representation

PubMed Central

Durán, América P.; Duffy, James P.; Gaston, Kevin J.

2014-01-01

Agroecosystems have traditionally been considered incompatible with biological conservation goals, and often been excluded from spatial conservation prioritization strategies. The consequences for the representativeness of identified priority areas have been little explored. Here, we evaluate these for biodiversity and carbon storage representation when agricultural land areas are excluded from a spatial prioritization strategy for South America. Comparing different prioritization approaches, we also assess how the spatial overlap of priority areas changes. The exclusion of agricultural lands was detrimental to biodiversity representation, indicating that priority areas for agricultural production overlap with areas of relatively high occurrence of species. By contrast, exclusion of agricultural lands benefits representation of carbon storage within priority areas, as lands of high value for agriculture and carbon storage overlap little. When agricultural lands were included and equally weighted with biodiversity and carbon storage, a balanced representation resulted. Our findings suggest that with appropriate management, South American agroecosystems can significantly contribute to biodiversity conservation. PMID:25143040

A Comparative Study of Simulated and Measured Main Landing Gear Noise for Large Civil Transports

NASA Technical Reports Server (NTRS)

Konig, Benedikt; Fares, Ehab; Ravetta, Patricio; Khorrami, Mehdi R.

2017-01-01

Computational results for the NASA 26%-scale model of a six-wheel main landing gear with and without a toboggan-shaped noise reduction fairing are presented. The model is a high-fidelity representation of a Boeing 777-200 aircraft main landing gear. A lattice Boltzmann method was used to simulate the unsteady flow around the model in isolation. The computations were conducted in free-air at a Mach number of 0.17, matching a recent acoustic test of the same gear model in the Virginia Tech Stability Wind Tunnel in its anechoic configuration. Results obtained on a set of grids with successively finer spatial resolution demonstrate the challenge in resolving/capturing the flow field for the smaller components of the gear and their associated interactions, and the resulting effects on the high-frequency segment of the farfield noise spectrum. Farfield noise spectra were computed based on an FWH integral approach, with simulated pressures on the model solid surfaces or flow-field data extracted on a set of permeable surfaces enclosing the model as input. Comparison of these spectra with microphone array measurements obtained in the tunnel indicated that, for the present complex gear model, the permeable surfaces provide a more accurate representation of farfield noise, suggesting that volumetric effects are not negligible. The present study also demonstrates that good agreement between simulated and measured farfield noise can be achieved if consistent post-processing is applied to both physical and synthetic pressure records at array microphone locations.

Integrating Nutrient Enrichment and Forest Management Experiments in Sweden to Constrain the Process-Based Land Surface Model ORCHIDEE

NASA Astrophysics Data System (ADS)

Resovsky, A.; Luyssaert, S.; Guenet, B.; Peylin, P.; Lansø, A. S.; Vuichard, N.; Messina, P.; Smith, B.; Ryder, J.; Naudts, K.; Chen, Y.; Otto, J.; McGrath, M.; Valade, A.

2017-12-01

Understanding coupling between carbon (C) and nitrogen (N) cycling in forest ecosystems is key to predicting global change. Numerous experimental studies have demonstrated the positive response of stand-level photosynthesis and net primary production (NPP) to atmospheric CO2 enrichment, while N availability has been shown to exert an important control on the timing and magnitude of such responses. However, several factors complicate efforts to precisely represent ecosystem-level C and N cycling in the current generation of land surface models (LSMs), including sparse in-situ data, uncertainty with regard to key state variables and disregard for the effects of natural and anthropogenic forest management. In this study, we incorporate empirical data from N-fertilization experiments at two long-term manipulation sites in Sweden to improve the representation of C and N interaction in the ORCHIDEE land surface model. Our version of the model represents the union of two existing ORCHIDEE branches: 1) ORCHIDEE-CN, which resolves processes related to terrestrial C and N cycling, and 2) ORCHIDEE-CAN, which integrates a multi-layer canopy structure and includes representation of forest management practices. Using this new model branch (referred to as ORCHIDEE-CN-CAN), we aim to replicate the growth patterns of managed forests both with and without N limitations. Our hope is that the results, in combination with measurements of various ecosystem parameters (such as soil N) will facilitate LSM optimization, inform future model development, and reduce structural uncertainty in global change predictions.

Quantifying uncertainties of permafrost carbon-climate feedbacks

NASA Astrophysics Data System (ADS)

Burke, Eleanor J.; Ekici, Altug; Huang, Ye; Chadburn, Sarah E.; Huntingford, Chris; Ciais, Philippe; Friedlingstein, Pierre; Peng, Shushi; Krinner, Gerhard

2017-06-01

The land surface models JULES (Joint UK Land Environment Simulator, two versions) and ORCHIDEE-MICT (Organizing Carbon and Hydrology in Dynamic Ecosystems), each with a revised representation of permafrost carbon, were coupled to the Integrated Model Of Global Effects of climatic aNomalies (IMOGEN) intermediate-complexity climate and ocean carbon uptake model. IMOGEN calculates atmospheric carbon dioxide (CO2) and local monthly surface climate for a given emission scenario with the land-atmosphere CO2 flux exchange from either JULES or ORCHIDEE-MICT. These simulations include feedbacks associated with permafrost carbon changes in a warming world. Both IMOGEN-JULES and IMOGEN-ORCHIDEE-MICT were forced by historical and three alternative future-CO2-emission scenarios. Those simulations were performed for different climate sensitivities and regional climate change patterns based on 22 different Earth system models (ESMs) used for CMIP3 (phase 3 of the Coupled Model Intercomparison Project), allowing us to explore climate uncertainties in the context of permafrost carbon-climate feedbacks. Three future emission scenarios consistent with three representative concentration pathways were used: RCP2.6, RCP4.5 and RCP8.5. Paired simulations with and without frozen carbon processes were required to quantify the impact of the permafrost carbon feedback on climate change. The additional warming from the permafrost carbon feedback is between 0.2 and 12 % of the change in the global mean temperature (ΔT) by the year 2100 and 0.5 and 17 % of ΔT by 2300, with these ranges reflecting differences in land surface models, climate models and emissions pathway. As a percentage of ΔT, the permafrost carbon feedback has a greater impact on the low-emissions scenario (RCP2.6) than on the higher-emissions scenarios, suggesting that permafrost carbon should be taken into account when evaluating scenarios of heavy mitigation and stabilization. Structural differences between the land surface models (particularly the representation of the soil carbon decomposition) are found to be a larger source of uncertainties than differences in the climate response. Inertia in the permafrost carbon system means that the permafrost carbon response depends on the temporal trajectory of warming as well as the absolute amount of warming. We propose a new policy-relevant metric - the frozen carbon residence time (FCRt) in years - that can be derived from these complex land surface models and used to quantify the permafrost carbon response given any pathway of global temperature change.

The role of groundwater in hydrological processes and memory

NASA Astrophysics Data System (ADS)

Lo, Min-Hui

The interactions between soil moisture and groundwater play important roles in controlling Earth's climate, by changing the terrestrial water cycle. However, most contemporary land surface models (LSMs) used for climate modeling lack any representation of groundwater aquifers. In this dissertation, the effects of water table dynamics on the National Center for Atmospheric Research (NCAR) Community Land Model (CLM) and Community Atmosphere Model (CAM) hydrology and land-atmosphere simulations are investigated. First, a simple, lumped unconfined aquifer model is incorporated into the CLM, in which the water table is interactively coupled to the soil moisture through groundwater recharge fluxes. The recent availability of GRACE water storage data provides a unique opportunity to constrain LSMs simulations of terrestrial hydrology. A multi-objective calibration framework using GRACE and streamflow data is developed. This approach improves parameter estimation and reduces the uncertainty of water table simulations in the CLM. Next, experiments are conducted with the off-line CLM to explore the effects of groundwater on land surface memory. Results show that feedbacks of groundwater on land surface memory can be positive, negative, or neutral depending on water table dynamics. The CAM-CLM is further utilized to investigate the effects of water table dynamics on spatial-temporal variations of precipitation. Results indicate that groundwater can increase short-term (seasonal) and long-term (interannual) memory of precipitation for some regions with suitable groundwater table depth. Finally, lower tropospheric water vapor is increased due to the presence of groundwater in the model. However, the impact of groundwater on the spatial distribution of precipitation is not globally homogeneous. In the boreal summer, tropical land regions show a positive (negative) anomaly over the Northern (Southern) Hemisphere. The increased tropical precipitation follows the climatology of the convective zone rather than that of evapotranspiration. In contrast, evapotranspiration is the major contribution to the increased precipitation in the transition climatic zone (e.g., Central North America), where the land and atmosphere are strongly coupled. This dissertation reveals the highly nonlinear responses of precipitation and soil moisture to the groundwater representation in the model, and also underscores the importance of subsurface hydrological memory processes in the climate system.

Photosynthesis sensitivity to climate change in land surface models

NASA Astrophysics Data System (ADS)

Manrique-Sunen, Andrea; Black, Emily; Verhoef, Anne; Balsamo, Gianpaolo

2016-04-01

Accurate representation of vegetation processes within land surface models is key to reproducing surface carbon, water and energy fluxes. Photosynthesis determines the amount of CO2 fixated by plants as well as the water lost in transpiration through the stomata. Photosynthesis is calculated in land surface models using empirical equations based on plant physiological research. It is assumed that CO2 assimilation is either CO2 -limited, radiation -limited ; and in some models export-limited (the speed at which the products of photosynthesis are used by the plant) . Increased levels of atmospheric CO2 concentration tend to enhance photosynthetic activity, but the effectiveness of this fertilization effect is regulated by environmental conditions and the limiting factor in the photosynthesis reaction. The photosynthesis schemes at the 'leaf level' used by land surface models JULES and CTESSEL have been evaluated against field photosynthesis observations. Also, the response of photosynthesis to radiation, atmospheric CO2 and temperature has been analysed for each model, as this is key to understanding the vegetation response that climate models using these schemes are able to reproduce. Particular emphasis is put on the limiting factor as conditions vary. It is found that while at present day CO2 concentrations export-limitation is only relevant at low temperatures, as CO2 levels rise it becomes an increasingly important restriction on photosynthesis.

An analysis of spatial representativeness of air temperature monitoring stations

NASA Astrophysics Data System (ADS)

Liu, Suhua; Su, Hongbo; Tian, Jing; Wang, Weizhen

2018-05-01

Surface air temperature is an essential variable for monitoring the atmosphere, and it is generally acquired at meteorological stations that can provide information about only a small area within an r m radius ( r-neighborhood) of the station, which is called the representable radius. In studies on a local scale, ground-based observations of surface air temperatures obtained from scattered stations are usually interpolated using a variety of methods without ascertaining their effectiveness. Thus, it is necessary to evaluate the spatial representativeness of ground-based observations of surface air temperature before conducting studies on a local scale. The present study used remote sensing data to estimate the spatial distribution of surface air temperature using the advection-energy balance for air temperature (ADEBAT) model. Two target stations in the study area were selected to conduct an analysis of spatial representativeness. The results showed that one station (AWS 7) had a representable radius of about 400 m with a possible error of less than 1 K, while the other station (AWS 16) had the radius of about 250 m. The representable radius was large when the heterogeneity of land cover around the station was small.

A prognostic pollen emissions model for climate models (PECM1.0)

NASA Astrophysics Data System (ADS)

Wozniak, Matthew C.; Steiner, Allison L.

2017-11-01

We develop a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1) a taxa-specific land cover database, phenology, and emission potential, and (2) a plant functional type (PFT) land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.

Diagnosing the Nature of Land-Atmosphere Coupling: A Case Study of Dry/Wet Extremes

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa; Kennedy, Aaron D.

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address deficiencies in numerical weather prediction and climate models due to improper treatment of L-A interactions, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land-PBL coupling at the process-level. In this study, a diagnosis of the nature and impacts oflocalland-atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of2006-7 in the U.S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to NASA's Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation are examined for the dry/wet regimes of this region, along with the behavior and accuracy of different land-PBL scheme couplings under these conditions. In addition, we examine the impact of improved specification ofland surface states, anomalies, and fluxes that are obtained through the use of a hew optimization and uncertainty module in LIS, on the L-A coupling in WRF forecasts. Results demonstrate how LoCo diagnostics can be applied to coupled model components in the context of their integrated impacts on the process-chain connecting the land surface to the PBL and support of hydrological anomalies.

The interactions between soil-biosphere-atmosphere land surface model with a multi-energy balance (ISBA-MEB) option in SURFEXv8 - Part 1: Model description

NASA Astrophysics Data System (ADS)

Boone, Aaron; Samuelsson, Patrick; Gollvik, Stefan; Napoly, Adrien; Jarlan, Lionel; Brun, Eric; Decharme, Bertrand

2017-02-01

Land surface models (LSMs) are pushing towards improved realism owing to an increasing number of observations at the local scale, constantly improving satellite data sets and the associated methodologies to best exploit such data, improved computing resources, and in response to the user community. As a part of the trend in LSM development, there have been ongoing efforts to improve the representation of the land surface processes in the interactions between the soil-biosphere-atmosphere (ISBA) LSM within the EXternalized SURFace (SURFEX) model platform. The force-restore approach in ISBA has been replaced in recent years by multi-layer explicit physically based options for sub-surface heat transfer, soil hydrological processes, and the composite snowpack. The representation of vegetation processes in SURFEX has also become much more sophisticated in recent years, including photosynthesis and respiration and biochemical processes. It became clear that the conceptual limits of the composite soil-vegetation scheme within ISBA had been reached and there was a need to explicitly separate the canopy vegetation from the soil surface. In response to this issue, a collaboration began in 2008 between the high-resolution limited area model (HIRLAM) consortium and Météo-France with the intention to develop an explicit representation of the vegetation in ISBA under the SURFEX platform. A new parameterization has been developed called the ISBA multi-energy balance (MEB) in order to address these issues. ISBA-MEB consists in a fully implicit numerical coupling between a multi-layer physically based snowpack model, a variable-layer soil scheme, an explicit litter layer, a bulk vegetation scheme, and the atmosphere. It also includes a feature that permits a coupling transition of the snowpack from the canopy air to the free atmosphere. It shares many of the routines and physics parameterizations with the standard version of ISBA. This paper is the first of two parts; in part one, the ISBA-MEB model equations, numerical schemes, and theoretical background are presented. In part two (Napoly et al., 2016), which is a separate companion paper, a local scale evaluation of the new scheme is presented along with a detailed description of the new forest litter scheme.

Sensitivity of Climate Simulations to Land-Surface and Atmospheric Boundary-Layer Treatments-A Review.

NASA Astrophysics Data System (ADS)

Garratt, J. R.

1993-03-01

Aspects of the land-surface and boundary-layer treatments in some 20 or so atmospheric general circulation models (GCMS) are summarized. In only a small fraction of these have significant sensitivity studies been carried out and published. Predominantly, the sensitivity studies focus upon the parameterization of land-surface processes and specification of land-surface properties-the most important of these include albedo, roughness length, soil moisture status, and vegetation density. The impacts of surface albedo and soil moisture upon the climate simulated in GCMs with bare-soil land surfaces are well known. Continental evaporation and precipitation tend to decrease with increased albedo and decreased soil moisture availability. For example, results from numerous studies give an average decrease in continental precipitation of 1 mm day1 in response to an average albedo increase of 0.13. Few conclusive studies have been carried out on the impact of a gross roughness-length change-the primary study included an important statistical assessment of the impact upon the mean July climate around the globe of a decreased continental roughness (by three orders of magnitude). For example, such a decrease reduced the precipitation over Amazonia by 1 to 2 mm day1.The inclusion of a canopy scheme in a GCM ensures the combined impacts of roughness (canopies tend to be rougher than bare soil), albedo (canopies tend to be less reflective than bare soil), and soil-moisture availability (canopies prevent the near-surface soil region from drying out and can access the deep soil moisture) upon the simulated climate. The most revealing studies to date involve the regional impact of Amazonian deforestation. The results of four such studies show that replacing tropical forest with a degraded pasture results in decreased evaporation ( 1 mm day1) and precipitation (1-2 mm day1), and increased near-surface air temperatures (2 K).Sensitivity studies as a whole suggest the need for a realistic surface representation in general circulation models of the atmosphere. It is not yet clear how detailed this representation needs to be, but even allowing for the importance of surface processes, the parameterization of boundary-layer and convective clouds probably represents a greater challenge to improved climate simulations. This is illustrated in the case of surface net radiation for Aniazonia, which is not well simulated and tends to be overestimated, leading to evaporation rates that are too large. Underestimates in cloudiness, cloud albedo, and clear-sky shortwave absorption, rather than in surface albedo, appear to be the main culprits.There are three major tasks that confront the researcher so far as the development and validation of atmospheric boundary-layer (ABL) and surface schemes in GCMs are concerned:(i) There is a need to as' critically the impact of `improved' parameterization schemes on WM simulations, taking into account the problem of natural variability and hence the statistical significance of the induced changes.(ii) There is a need to compare GCM simulations of surface and ABL behavior (particularly regarding the diurnal cycle of surface fluxes, air temperature, and ABL depth) with observations over a range of surface types (vegetation, desert, ocean). In this context, area-average values of surface fluxes will be required to calibrate directly the ABL/land-surface scheme in the GCM.(iii) There is a need for intercomparisons of ABL and land-surface schemes used in GCMS, both for one- dimensional stand-alone models and for GCMs that incorporate the respective schemes.

Land-atmosphere coupling manifested in warm-season observations on the U.S. southern great plains

DOE PAGES

Phillips, Thomas J.; Klein, Stephen A.

2014-01-28

This study examines several observational aspects of land-atmosphere coupling on daily average time scales during warm seasons of the years 1997 to 2008 at the Department of Energy Atmospheric Radiation Measurement Program’s Southern Great Plains (SGP) Central Facility site near Lamont, Oklahoma. Characteristics of the local land-atmosphere coupling are inferred by analyzing the covariability of selected land and atmospheric variables that include precipitation and soil moisture, surface air temperature, relative humidity, radiant and turbulent fluxes, as well as low-level cloud base height and fractional coverage. For both the energetic and hydrological aspects of this coupling, it is found that large-scalemore » atmospheric forcings predominate, with local feedbacks of the land on the atmosphere being comparatively small much of the time. The weak land feedbacks are manifested by 1) the inability of soil moisture to comprehensively impact the coupled land-atmosphere energetics, and 2) the limited recycling of local surface moisture under conditions where most of the rainfall derives from convective cells that originate at remote locations. There is some evidence, nevertheless, of the local land feedback becoming stronger as the soil dries out in the aftermath of precipitation events, or on days when the local boundary-layer clouds are influenced by thermal updrafts known to be associated with convection originating at the surface. Finally, we also discuss potential implications of these results for climate-model representation of regional land-atmosphere coupling.« less

Modeling and Observational Framework for Diagnosing Local Land-Atmosphere Coupling on Diurnal Time Scales

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Alonge, Charles; Tao, Wei-Kuo

2009-01-01

Land-atmosphere interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture states. The degree of coupling between the land surface and PBL in numerical weather prediction and climate models remains largely unexplored and undiagnosed due to the complex interactions and feedbacks present across a range of scales. Further, uncoupled systems or experiments (e.g., the Project for Intercomparison of Land Parameterization Schemes, PILPS) may lead to inaccurate water and energy cycle process understanding by neglecting feedback processes such as PBL-top entrainment. In this study, a framework for diagnosing local land-atmosphere coupling is presented using a coupled mesoscale model with a suite of PBL and land surface model (LSM) options along with observations during field experiments in the U. S. Southern Great Plains. Specifically, the Weather Research and Forecasting (WRF) model has been coupled to the Land Information System (LIS), which provides a flexible and high-resolution representation and initialization of land surface physics and states. Within this framework, the coupling established by each pairing of the available PBL schemes in WRF with the LSMs in LIS is evaluated in terms of the diurnal temperature and humidity evolution in the mixed layer. The co-evolution of these variables and the convective PBL is sensitive to and, in fact, integrative of the dominant processes that govern the PBL budget, which are synthesized through the use of mixing diagrams. Results show how the sensitivity of land-atmosphere interactions to the specific choice of PBL scheme and LSM varies across surface moisture regimes and can be quantified and evaluated against observations. As such, this methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

Exclusion of agricultural lands in spatial conservation prioritization strategies: consequences for biodiversity and ecosystem service representation.

PubMed

Durán, América P; Duffy, James P; Gaston, Kevin J

2014-10-07

Agroecosystems have traditionally been considered incompatible with biological conservation goals, and often been excluded from spatial conservation prioritization strategies. The consequences for the representativeness of identified priority areas have been little explored. Here, we evaluate these for biodiversity and carbon storage representation when agricultural land areas are excluded from a spatial prioritization strategy for South America. Comparing different prioritization approaches, we also assess how the spatial overlap of priority areas changes. The exclusion of agricultural lands was detrimental to biodiversity representation, indicating that priority areas for agricultural production overlap with areas of relatively high occurrence of species. By contrast, exclusion of agricultural lands benefits representation of carbon storage within priority areas, as lands of high value for agriculture and carbon storage overlap little. When agricultural lands were included and equally weighted with biodiversity and carbon storage, a balanced representation resulted. Our findings suggest that with appropriate management, South American agroecosystems can significantly contribute to biodiversity conservation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

2014-01-01

Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

Distributed parameterization of complex terrain

NASA Astrophysics Data System (ADS)

Band, Lawrence E.

1991-03-01

This paper addresses the incorporation of high resolution topography, soils and vegetation information into the simulation of land surface processes in atmospheric circulation models (ACM). Recent work has concentrated on detailed representation of one-dimensional exchange processes, implicitly assuming surface homogeneity over the atmospheric grid cell. Two approaches that could be taken to incorporate heterogeneity are the integration of a surface model over distributed, discrete portions of the landscape, or over a distribution function of the model parameters. However, the computational burden and parameter intensive nature of current land surface models in ACM limits the number of independent model runs and parameterizations that are feasible to accomplish for operational purposes. Therefore, simplications in the representation of the vertical exchange processes may be necessary to incorporate the effects of landscape variability and horizontal divergence of energy and water. The strategy is then to trade off the detail and rigor of point exchange calculations for the ability to repeat those calculations over extensive, complex terrain. It is clear the parameterization process for this approach must be automated such that large spatial databases collected from remotely sensed images, digital terrain models and digital maps can be efficiently summarized and transformed into the appropriate parameter sets. Ideally, the landscape should be partitioned into surface units that maximize between unit variance while minimizing within unit variance, although it is recognized that some level of surface heterogeneity will be retained at all scales. Therefore, the geographic data processing necessary to automate the distributed parameterization should be able to estimate or predict parameter distributional information within each surface unit.

Global variability in leaf respiration in relation to climate, plant functional types and leaf traits

Treesearch

Owen K. Atkin; Keith J. Bloomfield; Peter B. Reich; Mark G. Tjoelker; Gregory P. Asner; Damien Bonal; Gerhard Bonisch; Matt G. Bradford; Lucas A. Cernusak; Eric G. Cosio; Danielle Creek; Kristine Y. Crous; Tomas F. Domingues; Jeffrey S. Dukes; John J. G. Egerton; John R. Evans; Graham D. Farquhar; Nikolaos M. Fyllas; Paul P. G. Gauthier; Emanuel Gloor; Teresa E. Gimeno; Kevin L. Griffin; Rossella Guerrieri; Mary A. Heskel; Chris Huntingford; Franc_oise Yoko Ishida; Jens Kattge; Hans Lambers; Michael J. Liddell; Jon Lloyd; Christopher H. Lusk; Roberta E. Martin; Ayal P. Maksimov; Trofim C. Maximov; Yadvinder Malhi; Belinda E. Medlyn; Patrick Meir; Lina M. Mercado; Nicholas Mirotchnick; Desmond Ng; Ulo Niinemets; Odhran S. O’Sullivan; Oliver L. Phillips; Lourens Poorter; Pieter Poot; I. Colin Prentice; Norma Salinas; Lucy M. Rowland; Michael G. Ryan; Stephen Sitch; Martijn Slot; Nicholas G. Smith; Matthew H. Turnbull; Mark C. VanderWel; Fernando Valladares; Erik J. Veneklaas; Lasantha K. Weerasinghe; Christian Wirth; Ian J. Wright; Kirk R. Wythers; Jen Xiang; Shuang Xiang; Joana Zaragoza-Castells

2015-01-01

A challenge for the development of terrestrial biosphere models (TBMs) and associated land surface components of Earth system models (ESMs) is improving representation of carbon (C) exchange between terrestrial plants and the atmosphere, and incorporating biological variation arising from diversity in plant functional types (PFTs) and climate (Sitch et al.,...

Recent land cover changes and sensitivity of the model simulations to various land cover datasets for China

NASA Astrophysics Data System (ADS)

Chen, Liang; Ma, Zhuguo; Mahmood, Rezaul; Zhao, Tianbao; Li, Zhenhua; Li, Yanping

2017-08-01

Reliable land cover data are important for improving numerical simulation by regional climate model, because the land surface properties directly affect climate simulation by partitioning of energy, water and momentum fluxes and by determining temperature and moisture at the interface between the land surface and atmosphere. China has experienced significant land cover change in recent decades and accurate representation of these changes is, hence, essential. In this study, we used a climate model to examine the changes experienced in the regional climate because of the different land cover data in recent decades. Three sets of experiments are performed using the same settings, except for the land use/cover (LC) data for the years 1990, 2000, 2009, and the model default LC data. Three warm season periods are selected, which represented a wet (1998), normal (2000) and a dry year (2011) for China in each set of experiment. The results show that all three sets of land cover experiments simulate a warm bias relative to the control with default LC data for near-surface temperature in summertime in most parts of China. It is especially noticeable in the southwest China and south of the Yangtze River, where significant changes of LC occurred. Deforestation in southwest China and to the south of Yangtze River in the experiment cases may have contributed to the negative precipitation bias relative to the control cases. Large LC changes in northwestern Tibetan Plateau for 2000 and 2009 datasets are also associated with changes in surface temperature, precipitation, and heat fluxes. Wind anomalies and energy budget changes are consistent with the precipitation and temperature changes.

Archetypal Analysis for Sparse Representation-Based Hyperspectral Sub-Pixel Quantification

NASA Astrophysics Data System (ADS)

Drees, L.; Roscher, R.

2017-05-01

This paper focuses on the quantification of land cover fractions in an urban area of Berlin, Germany, using simulated hyperspectral EnMAP data with a spatial resolution of 30m×30m. For this, sparse representation is applied, where each pixel with unknown surface characteristics is expressed by a weighted linear combination of elementary spectra with known land cover class. The elementary spectra are determined from image reference data using simplex volume maximization, which is a fast heuristic technique for archetypal analysis. In the experiments, the estimation of class fractions based on the archetypal spectral library is compared to the estimation obtained by a manually designed spectral library by means of reconstruction error, mean absolute error of the fraction estimates, sum of fractions and the number of used elementary spectra. We will show, that a collection of archetypes can be an adequate and efficient alternative to the spectral library with respect to mentioned criteria.

Modeling the Effects of Irrigation on Land Surface Fluxes and States over the Conterminous United States: Sensitivity to Input Data and Model Parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong; Huang, Maoyi; Tang, Qiuhong

2013-09-16

Previous studies on irrigation impacts on land surface fluxes/states were mainly conducted as sensitivity experiments, with limited analysis of uncertainties from the input data and model irrigation schemes used. In this study, we calibrated and evaluated the performance of irrigation water use simulated by the Community Land Model version 4 (CLM4) against observations from agriculture census. We investigated the impacts of irrigation on land surface fluxes and states over the conterminous United States (CONUS) and explored possible directions of improvement. Specifically, we found large uncertainty in the irrigation area data from two widely used sources and CLM4 tended to producemore » unrealistically large temporal variations of irrigation demand for applications at the water resources region scale over CONUS. At seasonal to interannual time scales, the effects of irrigation on surface energy partitioning appeared to be large and persistent, and more pronounced in dry than wet years. Even with model calibration to yield overall good agreement with the irrigation amounts from the National Agricultural Statistics Service (NASS), differences between the two irrigation area datasets still dominate the differences in the interannual variability of land surface response to irrigation. Our results suggest that irrigation amount simulated by CLM4 can be improved by (1) calibrating model parameter values to account for regional differences in irrigation demand and (2) accurate representation of the spatial distribution and intensity of irrigated areas.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Guoping; Zheng, Jianqiu; Xu, Xiaofeng

Soil organic carbon turnover to CO 2 and CH 4 is sensitive to soil redox potential and pH conditions. But, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model with coupled carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximatelymore » describe the observed pH evolution without additional parameterization. Though Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. Furthermore, the equilibrium speciation predicts a substantial increase in CO 2 solubility as pH increases, and taking into account CO 2 adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, as well as the impacts of pH, temperature, and pressure, the CO 2 production from closed microcosms can be substantially underestimated based on headspace CO 2 measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be incorporated into land surface models to improve climate predictions.« less

Biogeochemical modeling of CO2 and CH4 production in anoxic Arctic soil microcosms

NASA Astrophysics Data System (ADS)

Tang, Guoping; Zheng, Jianqiu; Xu, Xiaofeng; Yang, Ziming; Graham, David E.; Gu, Baohua; Painter, Scott L.; Thornton, Peter E.

2016-09-01

Soil organic carbon turnover to CO2 and CH4 is sensitive to soil redox potential and pH conditions. However, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model with coupled carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximately describe the observed pH evolution without additional parameterization. Although Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. The equilibrium speciation predicts a substantial increase in CO2 solubility as pH increases, and taking into account CO2 adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, as well as the impacts of pH, temperature, and pressure, the CO2 production from closed microcosms can be substantially underestimated based on headspace CO2 measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be incorporated into land surface models to improve climate predictions.

Towards an Improved Represenation of Reservoirs and Water Management in a Land Surface-Hydrology Model

NASA Astrophysics Data System (ADS)

Yassin, F.; Anis, M. R.; Razavi, S.; Wheater, H. S.

2017-12-01

Water management through reservoirs, diversions, and irrigation have significantly changed river flow regimes and basin-wide energy and water balance cycles. Failure to represent these effects limits the performance of land surface-hydrology models not only for streamflow prediction but also for the estimation of soil moisture, evapotranspiration, and feedbacks to the atmosphere. Despite recent research to improve the representation of water management in land surface models, there remains a need to develop improved modeling approaches that work in complex and highly regulated basins such as the 406,000 km2 Saskatchewan River Basin (SaskRB). A particular challenge for regional and global application is a lack of local information on reservoir operational management. To this end, we implemented a reservoir operation, water abstraction, and irrigation algorithm in the MESH land surface-hydrology model and tested it over the SaskRB. MESH is Environment Canada's Land Surface-hydrology modeling system that couples Canadian Land Surface Scheme (CLASS) with hydrological routing model. The implemented reservoir algorithm uses an inflow-outflow relationship that accounts for the physical characteristics of reservoirs (e.g., storage-area-elevation relationships) and includes simplified operational characteristics based on local information (e.g., monthly target volume and release under limited, normal, and flood storage zone). The irrigation algorithm uses the difference between actual and potential evapotranspiration to estimate irrigation water demand. This irrigation demand is supplied from the neighboring reservoirs/diversion in the river system. We calibrated the model enabled with the new reservoir and irrigation modules in a multi-objective optimization setting. Results showed that the reservoir and irrigation modules significantly improved the MESH model performance in generating streamflow and evapotranspiration across the SaskRB and that this our approach provides a basis for improved large scale hydrological modelling.

Testing the Joint UK Land Environment Simulator (JULES) for flood forecasting

NASA Astrophysics Data System (ADS)

Batelis, Stamatios-Christos; Rosolem, Rafael; Han, Dawei; Rahman, Mostaquimur

2017-04-01

Land Surface Models (LSM) are based on physics principles and simulate the exchanges of energy, water and biogeochemical cycles between the land surface and lower atmosphere. Such models are typically applied for climate studies or effects of land use changes but as the resolution of LSMs and supporting observations are continuously increasing, its representation of hydrological processes need to be addressed adequately. For example, changes in climate and land use can alter the hydrology of a region, for instance, by altering its flooding regime. LSMs can be a powerful tool because of their ability to spatially represent a region with much finer resolution. However, despite such advantages, its performance has not been extensively assessed for flood forecasting simply because its representation of typical hydrological processes, such as overland flow and river routing, are still either ignored or roughly represented. In this study, we initially test the Joint UK Land Environment Simulator (JULES) as a flood forecast tool focusing on its river routing scheme. In particular, JULES river routing parameterization is based on the Rapid Flow Model (RFM) which relies on six prescribed parameters (two surface and two subsurface wave celerities, and two return flow fractions). Although this routing scheme is simple, the prescription of its six default parameters is still too generalized. Our aim is to understand the importance of each RFM parameter in a series of JULES simulations at a number of catchments in the UK for the 2006-2015 period. This is carried out, for instance, by making a number of assumptions of parameter behaviour (e.g., spatially uniform versus varying and/or temporally constant or time-varying parameters within each catchment). Hourly rainfall radar in combination with the CHESS (Climate, Hydrological and Ecological research Support System) meteorological daily data both at 1 km2 resolution are used. The evaluation of the model is based on hourly runoff data provided by the National River Flood Archive using a number of model performance metrics. We use a calibrated conceptually-based lumped model, more typically applied in flood studies, as a benchmark for our analysis.

The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations

NASA Astrophysics Data System (ADS)

Walters, David; Boutle, Ian; Brooks, Malcolm; Melvin, Thomas; Stratton, Rachel; Vosper, Simon; Wells, Helen; Williams, Keith; Wood, Nigel; Allen, Thomas; Bushell, Andrew; Copsey, Dan; Earnshaw, Paul; Edwards, John; Gross, Markus; Hardiman, Steven; Harris, Chris; Heming, Julian; Klingaman, Nicholas; Levine, Richard; Manners, James; Martin, Gill; Milton, Sean; Mittermaier, Marion; Morcrette, Cyril; Riddick, Thomas; Roberts, Malcolm; Sanchez, Claudio; Selwood, Paul; Stirling, Alison; Smith, Chris; Suri, Dan; Tennant, Warren; Vidale, Pier Luigi; Wilkinson, Jonathan; Willett, Martin; Woolnough, Steve; Xavier, Prince

2017-04-01

We describe Global Atmosphere 6.0 and Global Land 6.0 (GA6.0/GL6.0): the latest science configurations of the Met Office Unified Model and JULES (Joint UK Land Environment Simulator) land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame (Even Newer Dynamics for General atmospheric modelling of the environment) dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model's physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe GA6.1/GL6.1, which includes a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global numerical weather prediction, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.

Grand challenges in understanding the interplay of climate and land changes

DOE PAGES

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; ...

2017-03-28

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Grand challenges in understanding the interplay of climate and land changes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.

Half of the Earth s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affects a myriad of land surface processes and our adaptation behaviors. We here review the status and major knowledge gaps of studying the interactions of land and atmospheric changes and present eleven grand challenge areas for scientific research and adaptation communities in the coming decade: (1) collective and separate impacts of major land changes and the interactions with non-land-change factors such as atmospheric CO2 increase, (2) carbon and other biogeochemicalmore » cycles, (3) climatically relevant biospheric emissions such as aerosols, (4) water cycle, (5) agriculture, (6) urbanization, (7) gradual acclimation of plants, communities, and ecosystems to climate and environmental changes, (8) plant migration, (9) land use projections, (10) reduction of uncertainties in models and data, and finally (11) adaptation strategies. We conclude that we need to create and maintain a close cross-disciplinary coordination between measurements and process representation in models to analyze complex multi-facet interrelated perturbations and feedbacks between land and climate changes. Along with major scientific research thrusts, land-use and land cover change mitigation and adaptation assessments should be strengthened to identify barriers that need to be overcome, evaluate and prioritize opportunities, and examine how decision making processes work in specific contexts.« less

Improving Numerical Weather Predictions of Summertime Precipitation Over the Southeastern U.S. Through a High-Resolution Initialization of the Surface State

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Krikishen, Jayanthi; Jedlovec, Gary J.

2011-01-01

It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high resolution models. This paper presents model verification results of a case study period from June-August 2008 over the Southeastern U.S. using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the NASA Land Information System (LIS) and sea surface temperature (SST) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spin-up run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer, but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS/MODIS data substantially impact surface and boundary layer properties.

Model developments in TERRA_URB, the upcoming standard urban parametrization of the atmospheric numerical model COSMO(-CLM)

NASA Astrophysics Data System (ADS)

Wouters, Hendrik; Blahak, Ulrich; Helmert, Jürgen; Raschendorfer, Matthias; Demuzere, Matthias; Fay, Barbara; Trusilova, Kristina; Mironov, Dmitrii; Reinert, Daniel; Lüthi, Daniel; Machulskaya, Ekaterina

2015-04-01

In order to address urban climate at the regional scales, a new efficient urban land-surface parametrization TERRA_URB has been developed and coupled to the atmospheric numerical model COSMO-CLM. Hereby, several new advancements for urban land-surface models are introduced which are crucial for capturing the urban surface-energy balance and its seasonal dependency in the mid-latitudes. This includes a new PDF-based water-storage parametrization for impervious land, the representation of radiative absorption and emission by greenhouse gases in the infra-red spectrum in the urban canopy layer, and the inclusion of heat emission from human activity. TERRA_URB has been applied in offline urban-climate studies during European observation campaigns at Basel (BUBBLE), Toulouse (CAPITOUL), and Singapore, and currently applied in online studies for urban areas in Belgium, Germany, Switzerland, Helsinki, Singapore, and Melbourne. Because of its computational efficiency, high accuracy and its to-the-point conceptual easiness, TERRA_URB has been selected to become the standard urban parametrization of the atmospheric numerical model COSMO(-CLM). This allows for better weather forecasts for temperature and precipitation in cities with COSMO, and an improved assessment of urban outdoor hazards in the context of global climate change and urban expansion with COSMO-CLM. We propose additional extensions to TERRA_URB towards a more robust representation of cities over the world including their structural design. In a first step, COSMO's standard EXTernal PARarameter (EXTPAR) tool is updated for representing the cities into the land cover over the entire globe. Hereby, global datasets in the standard EXTPAR tool are used to retrieve the 'Paved' or 'sealed' surface Fraction (PF) referring to the presence of buildings and streets. Furthermore, new global data sets are incorporated in EXTPAR for describing the Anthropogenic Heat Flux (AHF) due to human activity, and optionally the Surface Area Index (SAI) derived from the Floor Space Index (FSI). In a second step, it is focussed on the urban/rural contrast in terms of turbulent transport in the surface layer by means of model sensivity experiments: On the theoretical basis of the TKE-based surface-layer transfer scheme of COSMO, we investigate the consistency between empirical functions for thermal roughness lengths and the urban/rural canopy morphology.

Towards Improved High-Resolution Land Surface Hydrologic Reanalysis Using a Physically-Based Hydrologic Model and Data Assimilation

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Zhang, F.; Duffy, C.; Yu, X.

2014-12-01

A coupled physically based land surface hydrologic model, Flux-PIHM, has been developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Flux-PIHM has been implemented and manually calibrated at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Model predictions of discharge, point soil moisture, point water table depth, sensible and latent heat fluxes, and soil temperature show good agreement with observations. When calibrated only using discharge, and soil moisture and water table depth at one point, Flux-PIHM is able to resolve the observed 101 m scale soil moisture pattern at the Shale Hills watershed when an appropriate map of soil hydraulic properties is provided. A Flux-PIHM data assimilation system has been developed by incorporating EnKF for model parameter and state estimation. Both synthetic and real data assimilation experiments have been performed at the Shale Hills watershed. Synthetic experiment results show that the data assimilation system is able to simultaneously provide accurate estimates of multiple parameters. In the real data experiment, the EnKF estimated parameters and manually calibrated parameters yield similar model performances, but the EnKF method significantly decreases the time and labor required for calibration. The data requirements for accurate Flux-PIHM parameter estimation via data assimilation using synthetic observations have been tested. Results show that by assimilating only in situ outlet discharge, soil water content at one point, and the land surface temperature averaged over the whole watershed, the data assimilation system can provide an accurate representation of watershed hydrology. Observations of these key variables are available with national and even global spatial coverage (e.g., MODIS surface temperature, SMAP soil moisture, and the USGS gauging stations). National atmospheric reanalysis products, soil databases and land cover databases (e.g., NLDAS-2, SSURGO, NLCD) can provide high resolution forcing and input data. Therefore the Flux-PIHM data assimilation system could be readily expanded to other watersheds to provide regional scale land surface and hydrologic reanalysis with high spatial temporal resolution.

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

PubMed

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

Local Climate Changes Forced by Changes in Land Use and topography in the Aburrá Valley, Colombia.

NASA Astrophysics Data System (ADS)

Zapata Henao, M. Z.; Hoyos Ortiz, C. D.

2017-12-01

One of the challenges in the numerical weather models is the adequate representation of soil-vegetation-atmosphere interaction at different spatial scales, including scenarios with heterogeneous land cover and complex mountainous terrain. The interaction determines the energy, mass and momentum exchange at the surface and could affect different variables including precipitation, temperature and wind. In order to quantify the long-term climate impact of changes in local land use and to assess the role of topography, two numerical experiments were examined. The first experiment allows assessing the continuous growth of urban areas within the Aburrá Valley, a complex terrain region located in Colombian Andes. The Weather Research Forecast model (WRF) is used as the basis of the experiment. The basic setup involves two nested domains, one representing the continental scale (18 km) and the other the regional scale (2 km). The second experiment allows drastic topography modification, including changing the valley configuration to a plateau. The control run for both experiments corresponds to a climatological scenario. In both experiments the boundary conditions correspond to the climatological continental domain output. Surface temperature, surface winds and precipitation are used as the main variables to compare both experiments relative to the control run. The results of the first experiment show a strong relationship between land cover and the variables, specially for surface temperature and wind speed, due to the strong forcing land cover imposes on the albedo, heat capacity and surface roughness, changing temperature and wind speed magnitudes. The second experiment removes the winds spatial variability related with hill slopes, the direction and magnitude are modulated only by the trade winds and roughness of land cover.

Addressing numerical challenges in introducing a reactive transport code into a land surface model: A biogeochemical modeling proof-of-concept with CLM-PFLOTRAN 1.0: Modeling Archive

DOE Data Explorer

Tang, G.; Andre, B.; Hoffman, F. M.; Painter, S. L.; Thornton, P. E.; Yuan, F.; Bisht, G.; Hammond, G. E.; Lichtner, P. C.; Kumar, J.; Mills, R. T.; Xu, X.

2016-04-19

This Modeling Archive is in support of an NGEE Arctic discussion paper under review and available at doi:10.5194/gmd-9-927-2016. The purpose is to document the simulations to allow verification, reproducibility, and follow-up studies. This dataset contains shell scripts to create the CLM-PFLOTRAN cases, specific input files for PFLOTRAN and CLM, outputs, and python scripts to make the figures using the outputs in the publication. Through these results, we demonstrate that CLM-PFLOTRAN can approximately reproduce CLM results in selected cases for the Arctic, temperate and tropic sites. In addition, the new framework facilitates mechanistic representations of soil biogeochemistry processes in the land surface model.

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaCasse, Katherine M.; Santanello, Joseph A., Jr.; Lapenta, William M.; Petars-Lidard, Christa D.

2007-01-01

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

Evaluating runoff simulations from the Community Land Model 4.0 using observations from flux towers and a mountainous watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Hongyi; Huang, Maoyi; Wigmosta, Mark S.

2011-12-24

Previous studies using the Community Land Model (CLM) focused on simulating landatmosphere interactions and water balance at continental to global scales, with limited attention paid to its capability for hydrologic simulations at watershed or regional scales. This study evaluates the performance of CLM 4.0 (CLM4) for hydrologic simulations, and explores possible directions of improvement. Specifically, it is found that CLM4 tends to produce unrealistically large temporal variation of runoff for applications at a mountainous catchment in the Northwest United States where subsurface runoff is dominant, as well as at a few flux tower sites. We show that runoff simulations frommore » CLM4 can be improved by: (1) increasing spatial resolution of the land surface representations; (2) calibrating parameter values; (3) replacing the subsurface formulation with a more general nonlinear function; (4) implementing the runoff generation schemes from the Variability Infiltration Capacity (VIC) model. This study also highlights the importance of evaluating both the energy and water fluxes application of land surface models across multiple scales.« less

Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

Treesearch

Congsheng Fu; Guiling Wang; Michael L. Goulden; Russell L. Scott; Kenneth Bible; Zoe G. Cardon

2016-01-01

Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) have done cross-site...

A representation of the phosphorus cycle for ORCHIDEE (revision 4520)

NASA Astrophysics Data System (ADS)

Goll, Daniel S.; Vuichard, Nicolas; Maignan, Fabienne; Jornet-Puig, Albert; Sardans, Jordi; Violette, Aurelie; Peng, Shushi; Sun, Yan; Kvakic, Marko; Guimberteau, Matthieu; Guenet, Bertrand; Zaehle, Soenke; Penuelas, Josep; Janssens, Ivan; Ciais, Philippe

2017-10-01

Land surface models rarely incorporate the terrestrial phosphorus cycle and its interactions with the carbon cycle, despite the extensive scientific debate about the importance of nitrogen and phosphorus supply for future land carbon uptake. We describe a representation of the terrestrial phosphorus cycle for the ORCHIDEE land surface model, and evaluate it with data from nutrient manipulation experiments along a soil formation chronosequence in Hawaii. ORCHIDEE accounts for the influence of the nutritional state of vegetation on tissue nutrient concentrations, photosynthesis, plant growth, biomass allocation, biochemical (phosphatase-mediated) mineralization, and biological nitrogen fixation. Changes in the nutrient content (quality) of litter affect the carbon use efficiency of decomposition and in return the nutrient availability to vegetation. The model explicitly accounts for root zone depletion of phosphorus as a function of root phosphorus uptake and phosphorus transport from the soil to the root surface. The model captures the observed differences in the foliage stoichiometry of vegetation between an early (300-year) and a late (4.1 Myr) stage of soil development. The contrasting sensitivities of net primary productivity to the addition of either nitrogen, phosphorus, or both among sites are in general reproduced by the model. As observed, the model simulates a preferential stimulation of leaf level productivity when nitrogen stress is alleviated, while leaf level productivity and leaf area index are stimulated equally when phosphorus stress is alleviated. The nutrient use efficiencies in the model are lower than observed primarily due to biases in the nutrient content and turnover of woody biomass. We conclude that ORCHIDEE is able to reproduce the shift from nitrogen to phosphorus limited net primary productivity along the soil development chronosequence, as well as the contrasting responses of net primary productivity to nutrient addition.

Biogeochemical modeling of CO 2 and CH 4 production in anoxic Arctic soil microcosms

DOE PAGES

Tang, Guoping; Zheng, Jianqiu; Xu, Xiaofeng; ...

2016-09-12

Soil organic carbon turnover to CO 2 and CH 4 is sensitive to soil redox potential and pH conditions. But, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model with coupled carbon and nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximatelymore » describe the observed pH evolution without additional parameterization. Though Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. Furthermore, the equilibrium speciation predicts a substantial increase in CO 2 solubility as pH increases, and taking into account CO 2 adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, as well as the impacts of pH, temperature, and pressure, the CO 2 production from closed microcosms can be substantially underestimated based on headspace CO 2 measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be incorporated into land surface models to improve climate predictions.« less

Improving Permafrost Hydrology Prediction Through Data-Model Integration

NASA Astrophysics Data System (ADS)

Wilson, C. J.; Andresen, C. G.; Atchley, A. L.; Bolton, W. R.; Busey, R.; Coon, E.; Charsley-Groffman, L.

2017-12-01

The CMIP5 Earth System Models were unable to adequately predict the fate of the 16GT of permafrost carbon in a warming climate due to poor representation of Arctic ecosystem processes. The DOE Office of Science Next Generation Ecosystem Experiment, NGEE-Arctic project aims to reduce uncertainty in the Arctic carbon cycle and its impact on the Earth's climate system by improved representation of the coupled physical, chemical and biological processes that drive how much buried carbon will be converted to CO2 and CH4, how fast this will happen, which form will dominate, and the degree to which increased plant productivity will offset increased soil carbon emissions. These processes fundamentally depend on permafrost thaw rate and its influence on surface and subsurface hydrology through thermal erosion, land subsidence and changes to groundwater flow pathways as soil, bedrock and alluvial pore ice and massive ground ice melts. LANL and its NGEE colleagues are co-developing data and models to better understand controls on permafrost degradation and improve prediction of the evolution of permafrost and its impact on Arctic hydrology. The LANL Advanced Terrestrial Simulator was built using a state of the art HPC software framework to enable the first fully coupled 3-dimensional surface-subsurface thermal-hydrology and land surface deformation simulations to simulate the evolution of the physical Arctic environment. Here we show how field data including hydrology, snow, vegetation, geochemistry and soil properties, are informing the development and application of the ATS to improve understanding of controls on permafrost stability and permafrost hydrology. The ATS is being used to inform parameterizations of complex coupled physical, ecological and biogeochemical processes for implementation in the DOE ACME land model, to better predict the role of changing Arctic hydrology on the global climate system. LA-UR-17-26566.

Exploring the Influence of Topography on Belowground C Processes Using a Coupled Hydrologic-Biogeochemical Model

NASA Astrophysics Data System (ADS)

Shi, Y.; Davis, K. J.; Eissenstat, D. M.; Kaye, J. P.; Duffy, C.; Yu, X.; He, Y.

2014-12-01

Belowground carbon processes are affected by soil moisture and soil temperature, but current biogeochemical models are 1-D and cannot resolve topographically driven hill-slope soil moisture patterns, and cannot simulate the nonlinear effects of soil moisture on carbon processes. Coupling spatially-distributed physically-based hydrologic models with biogeochemical models may yield significant improvements in the representation of topographic influence on belowground C processes. We will couple the Flux-PIHM model to the Biome-BGC (BBGC) model. Flux-PIHM is a coupled physically-based land surface hydrologic model, which incorporates a land-surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater, Flux-PIHM is able to represent the link between groundwater and the surface energy balance, as well as the land surface heterogeneities caused by topography. The coupled Flux-PIHM-BBGC model will be tested at the Susquehanna/Shale Hills critical zone observatory (SSHCZO). The abundant observations, including eddy covariance fluxes, soil moisture, groundwater level, sap flux, stream discharge, litterfall, leaf area index, above ground carbon stock, and soil carbon efflux, make SSHCZO an ideal test bed for the coupled model. In the coupled model, each Flux-PIHM model grid will couple a BBGC cell. Flux-PIHM will provide BBGC with soil moisture and soil temperature information, while BBGC provides Flux-PIHM with leaf area index. Preliminary results show that when Biome- BGC is driven by PIHM simulated soil moisture pattern, the simulated soil carbon is clearly impacted by topography.

Introducing the MIT Regional Climate Model (MRCM)

NASA Astrophysics Data System (ADS)

Eltahir, Elfatih A. B.; Winter, Jonathn M.; Marcella, Marc P.; Gianotti, Rebecca L.; Im, Eun-Soon

2013-04-01

During the last decade researchers at MIT have worked on improving the skill of Regional Climate Model version 3 (RegCM3) in simulating climate over different regions through the incorporation of new physical schemes or modification of original schemes. The MIT Regional Climate Model (MRCM) features several modifications over RegCM3 including coupling of Integrated Biosphere Simulator (IBIS), a new surface albedo assignment method, a new convective cloud and rainfall auto-conversion scheme, and a modified boundary layer height and cloud scheme. Here, we introduce the MRCM and briefly describe the major model modifications relative to RegCM3 and their impact on the model performance. The most significant difference relative to the RegCM3 original configuration is coupling the Integrated Biosphere Simulator (IBIS) land-surface scheme (Winter et al., 2009). Based on the simulations using IBIS over the North America, the Maritime Continent, Southwest Asia and West Africa, we demonstrate that the use of IBIS as the land surface scheme results in better representation of surface energy and water budgets in comparison to BATS. Furthermore, the addition of a new irrigation scheme to IBIS makes it possible to investigate the effects of irrigation over any region. Also a new surface albedo assignment method used together with IBIS brings further improvement in simulations of surface radiation (Marcella and Eltahir, 2013). Another important feature of the MRCM is the introduction of a new convective cloud and rainfall auto-conversion scheme (Gianotti and Eltahir, 2013). This modification brings more physical realism into an important component of the model, and succeeds in simulating convective-radiative feedback improving model performance across several radiation fields and rainfall characteristics. Other features of MRCM such as the modified boundary layer height and cloud scheme, and the improvements in the dust emission and transport representations will be discussed.

Improved global simulation of groundwater-ecosystem interactions via tight coupling of a dynamic global ecosystem model and a global hydrological model

NASA Astrophysics Data System (ADS)

Braakhekke, Maarten; Rebel, Karin; Dekker, Stefan; Smith, Benjamin; Sutanudjaja, Edwin; van Beek, Rens; van Kampenhout, Leo; Wassen, Martin

2017-04-01

In up to 30% of the global land surface ecosystems are potentially influenced by the presence of a shallow groundwater table. In these regions upward water flux by capillary rise increases soil moisture availability in the root zone, which has a strong effect on evapotranspiration, vegetation dynamics, and fluxes of carbon and nitrogen. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure, and biogeochemical processes and are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB, which explicitly simulates groundwater dynamics. This coupled model allows us to explicitly account for groundwater effects on terrestrial ecosystem processes at global scale. Results of global simulations indicate that groundwater strongly influences fluxes of water, carbon and nitrogen, in many regions, adding up to a considerable effect at the global scale.

Impact of Land Use/Land Cover Conditions on WRF Model Evaluation for Heat Island Assessment

NASA Astrophysics Data System (ADS)

Bhati, S.; Mohan, M.

2017-12-01

Urban heat island effect has been assessed using Weather Research and Forecasting model (WRF v3.5) focusing on air temperature and surface skin temperature in the sub-tropical urban Indian megacity of Delhi. Impact of urbanization related changes in land use/land cover (LULC) on model outputs has been analyzed. Four simulations have been carried out with different types of LULC data viz. (1) USGS , (2) MODIS, (3) user-modified USGS and (4) user modified land use data coupled with urban canopy model (UCM) for incorporation of canopy features. Heat island intensities have been estimated based on these simulations and subsequently compared with those derived from in-situ and satellite observations. There is a significant improvement in model performance with modification of LULC and inclusion of UCM. Overall, RMSEs for near surface temperature improved from 6.3°C to 3.9°C and index of agreement for mean urban heat island intensities (UHI) improved from 0.4 to 0.7 with modified land use coupled with UCM. In general, model is able to capture the magnitude of UHI as well as high UHI zones well. The study highlights the importance of appropriate and updated representation of landuse-landcover and urban canopies for improving predictive capabilities of the mesoscale models.

Improved prediction of severe thunderstorms over the Indian Monsoon region using high-resolution soil moisture and temperature initialization

PubMed Central

Osuri, K. K.; Nadimpalli, R.; Mohanty, U. C.; Chen, F.; Rajeevan, M.; Niyogi, D.

2017-01-01

The hypothesis that realistic land conditions such as soil moisture/soil temperature (SM/ST) can significantly improve the modeling of mesoscale deep convection is tested over the Indian monsoon region (IMR). A high resolution (3 km foot print) SM/ST dataset prepared from a land data assimilation system, as part of a national monsoon mission project, showed close agreement with observations. Experiments are conducted with (LDAS) and without (CNTL) initialization of SM/ST dataset. Results highlight the significance of realistic land surface conditions on numerical prediction of initiation, movement and timing of severe thunderstorms as compared to that currently being initialized by climatological fields in CNTL run. Realistic land conditions improved mass flux, convective updrafts and diabatic heating in the boundary layer that contributed to low level positive potential vorticity. The LDAS run reproduced reflectivity echoes and associated rainfall bands more efficiently. Improper representation of surface conditions in CNTL run limit the evolution boundary layer processes and thereby failed to simulate convection at right time and place. These findings thus provide strong support to the role land conditions play in impacting the deep convection over the IMR. These findings also have direct implications for improving heavy rain forecasting over the IMR, by developing realistic land conditions. PMID:28128293

Review: the atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Garratt, J. R.

1994-10-01

An overview is given of the atmospheric boundary layer (ABL) over both continental and ocean surfaces, mainly from observational and modelling perspectives. Much is known about ABL structure over homogeneous land surfaces, but relatively little so far as the following are concerned, (i) the cloud-topped ABL (over the sea predominantly); (ii) the strongly nonhomogeneous and nonstationary ABL; (iii) the ABL over complex terrain. These three categories present exciting challenges so far as improved understanding of ABL behaviour and improved representation of the ABL in numerical models of the atmosphere are concerned.

Modification of land-atmosphere interactions by CO2 effects: Implications for summer dryness and heat wave amplitude

NASA Astrophysics Data System (ADS)

Lemordant, Léo.; Gentine, Pierre; Stéfanon, Marc; Drobinski, Philippe; Fatichi, Simone

2016-10-01

Plant stomata couple the energy, water, and carbon cycles. We use the framework of Regional Climate Modeling to simulate the 2003 European heat wave and assess how higher levels of surface CO2 may affect such an extreme event through land-atmosphere interactions. Increased CO2 modifies the seasonality of the water cycle through stomatal regulation and increased leaf area. As a result, the water saved during the growing season through higher water use efficiency mitigates summer dryness and the heat wave impact. Land-atmosphere interactions and CO2 fertilization together synergistically contribute to increased summer transpiration. This, in turn, alters the surface energy budget and decreases sensible heat flux, mitigating air temperature rise. Accurate representation of the response to higher CO2 levels and of the coupling between the carbon and water cycles is therefore critical to forecasting seasonal climate, water cycle dynamics, and to enhance the accuracy of extreme event prediction under future climate.

Impacts of Soil-aquifer Heat and Water Fluxes on Simulated Global Climate

NASA Technical Reports Server (NTRS)

Krakauer, N.Y.; Puma, Michael J.; Cook, B. I.

2013-01-01

Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in landsurface temperature, and decrease the soil moisture memory of the land surface on seasonal to annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.

The managed clearing: An overlooked land-cover type in urbanizing regions?

PubMed Central

Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K.

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems. PMID:29432442

The managed clearing: An overlooked land-cover type in urbanizing regions?

PubMed

Singh, Kunwar K; Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type-semi-natural, vegetated land surfaces with varying degrees of management practices-for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area- 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems.

Simulated Climate Impacts of Mexico City's Historical Urban Expansion

NASA Astrophysics Data System (ADS)

Benson-Lira, Valeria

Urbanization, a direct consequence of land use and land cover change, is responsible for significant modification of local to regional scale climates. It is projected that the greatest urban growth of this century will occur in urban areas in the developing world. In addition, there is a significant research gap in emerging nations concerning this topic. Thus, this research focuses on the assessment of climate impacts related to urbanization on the largest metropolitan area in Latin America: Mexico City. Numerical simulations using a state-of-the-science regional climate model are utilized to address a trio of scientifically relevant questions with wide global applicability. The importance of an accurate representation of land use and land cover is first demonstrated through comparison of numerical simulations against observations. Second, the simulated effect of anthropogenic heating is quantified. Lastly, numerical simulations are performed using pre-historic scenarios of land use and land cover to examine and quantify the impact of Mexico City's urban expansion and changes in surface water features on its regional climate.

Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes

NASA Astrophysics Data System (ADS)

Ekici, A.; Chadburn, S.; Chaudhary, N.; Hajdu, L. H.; Marmy, A.; Peng, S.; Boike, J.; Burke, E.; Friend, A. D.; Hauck, C.; Krinner, G.; Langer, M.; Miller, P. A.; Beer, C.

2015-07-01

Modeling soil thermal dynamics at high latitudes and altitudes requires representations of physical processes such as snow insulation, soil freezing and thawing and subsurface conditions like soil water/ice content and soil texture. We have compared six different land models: JSBACH, ORCHIDEE, JULES, COUP, HYBRID8 and LPJ-GUESS, at four different sites with distinct cold region landscape types, to identify the importance of physical processes in capturing observed temperature dynamics in soils. The sites include alpine, high Arctic, wet polygonal tundra and non-permafrost Arctic, thus showing how a range of models can represent distinct soil temperature regimes. For all sites, snow insulation is of major importance for estimating topsoil conditions. However, soil physics is essential for the subsoil temperature dynamics and thus the active layer thicknesses. This analysis shows that land models need more realistic surface processes, such as detailed snow dynamics and moss cover with changing thickness and wetness, along with better representations of subsoil thermal dynamics.

Integration of satellite-induced fluorescence and vegetation optical depth to improve the retrieval of land evaporation

NASA Astrophysics Data System (ADS)

Pagán, B. R.; Martens, B.; Maes, W. H.; Miralles, D. G.

2017-12-01

Global satellite-based data sets of land evaporation overcome limitations in coverage of in situ measurements while retaining some observational nature. Although their potential for real world applications are promising, their value during dry conditions is still poorly understood. Most evaporation retrieval algorithms are not directly sensitive to soil moisture. An exception is the Global Land Evaporation Amsterdam Model (GLEAM), which uses satellite surface soil moisture and precipitation to account for land water availability. The existing methodology may greatly benefit from the optimal integration of novel observations of the land surface. Microwave vegetation optical depth (VOD) and near-infrared solar-induced fluorescence (SIF) are expected to reflect different aspects of evaporative stress. While the former is considered to be a proxy of vegetation water content, the latter is indicative of the activity of photosynthetic machinery. As stomata regulate both photosynthesis and transpiration, we expect a relationship between SIF and transpiration. An important motivation to incorporate observations in land evaporation calculations is that plant transpiration - usually the largest component of the flux - is extremely challenging to model due to species-dependent responses to drought. Here we present an innovative integration of VOD and SIF into the GLEAM evaporative stress function. VOD is utilized as a measurement of isohydricity to improve the representation of species specific drought responses. SIF is used for transpiration modelling, a novel application, and standardized by incoming solar radiation to better account for radiation-limited periods. Results are validated with global FLUXNET and International Soil Moisture Network data and demonstrate that the incorporation of VOD and SIF can yield accurate estimates of transpiration over large-scales, which are essential to further understand ecosystem-atmosphere feedbacks and the response of terrestrial hydrology and ecology to meteorological drought. The resulting retrievals of land evaporation can be used to benchmark climate model representation of turbulent fluxes, at a time when these models still consider water stress rudimentarily, and typically assume the same sensitivity for all vegetation types to drought stress.

Effects of spatial resolution and landscape structure on land cover characterization

NASA Astrophysics Data System (ADS)

Yang, Wenli

This dissertation addressed problems in scaling, problems that are among the main challenges in remote sensing. The principal objective of the research was to investigate the effects of changing spatial scale on the representation of land cover. A second objective was to determine the relationship between such effects, characteristics of landscape structure and scaling procedures. Four research issues related to spatial scaling were examined. They included: (1) the upscaling of Normalized Difference Vegetation Index (NDVI); (2) the effects of spatial scale on indices of landscape structure; (3) the representation of land cover databases at different spatial scales; and (4) the relationships between landscape indices and land cover area estimations. The overall bias resulting from non-linearity of NDVI in relation to spatial resolution is generally insignificant as compared to other factors such as influences of aerosols and water vapor. The bias is, however, related to land surface characteristics. Significant errors may be introduced in heterogeneous areas where different land cover types exhibit strong spectral contrast. Spatially upscaled SPOT and TM NDVIs have information content comparable with the AVHRR-derived NDVI. Indices of landscape structure and spatial resolution are generally related, but the exact forms of the relationships are subject to changes in other factors including the basic patch unit constituting a landscape and the proportional area of foreground land cover under consideration. The extent of agreement between spatially aggregated coarse resolution land cover datasets and full resolution datasets changes with the properties of the original datasets, including the pixel size and class definition. There are close relationships between landscape structure and class areas estimated from spatially aggregated land cover databases. The relationships, however, do not permit extension from one area to another. Inversion calibration across different geographic/ecological areas is, therefore, not feasible. Different rules govern the land cover area changes across resolutions when different upscaling methods are used. Special attention should be given to comparison between land cover maps derived using different methods.

Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2017-12-01

Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.Above results are discussed in a peer-review paper just being accepted for publication on Climate Dynamics (Alessandri et al., 2017; doi:10.1007/s00382-017-3766-y).

Evaluation of hydrologic components of community land model 4 and bias identification

DOE PAGES

Du, Enhao; Vittorio, Alan Di; Collins, William D.

2015-04-01

Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. Here, we have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties inmore » the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Finally, our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation.« less

Refining multi-model projections of temperature extremes by evaluation against land-atmosphere coupling diagnostics

NASA Astrophysics Data System (ADS)

Sippel, Sebastian; Zscheischler, Jakob; Mahecha, Miguel D.; Orth, Rene; Reichstein, Markus; Vogel, Martha; Seneviratne, Sonia I.

2017-05-01

The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter. This coupled behaviour causes various land-atmosphere feedbacks, and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in midlatitude regions has been identified empirically for high-impact heat waves, but individual climate models differ widely in their respective representation of land-atmosphere coupling. Here, we compile an ensemble of 54 combinations of observations-based temperature (T) and evapotranspiration (ET) benchmarking datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land-atmosphere interactions during periods of anomalously warm temperatures. First, we demonstrate that a large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5) archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round. These coincidences (high T, low ET) are closely related to the representation of temperature variability and extremes across the multi-model ensemble. Second, we derive a land-coupling constraint based on the spread of the T-ET datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these benchmark estimates. The constrained multi-model simulations exhibit more realistic temperature extremes of reduced magnitude in present climate in regions where models show substantial spread in T-ET coupling, i.e. biases in the model ensemble are consistently reduced. Also the multi-model simulations for the coming decades display decreased absolute temperature extremes in the constrained ensemble. On the other hand, the differences between projected and present-day climate extremes are affected to a lesser extent by the applied constraint, i.e. projected changes are reduced locally by around 0.5 to 1 °C - but this remains a local effect in regions that are highly sensitive to land-atmosphere coupling. In summary, our approach offers a physically consistent, diagnostic-based avenue to evaluate multi-model ensembles and subsequently reduce model biases in simulated and projected extreme temperatures.

Modeling alpine grasslands with two integrated hydrologic models: a comparison of the different process representation in CATHY and GEOtop

NASA Astrophysics Data System (ADS)

Camporese, M.; Bertoldi, G.; Bortoli, E.; Wohlfahrt, G.

2017-12-01

Integrated hydrologic surface-subsurface models (IHSSMs) are increasingly used as prediction tools to solve simultaneously states and fluxes in and between multiple terrestrial compartments (e.g., snow cover, surface water, groundwater), in an attempt to tackle environmental problems in a holistic approach. Two such models, CATHY and GEOtop, are used in this study to investigate their capabilities to reproduce hydrological processes in alpine grasslands. The two models differ significantly in the complexity of the representation of the surface energy balance and the solution of Richards equation for water flow in the variably saturated subsurface. The main goal of this research is to show how these differences in process representation can lead to different predictions of hydrologic states and fluxes, in the simulation of an experimental site located in the Venosta Valley (South Tyrol, Italy). Here, a large set of relevant hydrological data (e.g., evapotranspiration, soil moisture) has been collected, with ground and remote sensing observations. The area of interest is part of a Long-Term Ecological Research (LTER) site, a mountain steep, heterogeneous slope, where the predominant land use types are meadow, pasture, and forest. The comparison between data and model predictions, as well as between simulations with the two IHSSMs, contributes to advance our understanding of the tradeoffs between different complexities in modeĺs process representation, model accuracy, and the ability to explain observed hydrological dynamics in alpine environments.

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Miao; Wang, Guiling; Chen, Haishan

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE PAGES

Yu, Miao; Wang, Guiling; Chen, Haishan

2016-03-01

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less

Using dry spell dynamics of land surface temperature to evaluate large-scale model representation of soil moisture control on evapotranspiration

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Harris, Philip P.; Gallego-Elvira, Belen; Folwell, Sonja S.

2017-04-01

The soil moisture control on the partition of land surface fluxes between sensible and latent heat is a key aspect of land surface models used within numerical weather prediction and climate models. As soils dry out, evapotranspiration (ET) decreases, and the excess energy is used to warm the atmosphere. Poor simulations of this dynamic process can affect predictions of mean, and in particular, extreme air temperatures, and can introduce substantial biases into projections of climate change at regional scales. The lack of reliable observations of fluxes and root zone soil moisture at spatial scales that atmospheric models use (typically from 1 to several hundred kilometres), coupled with spatial variability in vegetation and soil properties, makes it difficult to evaluate the flux partitioning at the model grid box scale. To overcome this problem, we have developed techniques to use Land Surface Temperature (LST) to evaluate models. As soils dry out, LST rises, so it can be used under certain circumstances as a proxy for the partition between sensible and latent heat. Moreover, long time series of reliable LST observations under clear skies are available globally at resolutions of the order of 1km. Models can exhibit large biases in seasonal mean LST for various reasons, including poor description of aerodynamic coupling, uncertainties in vegetation mapping, and errors in down-welling radiation. Rather than compare long-term average LST values with models, we focus on the dynamics of LST during dry spells, when negligible rain falls, and the soil moisture store is drying out. The rate of warming of the land surface, or, more precisely, its warming rate relative to the atmosphere, emphasises the impact of changes in soil moisture control on the surface energy balance. Here we show the application of this approach to model evaluation, with examples at continental and global scales. We can compare the behaviour of both fully-coupled land-atmosphere models, and land surface models forced by observed meteorology. This approach provides insight into a fundamental process that affects predictions on multiple time scales, and which has an important impact for society.

The UKC2 regional coupled prediction system

NASA Astrophysics Data System (ADS)

Castillo, Juan; Lewis, Huw; Graham, Jennifer; Saulter, Andrew; Arnold, Alex; Fallmann, Joachim; Martinez de la Torre, Alberto; Blyth, Eleanor; Bricheno, Lucy

2017-04-01

It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather through the environment, requires a more integrated approach to forecasting. This approach also delivers research benefits through providing tools with which to explore the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land. This hypothesis is being tested in a UK regional context at km-scale through the UK Environmental Prediction Project. This presentation will provide an introduction to the UKC2 UK Environmental Prediction research system. This incorporates models of the atmosphere (Met Office Unified Model), land surface (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled (via OASIS3-MCT libraries) at unprecedentedly high resolution across the UK and the wider north-west European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a unique new research tool for UK environmental science. The presentation will highlight work undertaken to review and improve the computational cost of running these systems for efficient research application. Research will be presented highlighting case study evaluation on the sensitivity of the ocean and surface waves to the representation of feedbacks to the atmosphere, and on the sensitivity of weather systems and boundary layer cloud development to the exchange of heat and momentum at the ocean surface modified through sea surface temperature and wave-induced roughness. The presentation will discuss plans for future development through UKC3 and beyond.

The Impacts of Urbanization on Meteorology and Air Quality in the Los Angeles Basin

NASA Astrophysics Data System (ADS)

Li, Y.; Zhang, J.; Sailor, D.; Ban-Weiss, G. A.

2017-12-01

Urbanization has a profound influence on regional meteorology in mega cities like Los Angeles. This influence is driven by changes in land surface physical properties and urban processes, and their corresponding influence on surface-atmosphere coupling. Changes in meteorology from urbanization in turn influences air quality through weather-dependent chemical reaction, pollutant dispersion, etc. Hence, a real-world representation of the urban land surface properties and urban processes should be accurately resolved in regional climate-chemistry models for better understanding the role of urbanization on changing urban meteorology and associated pollutant dynamics. By incorporating high-resolution land surface data, previous research has improved model-observation comparisons of meteorology in urban areas including the Los Angeles basin, and indicated that historical urbanization has increased urban temperatures and altered wind flows significantly. However, the impact of urban expansion on air quality has been less studied. Thus, in this study, we aim to evaluate the effectiveness of resolving high-resolution heterogeneity in urban land surface properties and processes for regional weather and pollutant concentration predictions. We coupled the Weather Research and Forecasting model with Chemistry to the single-layer Urban Canopy Model to simulate a typical summer period in year 2012 for Southern California. Land cover type and urban fraction were determined from National Land Cover Data. MODIS observations were used to determine satellite-derived albedo, green vegetation fraction, and leaf area index. Urban morphology was determined from GIS datasets of 3D building geometries. An urban irrigation scheme was also implemented in the model. Our results show that the improved model captures the diurnal cycle of 2m air temperature (T2) and Ozone (O3) concentrations. However, it tends to overestimate wind speed and underestimate T2, which leads to an underestimation of O3 and fine particulate matter concentrations. By comparing simulations assuming current land cover of the Los Angeles basin versus pre-urbanization land cover, we find that land cover change through urbanization has led to important shifts in regional air pollution via the aforementioned physical and chemical mechanisms.

Disagreement between Hydrological and Land Surface models on the water budgets in the Arctic: why is this and which of them is right?

NASA Astrophysics Data System (ADS)

Blyth, E.; Martinez-de la Torre, A.; Ellis, R.; Robinson, E.

2017-12-01

The fresh-water budget of the Artic region has a diverse range of impacts: the ecosystems of the region, ocean circulation response to Arctic freshwater, methane emissions through changing wetland extent as well as the available fresh water for human consumption. But there are many processes that control the budget including a seasonal snow packs building and thawing, freezing soils and permafrost, extensive organic soils and large wetland systems. All these processes interact to create a complex hydrological system. In this study we examine a suite of 10 models that bring all those processes together in a 25 year reanalysis of the global water budget. We assess their performance in the Arctic region. There are two approaches to modelling fresh-water flows at large scales, referred to here as `Hydrological' and `Land Surface' models. While both approaches include a physically based model of the water stores and fluxes, the Land Surface models links the water flows to an energy-based model for processes such as snow melt and soil freezing. This study will analyse the impact of that basic difference on the regional patterns of evapotranspiration, runoff generation and terrestrial water storage. For the evapotranspiration, the Hydrological models tend to have a bigger spatial range in the model bias (difference to observations), implying greater errors compared to the Land-Surface models. For instance, some regions such as Eastern Siberia have consistently lower Evaporation in the Hydrological models than the Land Surface models. For the Runoff however, the results are the other way round with a slightly higher spatial range in bias for the Land Surface models implying greater errors than the Hydrological models. A simple analysis would suggest that Hydrological models are designed to get the runoff right, while Land Surface models designed to get the evapotranspiration right. Tracing the source of the difference suggests that the difference comes from the treatment of snow and evapotranspiration. The study reveals that expertise in the role of snow on runoff generation and evapotranspiration in Hydrological and Land Surface could be combined to improve the representation of the fresh water flows in the Arctic in both approaches. Improved observations are essential to make these modelling advances possible.

Topological Relations-Based Detection of Spatial Inconsistency in GLOBELAND30

NASA Astrophysics Data System (ADS)

Kang, S.; Chen, J.; Peng, S.

2017-09-01

Land cover is one of the fundamental data sets on environment assessment, land management and biodiversity protection, etc. Hence, data quality control of land cover is extremely critical for geospatial analysis and decision making. Due to the similar remote-sensing reflectance for some land cover types, omission and commission errors occurred in preliminary classification could result to spatial inconsistency between land cover types. In the progress of post-classification, this error checking mainly depends on manual labour to assure data quality, by which it is time-consuming and labour intensive. So a method required for automatic detection in post-classification is still an open issue. From logical inconsistency point of view, an inconsistency detection method is designed. This method consist of a grids extended 4-intersection model (GE4IM) for topological representation in single-valued space, by which three different kinds of topological relations including disjoint, touch, contain or contained-by are described, and an algorithm of region overlay for the computation of spatial inconsistency. The rules are derived from universal law in nature between water body and wetland, cultivated land and artificial surface. Through experiment conducted in Shandong Linqu County, data inconsistency can be pointed out within 6 minutes through calculation of topological inconsistency between cultivated land and artificial surface, water body and wetland. The efficiency evaluation of the presented algorithm is demonstrated by Google Earth images. Through comparative analysis, the algorithm is proved to be promising for inconsistency detection in land cover data.

Blue Water Trade-Offs With Vegetation in a CO2-Enriched Climate

NASA Astrophysics Data System (ADS)

Mankin, Justin S.; Seager, Richard; Smerdon, Jason E.; Cook, Benjamin I.; Williams, A. Park; Horton, Radley M.

2018-04-01

Present and future freshwater availability and drought risks are physically tied to the responses of surface vegetation to increasing CO2. A single-model large ensemble identifies the occurrence of colocated warming- and CO2-induced leaf area index increases with summer soil moisture declines. This pattern of "greening" and "drying," which occurs over 42% of global vegetated land area, is largely attributable to changes in the partitioning of precipitation at the land surface away from runoff and toward terrestrial vegetation ecosystems. Changes in runoff and ecosystem partitioning are inversely related, with changes in runoff partitioning being governed by changes in precipitation (mean and extremes) and ecosystem partitioning being governed by ecosystem water use and surface resistance to evapotranspiration (ET). Projections show that warming-influenced and CO2-enriched terrestrial vegetation ecosystems use water that historically would have been partitioned to runoff over 48% of global vegetated land areas, largely in Western North America, the Amazon, and Europe, many of the same regions with colocated greening and drying. These results have implications for how water available for people will change in response to anthropogenic warming and raise important questions about model representations of vegetation water responses to high CO2.

Simulating Snow in Canadian Boreal Environments with CLASS for ESM-SnowMIP

NASA Astrophysics Data System (ADS)

Wang, L.; Bartlett, P. A.; Derksen, C.; Ireson, A. M.; Essery, R.

2017-12-01

The ability of land surface schemes to provide realistic simulations of snow cover is necessary for accurate representation of energy and water balances in climate models. Historically, this has been particularly challenging in boreal forests, where poor treatment of both snow masking by forests and vegetation-snow interaction has resulted in biases in simulated albedo and snowpack properties, with subsequent effects on both regional temperatures and the snow albedo feedback in coupled simulations. The SnowMIP (Snow Model Intercomparison Project) series of experiments or `MIPs' was initiated in order to provide assessments of the performance of various snow- and land-surface-models at selected locations, in order to understand the primary factors affecting model performance. Here we present preliminary results of simulations conducted for the third such MIP, ESM-SnowMIP (Earth System Model - Snow Model Intercomparison Project), using the Canadian Land Surface Scheme (CLASS) at boreal forest sites in central Saskatchewan. We assess the ability of our latest model version (CLASS 3.6.2) to simulate observed snowpack properties (snow water equivalent, density and depth) and above-canopy albedo over 13 winters. We also examine the sensitivity of these simulations to climate forcing at local and regional scales.

Examining the Impacts of High-Resolution Land Surface Initialization on Model Predictions of Convection in the Southeastern U.S.

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Santos, Pablo; Medlin, Jeffrey M.; Jedlovec, Gary J.

2009-01-01

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within physics parameterizations, model resolution limitations, as well as uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture and temperature, ground fluxes, and vegetation are necessary to better simulate the interactions between the land surface and atmosphere, and ultimately improve predictions of local circulations and summertime pulse convection. The NASA Short-term Prediction Research and Transition (SPORT) Center has been conducting studies to examine the impacts of high-resolution land surface initialization data generated by offline simulations of the NASA Land Informatiot System (LIS) on subsequent numerical forecasts using the Weather Research and Forecasting (WRF) model (Case et al. 2008, to appear in the Journal of Hydrometeorology). Case et al. presents improvements to simulated sea breezes and surface verification statistics over Florida by initializing WRF with land surface variables from an offline LIS spin-up run, conducted on the exact WRF domain and resolution. The current project extends the previous work over Florida, focusing on selected case studies of typical pulse convection over the southeastern U.S., with an emphasis on improving local short-term WRF simulations over the Mobile, AL and Miami, FL NWS county warning areas. Future efforts may involve examining the impacts of assimilating remotely-sensed soil moisture data, and/or introducing weekly greenness vegetation fraction composites (as opposed to monthly climatologies) into ol'fline NASA LIS runs. Based on positive impacts, the offline LIS runs could be transitioned into an operational mode, providing land surface initialization data to NWS forecast offices in real time.

Measuring and modeling changes in land-atmosphere exchanges and hydrologic response in forests undergoing insect-driven mortality

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Brooks, P. D.; Harpold, A. A.; Ewers, B. E.; Pendall, E.; Barnard, H. R.; Reed, D.; Harley, P. C.; Hu, J.; Biederman, J.

2010-12-01

Given the magnitude and spatial extent of recent forest mortality in the western U.S. there is a pressing need to improve representation of such influences on the exchange of energy, water, biogeochemical and momentum fluxes in land-atmosphere parameterizations coupled to weather and climate models. In this talk we present observational data and model results from a new study aimed at improving understanding the impacts of mountain pine beetle-induced forest mortality in the central Rocky Mountains. Baseline observations and model runs from undisturbed lodgepole pine forest conditions are developed as references against which new observations and model runs from infested stands are compared. We will specifically look at the structure and evolution of sub-canopy energy exchange variables such as shortwave and longwave radiation and sub-canopy turbulence as well as sub-canopy precipitation, sapflow fluxes, canopy-scale fluxes and soil moisture and temperature. In this manner we seek to lay the ground work for evaluating the recent generation of land surface model changes aimed at representing insect-related forest dynamics in the CLM-C/N and Noah land surface models.

A new concept for simulation of vegetated land surface dynamics - Part 1: The event driven phenology model

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G. M.

2012-01-01

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameriflux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE < 0.08; r2 > 0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons.

A new concept for simulation of vegetated land surface dynamics - Part 1: The event driven phenology model

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G. M.

2011-05-01

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameriflux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE < 0.08; r2>0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons.

Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships

NASA Astrophysics Data System (ADS)

Haghighi, Erfan; Kirchner, James W.

2017-07-01

Despite many efforts to develop evapotranspiration (ET) models with improved parametrizations of resistance terms for water vapor transfer into the atmosphere, estimates of ET and its partitioning remain prone to bias. Much of this bias could arise from inadequate representations of physical interactions near nonuniform surfaces from which localized heat and water vapor fluxes emanate. This study aims to provide a mechanistic bridge from land-surface characteristics to vertical transport predictions, and proposes a new physically based ET model that builds on a recently developed bluff-rough bare soil evaporation model incorporating coupled soil moisture-atmospheric controls. The newly developed ET model explicitly accounts for (1) near-surface turbulent interactions affecting soil drying and (2) soil-moisture-dependent stomatal responses to atmospheric evaporative demand that influence leaf (and canopy) transpiration. Model estimates of ET and its partitioning were in good agreement with available field-scale data, and highlight hidden processes not accounted for by commonly used ET schemes. One such process, nonlinear vegetation-induced turbulence (as a function of vegetation stature and cover fraction) significantly influences ET-soil moisture relationships. Our results are particularly important for water resources and land use planning of semiarid sparsely vegetated ecosystems where soil surface interactions are known to play a critical role in land-climate interactions. This study potentially facilitates a mathematically tractable description of the strength (i.e., the slope) of the ET-soil moisture relationship, which is a core component of models that seek to predict land-atmosphere coupling and its feedback to the climate system in a changing climate.

On the Use and Validation of Mosaic Heterogeneity in Atmospheric Numerical Models

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Atlas, Robert M. (Technical Monitor)

2001-01-01

The mosaic land modeling approach allows for the representation of multiple surface types in a single atmospheric general circulation model grid box. Each surface type, collectively called 'tiles' correspond to different sets of surface characteristics (e.g. for grass, crop or forest). Typically, the tile space data is averaged to grid space by weighting the tiles with their fractional cover. While grid space data is routinely evaluated, little attention has been given to the tile space data. The present paper explores uses of the tile space surface data in validation with station observations. The results indicate the limitations that the mosaic heterogeneity parameterization has in reproducing variations observed between stations at the Atmospheric Radiation Measurement Southern Great Plains field site.

Testing the capability of ORCHIDEE land surface model to simulate Arctic ecosystems: Sensitivity analysis and site-level model calibration

NASA Astrophysics Data System (ADS)

Dantec-Nédélec, S.; Ottlé, C.; Wang, T.; Guglielmo, F.; Maignan, F.; Delbart, N.; Valdayskikh, V.; Radchenko, T.; Nekrasova, O.; Zakharov, V.; Jouzel, J.

2017-06-01

The ORCHIDEE land surface model has recently been updated to improve the representation of high-latitude environments. The model now includes improved soil thermodynamics and the representation of permafrost physical processes (soil thawing and freezing), as well as a new snow model to improve the representation of the seasonal evolution of the snow pack and the resulting insulation effects. The model was evaluated against data from the experimental sites of the WSibIso-Megagrant project (www.wsibiso.ru). ORCHIDEE was applied in stand-alone mode, on two experimental sites located in the Yamal Peninsula in the northwestern part of Siberia. These sites are representative of circumpolar-Arctic tundra environments and differ by their respective fractions of shrub/tree cover and soil type. After performing a global sensitivity analysis to identify those parameters that have most influence on the simulation of energy and water transfers, the model was calibrated at local scale and evaluated against in situ measurements (vertical profiles of soil temperature and moisture, as well as active layer thickness) acquired during summer 2012. The results show how sensitivity analysis can identify the dominant processes and thereby reduce the parameter space for the calibration process. We also discuss the model performance at simulating the soil temperature and water content (i.e., energy and water transfers in the soil-vegetation-atmosphere continuum) and the contribution of the vertical discretization of the hydrothermal properties. This work clearly shows, at least at the two sites used for validation, that the new ORCHIDEE vertical discretization can represent the water and heat transfers through complex cryogenic Arctic soils—soils which present multiple horizons sometimes with peat inclusions. The improved model allows us to prescribe the vertical heterogeneity of the soil hydrothermal properties.

Insights in time dependent cross compartment sensitivities from ensemble simulations with the fully coupled subsurface-land surface-atmosphere model TerrSysMP

NASA Astrophysics Data System (ADS)

Schalge, Bernd; Rihani, Jehan; Haese, Barbara; Baroni, Gabriele; Erdal, Daniel; Haefliger, Vincent; Lange, Natascha; Neuweiler, Insa; Hendricks-Franssen, Harrie-Jan; Geppert, Gernot; Ament, Felix; Kollet, Stefan; Cirpka, Olaf; Saavedra, Pablo; Han, Xujun; Attinger, Sabine; Kunstmann, Harald; Vereecken, Harry; Simmer, Clemens

2017-04-01

Currently, an integrated approach to simulating the earth system is evolving where several compartment models are coupled to achieve the best possible physically consistent representation. We used the model TerrSysMP, which fully couples subsurface, land surface and atmosphere, in a synthetic study that mimicked the Neckar catchment in Southern Germany. A virtual reality run at a high resolution of 400m for the land surface and subsurface and 1.1km for the atmosphere was made. Ensemble runs at a lower resolution (800m for the land surface and subsurface) were also made. The ensemble was generated by varying soil and vegetation parameters and lateral atmospheric forcing among the different ensemble members in a systematic way. It was found that the ensemble runs deviated for some variables and some time periods largely from the virtual reality reference run (the reference run was not covered by the ensemble), which could be related to the different model resolutions. This was for example the case for river discharge in the summer. We also analyzed the spread of model states as function of time and found clear relations between the spread and the time of the year and weather conditions. For example, the ensemble spread of latent heat flux related to uncertain soil parameters was larger under dry soil conditions than under wet soil conditions. Another example is that the ensemble spread of atmospheric states was more influenced by uncertain soil and vegetation parameters under conditions of low air pressure gradients (in summer) than under conditions with larger air pressure gradients in winter. The analysis of the ensemble of fully coupled model simulations provided valuable insights in the dynamics of land-atmosphere feedbacks which we will further highlight in the presentation.

Do convection-permitting models improve the representation of the impact of LUC?

NASA Astrophysics Data System (ADS)

Vanden Broucke, Sam; Van Lipzig, Nicole

2017-10-01

In this study we assess the added value of convection permitting scale (CPS) simulations in studies using regional climate models to quantify the bio-geophysical climate impact of land-use change (LUC). To accomplish this, a comprehensive model evaluation methodology is applied to both non-CPS and CPS simulations. The main characteristics of the evaluation methodology are (1) the use of paired eddy-covariance site observations (forest vs open land) and (2) a simultaneous evaluation of all surface energy budget components. Results show that although generally satisfactory, non-CPS simulations fall short of completely reproducing the observed LUC signal because of three key biases. CPS scale simulations succeed at significantly reducing two of these biases, namely, those in daytime shortwave radiation and daytime sensible heat flux. Also, CPS slightly reduces a third bias in nighttime incoming longwave radiation. The daytime improvements can be attributed partially to the switch from parameterized to explicit convection, the associated improvement in the simulation of afternoon convective clouds, and resulting surface energy budget and atmospheric feedbacks. Also responsible for the improvements during daytime is a better representation of surface heterogeneity and thus, surface roughness. Meanwhile, the modest nighttime longwave improvement can be attributed to increased vertical atmospheric resolution. However, the model still fails at reproducing the magnitude of the observed nighttime longwave difference. One possible explanation for this persistent bias is the nighttime radiative effect of biogenic volatile organic compound emissions over the forest site. A correlation between estimated emission rates and the observed nighttime longwave difference, as well as the persistence of the longwave bias provide support for this hypothesis. However, more research is needed to conclusively determine if the effect indeed exists.

Towards a Representation of Flexible Canopy N Stiochiometry for Land-surface Models Based on Optimality Concepts

NASA Astrophysics Data System (ADS)

Zaehle, S.; Caldararu, S.

2015-12-01

Foliar nitrogen (N) is know to acclimate to environmental conditions. One particular pertinent response is the general decline in foliar N following exposure to elevated levels of atmospheric CO2 (eCO2). Associated with reduced foliar N is an increased plant nitrogen-use efficiency, which contributes to the plants' sustained growth response to eCO2 in the absence of any counteracting litter N feedbacks. Flexible leaf N thus has important consequences for the mid- to long-term response of terrestrial ecosystems to eCO2. The current generation of land-surface models including a prognostic N cycle generally employ heuristic, and simply mass-balancing parameterisations to estimate changes in stoichiometry given altered N and carbon (C) availability. This generation generally and substantially overestimates the decline of foliar N (and thus the increase in plant nitrogen use efficiency) observed in Free Air CO2 Enrichment Experiments (FACE; Zaehle et al. 2014). In this presentation, I develop a simple, prognostic and dynamic representation of flexible foliar N for use in land-surface models by maximising the marginal gain of net assimilation with respect to the energy investment to generate foliar area and foliar N. I elucidate the underlying assumptions required to simulate the commonly observed decline in foliar N with eCO2 under different scenarios of N availability (Feng et al. 2015). References: Zaehle, Sönke, Belinda E Medlyn, Martin G De Kauwe, Anthony P Walker, Michael C Dietze, Hickler Thomas, Yiqi Luo, et al. 2014. "Evaluation of 11 Terrestrial Carbon-Nitrogen Cycle Models Against Observations From Two Temperate Free-Air CO2 Enrichment Studies." New Phytologist 202 (3): 803-22. doi:10.1111/nph.12697. Feng, Zhaozhong, Tobias RUtting, Håkan Pleijel, GORAN WALLIN, Peter B Reich, Claudia I Kammann, Paul C D Newton, Kazuhiko Kobayashi, Yunjian Luo, and Johan Uddling. 2015. "Constraints to Nitrogen Acquisition of Terrestrial Plants Under Elevated CO 2." Global Change Biology 21 (8): 3152-68. doi:10.1111/gcb.12938.

Improving Representations of Near-Surface Permafrost and Soil Temperature Profiles in the Regional Arctic System Model (RASM)

NASA Astrophysics Data System (ADS)

Gergel, D. R.; Hamman, J.; Nijssen, B.

2017-12-01

Permafrost and seasonally frozen soils are a key characteristic of the terrestrial Arctic, and the fate of near-surface permafrost as a result of climate change is projected to have strong impacts on terrestrial biogeochemistry. The active layer thickness (ALT) is the layer of soil that freezes and thaws annually, and shifts in the depth of the ALT are projected to occur over large areas of the Arctic that are characterized by discontinuous permafrost. Faithful representation of permafrost in land models in climate models is a product of both soil dynamics and the coupling of air and soil temperatures. A common problem is a large bias in simulated ALT due to a model depth that is too shallow. Similarly, soil temperatures often show systematic biases, which lead to biases in air temperature due to poorly modeled air-soil temperature feedbacks in a coupled environment. In this study, we use the Regional Arctic System Model (RASM), a fully-coupled regional earth system model that is run at a 50-km land/atmosphere resolution over a pan-Arctic domain and uses the Variable Infiltration Capacity (VIC) model as its land model. To understand what modeling decisions are necessary to accurately represent near-surface permafrost and soil temperature profiles, we perform a large number of RASM simulations with prescribed atmospheric forcings (e.g. VIC in standalone mode in RASM) while varying the model soil depth, thickness of soil moisture layers, number of soil layers and the distribution of soil nodes. We compare modeled soil temperatures and ALT to observations from the Circumpolar Active Layer Monitoring (CALM) network. CALM observations include annual ALT observations as well as daily soil temperature measurements at three soil depths for three sites in Alaska. In the future, we will use our results to inform our modeling of permafrost dynamics in fully-coupled RASM simulations.

Evaluating GCM land surface hydrology parameterizations by computing river discharges using a runoff routing model: Application to the Mississippi basin

NASA Technical Reports Server (NTRS)

Liston, G. E.; Sud, Y. C.; Wood, E. F.

1994-01-01

To relate general circulation model (GCM) hydrologic output to readily available river hydrographic data, a runoff routing scheme that routes gridded runoffs through regional- or continental-scale river drainage basins is developed. By following the basin overland flow paths, the routing model generates river discharge hydrographs that can be compared to observed river discharges, thus allowing an analysis of the GCM representation of monthly, seasonal, and annual water balances over large regions. The runoff routing model consists of two linear reservoirs, a surface reservoir and a groundwater reservoir, which store and transport water. The water transport mechanisms operating within these two reservoirs are differentiated by their time scales; the groundwater reservoir transports water much more slowly than the surface reservior. The groundwater reservior feeds the corresponding surface store, and the surface stores are connected via the river network. The routing model is implemented over the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project Mississippi River basin on a rectangular grid of 2 deg X 2.5 deg. Two land surface hydrology parameterizations provide the gridded runoff data required to run the runoff routing scheme: the variable infiltration capacity model, and the soil moisture component of the simple biosphere model. These parameterizations are driven with 4 deg X 5 deg gridded climatological potential evapotranspiration and 1979 First Global Atmospheric Research Program (GARP) Global Experiment precipitation. These investigations have quantified the importance of physically realistic soil moisture holding capacities, evaporation parameters, and runoff mechanisms in land surface hydrology formulations.

High-Resolution Specification of the Land and Ocean Surface for Improving Regional Mesoscale Model Predictions

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Lazarus, Steven M.; Splitt, Michael E.; Crosson, William L.; Lapenta, William M.; Jedlovec, Gary J.; Peters-Lidard, Christa D.

2008-01-01

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many meteorological processes. High-resolution, accurate representations of surface properties such as sea-surface temperature (SST), soil temperature and moisture content, ground fluxes, and vegetation are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of sensible weather. The NASA Short-term Prediction Research and Transition (SPoRT) Center has been conducting separate studies to examine the impacts of high-resolution land-surface initialization data from the Goddard Space Flight Center Land Information System (LIS) on subsequent WRF forecasts, as well as the influence of initializing WRF with SST composites derived from the MODIS instrument. This current project addresses the combined impacts of using high-resolution lower boundary data over both land (LIS data) and water (MODIS SSTs) on the subsequent daily WRF forecasts over Florida during May 2004. For this experiment, the WRF model is configured to run on a nested domain with 9- km and 3-kin grid spacing, centered on the Florida peninsula and adjacent coastal waters of the Gulf of Mexico and Atlantic Ocean. A control configuration of WRF is established to take all initial condition data from the NCEP Eta model. Meanwhile, two WRF experimental runs are configured to use high-resolution initialization data from (1) LIS land-surface data only, and (2) a combination of LIS data and high-resolution MODIS SST composites. The experiment involves running 24-hour simulations of the control WRF configuration, the MS-initialized WRF, and the LIS+MODIS-initialized WRF daily for the entire month of May 2004. All atmospheric data for initial and boundary conditions for the Control, LIS, and LIS+MODIS runs come from the NCEP Eta model on a 40-km grid. Verification statistics are generated at land surface observation sites and buoys, and the impacts of the high-resolution lower boundary data on the development and evolution of mesoscale circulations such as sea and land breezes are examined, This paper will present the results of these WRF modeling experiments using LIS and MODIS lower boundary datasets over the Florida peninsula during May 2004.

Surface ozone seasonality under global change: Influence from dry deposition and isoprene emissions at northern mid-latitudes

NASA Astrophysics Data System (ADS)

Clifton, O.; Paulot, F.; Fiore, A. M.; Horowitz, L. W.; Malyshev, S.; Shevliakova, E.; Correa, G. J. P.; Lin, M.

2017-12-01

Identifying the contributions of nonlinear chemistry and transport to observed surface ozone seasonal cycles over land using global models relies on an accurate representation of ozone uptake by vegetation (dry deposition). It is well established that in the absence of ozone precursor emission changes, a warming climate will increase surface ozone in polluted regions, and that a rise in temperature-dependent isoprene emissions would exacerbate this "climate penalty". However, the influence of changes in ozone dry deposition, expected to evolve with climate and land use, is often overlooked in air quality projections. With a new scheme that represents dry deposition within the NOAA GFDL dynamic vegetation land model (LM3) coupled to the NOAA GFDL atmospheric chemistry-climate model (AM3), we simulate the impact of 21st century climate and land use on ozone dry deposition and isoprene emissions. This dry deposition parameterization is a version of the Wesely scheme, but uses parameters explicitly calculated by LM3 that respond to climate and land use (e.g., stomatal conductance, canopy interception of water, leaf area index). The parameterization includes a nonstomatal deposition dependence on humidity. We evaluate climatological present-day seasonal cycles of ozone deposition velocities and abundances with those observed at northern mid-latitude sites. With a set of 2010s and 2090s decadal simulations under a high climate warming scenario (RCP8.5) and a sensitivity simulation with well-mixed greenhouse gases following RCP8.5 but air pollutants held at 2010 levels (RCP8.5_WMGG), we examine changes in surface ozone seasonal cycles. We build on our previous findings, which indicate that strong reductions in anthropogenic NOx emissions under RCP8.5 cause the surface ozone seasonal cycle over the NE USA to reverse, shifting from a summer peak at present to a winter peak by 2100. Under RCP8.5_WMGG, we parse the separate effects of climate and land use on ozone dry deposition vs. isoprene emissions to quantify the impact of each process on surface ozone seasonal cycles and compare to the changes induced by declining anthropogenic NOx emissions (RCP8.5).

An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models

DOE PAGES

Ma, H. -Y.; Chuang, C. C.; Klein, S. A.; ...

2015-11-06

Here, we present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge onlymore » the model horizontal velocities towards operational analysis/reanalysis values, given a 6-hour relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an offline land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a “Core” integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modelled cloud-associated processes relative to observations.« less

An improved hindcast approach for evaluation and diagnosis of physical processes in global climate models

NASA Astrophysics Data System (ADS)

Ma, H.-Y.; Chuang, C. C.; Klein, S. A.; Lo, M.-H.; Zhang, Y.; Xie, S.; Zheng, X.; Ma, P.-L.; Zhang, Y.; Phillips, T. J.

2015-12-01

We present an improved procedure of generating initial conditions (ICs) for climate model hindcast experiments with specified sea surface temperature and sea ice. The motivation is to minimize errors in the ICs and lead to a better evaluation of atmospheric parameterizations' performance in the hindcast mode. We apply state variables (horizontal velocities, temperature, and specific humidity) from the operational analysis/reanalysis for the atmospheric initial states. Without a data assimilation system, we apply a two-step process to obtain other necessary variables to initialize both the atmospheric (e.g., aerosols and clouds) and land models (e.g., soil moisture). First, we nudge only the model horizontal velocities toward operational analysis/reanalysis values, given a 6 h relaxation time scale, to obtain all necessary variables. Compared to the original strategy in which horizontal velocities, temperature, and specific humidity are nudged, the revised approach produces a better representation of initial aerosols and cloud fields which are more consistent and closer to observations and model's preferred climatology. Second, we obtain land ICs from an off-line land model simulation forced with observed precipitation, winds, and surface fluxes. This approach produces more realistic soil moisture in the land ICs. With this refined procedure, the simulated precipitation, clouds, radiation, and surface air temperature over land are improved in the Day 2 mean hindcasts. Following this procedure, we propose a "Core" integration suite which provides an easily repeatable test allowing model developers to rapidly assess the impacts of various parameterization changes on the fidelity of modeled cloud-associated processes relative to observations.

Diagnosing the influence of model structure on the simulation of water, energy and carbon fluxes on bark beetle infested forests

NASA Astrophysics Data System (ADS)

Gochis, D. J.; Gutmann, E. D.; Brooks, P. D.; Reed, D. E.; Ewers, B. E.; Pendall, E.; Biederman, J. A.; Harpold, A. A.; Barnard, H. R.; Hu, J.

2011-12-01

Forest dynamics induced by insect infestation can have a significant, local impact on plant physiological regulation of water, energy and carbon fluxes. Rapid mortality succeeded by more gradually varying land cover changes are presently thought to initiate a cascade of changes to water, energy and carbon budgets at the forest stand scale. Initial model sensitivity results have suggested very strong changes in land-atmosphere exchanges of these variables. Specifically, model results from the Noah land surface model, a relatively simple model, have suggested that loss of transpiration function may result in a nearly 50% increase in seasonal soil moisture values and similar increases in runoff production for locations in the central Rocky Mountains. However, differing model structures, such as the representation of plant canopy architecture, snowpack dynamics, dynamic vegetation and hillslope hydrologic processes, may significantly confound the synthesis of results from different modeling systems. We assess the performance of new suite of model simulations from three different land surface models of differing model structures and complexity levels against a comprehensive set of field observations of land surface flux and state variables. The focus of the analysis is in diagnosing how model structure influences changes in energy, water and carbon budget partitioning prior to and following insect infestation. Specific emphasis in this presentation is placed on verifying variables that characterize top of canopy and within canopy energy and water fluxes. We conclude the presentation with a set of recommendations about the advantages and disadvantages of various model structures in their simulation of insect driven forest dynamics.

Plant functional diversity affects climate-vegetation interaction

NASA Astrophysics Data System (ADS)

Groner, Vivienne P.; Raddatz, Thomas; Reick, Christian H.; Claussen, Martin

2018-04-01

We present how variations in plant functional diversity affect climate-vegetation interaction towards the end of the African Humid Period (AHP) in coupled land-atmosphere simulations using the Max Planck Institute Earth system model (MPI-ESM). In experiments with AHP boundary conditions, the extent of the green Sahara varies considerably with changes in plant functional diversity. Differences in vegetation cover extent and plant functional type (PFT) composition translate into significantly different land surface parameters, water cycling, and surface energy budgets. These changes have not only regional consequences but considerably alter large-scale atmospheric circulation patterns and the position of the tropical rain belt. Towards the end of the AHP, simulations with the standard PFT set in MPI-ESM depict a gradual decrease of precipitation and vegetation cover over time, while simulations with modified PFT composition show either a sharp decline of both variables or an even slower retreat. Thus, not the quantitative but the qualitative PFT composition determines climate-vegetation interaction and the climate-vegetation system response to external forcing. The sensitivity of simulated system states to changes in PFT composition raises the question how realistically Earth system models can actually represent climate-vegetation interaction, considering the poor representation of plant diversity in the current generation of land surface models.

Investigation of a long time series of CO2 from a tall tower using WRF-SPA

NASA Astrophysics Data System (ADS)

Smallman, Luke; Williams, Mathew; Moncrieff, John B.

2013-04-01

Atmospheric observations from tall towers are an important source of information about CO2 exchange at the regional scale. Here, we have used a forward running model, WRF-SPA, to generate a time series of CO2 at a tall tower for comparison with observations from Scotland over multiple years (2006-2008). We use this comparison to infer strength and distribution of sources and sinks of carbon and ecosystem process information at the seasonal scale. The specific aim of this research is to combine a high resolution (6 km) forward running meteorological model (WRF) with a modified version of a mechanistic ecosystem model (SPA). SPA provides surface fluxes calculated from coupled energy, hydrological and carbon cycles. This closely coupled representation of the biosphere provides realistic surface exchanges to drive mixing within the planetary boundary layer. The combined model is used to investigate the sources and sinks of CO2 and to explore which land surfaces contribute to a time series of hourly observations of atmospheric CO2 at a tall tower, Angus, Scotland. In addition to comparing the modelled CO2 time series to observations, modelled ecosystem specific (i.e. forest, cropland, grassland) CO2 tracers (e.g., assimilation and respiration) have been compared to the modelled land surface assimilation to investigate how representative tall tower observations are of land surface processes. WRF-SPA modelled CO2 time series compares well to observations (R2 = 0.67, rmse = 3.4 ppm, bias = 0.58 ppm). Through comparison of model-observation residuals, we have found evidence that non-cropped components of agricultural land (e.g., hedgerows and forest patches) likely contribute a significant and observable impact on regional carbon balance.

Cross-compartment evaluation of a fully-coupled hydrometeorological modeling system using comprehensive observation data

NASA Astrophysics Data System (ADS)

Fersch, Benjamin; Senatore, Alfonso; Kunstmann, Harald

2017-04-01

Fully-coupled hydrometeorological modeling enables investigations about the complex and often non-linear exchange mechanisms among subsurface, land, and atmosphere with respect to water and energy fluxes. The consideration of lateral redistribution of surface and subsurface water in such modeling systems is a crucial enhancement, allowing for a better representation of surface spatial patterns and providing also channel discharge predictions. However, the evaluation of fully-coupled simulations is difficult since the amount of physical detail along with feedback mechanisms leads to high degrees of freedom. Therefore, comprehensive observation data is required to obtain meaningful model configurations. We present a case study for a medium-sized river catchment in southern Germany that includes the calibration of the stand-alone and the evaluation of the fully-coupled WRF-Hydro modeling system with a horizontal resolution of 1 x 1 km2, for the period June to August 2015. ECMWF ERA-Interim reanalysis is used for model driving. Land-surface processes are represented by the Noah-MP land surface model. Land-cover is described by the EU CORINE data set. Observations for model evaluation are obtained from the TERENO Pre-Alpine observatory (http://www.imk-ifu.kit.edu/tereno.php) and are complemented by further measurements from the ScaleX campaign (http://scalex.imk-ifu.kit.edu) such as atmospheric profiles obtained from radiometer sounding and airborne systems as well as soil moisture and -temperature networks. We show how well water budgets and heat-fluxes are being reproduced by the stand-alone WRF, the stand-alone WRF-Hydro and the fully-coupled WRF-Hydro model.

The Joint UK Land Environment Simulator (JULES), model description - Part 2: Carbon fluxes and vegetation dynamics

NASA Astrophysics Data System (ADS)

Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Huntingford, C.; Cox, P. M.

2011-09-01

The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

Spatial heterogeneity of leaf area index across scales from simulation and remote sensing

NASA Astrophysics Data System (ADS)

Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl

2016-04-01

Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.

Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

NASA Technical Reports Server (NTRS)

Reichle, R. H.

2010-01-01

Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model: SECTORAL WATER MANAGEMENT IN IA-ESM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voisin, Nathalie; Hejazi, Mohamad I.; Leung, L. Ruby

To advance understanding of the interactions between human activities and the water cycle, an integrated terrestrial water cycle component has been developed for Earth system models. This includes a land surface model fully coupled to a river routing model and a generic water management model to simulate natural and regulated flows. A global integrated assessment model and its regionalized version for the U.S. are used to simulate water demand consistent with the energy technology and socio-economics scenarios. Human influence on the hydrologic cycle includes regulation and storage from reservoirs, consumptive use and withdrawal from multiple sectors ( irrigation and non-irrigation)more » and overall redistribution of water resources in space and time. As groundwater provides an important source of water supply for irrigation and other uses, the integrated modeling framework has been extended with a simplified representation of groundwater as an additional supply source, and return flow generated from differences between withdrawals and consumptive uses from both groundwater and surface water systems. The groundwater supply and return flow modules are evaluated by analyzing the simulated regulated flow, reservoir storage and supply deficit for irrigation and non-irrigation sectors over major hydrologic regions of the conterminous U.S. The modeling framework is then used to provide insights on the reliability of water resources by isolating the reliability due to return flow and/or groundwater sources of water. Our results show that high sectoral ratio of withdrawals over consumptive demand adds significant stress on the water resources management that can be alleviated by reservoir storage capacity. The return flow representation therefore exhibits a clear east-west contrast in its hydrologic signature, as well as in its ability to help meet water demand. Groundwater use has a limited hydrologic signature but the most pronounced signature is in terms of decreasing water supply deficit. The combined return flow and groundwater use signature conserves the east-west constrast with overall uncertainties due to the groundwater-return flow representation, varying ratios combined with different hydroclimate conditions, storage infrastructures, sectoral water uses and dependence on groundwater. The redistribution of surface and groundwater by human activities, and the uncertainties in their representation have important implications to the water and energy balances in the Earth system and land-atmosphere interactions.« less

Microwave Remote Sensing and the Cold Land Processes Field Experiment

NASA Technical Reports Server (NTRS)

Kim, Edward J.; Cline, Don; Davis, Bert; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

The Cold Land Processes Field Experiment (CLPX) has been designed to advance our understanding of the terrestrial cryosphere. Developing a more complete understanding of fluxes, storage, and transformations of water and energy in cold land areas is a critical focus of the NASA Earth Science Enterprise Research Strategy, the NASA Global Water and Energy Cycle (GWEC) Initiative, the Global Energy and Water Cycle Experiment (GEWEX), and the GEWEX Americas Prediction Project (GAPP). The movement of water and energy through cold regions in turn plays a large role in ecological activity and biogeochemical cycles. Quantitative understanding of cold land processes over large areas will require synergistic advancements in 1) understanding how cold land processes, most comprehensively understood at local or hillslope scales, extend to larger scales, 2) improved representation of cold land processes in coupled and uncoupled land-surface models, and 3) a breakthrough in large-scale observation of hydrologic properties, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed soil conditions. The CLPX Plan has been developed through the efforts of over 60 interested scientists that have participated in the NASA Cold Land Processes Working Group (CLPWG). This group is charged with the task of assessing, planning and implementing the required background science, technology, and application infrastructure to support successful land surface hydrology remote sensing space missions. A major product of the experiment will be a comprehensive, legacy data set that will energize many aspects of cold land processes research. The CLPX will focus on developing the quantitative understanding, models, and measurements necessary to extend our local-scale understanding of water fluxes, storage, and transformations to regional and global scales. The experiment will particularly emphasize developing a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. The experimental design is a multi-sensor, multi-scale (1-ha to 160,000 km ^ {2}) approach to providing the comprehensive data set necessary to address several experiment objectives. A description focusing on the microwave remote sensing components (ground, airborne, and spaceborne) of the experiment will be presented.

Surface energy fluxes and their representation in CMIP5 models

NASA Astrophysics Data System (ADS)

Wild, M.

2016-12-01

Energy fluxes at the Earth surface play a key role in the determination of surface climate and in the coupling of atmosphere, land and ocean components. Unlike their counterparts at the top of atmosphere (TOA), surface fluxes cannot be directly measured from satellites, but have to be inferred from the space-born observations using additional models to account for atmospheric perturbations, or from the limited number of surface observations. Uncertainties in the energy fluxes at the surface have therefore traditionally been larger than at the TOA, and have limited our knowledge on the distribution of the energy flows within the climate system. Accordingly, current climate models still largely differ in their representation of surface and atmospheric energy fluxes. Since the mid-1990s, accurate flux measurements became increasingly available from surface networks such as BSRN, which allow to better constrain the surface energy fluxes. There is, however, still a lack of flux measurements particularly over oceans. Further, the larger-scale representativeness of the station records needs to be assessed to judge their suitability as anchor sites for gridded flux products inferred from satellites, reanalyses and climate models. In addition, historic records need to be carefully quality-checked and homogeneized. In parallel, satellite-derived products of surface fluxes profit from the great advancement in space-born observations since the turn of the millennium, and from improved validation capabilities with surface observations. Ultimately, it is the combination of surface and space-born observations, reanalyses and modeling approaches that will advance our knowledge on the distribution of the surface energy fluxes. Uncertainties remain in the determination of surface albedo, skin temperatures and the partitioning of surface net radiation into the sensible and latent heat. Climate models over generations up to present day (CMIP5) tend to overestimate the downward shortwave and underestimate the downward longwave radiation. A challenge also remains the consistent representation of the global energy and water cycles. Yet it is shown that those climate models with a realistic surface radiation balance also simulate global precipitation amounts within the uncertainty range of observational estimates.

Land surface hydrology parameterization for atmospheric general circulation models including subgrid scale spatial variability

NASA Technical Reports Server (NTRS)

Entekhabi, D.; Eagleson, P. S.

1989-01-01

Parameterizations are developed for the representation of subgrid hydrologic processes in atmospheric general circulation models. Reasonable a priori probability density functions of the spatial variability of soil moisture and of precipitation are introduced. These are used in conjunction with the deterministic equations describing basic soil moisture physics to derive expressions for the hydrologic processes that include subgrid scale variation in parameters. The major model sensitivities to soil type and to climatic forcing are explored.

Benchmarking sensitivity of biophysical processes to leaf area changes in land surface models

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Duveiller, Gregory; Georgievski, Goran; Li, Wei; Robestson, Eddy; Kautz, Markus; Lawrence, Peter; Ciais, Philippe; Pongratz, Julia; Sitch, Stephen; Wiltshire, Andy; Arneth, Almut; Cescatti, Alessandro

2017-04-01

Land surface models (LSM) are widely applied as supporting tools for policy-relevant assessment of climate change and its impact on terrestrial ecosystems, yet knowledge of their performance skills in representing the sensitivity of biophysical processes to changes in vegetation density is still limited. This is particularly relevant in light of the substantial impacts on regional climate associated with the changes in leaf area index (LAI) following the observed global greening. Benchmarking LSMs on the sensitivity of the simulated processes to vegetation density is essential to reduce their uncertainty and improve the representation of these effects. Here we present a novel benchmark system to assess model capacity in reproducing land surface-atmosphere energy exchanges modulated by vegetation density. Through a collaborative effort of different modeling groups, a consistent set of land surface energy fluxes and LAI dynamics has been generated from multiple LSMs, including JSBACH, JULES, ORCHIDEE, CLM4.5 and LPJ-GUESS. Relationships of interannual variations of modeled surface fluxes to LAI changes have been analyzed at global scale across different climatological gradients and compared with satellite-based products. A set of scoring metrics has been used to assess the overall model performances and a detailed analysis in the climate space has been provided to diagnose possible model errors associated to background conditions. Results have enabled us to identify model-specific strengths and deficiencies. An overall best performing model does not emerge from the analyses. However, the comparison with other models that work better under certain metrics and conditions indicates that improvements are expected to be potentially achievable. A general amplification of the biophysical processes mediated by vegetation is found across the different land surface schemes. Grasslands are characterized by an underestimated year-to-year variability of LAI in cold climates, ultimately affecting the amount of absorbed radiation. In addition patterns of simulated turbulent fluxes appear opposite to observations. Such systematic errors shed light on the current partial understanding of some of the mechanisms controlling the surface energy balance. In contrast forests appear reasonably well represented with respect to the interactions between LAI and turbulent fluxes across most climatological gradients, while for net radiation this is only true for warm climates. These proven strengths increase the confidence on how certain processes are simulated in LSMs. The model capacity to mimic the vegetation-biophysics interplay has been tested over the real scenario of greening that occurred in the last 30 years. We found that the modeled trends in surface heat fluxes associated with the long-term changes in leaf area could vary largely from those observed, with different discrepancies across models and climate zones. Our findings help to identify knowledge gaps and improve model representation of the sensitivity of biophysical processes to changes in leaf area density. In particular, comparing models and observations over a wide range of climate and vegetation conditions, as analyzed here, allowed capturing non-linearity of system responses that may emerge more frequently in future climate scenarios.

Using SMAP to identify structural errors in hydrologic models

NASA Astrophysics Data System (ADS)

Crow, W. T.; Reichle, R. H.; Chen, F.; Xia, Y.; Liu, Q.

2017-12-01

Despite decades of effort, and the development of progressively more complex models, there continues to be underlying uncertainty regarding the representation of basic water and energy balance processes in land surface models. Soil moisture occupies a central conceptual position between atmosphere forcing of the land surface and resulting surface water fluxes. As such, direct observations of soil moisture are potentially of great value for identifying and correcting fundamental structural problems affecting these models. However, to date, this potential has not yet been realized using satellite-based retrieval products. Using soil moisture data sets produced by the NASA Soil Moisture Active/Passive mission, this presentation will explore the use of the remotely-sensed soil moisture data products as a constraint to reject certain types of surface runoff parameterizations within a land surface model. Results will demonstrate that the precision of the SMAP Level 4 Surface and Root-Zone soil moisture product allows for the robust sampling of correlation statistics describing the true strength of the relationship between pre-storm soil moisture and subsequent storm-scale runoff efficiency (i.e., total storm flow divided by total rainfall both in units of depth). For a set of 16 basins located in the South-Central United States, we will use these sampled correlations to demonstrate that so-called "infiltration-excess" runoff parameterizations under predict the importance of pre-storm soil moisture for determining storm-scale runoff efficiency. To conclude, we will discuss prospects for leveraging this insight to improve short-term hydrologic forecasting and additional avenues for SMAP soil moisture products to provide process-level insight for hydrologic modelers.

Modification of land-atmosphere interactions by CO2 effects

NASA Astrophysics Data System (ADS)

Lemordant, Leo; Gentine, Pierre

2017-04-01

Plant stomata couple the energy, water and carbon cycles. Increased CO2 modifies the seasonality of the water cycle through stomatal regulation and increased leaf area. As a result, the water saved during the growing season through higher water use efficiency mitigates summer dryness and the impact of potential heat waves. Land-atmosphere interactions and CO2 fertilization together synergistically contribute to increased summer transpiration. This, in turn, alters the surface energy budget and decreases sensible heat flux, mitigating air temperature rise. Accurate representation of the response to higher CO2 levels, and of the coupling between the carbon and water cycles are therefore critical to forecasting seasonal climate, water cycle dynamics and to enhance the accuracy of extreme event prediction under future climate.

Assimilation and High Resolution Forecasts of Surface and Near Surface Conditions for the 2010 Vancouver Winter Olympic and Paralympic Games

NASA Astrophysics Data System (ADS)

Bernier, Natacha B.; Bélair, Stéphane; Bilodeau, Bernard; Tong, Linying

2014-01-01

A dynamical model was experimentally implemented to provide high resolution forecasts at points of interests in the 2010 Vancouver Olympics and Paralympics Region. In a first experiment, GEM-Surf, the near surface and land surface modeling system, is driven by operational atmospheric forecasts and used to refine the surface forecasts according to local surface conditions such as elevation and vegetation type. In this simple form, temperature and snow depth forecasts are improved mainly as a result of the better representation of real elevation. In a second experiment, screen level observations and operational atmospheric forecasts are blended to drive a continuous cycle of near surface and land surface hindcasts. Hindcasts of the previous day conditions are then regarded as today's optimized initial conditions. Hence, in this experiment, given observations are available, observation driven hindcasts continuously ensure that daily forecasts are issued from improved initial conditions. GEM-Surf forecasts obtained from improved short-range hindcasts produced using these better conditions result in improved snow depth forecasts. In a third experiment, assimilation of snow depth data is applied to further optimize GEM-Surf's initial conditions, in addition to the use of blended observations and forecasts for forcing. Results show that snow depth and summer temperature forecasts are further improved by the addition of snow depth data assimilation.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.

2011-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite-and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected as a co-winner of NASA?s 2005 Software of the Year award.LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has e volved from two earlier efforts -- North American Land Data Assimilation System (NLDAS) and Global Land Data Assimilation System (GLDAS) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations.In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems

43 CFR 8340.0-5 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Public Lands: Interior Regulations Relating to Public Lands (Continued) BUREAU OF LAND MANAGEMENT... Bureau of Land Management. (c) Bureau means the Bureau of Land Management. (d) Official use means use by..., in the course of his employment, agency, or representation. (e) Planning system means the approach...

Automatic detection of sweep-meshable volumes

DOEpatents

Tautges,; Timothy J. , White; David, R [Pittsburgh, PA

2006-05-23

A method of and software for automatically determining whether a mesh can be generated by sweeping for a representation of a geometric solid comprising: classifying surface mesh schemes for surfaces of the representation locally using surface vertex types; grouping mappable and submappable surfaces of the representation into chains; computing volume edge types for the representation; recursively traversing surfaces of the representation and grouping the surfaces into source, target, and linking surface lists; and checking traversal direction when traversing onto linking surfaces.

Modeling the impact of agricultural land use and management on US carbon budgets

DOE PAGES

Drewniak, B. A.; Mishra, U.; Song, J.; ...

2014-09-22

Cultivation of the terrestrial land surface can create either a source or sink of atmospheric CO 2, depending on land management practices. The Community Land Model (CLM) provides a useful tool to explore how land use and management impact the soil carbon pool at regional to global scales. CLM was recently updated to include representation of managed lands growing maize, soybean, and spring wheat. In this study, CLM-Crop is used to investigate the impacts of various management practices, including fertilizer use and differential rates of crop residue removal, on the soil organic carbon (SOC) storage of croplands in the continentalmore » United States over approximately a 170 year period. Results indicate that total US SOC stocks have already lost over 8 Pg C (10%) due to land cultivation practices (e.g., fertilizer application, cultivar choice, and residue removal), compared to a land surface composed of native vegetation (i.e., grasslands). After long periods of cultivation, individual plots growing maize and soybean lost up to 65% of the carbon stored, compared to a grassland site. Crop residue management showed the greatest effect on soil carbon storage, with low and medium residue returns resulting in additional losses of 5% and 3.5%, respectively, in US carbon storage, while plots with high residue returns stored 2% more carbon. Nitrogenous fertilizer can alter the amount of soil carbon stocks significantly. Under current levels of crop residue return, not applying fertilizer resulted in a 5% loss of soil carbon. Our simulations indicate that disturbance through cultivation will always result in a loss of soil carbon, and management practices will have a large influence on the magnitude of SOC loss.« less

Modeling the impact of agricultural land use and management on US carbon budgets

DOE PAGES

Drewniak, B. A.; Mishra, U.; Song, J.; ...

2015-04-09

Cultivation of the terrestrial land surface can create either a source or sink of atmospheric CO₂, depending on land management practices. The Community Land Model (CLM) provides a useful tool for exploring how land use and management impact the soil carbon pool at regional to global scales. CLM was recently updated to include representation of managed lands growing maize, soybean, and spring wheat. In this study, CLM-Crop is used to investigate the impacts of various management practices, including fertilizer use and differential rates of crop residue removal, on the soil organic carbon (SOC) storage of croplands in the continental Unitedmore » States over approximately a 170-year period. Results indicate that total US SOC stocks have already lost over 8 Pg C (10%) due to land cultivation practices (e.g., fertilizer application, cultivar choice, and residue removal), compared to a land surface composed of native vegetation (i.e., grasslands). After long periods of cultivation, individual subgrids (the equivalent of a field plot) growing maize and soybean lost up to 65% of the carbon stored compared to a grassland site. Crop residue management showed the greatest effect on soil carbon storage, with low and medium residue returns resulting in additional losses of 5 and 3.5%, respectively, in US carbon storage, while plots with high residue returns stored 2% more carbon. Nitrogenous fertilizer can alter the amount of soil carbon stocks significantly. Under current levels of crop residue return, not applying fertilizer resulted in a 5% loss of soil carbon. Our simulations indicate that disturbance through cultivation will always result in a loss of soil carbon, and management practices will have a large influence on the magnitude of SOC loss.« less

Issues related to incorporating northern peatlands into global climate models

NASA Astrophysics Data System (ADS)

Frolking, Steve; Roulet, Nigel; Lawrence, David

Northern peatlands cover ˜3-4 million km2 (˜10% of the land north of 45°N) and contain ˜200-400 Pg carbon (˜10-20% of total global soil carbon), almost entirely as peat (organic soil). Recent developments in global climate models have included incorporation of the terrestrial carbon cycle and representation of several terrestrial ecosystem types and processes in their land surface modules. Peatlands share many general properties with upland, mineral-soil ecosystems, and general ecosystem carbon, water, and energy cycle functions (productivity, decomposition, water infiltration, evapotranspiration, runoff, latent, sensible, and ground heat fluxes). However, northern peatlands also have several unique characteristics that will require some rethinking or revising of land surface algorithms in global climate models. Here we review some of these characteristics, deep organic soils, a significant fraction of bryophyte vegetation, shallow water tables, spatial heterogeneity, anaerobic biogeochemistry, and disturbance regimes, in the context of incorporating them into global climate models. With the incorporation of peatlands, global climate models will be able to simulate the fate of northern peatland carbon under climate change, and estimate the magnitude and strength of any climate system feedbacks associated with the dynamics of this large carbon pool.

African Easterly Waves in 30-day High-Resolution Global Simulations: A Case Study During the 2006 NAMMA Period

NASA Technical Reports Server (NTRS)

Shen, Bo-Wen; Tao, Wei-Kuo; Wu, Man-Li C.

2010-01-01

In this study, extended -range (30 -day) high-resolution simulations with the NASA global mesoscale model are conducted to simulate the initiation and propagation of six consecutive African easterly waves (AEWs) from late August to September 2006 and their association with hurricane formation. It is shown that the statistical characteristics of individual AEWs are realistically simulated with larger errors in the 5th and 6th AEWs. Remarkable simulations of a mean African easterly jet (AEJ) are also obtained. Nine additional 30 -day experiments suggest that although land surface processes might contribute to the predictability of the AEJ and AEWs, the initiation and detailed evolution of AEWs still depend on the accurate representation of dynamic and land surface initial conditions and their time -varying nonlinear interactions. Of interest is the potential to extend the lead time for predicting hurricane formation (e.g., a lead time of up to 22 days) as the 4th AEW is realistically simulated.

[Multi-Scale Convergence of Cold-Land Process Representation in Land-Surface Models, Microwave Remote Sensing, and Field Observations

NASA Technical Reports Server (NTRS)

Shi, Jiancheng

2005-01-01

The cryosphere is a major component of the hydrosphere and interacts significantly with the global climate system, the geosphere, and the biosphere. Measurement of the amount of water stored in the snow pack and forecasting the rate of melt are thus essential for managing water supply and flood control systems. Snow hydrologists are confronted with the dual problems of estimating both the quantity of water held by seasonal snow packs and time of snow melt. Monitoring these snow parameters is essential for one of the objectives of the Earth Science Enterprise-understanding of the global hydrologic cycle. Measuring spatially distributed snow properties, such as snow water equivalence (SWE) and wetness, from space is a key component for improvement of our understanding of coupled atmosphere-surface processes. Through the GWEC project, we have significantly advanced our understandings and improved modeling capabilities of the microwave signatures in response to snow and underground properties.

Using satellite observations to improve model estimates of CO2 and CH4 flux: a Metropolis Hastings Markov Chain Monte Carlo approach

NASA Astrophysics Data System (ADS)

MacBean, Natasha; Disney, Mathias; Lewis, Philip; Ineson, Phil

2010-05-01

Peatlands are wetlands with an organic soil layer of >30cm (Limpens et al., 2008) that occur beneath a living plant layer as a result of the waterlogged nature of the soil restricting complete decay of the biomass (Charman, 2002). Peatlands are important ecosystems; boreal and subarctic peatlands are estimated to contain 455Pg of carbon (Gorham, 1991), about 15-30% of the world's soil carbon (Limpens et al., 2008), and yet constitute less than 3% of the world's total land area (Lai, 2009). Peatlands not only sequester CO2 through photosynthesis and the partial decomposition of organic matter but they release methane (CH4) due to anaerobic microbial activity under waterlogged conditions. The balance is even more complex, as microbial consumption of CH4 can result in additional CO2 being emitted to the atmosphere. Wetlands are the main source of natural CH4 (Le Mer and Roger, 2001). Northern wetlands contribute about 35Tgyr-1 (Bubier and Moore, 1994). The uncertainty on this estimate is large 1 mgm-2yr-1 to 2200 mgm-2yr-1. Given that CH4 is 20 to 30 times more efficient at absorbing infrared radiation than CO2 there is a need to better quantify CH4 emissions and their role in the net carbon balance of peatlands. Two of the key variables in the calculation of CH4 production are water table depth and soil temperature. Water table depth is important as methanogenic bacteria are predominantly active in the anoxic zone. In order to accurately model the water table depth a correct representation of the whole soil moisture profile is important. Soil moisture and soil temperature are important variables in model calculations, as they affect the decomposition of carbon in the soil, as well as influencing the water and energy fluxes at the surface - atmosphere boundary. Microwave measurements of surface soil moisture and thermal measurements of land surface temperature from satellites can theoretically be used to improve the representation of the hydrology and soil temperature profile as a whole. We present results from an Observing System Simulation Experiment (OSSE) designed to investigate the impact of management and climate change on peatland carbon fluxes, as well as how observations from satellites may be able to constrain modeled carbon fluxes. We use an adapted version of the Carnegie-Ames-Stanford Approach (CASA) model (Potter et al., 1993) that includes a representation of methane dynamics (Potter, 1997). The model formulation is further modified to allow for assimilation of satellite observations of surface soil moisture and land surface temperature. The observations are used to update model estimates using a Metropolis Hastings Markov Chain Monte Carlo (MCMC) approach. We examine the effect of temporal frequency and precision of satellite observations with a view to establishing how, and at what level, such observations would make a significant improvement in model uncertainty. We compare this with the system characteristics of existing and future satellites. We believe this is the first attempt to assimilate surface soil moisture and land surface temperature into an ecosystem model that includes a full representation of CH4 flux. Bubier, J., and T. Moore (1994), An ecological perspective on methane emissions from northern wetlands, TREE, 9, 460-464. Charman, D. (2002), Peatlands and Environmental Change, JohnWiley and Sons, Ltd, England. Gorham, E. (1991), Northern peatlands: Role in the carbon cycle and probable responses to climatic warming, Ecological Applications, 1, 182-195. Lai, D. (2009), Methane dynamics in northern peatlands: A review, Pedosphere, 19, 409-421. Le Mer, J., and P. Roger (2001), Production, oxidation, emission and consumption of methane by soils: A review, European Journal of Soil Biology, 37, 25-50. Limpens, J., F. Berendse, J. Canadell, C. Freeman, J. Holden, N. Roulet, H. Rydin, and Potter, C. (1997), An ecosystem simulation model for methane production and emission from wetlands, Global Biogeochemical Cycles, 11, 495-506. Potter, C., J. Randerson, C. Field, P. Matson, P. Vitousek, H. Mooney, and S. Klooster (1993), Terrestrial ecosystem production: A process model based on global satellite and surface data, Global Biogeochemical Cycles, 7, 811-841.

Changes in the lower boundary condition of water fluxes in the NOAH land surface scheme

NASA Astrophysics Data System (ADS)

Lohmann, D.; Peters-Lidard, C. D.

2002-05-01

One problem with current land surface schemes (LSS) used in weather prediction and climate models is their inabilty to reproduce streamflow in large river basins. This can be attributed to the weak representation of their upper (infiltration) and lower (baseflow) boundary conditions in their water balance / transport equations. Operational (traditional) hydrological models, which operate on the same spatial scale as a LSS, on the other hand, are able to reproduce streamflow time series. Their infiltration and baseflow equations are often empirically based and therefore have been neglected by the LSS community. It must be argued that we need to include a better representation of long time scales (as represented by groundwater and baseflow) into the current LSS to make valuable predictions of streamflow and water resources. This talk concentrates on the lower boundary condition of water fluxes within LSS. It reviews briefly previous attempts to incorporate groundwater and more realistic lower boundary conditions into LSS and summarizes the effect on the runoff (baseflow) production time scales as compared to currently used lower boundary conditions in LSS. The NOAH - LSM in the LDAS and DMIP setting is used to introduce a simplified groundwater model, based on the linearized Boussinesq equation, and the TOPMODEL. The NOAH - LSM will be coupled to a linear routing model to investigate the effects of the new lower boundary condition on the water balance (in particular, streamflow) in small to medium sized catchments in the LDAS / DMIP domain.

Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

NASA Technical Reports Server (NTRS)

Zaitchik, Benjamin F.; Rodell, Matthew

2008-01-01

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

Improving the Understanding and Model Representation of Processes that Couple Shallow Clouds, Aerosols, and Land-Ecosystems

NASA Astrophysics Data System (ADS)

Fast, J. D.; Berg, L. K.; Schmid, B.; Alexander, M. L. L.; Bell, D.; D'Ambro, E.; Hubbe, J. M.; Liu, J.; Mei, F.; Pekour, M. S.; Pinterich, T.; Schobesberger, S.; Shilling, J.; Springston, S. R.; Thornton, J. A.; Tomlinson, J. M.; Wang, J.; Zelenyuk, A.

2016-12-01

Cumulus convection is an important component in the atmospheric radiation budget and hydrologic cycle over the southern Great Plains and over many regions of the world, particularly during the summertime growing season when intense turbulence induced by surface radiation couples the land surface to clouds. Current convective cloud parameterizations, however, contain uncertainties resulting from insufficient coincident data that couples cloud macrophysical and microphysical properties to inhomogeneity in surface layer, boundary layer, and aerosol properties. We describe the measurement strategy and preliminary findings from the recent Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign conducted in May and September of 2016 in the vicinity of the DOE's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site located in Oklahoma. The goal of the HI-SCALE campaign is to provide a detailed set of aircraft and surface measurements needed to obtain a more complete understanding and improved parameterizations of the lifecycle of shallow clouds. The sampling is done in two periods, one in the spring and the other in the late summer to take advantage of variations in the "greenness" for various types of vegetation, new particle formation, anthropogenic enhancement of biogenic secondary organic aerosol (SOA), and other aerosol properties. The aircraft measurements will be coupled with extensive routine ARM SGP measurements as well as Large Eddy Simulation (LES), cloud resolving, and cloud-system resolving models. Through these integrated analyses and modeling studies, the affects of inhomogeneity in land use, vegetation, soil moisture, convective eddies, and aerosol properties on the evolution of shallow clouds will be determined, including the feedbacks of cloud radiative effects.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we contend that creating believable soil carbon predictions requires a robust, transparent, and community-available benchmarking framework. I will present an ILAMB evaluation of several of the above-mentioned approaches in ACME, and attempt to motivate community adoption of this evaluation approach.

A WRF sensitivity study for summer ozone and winter PM events in California

NASA Astrophysics Data System (ADS)

Zhao, Z.; Chen, J.; Mahmud, A.; Di, P.; Avise, J.; DaMassa, J.; Kaduwela, A. P.

2014-12-01

Elevated summer ozone and winter PM frequently occur in the San Joaquin Valley (SJV) and the South Coast Air Basin (SCAB) in California. Meteorological conditions, such as wind, temperature and planetary boundary layer height (PBLH) play crucial roles in these air pollution events. Therefore, accurate representation of these fields from a meteorological model is necessary to successfully reproduce these air pollution events in subsequent air quality model simulations. California's complex terrain and land-sea interface can make it challenging for meteorological models to replicate the atmospheric conditions over the SJV and SCAB during extreme pollution events. In this study, the performance of the Weather Research and Forecasting Model (WRF) over these two regions for a summer month (July 2012) and a winter month (January 2013) is evaluated with different model configurations and forcing. Different land surface schemes (Pleim-Xiu vs. hybrid scheme), the application of observational and soil nudging, two SST datasets (the Global Ocean Data Assimilation Experiment (GODAE) SST vs. the default SST from North American Regional Reanalysis (NARR) reanalysis), and two land use datasets (the National Land Cover Data (NLCD) 2006 40-category vs. USGS 24-category land use data) have been tested. Model evaluation will focus on both surface and vertical profiles for wind, temperature, relative humidity, as well as PBLH. Sensitivity of the Community Multi-scale Air Quality Model (CMAQ) results to different WRF configurations will also be presented and discussed.

Heterogeneity and scaling land-atmospheric water and energy fluxes in climate systems

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, three modeling experiments were performed and are reviewed in the paper. The first is concerned with the aggregation of parameters and inputs for a terrestrial water and energy balance model. The second experiment analyzed the scaling behavior of hydrologic responses during rain events and between rain events. The third experiment compared the hydrologic responses from distributed models with a lumped model that uses spatially constant inputs and parameters. The results show that the patterns of small scale variations can be represented statistically if the scale is larger than a representative elementary area scale, which appears to be about 2 - 3 times the correlation length of the process. For natural catchments this appears to be about 1 - 2 sq km. The results concerning distributed versus lumped representations are more complicated. For conditions when the processes are nonlinear, then lumping results in biases; otherwise a one-dimensional model based on 'equivalent' parameters provides quite good results. Further research is needed to fully understand these conditions.

The Joint UK Land Environment Simulator (JULES), Model description - Part 2: Carbon fluxes and vegetation

NASA Astrophysics Data System (ADS)

Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Cox, P. M.

2011-03-01

The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Past studies with JULES have demonstrated the important role of the land surface in the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of separately changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. There was a need to consolidate these and other advances into a single model code so as to be able to study interactions in a consistent manner. This paper describes the consolidation of these advances into the modelling of carbon fluxes and stores, in the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.

The Aggregate Representation of Terrestrial Land Covers Within Global Climate Models (GCM)

NASA Technical Reports Server (NTRS)

Shuttleworth, W. James; Sorooshian, Soroosh

1996-01-01

This project had four initial objectives: (1) to create a realistic coupled surface-atmosphere model to investigate the aggregate description of heterogeneous surfaces; (2) to develop a simple heuristic model of surface-atmosphere interactions; (3) using the above models, to test aggregation rules for a variety of realistic cover and meteorological conditions; and (4) to reconcile biosphere-atmosphere transfer scheme (BATS) land covers with those that can be recognized from space; Our progress in meeting these objectives can be summarized as follows. Objective 1: The first objective was achieved in the first year of the project by coupling the Biosphere-Atmosphere Transfer Scheme (BATS) with a proven two-dimensional model of the atmospheric boundary layer. The resulting model, BATS-ABL, is described in detail in a Masters thesis and reported in a paper in the Journal of Hydrology Objective 2: The potential value of the heuristic model was re-evaluated early in the project and a decision was made to focus subsequent research around modeling studies with the BATS-ABL model. The value of using such coupled surface-atmosphere models in this research area was further confirmed by the success of the Tucson Aggregation Workshop. Objective 3: There was excellent progress in using the BATS-ABL model to test aggregation rules for a variety of realistic covers. The foci of attention have been the site of the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) in Kansas and one of the study sites of the Anglo-Brazilian Amazonian Climate Observational Study (ABRACOS) near the city of Manaus, Amazonas, Brazil. These two sites were selected because of the ready availability of relevant field data to validate and initiate the BATS-ABL model. The results of these tests are given in a Masters thesis, and reported in two papers. Objective 4: Progress far exceeded original expectations not only in reconciling BATS land covers with those that can be recognized from space, but also in then applying remotely-sensed land cover data to map aggregate values of BATS parameters for heterogeneous covers and interpreting these parameters in terms of surface-atmosphere exchanges.

Validating modeled soil moisture with in-situ data for agricultural drought monitoring in West Africa

NASA Astrophysics Data System (ADS)

McNally, A.; Yatheendradas, S.; Jayanthi, H.; Funk, C. C.; Peters-Lidard, C. D.

2011-12-01

The declaration of famine in Somalia on July 21, 2011 highlights the need for regional hydroclimate analysis at a scale that is relevant for agropastoral drought monitoring. A particularly critical and robust component of such a drought monitoring system is a land surface model (LSM). We are currently enhancing the Famine Early Warning Systems Network (FEWS NET) monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System (FLDAS). Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following question: How can Noah be best parameterized to accurately simulate hydroclimate variables associated with crop performance? Parameter value testing and validation is done by comparing modeled soil moisture against fortuitously available in-situ soil moisture observations in the West Africa. Direct testing and application of the FLDAS over African agropastoral locations is subject to some issues: [1] In many regions that are vulnerable to food insecurity ground based measurements of precipitation, evapotranspiration and soil moisture are sparse or non-existent, [2] standard landcover classes (e.g., the University of Maryland 5 km dataset), do not include representations of specific agricultural crops with relevant parameter values, and phenologies representing their growth stages from the planting date and [3] physically based land surface models and remote sensing rain data might still need to be calibrated or bias-corrected for the regions of interest. This research aims to address these issues by focusing on sites in the West African countries of Mali, Niger, and Benin where in-situ rainfall and soil moisture measurements are available from the African Monsoon Multidisciplinary Analysis (AMMA). Preliminary results from model experiments over Southern Malawi, validated with Normalized Difference Vegetation Index (NDVI) and maize yield data, show that the ability to detect a drought signal in modeled soil moisture and actual evapotranspiration was sensitive to parameters like minimum stomatal resistance, green vegetation fraction, and minimum threshold for transpiration stress. In addition to improving our understanding and representation of the land surface physics in agropastoral drought, this study moves us closer to confidently validating LSM estimates with remotely sensed data (e.g. MODIS NDVI), essential in regions that lack ground based measurements. Ultimately, these improved information products serve to better inform decision makers about seasonal food production and anticipate the need for relief, as well as guide climate change adaptation strategies, potentially saving millions of lives.

Simulation of the West African Monsoon using the MIT Regional Climate Model

NASA Astrophysics Data System (ADS)

Im, Eun-Soon; Gianotti, Rebecca L.; Eltahir, Elfatih A. B.

2013-04-01

We test the performance of the MIT Regional Climate Model (MRCM) in simulating the West African Monsoon. MRCM introduces several improvements over Regional Climate Model version 3 (RegCM3) including coupling of Integrated Biosphere Simulator (IBIS) land surface scheme, a new albedo assignment method, a new convective cloud and rainfall auto-conversion scheme, and a modified boundary layer height and cloud scheme. Using MRCM, we carried out a series of experiments implementing two different land surface schemes (IBIS and BATS) and three convection schemes (Grell with the Fritsch-Chappell closure, standard Emanuel, and modified Emanuel that includes the new convective cloud scheme). Our analysis primarily focused on comparing the precipitation characteristics, surface energy balance and large scale circulations against various observations. We document a significant sensitivity of the West African monsoon simulation to the choices of the land surface and convection schemes. In spite of several deficiencies, the simulation with the combination of IBIS and modified Emanuel schemes shows the best performance reflected in a marked improvement of precipitation in terms of spatial distribution and monsoon features. In particular, the coupling of IBIS leads to representations of the surface energy balance and partitioning that are consistent with observations. Therefore, the major components of the surface energy budget (including radiation fluxes) in the IBIS simulations are in better agreement with observation than those from our BATS simulation, or from previous similar studies (e.g Steiner et al., 2009), both qualitatively and quantitatively. The IBIS simulations also reasonably reproduce the dynamical structure of vertically stratified behavior of the atmospheric circulation with three major components: westerly monsoon flow, African Easterly Jet (AEJ), and Tropical Easterly Jet (TEJ). In addition, since the modified Emanuel scheme tends to reduce the precipitation amount, it improves the precipitation over regions suffering from systematic wet bias.

Multi-Scale Hydrometeorological Modeling, Land Data Assimilation and Parameter Estimation with the Land Information System

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Kumar, Sujay V.; Santanello, Joseph A., Jr.; Reichle, Rolf H.

2009-01-01

The Land Information System (LIS; http://lis.gsfc.nasa.gov; Kumar et al., 2006; Peters- Lidard et al.,2007) is a flexible land surface modeling framework that has been developed with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. As such, LIS represents a step towards the next generation land component of an integrated Earth system model. In recognition of LIS object-oriented software design, use and impact in the land surface and hydrometeorological modeling community, the LIS software was selected ase co-winner of NASA's 2005 Software of the Year award. LIS facilitates the integration of observations from Earth-observing systems and predictions and forecasts from Earth System and Earth science models into the decision-making processes of partnering agency and national organizations. Due to its flexible software design, LIS can serve both as a Problem Solving Environment (PSE) for hydrologic research to enable accurate global water and energy cycle predictions, and as a Decision Support System (DSS) to generate useful information for application areas including disaster management, water resources management, agricultural management, numerical weather prediction, air quality and military mobility assessment. LIS has evolved from two earlier efforts North American Land Data Assimilation System (NLDAS; Mitchell et al. 2004) and Global Land Data Assimilation System (GLDAS; Rodell al. 2004) that focused primarily on improving numerical weather prediction skills by improving the characterization of the land surface conditions. Both of GLDAS and NLDAS now use specific configurations of the LIS software in their current implementations. In addition, LIS was recently transitioned into operations at the US Air Force Weather Agency (AFWA) to ultimately replace their Agricultural Meteorology (AGRMET) system, and is also used routinely by NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.

A Modeling and Verification Study of Summer Precipitation Systems Using NASA Surface Initialization Datasets

NASA Technical Reports Server (NTRS)

Jonathan L. Case; Kumar, Sujay V.; Srikishen, Jayanthi; Jedlovec, Gary J.

2010-01-01

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse-type convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within parameterization schemes, model resolution limitations, and uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture, soil temperature, and sea surface temperature (SST) are necessary to better simulate the interactions between the surface and atmosphere, and ultimately improve predictions of summertime pulse convection. This paper describes a sensitivity experiment using the Weather Research and Forecasting (WRF) model. Interpolated land and ocean surface fields from a large-scale model are replaced with high-resolution datasets provided by unique NASA assets in an experimental simulation: the Land Information System (LIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) SSTs. The LIS is run in an offline mode for several years at the same grid resolution as the WRF model to provide compatible land surface initial conditions in an equilibrium state. The MODIS SSTs provide detailed analyses of SSTs over the oceans and large lakes compared to current operational products. The WRF model runs initialized with the LIS+MODIS datasets result in a reduction in the overprediction of rainfall areas; however, the skill is almost equally as low in both experiments using traditional verification methodologies. Output from object-based verification within NCAR s Meteorological Evaluation Tools reveals that the WRF runs initialized with LIS+MODIS data consistently generated precipitation objects that better matched observed precipitation objects, especially at higher precipitation intensities. The LIS+MODIS runs produced on average a 4% increase in matched precipitation areas and a simultaneous 4% decrease in unmatched areas during three months of daily simulations.

Comparing Noah-MP simulations of energy and water fluxes in the soil-vegetation-atmosphere continuum with plot scale measurements

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Högy, Petra; Ingwersen, Joachim; Wizemann, Hans-Dieter; Wulfmeyer, Volker; Streck, Thilo

2013-04-01

During the last years, land-surface models have proven to perform well in several studies that compared simulated fluxes of water and energy from the land surface to the atmosphere against measured fluxes at the plot-scale. In contrast, considerable deficits of land-surface models have been identified to simulate soil water fluxes and vertical soil moisture distribution. For example, Gayler et al. (2013) showed that simplifications in the representation of root water uptake can result in insufficient simulations of the vertical distribution of soil moisture and its dynamics. However, in coupled simulations of the terrestrial water cycle, both sub-systems, the atmosphere and the subsurface hydrogeo-system, must fit together and models are needed, which are able to adequately simulate soil moisture, latent heat flux, and their interrelationship. Consequently, land-surface models must be further improved, e.g. by incorporation of advanced biogeophysics models. To improve the conceptual realism in biophysical and hydrological processes in the community land surface model Noah, this model was recently enhanced to Noah-MP by a multi-options framework to parameterize individual processes (Niu et al., 2011). Thus, in Noah-MP the user can choose from several alternative models for vegetation and hydrology processes that can be applied in different combinations. In this study, we evaluate the performance of different Noah-MP model settings to simulate water and energy fluxes across the land surface at two contrasting field sites in South-West Germany. The evaluation is done in 1D offline-mode, i.e. without coupling to an atmospheric model. The atmospheric forcing is provided by measured time series of the relevant variables. Simulation results are compared with eddy covariance measurements of turbulent fluxes and measured time series of soil moisture at different depths. The aims of the study are i) to carve out the most appropriate combination of process parameterizations in Noah-MP to simultaneously match the different components of the water and energy cycle at the field sites under consideration, and ii) to estimate the uncertainty in model structure. We further investigate the potential to improve simulation results by incorporating concepts of more advanced root water uptake models from agricultural field scale models into the land-surface-scheme. Gayler S, Ingwersen J, Priesack E, Wöhling T, Wulfmeyer V, Streck T (2013): Assessing the relevance of sub surface processes for the simulation of evapotranspiration and soil moisture dynamics with CLM3.5: Comparison with field data and crop model simulations. Environ. Earth Sci., 69(2), under revision. Niu G-Y, Yang Z-L, Mitchell KE, Chen F, Ek MB, Barlage M, Kumar A, Manning K, Niyogi D, Rosero E, Tewari M and Xia Y (2011): The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal of Geophysical Research 116(D12109).

An approach for modelling snowcover ablation and snowmelt runoff in cold region environments

NASA Astrophysics Data System (ADS)

Dornes, Pablo Fernando

Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments. This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements. Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments.

Design and Impacts of Land-Biogenic-Atmosphere Coupling in the NASA-Unified WRF (NU-WRF) Modeling System

NASA Technical Reports Server (NTRS)

Tan, Qian; Santanello, Joseph A., Jr.; Zhou, Shujia; Tao, Zhining; Peters-Lidard, Christa d.; Chn, Mian

2011-01-01

Land-Atmosphere coupling is typically designed and implemented independently for physical (e.g. water and energy) and chemical (e.g. biogenic emissions and surface depositions)-based models and applications. Differences in scale, data requirements, and physics thus limit the ability of Earth System models to be fully coupled in a consistent manner. In order for the physical-chemical-biological coupling to be complete, treatment of the land in terms of surface classification, condition, fluxes, and emissions must be considered simultaneously and coherently across all components. In this study, we investigate a coupling strategy for the NASA-Unified Weather Research and Forecasting (NU-WRF) model that incorporates the traditionally disparate fluxes of water and energy through NASA's LIS (Land Information System) and biogenic emissions through BEIS (Biogenic Emissions Inventory System) and MEGAN (Model of Emissions of Gases and Aerosols from Nature) into the atmosphere. In doing so, inconsistencies across model inputs and parameter data are resolved such that the emissions from a particular plant species are consistent with the heat and moisture fluxes calculated for that land cover type. In turn, the response of the atmospheric turbulence and mixing in the planetary boundary layer (PBL) acts on the identical surface type, fluxes, and emissions for each. In addition, the coupling of dust emission within the NU-WRF system is performed in order to ensure consistency and to maximize the benefit of high-resolution land representation in LIS. The impacts of those self-consistent components on' the simulation of atmospheric aerosols are then evaluated through the WRF-Chem-GOCART (Goddard Chemistry Aerosol Radiation and Transport) model. Overall, this ambitious project highlights the current difficulties and future potential of fully coupled. components. in Earth System models, and underscores the importance of the iLEAPS community in supporting improved knowledge of processes and innovative approaches for models and observations.

Climatological Data For Clouds Over the Globe From Surface Observations, 1982-1991: The Total Cloud Edition (1994) (NDP-026a)

DOE Data Explorer

Hahn, Carole J. [Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES); Warren, Stephen G. [Department of Atmospheric Sciences, University of Colorado, Boulder, CO; London, Julius [Department of Astrophysical, Planetary, and Atmospheric Sciences, University of Colorado, Boulder, CO

1994-01-01

Routine, synoptic surface weather reports from ships and land stations over the entire globe, for the10-year period December 1981 through November 1991, were processed for total cloud cover and the frequencies of occurrence of clear sky, sky-obscured due to precipitation, and sky-obscured due to fog. Archived data, consisting of various annual, seasonal and monthly averages, are provided in grid boxes that are typically 2.5° × 2.5° for land and 5° × 5° for ocean. Day and nighttime averages are also given separately for each season. Several derived quantities, such as interannual variations and annual and diurnal harmonics, are provided as well. This data set incorporates an improved representation of nighttime cloudiness by utilizing only those nighttime observations for which the illuminance due to moonlight exceeds a specified threshold. This reduction in the night-detection bias increases the computed global average total cloud cover by about 2%. The impact on computed diurnal cycles is even greater, particularly over the oceans where it is found (in contrast to previous surface-based climatologies), that cloudiness is often greater at night than during the day.

Capturing the sensitivity of land-use regression models to short-term mobile monitoring campaigns using air pollution micro-sensors.

PubMed

Minet, L; Gehr, R; Hatzopoulou, M

2017-11-01

The development of reliable measures of exposure to traffic-related air pollution is crucial for the evaluation of the health effects of transportation. Land-use regression (LUR) techniques have been widely used for the development of exposure surfaces, however these surfaces are often highly sensitive to the data collected. With the rise of inexpensive air pollution sensors paired with GPS devices, we witness the emergence of mobile data collection protocols. For the same urban area, can we achieve a 'universal' model irrespective of the number of locations and sampling visits? Can we trade the temporal representation of fixed-point sampling for a larger spatial extent afforded by mobile monitoring? This study highlights the challenges of short-term mobile sampling campaigns in terms of the resulting exposure surfaces. A mobile monitoring campaign was conducted in 2015 in Montreal; nitrogen dioxide (NO 2 ) levels at 1395 road segments were measured under repeated visits. We developed LUR models based on sub-segments, categorized in terms of the number of visits per road segment. We observe that LUR models were highly sensitive to the number of road segments and to the number of visits per road segment. The associated exposure surfaces were also highly dissimilar. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of WRF local and nonlocal boundary layer Physics in Greater Kuala Lumpur, Malaysia

NASA Astrophysics Data System (ADS)

Ooi, M. C. G.; Chan, A.; Kumarenthiran, S.; Morris, K. I.; Oozeer, M. Y.; Islam, M. A.; Salleh, S. A.

2018-02-01

The urban boundary layer (UBL) is the internal advection layer of atmosphere above urban region which determines the exchanges of momentum, water and other atmospheric constituents between the urban land surface and the free troposphere. This paper tested the performance of three planetary boundary layer (PBL) physics schemes of Weather Research and Forecast (WRF) software to ensure the appropriate representation of vertical structure of UBL in Greater Kuala Lumpur (GKL). Comparison was conducted on the performance of respective PBL schemes to generate vertical and near-surface weather profile and rainfall. Mellor-Yamada- Janjíc (MYJ) local PBL scheme coupled with Eta MM5 surface layer scheme was found to predict the near-surface temperature and wind profile and mixing height better than the nonlocal schemes during the intermonsoonal period with least influences of the synoptic background weather.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

PubMed

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.

Incorporating human-water dynamics in a hyper-resolution land surface model

NASA Astrophysics Data System (ADS)

Vergopolan, N.; Chaney, N.; Wanders, N.; Sheffield, J.; Wood, E. F.

2017-12-01

The increasing demand for water, energy, and food is leading to unsustainable groundwater and surface water exploitation. As a result, the human interactions with the environment, through alteration of land and water resources dynamics, need to be reflected in hydrologic and land surface models (LSMs). Advancements in representing human-water dynamics still leave challenges related to the lack of water use data, water allocation algorithms, and modeling scales. This leads to an over-simplistic representation of human water use in large-scale models; this is in turn leads to an inability to capture extreme events signatures and to provide reliable information at stakeholder-level spatial scales. The emergence of hyper-resolution models allows one to address these challenges by simulating the hydrological processes and interactions with the human impacts at field scales. We integrated human-water dynamics into HydroBlocks - a hyper-resolution, field-scale resolving LSM. HydroBlocks explicitly solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs); and its HRU-based model parallelization allows computationally efficient long-term simulations as well as ensemble predictions. The implemented human-water dynamics include groundwater and surface water abstraction to meet agricultural, domestic and industrial water demands. Furthermore, a supply-demand water allocation scheme based on relative costs helps to determine sectoral water use requirements and tradeoffs. A set of HydroBlocks simulations over the Midwest United States (daily, at 30-m spatial resolution for 30 years) are used to quantify the irrigation impacts on water availability. The model captures large reductions in total soil moisture and water table levels, as well as spatiotemporal changes in evapotranspiration and runoff peaks, with their intensity related to the adopted water management strategy. By incorporating human-water dynamics in a hyper-resolution LSM this work allows for progress on hydrological monitoring and predictions, as well as drought preparedness and water impact assessments at relevant decision-making scales.

Biogenic isoprene emissions driven by regional weather predictions using different initialization methods: case studies during the SEAC4RS and DISCOVER-AQ airborne campaigns

NASA Astrophysics Data System (ADS)

Huang, Min; Carmichael, Gregory R.; Crawford, James H.; Wisthaler, Armin; Zhan, Xiwu; Hain, Christopher R.; Lee, Pius; Guenther, Alex B.

2017-08-01

Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that using land initial conditions directly downscaled from a coarser resolution dataset led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7) surface and near-surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF surface air temperature by ˜ 2 °C. We also show that the LIS land initialization can modify surface air temperature errors almost 10 times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF-based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the coarser resolution data-initialized NUWRF run, and are closer to aircraft-observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified discrepancies with aircraft-observation-derived emissions on small scales. This is possibly a result of some limitations of MEGAN's parameterization and uncertainty in its inputs on small scales, as well as the representation error and the neglect of horizontal transport in deriving emissions from aircraft data. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling. We anticipate it to also be critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

Mapping Surface Cover Parameters Using Aggregation Rules and Remotely Sensed Cover Classes. Version 1.9

NASA Technical Reports Server (NTRS)

Arain, Altaf M.; Shuttleworth, W. James; Yang, Z-Liang; Michaud, Jene; Dolman, Johannes

1997-01-01

A coupled model, which combines the Biosphere-Atmosphere Transfer Scheme (BATS) with an advanced atmospheric boundary-layer model, was used to validate hypothetical aggregation rules for BATS-specific surface cover parameters. The model was initialized and tested with observations from the Anglo-Brazilian Amazonian Climate Observational Study and used to simulate surface fluxes for rain forest and pasture mixes at a site near Manaus in Brazil. The aggregation rules are shown to estimate parameters which give area-average surface fluxes similar to those calculated with explicit representation of forest and pasture patches for a range of meteorological and surface conditions relevant to this site, but the agreement deteriorates somewhat when there are large patch-to-patch differences in soil moisture. The aggregation rules, validated as above, were then applied to remotely sensed 1 km land cover data set to obtain grid-average values of BATS vegetation parameters for 2.8 deg x 2.8 deg and 1 deg x 1 deg grids within the conterminous United States. There are significant differences in key vegetation parameters (aerodynamic roughness length, albedo, leaf area index, and stomatal resistance) when aggregate parameters are compared to parameters for the single, dominant cover within the grid. However, the surface energy fluxes calculated by stand-alone BATS with the 2-year forcing, data from the International Satellite Land Surface Climatology Project (ISLSCP) CDROM were reasonably similar using aggregate-vegetation parameters and dominant-cover parameters, but there were some significant differences, particularly in the western USA.

ORCHIDEE-SOM: modeling soil organic carbon (SOC) and dissolved organic carbon (DOC) dynamics along vertical soil profiles in Europe

NASA Astrophysics Data System (ADS)

Camino-Serrano, Marta; Guenet, Bertrand; Luyssaert, Sebastiaan; Ciais, Philippe; Bastrikov, Vladislav; De Vos, Bruno; Gielen, Bert; Gleixner, Gerd; Jornet-Puig, Albert; Kaiser, Klaus; Kothawala, Dolly; Lauerwald, Ronny; Peñuelas, Josep; Schrumpf, Marion; Vicca, Sara; Vuichard, Nicolas; Walmsley, David; Janssens, Ivan A.

2018-03-01

Current land surface models (LSMs) typically represent soils in a very simplistic way, assuming soil organic carbon (SOC) as a bulk, and thus impeding a correct representation of deep soil carbon dynamics. Moreover, LSMs generally neglect the production and export of dissolved organic carbon (DOC) from soils to rivers, leading to overestimations of the potential carbon sequestration on land. This common oversimplified processing of SOC in LSMs is partly responsible for the large uncertainty in the predictions of the soil carbon response to climate change. In this study, we present a new soil carbon module called ORCHIDEE-SOM, embedded within the land surface model ORCHIDEE, which is able to reproduce the DOC and SOC dynamics in a vertically discretized soil to 2 m. The model includes processes of biological production and consumption of SOC and DOC, DOC adsorption on and desorption from soil minerals, diffusion of SOC and DOC, and DOC transport with water through and out of the soils to rivers. We evaluated ORCHIDEE-SOM against observations of DOC concentrations and SOC stocks from four European sites with different vegetation covers: a coniferous forest, a deciduous forest, a grassland, and a cropland. The model was able to reproduce the SOC stocks along their vertical profiles at the four sites and the DOC concentrations within the range of measurements, with the exception of the DOC concentrations in the upper soil horizon at the coniferous forest. However, the model was not able to fully capture the temporal dynamics of DOC concentrations. Further model improvements should focus on a plant- and depth-dependent parameterization of the new input model parameters, such as the turnover times of DOC and the microbial carbon use efficiency. We suggest that this new soil module, when parameterized for global simulations, will improve the representation of the global carbon cycle in LSMs, thus helping to constrain the predictions of the future SOC response to global warming.

Global land-atmosphere coupling associated with cold climate processes

NASA Astrophysics Data System (ADS)

Dutra, Emanuel

This dissertation constitutes an assessment of the role of cold processes, associated with snow cover, in controlling the land-atmosphere coupling. The work was based on model simulations, including offline simulations with the land surface model HTESSEL, and coupled atmosphere simulations with the EC-EARTH climate model. A revised snow scheme was developed and tested in HTESSEL and EC-EARTH. The snow scheme is currently operational at the European Centre for Medium-Range Weather Forecasts integrated forecast system, and in the default configuration of EC-EARTH. The improved representation of the snowpack dynamics in HTESSEL resulted in improvements in the near surface temperature simulations of EC-EARTH. The new snow scheme development was complemented with the option of multi-layer version that showed its potential in modeling thick snowpacks. A key process was the snow thermal insulation that led to significant improvements of the surface water and energy balance components. Similar findings were observed when coupling the snow scheme to lake ice, where lake ice duration was significantly improved. An assessment on the snow cover sensitivity to horizontal resolution, parameterizations and atmospheric forcing within HTESSEL highlighted the role of the atmospheric forcing accuracy and snowpack parameterizations in detriment of horizontal resolution over flat regions. A set of experiments with and without free snow evolution was carried out with EC-EARTH to assess the impact of the interannual variability of snow cover on near surface and soil temperatures. It was found that snow cover interannual variability explained up to 60% of the total interannual variability of near surface temperature over snow covered regions. Although these findings are model dependent, the results showed consistency with previously published work. Furthermore, the detailed validation of the snow dynamics simulations in HTESSEL and EC-EARTH guarantees consistency of the results.

Unique relation between surface-limited evaporation and relative humidity profiles holds in both field data and climate model simulations

NASA Astrophysics Data System (ADS)

Salvucci, G.; Rigden, A. J.; Gentine, P.; Lintner, B. R.

2013-12-01

A new method was recently proposed for estimating evapotranspiration (ET) from weather station data without requiring measurements of surface limiting factors (e.g. soil moisture, leaf area, canopy conductance) [Salvucci and Gentine, 2013, PNAS, 110(16): 6287-6291]. Required measurements include diurnal air temperature, specific humidity, wind speed, net shortwave radiation, and either measured or estimated incoming longwave radiation and ground heat flux. The approach is built around the idea that the key, rate-limiting, parameter of typical ET models, the land-surface resistance to water vapor transport, can be estimated from an emergent relationship between the diurnal cycle of the relative humidity profile and ET. The emergent relation is that the vertical variance of the relative humidity profile is less than what would occur for increased or decreased evaporation rates, suggesting that land-atmosphere feedback processes minimize this variance. This relation was found to hold over a wide range of climate conditions (arid to humid) and limiting factors (soil moisture, leaf area, energy) at a set of Ameriflux field sites. While the field tests in Salvucci and Gentine (2013) supported the minimum variance hypothesis, the analysis did not reveal the mechanisms responsible for the behavior. Instead the paper suggested, heuristically, that the results were due to an equilibration of the relative humidity between the land surface and the surface layer of the boundary layer. Here we apply this method using surface meteorological fields simulated by a global climate model (GCM), and compare the predicted ET to that simulated by the climate model. Similar to the field tests, the GCM simulated ET is in agreement with that predicted by minimizing the profile relative humidity variance. A reasonable interpretation of these results is that the feedbacks responsible for the minimization of the profile relative humidity variance in nature are represented in the climate model. The climate model components, in particular the land surface model and boundary layer representation, can thus be analyzed in controlled numerical experiments to discern the specific processes leading to the observed behavior. Results of this analysis will be presented.

Spatial variability in land-atmosphere coupling strength at the ARM Southern Great Plains site under different cloud regimes

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Zhang, Y.

2016-12-01

The paucity of land/soil observations is a long-standing limitation for land-atmosphere (LA) coupling studies, in particular for estimating the spatial variability in the coupling strengths. Spatially dense atmospheric radiation measurement (ARM) sites deployed at the U.S. Southern Great Plains (SGP) covers a wide range of vegetation, surface, and soil types, and thus allow us to observe the spatial patterns of LA coupling. The upcoming "super site" at SGP will facilitate these studies at even finer scales. While many previous studies have focused only on the observations from the central facility (CF) site or the domain mean from multiple sites, in the present work we examine the robustness of many key surface and land observations (e.g., radiation, turbulence fluxes, soil moisture, etc.) at extended sites besides the CF site for a decade. The coupling strengths are estimated with temporal covariations between important variables. We subsample the data to different categories based on different cloud regimes (e.g., clear sky, shallow cumulus, and deep cumulus. These cloud regimes are strongly impacted by local factors. The spatial variability of coupling strengths at different ARM sites is assessed with respect to dominant drivers (i.e., vegetation, land type, etc.). The results of this study will provide insights for improving the representation of LA coupling in climate models by providing observational constraints to parameterizations, e.g., shallow convective schemes. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-698523

The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

NASA Astrophysics Data System (ADS)

Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

2012-10-01

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

Simulation of boreal Summer Monsoon Rainfall using CFSV2_SSiB model: sensitivity to Land Use Land Cover (LULC)

NASA Astrophysics Data System (ADS)

Chilukoti, N.; Xue, Y.

2016-12-01

The land surface play a vital role in determining the surface energy budget, accurate representation of land use and land cover (LULC) is necessary to improve forecast. In this study, we have investigated the influence of surface vegetation maps with different LULC on simulating the boreal summer monsoon rainfall. Using a National Centres for Environmental Prediction (NCEP) Coupled Forecast System version 2(CFSv2) model coupled with Simplified Simple Biosphere (SSiB) model, two experiments were conducted: one with old vegetation map and one with new vegetation map. The significant differences between new and old vegetation map were in semi-arid and arid areas. For example, in old map Tibetan plateau classified as desert, which is not appropriate, while in new map it was classified as grasslands or shrubs with bare soil. Old map classified the Sahara desert as a bare soil and shrubs with bare soil, whereas in new map it was classified as bare ground. In addition to central Asia and the Sahara desert, in new vegetation map, Europe had more cropped area and India's vegetation cover was changed from crops and forests to wooded grassland and small areas of grassland and shrubs. The simulated surface air temperature with new map shows a significant improvement over Asia, South Africa, and northern America by some 1 to 2ºC and 2 to 3ºC over north east China and these are consistent with the reduced rainfall biases over Africa, near Somali coast, north east India, Bangladesh, east China sea, eastern Pacific and northern USA. Over Indian continent and bay of Bengal dry rainfall anomalies that is the only area showing large dry rainfall bias, however, they were unchanged with new map simulation. Overall the CFSv2(coupled with SSiB) model with new vegetation map show a promising result in improving the monsoon forecast by improving the Land -Atmosphere interactions. To compare with the LULC forcing, experiment was conducted using the Global Forecast System (GFS) simulations forced with different observed Sea Surface Temperatures (SST) for the same period: one is from NCEP reanalysis and one from Hadley Center. They have substantial difference in Indian Ocean. Preliminary analysis shows that, the impact of these two SST data sets on Indian summer monsoon rainfall has no significant impact.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

ORCHIDEE-CNP: Site-Scale Evaluation against Observations from a Soil Formation Chronosequence in Hawaii

NASA Astrophysics Data System (ADS)

Goll, D. S.; Vuichard, N.; Maignan, F.; Jornet-Puig, A.; Sardans, J.; Peng, S.; Sun, Y.; Kvakić, M.; Guimberteau, M.; Guenet, B.; Zaehle, S.; Penuelas, J.; Jannssens, I.; Ciais, P.

2017-12-01

Land surface models rarely incorporate the terrestrial phosphorus cycle and its interactions with the carbon cycle, despite the extensive scientific debate about the importance of nitrogen and phosphorus supply for future land carbon uptake. We describe a representation of the terrestrial phosphorus cycle for the land surface model ORCHIDEE, and evaluate it with data from nutrient manipulation experiments along a soil formation chronosequence in Hawaii. ORCHIDEE accounts for influence of nutritional state of vegetation on tissue nutrient concentrations, photosynthesis, plant growth, biomass allocation, biochemical (phosphatase-mediated) mineralization and biological nitrogen fixation. Changes in nutrient content (quality) of litter affect the carbon use efficiency of decomposition and in return the nutrient availability to vegetation. The model explicitly accounts for root zone depletion of phosphorus as a function of root phosphorus uptake and phosphorus transport from soil to the root surface. The model captures the observed differences in the foliage stoichiometry of vegetation between an early (300yr) and a late stage (4.1 Myr) of soil development. The contrasting sensitivities of net primary productivity to the addition of either nitrogen, phosphorus or both among sites are in general reproduced by the model. As observed, the model simulates a preferential stimulation of leaf level productivity when nitrogen stress is alleviated, while leaf level productivity and leaf area index are stimulated equally when phosphorus stress is alleviated. The nutrient use efficiencies in the model are lower as observed primarily due to biases in the nutrient content and turnover of woody biomass.

Response of South American Ecosystems to Precipitation Variability

NASA Astrophysics Data System (ADS)

Knox, R. G.; Kim, Y.; Longo, M.; Medvigy, D.; Wang, J.; Moorcroft, P. R.; Bras, R. L.

2009-12-01

The Ecosystem Demography Model 2 is a dynamic ecosystem model and land surface energy balance model. ED2 discretizes landscapes of particular terrain and meteorology into fractional areas of unique disturbance history. Each fraction, defined by a shared vertical soil column and canopy air space, contains a stratum of plant groups unique in functional type, size and number density. The result is a vertically distributed representation of energy transfer and plant dynamics (mortality, productivity, recruitment, disturbance, resource competition, etc) that successfully approximates the behaviour of individual-based vegetation models. In previous exercises simulating Amazonian land surface dynamics with ED 2, it was observed that when using grid averaged precipitation as an external forcing the resulting water balance typically over-estimated leaf interception and leaf evaporation while under estimating through-fall and transpiration. To investigate this result, two scenario were conducted in which land surface biophysics and ecosystem demography over the Northern portion of South America are simulated over ~200 years: (1) ED2 is forced with grid averaged values taken from the ERA40 reanalysis meteorological dataset; (2) ED2 is forced with ERA40 reanalysis, but with its precipitation re-sampled to reflect statistical qualities of point precipitation found at rain gauge stations in the region. The findings in this study suggest that the equilibrium moisture states and vegetation demography are co-dependent and show sensitivity to temporal variability in precipitation. These sensitivities will need to be accounted for in future projections of coupled climate-ecosystem changes in South America.

Large-scale Modeling of Nitrous Oxide Production: Issues of Representing Spatial Heterogeneity

NASA Astrophysics Data System (ADS)

Morris, C. K.; Knighton, J.

2017-12-01

Nitrous oxide is produced from the biological processes of nitrification and denitrification in terrestrial environments and contributes to the greenhouse effect that warms Earth's climate. Large scale modeling can be used to determine how global rate of nitrous oxide production and consumption will shift under future climates. However, accurate modeling of nitrification and denitrification is made difficult by highly parameterized, nonlinear equations. Here we show that the representation of spatial heterogeneity in inputs, specifically soil moisture, causes inaccuracies in estimating the average nitrous oxide production in soils. We demonstrate that when soil moisture is averaged from a spatially heterogeneous surface, net nitrous oxide production is under predicted. We apply this general result in a test of a widely-used global land surface model, the Community Land Model v4.5. The challenges presented by nonlinear controls on nitrous oxide are highlighted here to provide a wider context to the problem of extraordinary denitrification losses in CLM. We hope that these findings will inform future researchers on the possibilities for model improvement of the global nitrogen cycle.

Customizing WRF-Hydro for the Laurentian Great Lakes Basin

NASA Astrophysics Data System (ADS)

Gronewold, A.; Pei, L.; Gochis, D.; Mason, L.; Sampson, K. M.; Dugger, A. L.; Read, L.; McCreight, J. L.; Xiao, C.; Lofgren, B. M.; Anderson, E. J.; Chu, P. Y.

2017-12-01

To advance the state of the art in regional hydrological forecasting, and to align with operational deployment of the National Water Model, a team of scientists has been customizing WRF-Hydro (the Weather Research and Forecasting model - Hydrological modeling extension package) to the entirety (including binational land and lake surfaces) of the Laurentian Great Lakes basin. Objectives of this customization project include opererational simulation and forecasting of the Great Lakes water balance and, in the short-term, research-oriented insights into modeling one- and two-way coupled lake-atmosphere and near-shore processes. Initial steps in this project have focused on overcoming inconsistencies in land surface hydrographic datasets between the United States and Canada. Improvements in the model's current representation of lake physics and stream routing are also critical components of this effort. Here, we present an update on the status of this project, including a synthesis of offline tests with WRF-Hydro based on the newly developed Great Lakes hydrographic data, and an assessment of the model's ability to simulate seasonal and multi-decadal hydrological response across the Great Lakes.

Characterizing Urban Volumetry Using LIDAR Data

NASA Astrophysics Data System (ADS)

Santos, T.; Rodrigues, A. M.; Tenedório, J. A.

2013-05-01

Urban indicators are efficient tools designed to simplify, quantify and communicate relevant information for land planners. Since urban data has a strong spatial representation, one can use geographical data as the basis for constructing information regarding urban environments. One important source of information about the land status is imagery collected through remote sensing. Afterwards, using digital image processing techniques, thematic detail can be extracted from those images and used to build urban indicators. Most common metrics are based on area (2D) measurements. These include indicators like impervious area per capita or surface occupied by green areas, having usually as primary source a spectral image obtained through a satellite or airborne camera. More recently, laser scanning data has become available for large-scale applications. Such sensors acquire altimetric information and are used to produce Digital Surface Models (DSM). In this context, LiDAR data available for the city is explored along with demographic information, and a framework to produce volumetric (3D) urban indexes is proposed, and measures like Built Volume per capita, Volumetric Density and Volumetric Homogeneity are computed.

Coupling integrated assessment and earth system models: concepts and an application to land use change

NASA Astrophysics Data System (ADS)

O'Neill, B. C.; Lawrence, P.; Ren, X.

2016-12-01

Collaboration between the integrated assessment modeling (IAM) and earth system modeling (ESM) communities is increasing, driven by a growing interest in research questions that require analysis integrating both social and natural science components. This collaboration often takes the form of integrating their respective models. There are a number of approaches available to implement this integration, ranging from one-way linkages to full two-way coupling, as well as approaches that retain a single modeling framework but improve the representation of processes from the other framework. We discuss the pros and cons of these different approaches and the conditions under which a two-way coupling of IAMs and ESMs would be favored over a one-way linkage. We propose a criterion that is necessary and sufficient to motivate two-way coupling: A human process must have an effect on an earth system process that is large enough to cause a change in the original human process that is substantial compared to other uncertainties in the problem being investigated. We then illustrate a test of this criterion for land use-climate interactions based on work using the Community Earth System Model (CESM) and land use scenarios from the Representative Concentration Pathways (RCPs), in which we find that the land use effect on regional climate is unlikely to meet the criterion. We then show an example of implementing a one-way linkage of land use and agriculture between an IAM, the integrated Population-Economy-Technology-Science (iPETS) model, and CESM that produces fully consistent outcomes between iPETS and the CESM land surface model. We use the linked system to model the influence of climate change on crop yields, agricultural land use, crop prices and food consumption under two alternative future climate scenarios. This application demonstrates the ability to link an IAM to a global land surface and climate model in a computationally efficient manner.

14 CFR 25.723 - Shock absorption tests.

Code of Federal Regulations, 2010 CFR

2010-01-01

... absorption tests. (a) The analytical representation of the landing gear dynamic characteristics that is used... previous tests conducted on the same basic landing gear system that has similar energy absorption...

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

NASA Astrophysics Data System (ADS)

Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing

2017-08-01

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiao, Yang; Lei, Huimin; Yang, Dawen

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less

The Role of Surface Energy Exchange for Simulating Wind Inflow: An Evaluation of Multiple Land Surface Models in WRF for the Southern Great Plains Site Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wharton, Sonia; Simpson, Matthew; Osuna, Jessica

The Weather Research and Forecasting (WRF) model is used to investigate choice of land surface model (LSM) on the near-surface wind profile, including heights reached by multi-megawatt wind turbines. Simulations of wind profiles and surface energy fluxes were made using five LSMs of varying degrees of sophistication in dealing with soil-plant-atmosphere feedbacks for the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) Central Facility in Oklahoma. Surface-flux and wind-profile measurements were available for validation. The WRF model was run for three two-week periods during which varying canopy and meteorological conditions existed. Themore » LSMs predicted a wide range of energy-flux and wind-shear magnitudes even during the cool autumn period when we expected less variability. Simulations of energy fluxes varied in accuracy by model sophistication, whereby LSMs with very simple or no soil-plant-atmosphere feedbacks were the least accurate; however, the most complex models did not consistently produce more accurate results. Errors in wind shear also were sensitive to LSM choice and were partially related to the accuracy of energy flux data. The variability of LSM performance was relatively high, suggesting that LSM representation of energy fluxes in the WRF model remains a significant source of uncertainty for simulating wind turbine inflow conditions.« less

Landscape Ecotoxicology of Coho Salmon Spawner Mortality in Urban Streams

PubMed Central

Feist, Blake E.; Buhle, Eric R.; Arnold, Paul; Davis, Jay W.; Scholz, Nathaniel L.

2011-01-01

In the Pacific Northwest of the United States, adult coho salmon (Oncorhynchus kisutch) returning from the ocean to spawn in urban basins of the Puget Sound region have been prematurely dying at high rates (up to 90% of the total runs) for more than a decade. The current weight of evidence indicates that coho deaths are caused by toxic chemical contaminants in land-based runoff to urban streams during the fall spawning season. Non-point source pollution in urban landscapes typically originates from discrete urban and residential land use activities. In the present study we conducted a series of spatial analyses to identify correlations between land use and land cover (roadways, impervious surfaces, forests, etc.) and the magnitude of coho mortality in six streams with different drainage basin characteristics. We found that spawner mortality was most closely and positively correlated with the relative proportion of local roads, impervious surfaces, and commercial property within a basin. These and other correlated variables were used to identify unmonitored basins in the greater Seattle metropolitan area where recurrent coho spawner die-offs may be likely. This predictive map indicates a substantial geographic area of vulnerability for the Puget Sound coho population segment, a species of concern under the U.S. Endangered Species Act. Our spatial risk representation has numerous applications for urban growth management, coho conservation, and basin restoration (e.g., avoiding the unintentional creation of ecological traps). Moreover, the approach and tools are transferable to areas supporting coho throughout western North America. PMID:21858112

Stepping towards new parameterizations for non-canonical atmospheric surface-layer conditions

NASA Astrophysics Data System (ADS)

Calaf, M.; Margairaz, F.; Pardyjak, E.

2017-12-01

Representing land-atmosphere exchange processes as a lower boundary condition remains a challenge. This is partially a result of the fact that land-surface heterogeneity exists at all spatial scales and its variability does not "average" out with decreasing scales. Such variability need not rapidly blend away from the boundary thereby impacting the near-surface region of the atmosphere. Traditionally, momentum and energy fluxes linking the land surface to the flow in NWP models have been parameterized using atmospheric surface layer (ASL) similarity theory. There is ample evidence that such representation is acceptable for stationary and planar-homogeneous flows in the absence of subsidence. However, heterogeneity remains a ubiquitous feature eliciting appreciable deviations when using ASL similarity theory, especially in scalars such moisture and air temperature whose blending is less efficient when compared to momentum. The focus of this project is to quantify the effect of surface thermal heterogeneity with scales Ο(1/10) the height of the atmospheric boundary layer and characterized by uniform roughness. Such near-canonical cases describe inhomogeneous scalar transport in an otherwise planar homogeneous flow when thermal stratification is weak or absent. In this work we present a large-eddy simulation study that characterizes the effect of surface thermal heterogeneities on the atmospheric flow using the concept of dispersive fluxes. Results illustrate a regime in which the flow is mostly driven by the surface thermal heterogeneities, in which the contribution of the dispersive fluxes can account for up to 40% of the total sensible heat flux. Results also illustrate an alternative regime in which the effect of the surface thermal heterogeneities is quickly blended, and the dispersive fluxes provide instead a quantification of the flow spatial heterogeneities produced by coherent turbulent structures result of the surface shear stress. A threshold flow-dynamics parameter is introduced to differentiate dispersive fluxes driven by surface thermal heterogeneities from those induced by surface shear. We believe that results from this research are a first step in developing new parameterizations appropriate for non-canonical ASL conditions.

Review of optical freeform surface representation technique and its application

NASA Astrophysics Data System (ADS)

Ye, Jingfei; Chen, Lu; Li, Xinhua; Yuan, Qun; Gao, Zhishan

2017-11-01

Modern advanced manufacturing and testing technologies allow the application of freeform optical elements. Compared with traditional spherical surfaces, an optical freeform surface has more degrees of freedom in optical design and provides substantially improved imaging performance. In freeform optics, the representation technique of a freeform surface has been a fundamental and key research topic in recent years. Moreover, it has a close relationship with other aspects of the design, manufacturing, testing, and application of optical freeform surfaces. Improvements in freeform surface representation techniques will make a significant contribution to the further development of freeform optics. We present a detailed review of the different types of optical freeform surface representation techniques and their applications and discuss their properties and differences. Additionally, we analyze the future trends of optical freeform surface representation techniques.

The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

NASA Astrophysics Data System (ADS)

Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

2012-02-01

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. The land-use modelling approach described in this paper entails several advantages. Firstly, it makes it possible to explore interactions among different types of biomass demand for food and animal feed, in a consistent approach, including indirect effects on land-use change resulting from international trade. Secondly, yield variations induced by the possible expansion of croplands on less suitable marginal lands are modelled by using regional land area distributions of potential yields, and a calculated boundary between intensive and extensive production. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

Evaluation of land surface model representation of phenology: an analysis of model runs submitted to the NACP Interim Site Synthesis

NASA Astrophysics Data System (ADS)

Richardson, A. D.; Nacp Interim Site Synthesis Participants

2010-12-01

Phenology represents a critical intersection point between organisms and their growth environment. It is for this reason that phenology is a sensitive and robust integrator of the biological impacts of year-to-year climate variability and longer-term climate change on natural systems. However, it is perhaps equally important that phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating ecosystem processes, competitive interactions, and feedbacks to the climate system. Unfortunately, the phenological sub-models implemented in most state-of-the-art ecosystem models and land surface schemes are overly simplified. We quantified model errors in the representation of the seasonal cycles of leaf area index (LAI), gross ecosystem photosynthesis (GEP), and net ecosystem exchange of CO2. Our analysis was based on site-level model runs (14 different models) submitted to the North American Carbon Program (NACP) Interim Synthesis, and long-term measurements from 10 forested (5 evergreen conifer, 5 deciduous broadleaf) sites within the AmeriFlux and Fluxnet-Canada networks. Model predictions of the seasonality of LAI and GEP were unacceptable, particularly in spring, and especially for deciduous forests. This is despite an historical emphasis on deciduous forest phenology, and the perception that controls on spring phenology are better understood than autumn phenology. Errors of up to 25 days in predicting “spring onset” transition dates were common, and errors of up to 50 days were observed. For deciduous sites, virtually every model was biased towards spring onset being too early, and autumn senescence being too late. Thus, models predicted growing seasons that were far too long for deciduous forests. For most models, errors in the seasonal representation of deciduous forest LAI were highly correlated with errors in the seasonality of both GPP and NEE, indicating the importance of getting the underlying canopy dynamics correct. Most of the models in this comparison were unable to successfully predict the observed interannual variability in either spring or autumn transition dates. And, perhaps surprisingly, the seasonal cycles of models using phenology prescribed by remote sensing observations was, in general, no better than that that predicted by models with prognostic phenology. Reasons for the poor performance of both approaches will be discussed. These results highlight the need for improved understanding of the environmental controls on vegetation phenology. Existing models are unlikely to accurately predict future responses of phenology to climate change, and therefore will misrepresent the seasonality of key biosphere-atmosphere feedbacks and interactions in coupled model runs. New data sets, as for example from webcam-based monitoring networks (e.g. PhenoCam) or citizen science efforts (USA National Phenology Network) should prove valuable in this regard.

Investigating the climate and carbon cycle impacts of CMIP6 Land Use and Land Cover Change in the Community Earth System Model (CESM2)

NASA Astrophysics Data System (ADS)

Lawrence, P.; Lawrence, D. M.; O'Neill, B. C.; Hurtt, G. C.

2017-12-01

For the next round of CMIP6 climate simulations there are new historical and SSP - RCP land use and land cover change (LULCC) data sets that have been compiled through the Land Use Model Intercomparison Project (LUMIP). The new time series data include new functionality following lessons learned through CMIP5 project and include new developments in the Community Land Model (CLM5) that will be used in all the CESM2 simulations of CMIP6. These changes include representing explicit crop modeling and better forest representation through the extended to 12 land units of the Global Land Model (GLM). To include this new information in CESM2 and CLM5 simulations new transient land surface data sets have been generated for the historical period 1850 - 2015 and for preliminary SSP - RCP paired future scenarios. The new data sets use updated MODIS Land Cover, Vegetation Continuous Fields, Leaf Area Index and Albedo to describe Primary and Secondary, Forested and Non Forested land units, as well as Rangelands and Pasture. Current day crop distributions are taken from the MIRCA2000 crop data set as done with the CLM 4.5 crop model and used to guide historical and future crop distributions. Preliminary "land only" simulations with CLM5 have been performed for the historical period and for the SSP1-RCP2.6 and SSP3-RCP7 land use and land cover change time series data. Equivalent no land use and land cover change simulations have been run for these periods under the same meteorological forcing data. The "land only" simulations use GSWP3 historical atmospheric forcing data from 1850 to 2010 and then time increasing RCP 8.5 atmospheric CO2 and climate anomalies on top of the current day GSWP3 atmospheric forcing data from 2011 to 2100. The offline simulations provide a basis to evaluate the surface climate, carbon cycle and crop production impacts of changing land use and land cover for each of these periods. To further evaluate the impacts of the new CLM5 model and the CMIP6 land use data, these results are compared to the equivalent investigations performed in CMIP5 with the CLM4/CESM1 model. We find the role of land use and land cover change in a changing climate is strongly dependent on both of these.

Towards a satellite driven land surface model using SURFEX modelling platform Offline Data Assimilation: an assessment of the method over Europe and the Mediterranean basin

NASA Astrophysics Data System (ADS)

Albergel, Clément; Munier, Simon; Leroux, Delphine; Fairbairn, David; Dorigo, Wouter; Decharme, Bertrand; Calvet, Jean-Christophe

2017-04-01

Modelling platforms including Land Surface Models (LSMs), forced by gridded atmospheric variables and coupled to river routing models are necessary to increase our understanding of the terrestrial water cycle. These LSMs need to simulate biogeophysical variables like Surface and Root Zone Soil Moisture (SSM, RZSM), Leaf Area Index (LAI) in a way that is fully consistent with the representation of surface/energy fluxes and river discharge simulations. Global SSM and LAI products are now operationally available from spaceborne instruments and they can be used to constrain LSMs through Data Assimilation (DA) techniques. In this study, an offline data assimilation system implemented in Météo-France's modelling platform (SURFEX) is tested over Europe and the Mediterranean basin to increase prediction accuracy for land surface variables. The resulting Land Data Assimilation System (LDAS) makes use of a simplified Extended Kalman Filter (SEKF). It is able to ingests information from satellite derived (i) SSM from the latest version of the ESA Climate Change Initiative as well as (ii) LAI from the Copernicus GLS project to constrain the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (ISBA-CTRIP). ERA-Interim observations based atmospheric forcing with precipitations corrected from Global Precipitation Climatology Centre observations (GPCC) is used to force ISBA-CTRIP at a resolution of 0.5 degree over 2000-2015. The model sensitivity to the assimilated observations is presented and a set of statistical diagnostics used to evaluate the impact of assimilating SSM and LAI on different model biogeophysical variables are provided. It is demonstrated that the assimilation scheme works effectively. The SEKF is able to extract useful information from the data signal at the grid scale and distribute the RZSM and LAI increments throughout the model impacting soil moisture, terrestrial vegetation and water cycle, surface carbon and energy fluxes.

The Application of Satellite-Derived, High-Resolution Land Use/Land Cover Data to Improve Urban Air Quality Model Forecasts

NASA Technical Reports Server (NTRS)

Quattrochi, D. A.; Lapenta, W. M.; Crosson, W. L.; Estes, M. G., Jr.; Limaye, A.; Kahn, M.

2006-01-01

Local and state agencies are responsible for developing state implementation plans to meet National Ambient Air Quality Standards. Numerical models used for this purpose simulate the transport and transformation of criteria pollutants and their precursors. The specification of land use/land cover (LULC) plays an important role in controlling modeled surface meteorology and emissions. NASA researchers have worked with partners and Atlanta stakeholders to incorporate an improved high-resolution LULC dataset for the Atlanta area within their modeling system and to assess meteorological and air quality impacts of Urban Heat Island (UHI) mitigation strategies. The new LULC dataset provides a more accurate representation of land use, has the potential to improve model accuracy, and facilitates prediction of LULC changes. Use of the new LULC dataset for two summertime episodes improved meteorological forecasts, with an existing daytime cold bias of approx. equal to 3 C reduced by 30%. Model performance for ozone prediction did not show improvement. In addition, LULC changes due to Atlanta area urbanization were predicted through 2030, for which model simulations predict higher urban air temperatures. The incorporation of UHI mitigation strategies partially offset this warming trend. The data and modeling methods used are generally applicable to other U.S. cities.

Sustainable land cover and terrain modification to enhance convection and precipitation in the arid region of the United Arab Emirates

NASA Astrophysics Data System (ADS)

Wulfmeyer, V.; Branch, O.; Adebabseh, A.; Temimi, M.

2017-12-01

Irrigated plantations and modified terrain can provide a sustainable means of enhancing convective rainfall in arid regions like the United Arab Emirates, or UAE, and can be used to aid ongoing cloud seeding operations through the geographic-localization of seedable cloud formation. The first method, the planting of vast irrigated plantations of hardy desert shrubs, can lead to wind convergence and vertical mixing through increased roughness and modified radiative balances. When upper-air atmospheric instability is present, these phenomena can initiate convection. The second method, increasing the elevation of moderate-sized mountains, is based on the correlation between elevation and the number of summertime convection initiation events observed in the mountains of the UAE and Oman. This augmentation of existing orographic features should therefore increase the likelihood and geographic range of convection initiation events. High-resolution simulations provide a powerful means of assessing the likely impacts of land surface modifications. Previous convection-permitting simulations have yielded some evidential support for these hypotheses, but higher resolutions down to 1 km provide more detail regarding convective processes and land surface representation. Using seasonal simulations with the WRF-NOAHMP land-atmosphere model at a 2.5 km resolution, we identify frequent zones of convergence and atmospheric instability in the UAE and select interesting cases. Using these results, as well as an agricultural feasibility study, we identify optimal plantation positions within the UAE. We then run realistic plantation scenarios for single case studies at 1 km resolution. Using the same cases, we simulate the impact of augmenting mountain elevations on convective processes, with the augmentation being achieved through GIS-based modification of the terrain data. For both methods, we assess the impacts quantitatively and qualitatively, and assess key processes and dependencies. If we can demonstrate that convective rainfall would be enhanced through feasible agricultural and engineering methods, then land surface-based weather modification deserves serious consideration as a solution for water scarcity and anthropogenic climate change.

Anthropogenic modifications to drainage conditions on streamflow variability in the Wabash River basin, Indiana

NASA Astrophysics Data System (ADS)

Chiu, C.; Bowling, L. C.

2011-12-01

The Wabash River watershed is the largest watershed in Indiana and includes the longest undammed river reach east of the Mississippi River. The land use of the Wabash River basin began to significantly change from mixed woodland dominated by small lakes and wetlands to agriculture in the mid-1800s and agriculture is now the predominant land use. Over 80% of natural wetland areas were drained to facilitate better crop production through both surface and subsurface drainage applications. Quantifying the change in hydrologic response in this intensively managed landscape requires a hydrologic model that can represent wetlands, crop growth, and impervious area as well as subsurface and surface drainage enhancements, coupled with high resolution soil and topographic inputs. The Variable Infiltration Capacity (VIC) model wetland algorithm has been previously modified to incorporate spatially-varying estimates of water table distribution using a topographic index approach, as well as a simple urban representation. Now, the soil water characteristics curve and a derived drained to equilibrium moisture profile are used to improve the model's estimation of the water table. In order to represent subsurface (tile) drainage, the tile drainage component of subsurface flow is calculated when the simulated water table rises above a specified drain depth. A map of the current estimated extent of subsurface tile drainage for the Wabash River based on a decision tree classifier of soil drainage class, soil slope and agricultural land use is used to activate the new tile drainage feature in the VIC model, while wetland depressional storage capacity is extracted from digital elevation and soil information. This modified VIC model is used to evaluate the performance of model physical variations in the intensively managed hydrologic regime of the Wabash River system and to understand the role of surface and subsurface storage, and land use and land cover change on hydrologic change.

Raster Vs. Point Cloud LiDAR Data Classification

NASA Astrophysics Data System (ADS)

El-Ashmawy, N.; Shaker, A.

2014-09-01

Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the classification results can be achieved by using the proposed approach.

Diagnosing the Sensitivity of Local Land-Atmosphere Coupling via the Soil Moisture-Boundary Layer Interaction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Peters-Lidard, Christa D.; Kumar, Sujay V.

2011-01-01

The inherent coupled nature of earth s energy and water cycles places significant importance on the proper representation and diagnosis of land atmosphere (LA) interactions in hydrometeorological prediction models. However, the precise nature of the soil moisture precipitation relationship at the local scale is largely determined by a series of nonlinear processes and feedbacks that are difficult to quantify. To quantify the strength of the local LA coupling (LoCo), this process chain must be considered both in full and as individual components through their relationships and sensitivities. To address this, recent modeling and diagnostic studies have been extended to 1) quantify the processes governing LoCo utilizing the thermodynamic properties of mixing diagrams, and 2) diagnose the sensitivity of coupled systems, including clouds and moist processes, to perturbations in soil moisture. This work employs NASA s Land Information System (LIS) coupled to the Weather Research and Forecasting (WRF) mesoscale model and simulations performed over the U.S. Southern Great Plains. The behavior of different planetary boundary layers (PBL) and land surface scheme couplings in LIS WRF are examined in the context of the evolution of thermodynamic quantities that link the surface soil moisture condition to the PBL regime, clouds, and precipitation. Specifically, the tendency toward saturation in the PBL is quantified by the lifting condensation level (LCL) deficit and addressed as a function of time and space. The sensitivity of the LCL deficit to the soil moisture condition is indicative of the strength of LoCo, where both positive and negative feedbacks can be identified. Overall, this methodology can be applied to any model or observations and is a crucial step toward improved evaluation and quantification of LoCo within models, particularly given the advent of next-generation satellite measurements of PBL and land surface properties along with advances in data assimilation schemes.

Representation of the West African Monsoon System in the aerosol-climate model ECHAM6-HAM2

NASA Astrophysics Data System (ADS)

Stanelle, Tanja; Lohmann, Ulrike; Bey, Isabelle

2017-04-01

The West African Monsoon (WAM) is a major component of the global monsoon system. The temperature contrast between the Saharan land surface in the North and the sea surface temperature in the South dominates the WAM formation. The West African region receives most of its precipitation during the monsoon season between end of June and September. Therefore the existence of the monsoon is of major social and economic importance. We discuss the ability of the climate model ECHAM6 as well as the coupled aerosol climate model ECHAM6-HAM2 to simulate the major features of the WAM system. The north-south temperature gradient is reproduced by both model versions but all model versions fail in reproducing the precipitation amount south of 10° N. A special focus is on the representation of the nocturnal low level jet (NLLJ) and the corresponding enhancement of low level clouds (LLC) at the Guinea Coast, which are a crucial factor for the regional energy budget. Most global climate models have difficulties to represent these features. The pure climate model ECHAM6 is able to simulate the existence of the NLLJ and LLC, but the model does not represent the pronounced diurnal cycle. Overall, the representation of LLC is worse in the coupled model. We discuss the model behaviors on the basis of outputted temperature and humidity tendencies and try to identify potential processes responsible for the model deficiencies.

Anticipated Improvements to Net Surface Freshwater Fluxes from GPM

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2005-01-01

Evaporation and precipitation over the oceans play very important roles in the global water cycle, upper-ocean heat budget, ocean dynamics, and coupled ocean-atmosphere dynamics. In the conventional representation of the terrestrial water cycle, the assumed role of the oceans is to act as near-infinite reservoirs of water with the main drivers of the water cycle being land- atmosphere interactions in which excess precipitation (P) over evaporation (E) is returned to the oceans as surface runoff and baseflow. Whereas this perspective is valid for short space and time scales -- fundamental principles, available observed estimates, and results from models indicate that the oceans play a far more important role in the large-scale water cycle at seasonal and longer timescales. Approximately 70-80% of the total global evaporation and precipitation occurs over oceans. Moreover, latent heat release into the atmosphere over the oceans is the major heat source driving global atmospheric circulations, with the moisture transported by circulations from oceans to continents being the major source of water precipitating over land. Notably, the major impediment in understanding and modeling the oceans role in the global water cycle is the lack of reliable net surface freshwater flux estimates (E - P fluxes) at the salient spatial and temporal resolutions, i.e., consistent coupled weekly to monthly E - P gridded datasets.

Influence of Leaf Area Index Prescriptions on Simulations of Heat, Moisture, and Carbon Fluxes

NASA Technical Reports Server (NTRS)

Kala, Jatin; Decker, Mark; Exbrayat, Jean-Francois; Pitman, Andy J.; Carouge, Claire; Evans, Jason P.; Abramowitz, Gab; Mocko, David

2013-01-01

Leaf-area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. We investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI data-set is generated using the MODIS LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980-2008) are carried out at 25 km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly-varying LAI data-sets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from -90 to 60 %. PFTs with high absolute LAI and low inter-annual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, whilst those with lower absolute LAI and higher inter-annual variability, such as croplands, were more sensitive. We show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of the terrestrial carbon fluxes, especially for PFTs with high inter-annual variability. Our study highlights that the accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence this will become critical in quantifying the uncertainty in future changes in primary production.

Downscaling of inundation extents

NASA Astrophysics Data System (ADS)

Aires, Filipe; Prigent, Catherine; Papa, Fabrice

2014-05-01

The Global Inundation Extent from Multi-Satellite (GIEMS) provides multi-year monthly variations of the global surface water extent at about 25 kmx25 km resolution, from 1993 to 2007. It is derived from multiple satellite observations. Its spatial resolution is usually compatible with climate model outputs and with global land surface model grids but is clearly not adequate for local applications that require the characterization of small individual water bodies. There is today a strong demand for high-resolution inundation extent datasets, for a large variety of applications such as water management, regional hydrological modeling, or for the analysis of mosquitos-related diseases. This paper present three approaches to do downscale GIEMS: The first one is based on a image-processing technique using neighborhood constraints. The third approach uses a PCA representation to perform an algebraic inversion. The PCA-representation is also very convenient to perform temporal and spatial interpolation of complexe inundation fields. The third downscaling method uses topography information from Hydroshed Digital Elevation Model (DEM). Information such as the elevation, distance to river and flow accumulation are used to define a ``flood ability index'' that is used by the downscaling. Three basins will be considered for illustrative purposes: Amazon, Niger and Mekong. Aires, F., F. Papa, C. Prigent, J.-F. Cretaux and M. Berge-Nguyen, Characterization and downscaling of the inundation extent over the Inner Niger delta using a multi-wavelength retrievals and Modis data, J. of Hydrometeorology, in press, 2014. Aires, F., F. Papa and C. Prigent, A long-term, high-resolution wetland dataset over the Amazon basin, downscaled from a multi-wavelength retrieval using SAR, J. of Hydrometeorology, 14, 594-6007, 2013. Prigent, C., F. Papa, F. Aires, C. Jimenez, W.B. Rossow, and E. Matthews. Changes in land surface water dynamics since the 1990s and relation to population pressure. Geophys. Res. Lett., 39(L08403), 2012.

Environment and Architecture - a Paradigm Shift

NASA Astrophysics Data System (ADS)

di Battista, Valerio

The interaction of human cultures and the built environment allows a wide range of interpretations and has been studied inside the domain of many disciplines. This paper discusses three interpretations descending from a systemic approach to the question: - architecture as an "emergence" of the settlement system; - place (and space) as an "accumulator" of time and a "flux" of systems; - landscape as one representation/description of the human settlement. Architecture emerges as a new physical conformation or layout, or as a change in a specific site, arising from actions and representations of political, religious, economical or social powers, being shaped at all times by the material culture belonging to a specific time and place in the course of human evolution. Any inhabited space becomes over time a place as well as a landscape, i.e. a representation of the settlement and a relationship between setting and people. Therefore, any place owns a landscape which, in turn, is a system of physical systems; it could be defined as a system of sites that builds up its own structure stemming from the orographical features and the geometry of land surfaces that set out the basic characters of its space.

Downscaling essential climate variable soil moisture using multisource data from 2003 to 2010 in China

NASA Astrophysics Data System (ADS)

Wang, Hui-Lin; An, Ru; You, Jia-jun; Wang, Ying; Chen, Yuehong; Shen, Xiao-ji; Gao, Wei; Wang, Yi-nan; Zhang, Yu; Wang, Zhe; Quaye-Ballard, Jonathan Arthur

2017-10-01

Soil moisture plays an important role in the water cycle within the surface ecosystem, and it is the basic condition for the growth of plants. Currently, the spatial resolutions of most soil moisture data from remote sensing range from ten to several tens of km, while those observed in-situ and simulated for watershed hydrology, ecology, agriculture, weather, and drought research are generally <1 km. Therefore, the existing coarse-resolution remotely sensed soil moisture data need to be downscaled. This paper proposes a universal and multitemporal soil moisture downscaling method suitable for large areas. The datasets comprise land surface, brightness temperature, precipitation, and soil and topographic parameters from high-resolution data and active/passive microwave remotely sensed essential climate variable soil moisture (ECV_SM) data with a spatial resolution of 25 km. Using this method, a total of 288 soil moisture maps of 1-km resolution from the first 10-day period of January 2003 to the last 10-day period of December 2010 were derived. The in-situ observations were used to validate the downscaled ECV_SM. In general, the downscaled soil moisture values for different land cover and land use types are consistent with the in-situ observations. Mean square root error is reduced from 0.070 to 0.061 using 1970 in-situ time series observation data from 28 sites distributed over different land uses and land cover types. The performance was also assessed using the GDOWN metric, a measure of the overall performance of the downscaling methods based on the same dataset. It was positive in 71.429% of cases, indicating that the suggested method in the paper generally improves the representation of soil moisture at 1-km resolution.

The use of LiDAR-derived high-resolution DSM and intensity data to support modelling of urban flooding

NASA Astrophysics Data System (ADS)

Aktaruzzaman, Md.; Schmitt, Theo G.

2011-11-01

This paper addresses the issue of a detailed representation of an urban catchment in terms of hydraulic and hydrologic attributes. Modelling of urban flooding requires a detailed knowledge of urban surface characteristics. The advancement in spatial data acquisition technology such as airborne LiDAR (Light Detection and Ranging) has greatly facilitated the collection of high-resolution topographic information. While the use of the LiDAR-derived Digital Surface Model (DSM) has gained popularity over the last few years as input data for a flood simulation model, the use of LiDAR intensity data has remained largely unexplored in this regard. LiDAR intensity data are acquired along with elevation data during the data collection mission by an aircraft. The practice of using of just aerial images with RGB (Red, Green and Blue) wavebands is often incapable of identifying types of surface under the shadow. On the other hand, LiDAR intensity data can provide surface information independent of sunlight conditions. The focus of this study is the use of intensity data in combination with aerial images to accurately map pervious and impervious urban areas. This study presents an Object-Based Image Analysis (OBIA) framework for detecting urban land cover types, mainly pervious and impervious surfaces in order to improve the rainfall-runoff modelling. Finally, this study shows the application of highresolution DSM and land cover maps to flood simulation software in order to visualize the depth and extent of urban flooding phenomena.

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

DOE PAGES

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; ...

2017-01-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain–Fritsch +more » Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.« less

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain–Fritsch +more » Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.« less

Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic

NASA Astrophysics Data System (ADS)

Marelle, Louis; Raut, Jean-Christophe; Law, Kathy S.; Berg, Larry K.; Fast, Jerome D.; Easter, Richard C.; Shrivastava, Manish; Thomas, Jennie L.

2017-10-01

In this study, the WRF-Chem regional model is updated to improve simulated short-lived pollutants (e.g., aerosols, ozone) in the Arctic. Specifically, we include in WRF-Chem 3.5.1 (with SAPRC-99 gas-phase chemistry and MOSAIC aerosols) (1) a correction to the sedimentation of aerosols, (2) dimethyl sulfide (DMS) oceanic emissions and gas-phase chemistry, (3) an improved representation of the dry deposition of trace gases over seasonal snow, and (4) an UV-albedo dependence on snow and ice cover for photolysis calculations. We also (5) correct the representation of surface temperatures over melting ice in the Noah Land Surface Model and (6) couple and further test the recent KF-CuP (Kain-Fritsch + Cumulus Potential) cumulus parameterization that includes the effect of cumulus clouds on aerosols and trace gases. The updated model is used to perform quasi-hemispheric simulations of aerosols and ozone, which are evaluated against surface measurements of black carbon (BC), sulfate, and ozone as well as airborne measurements of BC in the Arctic. The updated model shows significant improvements in terms of seasonal aerosol cycles at the surface and root mean square errors (RMSEs) for surface ozone, aerosols, and BC aloft, compared to the base version of the model and to previous large-scale evaluations of WRF-Chem in the Arctic. These improvements are mostly due to the inclusion of cumulus effects on aerosols and trace gases in KF-CuP (improved RMSE for surface BC and BC profiles, surface sulfate, and surface ozone), the improved surface temperatures over sea ice (surface ozone, BC, and sulfate), and the updated trace gas deposition and UV albedo over snow and ice (improved RMSE and correlation for surface ozone). DMS emissions and chemistry improve surface sulfate at all Arctic sites except Zeppelin, and correcting aerosol sedimentation has little influence on aerosols except in the upper troposphere.

Evaluation of improved land use data and canopy representation in BEIS with biogenic VOC measurements in California

EPA Pesticide Factsheets

The link provided access to all the datasets and metadata used in this manuscript for the model development and evaluation per Geoscientific Model Development's publication guidelines with the exception of the model output due to its size. This dataset is associated with the following publication:Bash , J., K. Baker , and M. Beaver. Evaluation of improved land use and canopy representation in BEIS v3.61 with biogenic VOC measurements in California. Geoscientific Model Development. Copernicus Publications, Katlenburg-Lindau, GERMANY, 9: 2191-2207, (2016).

Representation of Dissolved Organic Carbon in the JULES Dynamic Global Vegetation Model

NASA Astrophysics Data System (ADS)

Nakhavali, Mahdi; Friedlingstein, Pierre; Guenet, Bertrand; Ciais, Philip

2017-04-01

Current global models of the carbon cycle consider only vertical gas exchanges between terrestrial or oceanic reservoirs and the atmosphere, hence not considering lateral transport of carbon from the continent to the oceans. This also means that such models implicitly consider that all the CO2 which is not respired to the atmosphere is stored on land, hence overestimating the land sink of carbon. Moving toward a boundless carbon cycle that is integrating the whole continuum from land to ocean to atmosphere is needed in order to better understand Earth's carbon cycle and to make more reliable projection of its future. Here we present an original representation of Dissolved Organic Carbon (DOC) processes in the Joint UK Land Environment Simulator (JULES). The standard version of JULES represent energy, water and carbon cycles and exchanges with the atmosphere, but only account for water run-off, not including export of carbon from terrestrial ecosystems to the aquatic environments. The aim of the project is to include in JULES a representation of DOC production in terrestrial soils, due to incomplete decomposition of organic matter, its decomposition to the atmosphere, and its export to the river network by leaching. In new developed version of JULES (JULES-DOCM), DOC pools, based on their decomposition rate, are classified into labile and recalcitrant within 3 meters of soil. Based on turnover rate, DOC coming from plant material pools and microbial biomass is directed to labile pool, while DOC from humus is directed to recalcitrant pool. Both of these pools have free (dissolved) and locked (adsorbed) form where just the free pool is subjected to decomposition and leaching. DOC production and decomposition are controlled by rate modifiers (moisture, temperature, vegetation fraction and decomposition rate) at each soil layer. Decomposed DOC is released to the atmosphere following a fixed carbon use efficiency. Leaching accounts for both surface (runoff) and subsurface (groundwater) components and is parameterized as Top soil leaching (from top 20cm) and Bottom soil leaching (down to 3 meters) depending on DOC concentration and runoff leaving that layer. The model parameters are calibrated against specific sites (Brasschaat, Hainich and Carlow) for which observations of DOC concentration and leaching are available. Tuning is performed optimizing parameters such as DOC labile and recalcitrant resident time, DOC vertical distribution and CUE. Once this calibration has been performed at the site level, the model is used for global simulations with the major historical forcing (climate, atmospheric CO2 and land-use changes) in order to estimate the changes of DOC export and their attribution to anthropogenic activities.

Global Precipitation Responses to Land Hydrological Processes

NASA Astrophysics Data System (ADS)

Lo, M.; Famiglietti, J. S.

2012-12-01

Several studies have established that soil moisture increases after adding a groundwater component in land surface models due to the additional supply of subsurface water. However, impacts of groundwater on the spatial-temporal variability of precipitation have received little attention. Through the coupled groundwater-land-atmosphere model (NCAR Community Atmosphere Model + Community Land Model) simulations, this study explores how groundwater representation in the model alters the precipitation spatiotemporal distributions. Results indicate that the effect of groundwater on the amount of precipitation is not globally homogeneous. Lower tropospheric water vapor increases due to the presence of groundwater in the model. The increased water vapor destabilizes the atmosphere and enhances the vertical upward velocity and precipitation in tropical convective regions. Precipitation, therefore, is inhibited in the descending branch of convection. As a result, an asymmetric dipole is produced over tropical land regions along the equator during the summer. This is analogous to the "rich-get-richer" mechanism proposed by previous studies. Moreover, groundwater also increased short-term (seasonal) and long-term (interannual) memory of precipitation for some regions with suitable groundwater table depth and found to be a function of water table depth. Based on the spatial distributions of the one-month-lag autocorrelation coefficients as well as Hurst coefficients, air-land interaction can occur from short (several months) to long (several years) time scales. This study indicates the importance of land hydrological processes in the climate system and the necessity of including the subsurface processes in the global climate models.

Examining the Effects of Mosaic Land Cover on Extreme Events in Historical Downscaled WRF Simulations

EPA Science Inventory

The representation of land use and land cover (hereby referred to as “LU”) is a challenging aspect of dynamically downscaled simulations, as a mesoscale model that is utilized as a regional climate model (RCM) may be limited in its ability to represent LU over multi-d...

7 CFR 632.23 - Access to land unit and records.

Code of Federal Regulations, 2010 CFR

2010-01-01

... land unit and records. Any authorized NRCS employee or agent is to have the right of access to land under application or contract and the right to examine any program records to ascertain the accuracy of any representations made in the application or contract. This includes the right to furnish technical...

Masculinity, vulnerability and prevention of STD/HIV/AIDS among male adolescents: social representations in a land reform settlement.

PubMed

Arraes, Camila de Oliveira; Palos, Marinésia Aparecida Prado; Barbosa, Maria Alves; Teles, Sheila Araujo; Souza, Márcia Maria de; Matos, Marcos André de

2013-01-01

to analyze the relationship of masculinity, vulnerability and prevention of STD / HIV / AIDS among adolescent males of a land reform settlement in central Brazil. a qualitative study using as precepts the strands of social representations with teenagers between 12 to 24 years. three categories emerged - Perception of vulnerability; Gender and vulnerability; and, Prevention and vulnerability to STD / HIV / AIDS. Adolescents felt invulnerable to sexually transmitted diseases anchored in the social representations in favor of the male hegemony. An ignorance about forms of prevention for STD / HIV / AIDS was demonstrated in their statements. It is believed that institutional projects such as the School Health Program and the Men's Health Care Program constitute essential tools to minimize factors of vulnerability in this population, since the school is recognized as a social facility that promotes socialization of experiences and contributes to the construction of the identity of the adolescent. the social representations of masculinity collaborate for the vulnerable behavior of the adolescents for the acquisition of sexually transmitted diseases. One hopes that this study can contribute to the production of knowledge and technical-scientific improvement of the professionals, especially the nurse, in order to discuss issues related to male sexuality of adolescents in the situation of the land reform settlement.

Constraining the Surface Energy Balance of Snow in Complex Terrain

NASA Astrophysics Data System (ADS)

Lapo, Karl E.

Physically-based snow models form the basis of our understanding of current and future water and energy cycles, especially in mountainous terrain. These models are poorly constrained and widely diverge from each other, demonstrating a poor understanding of the surface energy balance. This research aims to improve our understanding of the surface energy balance in regions of complex terrain by improving our confidence in existing observations and improving our knowledge of remotely sensed irradiances (Chapter 1), critically analyzing the representation of boundary layer physics within land models (Chapter 2), and utilizing relatively novel observations to in the diagnoses of model performance (Chapter 3). This research has improved the understanding of the literal and metaphorical boundary between the atmosphere and land surface. Solar irradiances are difficult to observe in regions of complex terrain, as observations are subject to harsh conditions not found in other environments. Quality control methods were developed to handle these unique conditions. These quality control methods facilitated an analysis of estimated solar irradiances over mountainous environments. Errors in the estimated solar irradiance are caused by misrepresenting the effect of clouds over regions of topography and regularly exceed the range of observational uncertainty (up to 80Wm -2) in all regions examined. Uncertainty in the solar irradiance estimates were especially pronounced when averaging over high-elevation basins, with monthly differences between estimates up to 80Wm-2. These findings can inform the selection of a method for estimating the solar irradiance and suggest several avenues of future research for improving existing methods. Further research probed the relationship between the land surface and atmosphere as it pertains to the stable boundary layers that commonly form over snow-covered surfaces. Stable conditions are difficult to represent, especially for low wind speed values and coupled land-atmosphere models have difficulty representing these processes. We developed a new method analyzing turbulent fluxes at the land surface that relies on using the observed surface temperature, which we called the offline turbulence method. We used this method to test a number of stability schemes as they are implemented within land models. Stability schemes can cause small biases in the simulated sensible heat flux, but these are caused by compensating errors, as no single method was able to accurately reproduce the observed distribution of the sensible heat flux. We described how these turbulence schemes perform within different turbulence regimes, particularly noting the difficulty representing turbulence during conditions with faster wind speeds and the transition between weak and strong wind turbulence regimes. Heterogeneity in the horizontal distribution of surface temperature associated with different land surface types likely explains some of the missing physics within land models and is manifested as counter-gradient fluxes in observations. The coupling of land and atmospheric models needs further attention, as we highlight processes that are missing. Expanding on the utility of surface temperature, Ts, in model evaluations, we demonstrated the utility of using surface temperature in snow models evaluations. Ts is the diagnostic variable of the modeled surface energy balance within physically-based models and is an ideal supplement to traditional evaluation techniques. We demonstrated how modeling decisions affect Ts, specifically testing the impact of vertical layer structure, thermal conductivity, and stability corrections in addition to the effect of uncertainty in forcing data on simulated Ts. The internal modeling decisions had minimal impacts relative to uncertainty in the forcing data. Uncertainty in downwelling longwave was found to have the largest impact on simulated Ts. Using Ts, we demonstrated how various errors in the forcing data can be identified, noting that uncertainty in downwelling longwave and wind are the easiest to identify due to their effect on night time minimum Ts.

Evaluation of CLM4 Solar Radiation Partitioning Scheme Using Remote Sensing and Site Level FPAR Datasets

DOE PAGES

Wang, Kai; Mao, Jiafu; Dickinson, Robert; ...

2013-06-05

This paper examines a land surface solar radiation partitioning scheme, i.e., that of the Community Land Model version 4 (CLM4) with coupled carbon and nitrogen cycles. Taking advantage of a unique 30-year fraction of absorbed photosynthetically active radiation (FPAR) dataset derived from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data set, multiple other remote sensing datasets, and site level observations, we evaluated the CLM4 FPAR ’s seasonal cycle, diurnal cycle, long-term trends and spatial patterns. These findings show that the model generally agrees with observations in the seasonal cycle, long-term trends, and spatial patterns,more » but does not reproduce the diurnal cycle. Discrepancies also exist in seasonality magnitudes, peak value months, and spatial heterogeneity. Here, we identify the discrepancy in the diurnal cycle as, due to, the absence of dependence on sun angle in the model. Implementation of sun angle dependence in a one-dimensional (1-D) model is proposed. The need for better relating of vegetation to climate in the model, indicated by long-term trends, is also noted. Evaluation of the CLM4 land surface solar radiation partitioning scheme using remote sensing and site level FPAR datasets provides targets for future development in its representation of this naturally complicated process.« less

Project M: Scale Model of Lunar Landing Site of Apollo 17

NASA Technical Reports Server (NTRS)

O'Brien, Hollie; Crain, Timothy P.

2010-01-01

The basis of the project was creating a scale model representation of the Apollo 17 lunar landing site. Vital components included surface slope characteristics, crater sizes and locations, prominent rocks, and lighting conditions. The model was made for Project M support when evaluating approach and terminal descent as well as when planning surface operations with respect to the terrain. The project had five main mi lestones during the length of the project. The first was examining the best method to use to re-create the Apollo 17 landing site and then reviewing research fmdings with Dr. Tim Crain and EO staff which occurred on June 25, 2010 at a meeting. The second step was formulating a construction plan, budget, and schedule and then presenting the plan for authority to proceed which occurred on July 6,2010. The third part was building a prototype to test materials and building processes which were completed by July 13, 2010. Next was assembling the landing site model and presenting a mid-term construction status report on July 29, 2010. The fifth and final milestone was demonstrating the model and presenting an exit pitch which happened on August 4, 2010. The project was very technical: it needed a lot of research about moon topography, lighting conditions and angles of the sun on the moon, Apollo 17, and Autonomous Landing and Hazard Avoidance Technology (ALHAT), before starting the actual building process. This required using Spreadsheets, searching internet sources and conducting personal meetings with project representatives. This information assisted the interns in deciding the scale of the model with respect to cracks, craters and rocks and their relative sizes as the objects mentioned could interfere with any of the Lunar Landers: Apollo, Project M and future Landers. The project concluded with the completion of a three dimensional scale model of the Apollo 17 Lunar landing site. This model assists Project M members because they can now visualize approach phase, terminal descent phase, and surface phase operations on the physical model. The project had an additional requirement that was also satisfied: the granite table the model was placed on must be returnable to its original condition if needed in the future.

Response of permafrost to projected climate change: Results from global offline model simulations with JSBACH

NASA Astrophysics Data System (ADS)

Blome, Tanja; Ekici, Altug; Beer, Christian; Hagemann, Stefan

2014-05-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) lacked the sufficient representation of permafrost physics in their land surface schemes. In order to assess the response of permafrost to projected climate change for the 21st century, the land surface scheme of the Max-Planck-Institute for Meteorology, JSBACH, has recently been equipped with the important physical processes for permafrost studies, and was driven globally with bias corrected climate data, thereby spanning a period from 1850 until 2100. The applied land surface scheme JSBACH now considers the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. To address the uncertainty range arising through different greenhouse gas concentrations as well as through different climate realisations when using various climate models, combinations of two Representative Concentration Pathways (RCPs) and two GCMs were used as driving data. In order to focus only on the climatic impact on permafrost, effects due to feedbacks between climate and permafrost (namely via carbon fluxes between land and atmosphere) are excluded in the experiments. Differences between future time slices and today's climate are analysed. The effect in relevant variables, such as permafrost extent, depth of the Active Layer, ground temperature, and amount of soil carbon, is investigated. The experiments (as well as the development of JSBACH with respect to permafrost soil physics) are part of the European project PAGE21, where a focus is set on interactions between the changing climate and its impact on permafrost, especially for the 21st century.

Improved protein surface comparison and application to low-resolution protein structure data.

PubMed

Sael, Lee; Kihara, Daisuke

2010-12-14

Recent advancements of experimental techniques for determining protein tertiary structures raise significant challenges for protein bioinformatics. With the number of known structures of unknown function expanding at a rapid pace, an urgent task is to provide reliable clues to their biological function on a large scale. Conventional approaches for structure comparison are not suitable for a real-time database search due to their slow speed. Moreover, a new challenge has arisen from recent techniques such as electron microscopy (EM), which provide low-resolution structure data. Previously, we have introduced a method for protein surface shape representation using the 3D Zernike descriptors (3DZDs). The 3DZD enables fast structure database searches, taking advantage of its rotation invariance and compact representation. The search results of protein surface represented with the 3DZD has showngood agreement with the existing structure classifications, but some discrepancies were also observed. The three new surface representations of backbone atoms, originally devised all-atom-surface representation, and the combination of all-atom surface with the backbone representation are examined. All representations are encoded with the 3DZD. Also, we have investigated the applicability of the 3DZD for searching protein EM density maps of varying resolutions. The surface representations are evaluated on structure retrieval using two existing classifications, SCOP and the CE-based classification. Overall, the 3DZDs representing backbone atoms show better retrieval performance than the original all-atom surface representation. The performance further improved when the two representations are combined. Moreover, we observed that the 3DZD is also powerful in comparing low-resolution structures obtained by electron microscopy.

Direct-current resistivity profiling at the Pecos River Ecosystem Project study site near Mentone, Texas, 2006

USGS Publications Warehouse

Teeple, Andrew; McDonald, Alyson K.; Payne, Jason; Kress, Wade H.

2009-01-01

The U.S. Geological Survey, in cooperation with Texas A&M University AgriLife, did a surface geophysical investigation at the Pecos River Ecosystem Project study site near Mentone in West Texas intended to determine shallow (to about 14 meters below the water [river] surface) subsurface composition (lithology) in and near treated (eradicated of all saltcedar) and control (untreated) riparian zone sites during June-August 2006. Land-based direct-current resistivity profiling was applied in a 240-meter section of the riverbank at the control site, and waterborne direct-current continuous resistivity profiling (CRP) was applied along a 2.279-kilometer reach of the river adjacent to both sites to collect shallow subsurface resistivity data. Inverse modeling was used to obtain a nonunique estimate of the true subsurface resistivity from apparent resistivity calculated from the field measurements. The land-based survey showed that the sub-surface at the control site generally is of relatively low resis-tivity down to about 4 meters below the water surface. Most of the section from about 4 to 10 meters below the water surface is of relatively high resistivity. The waterborne CRP surveys convey essentially the same electrical representation of the lithology at the control site to 10 meters below the water surface; but the CRP surveys show considerably lower resistivity than the land-based survey in the subsection from about 4 to 10 meters below the water surface. The CRP surveys along the 2.279-kilometer reach of the river adjacent to both the treated and control sites show the same relatively low resistivity zone from the riverbed to about 4 meters below the water surface evident at the control site. A slightly higher resistivity zone is observed from about 4 to 14 meters below the water surface along the upstream approximately one-half of the profile than along the downstream one-half. The variations in resistivity could not be matched to variations in lithology because sufficient rock samples were not available.

A Land System representation for global assessments and land-use modeling.

PubMed

van Asselen, Sanneke; Verburg, Peter H

2012-10-01

Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. © 2012 Blackwell Publishing Ltd.

Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Zaitchik, Benjamin F.; Peters-Lidard, Christa D.; Rodell, Matthew; Reichle, Rolf; Li, Bailing; Jasinski, Michael; Mocko, David; Getirana, Augusto; De Lannoy, Gabrielle;

LDAS-Monde: Global scale satellite driven Land Data Assimilation System based on SURFEX modelling platform

NASA Astrophysics Data System (ADS)

Munier, Simon; Albergel, Clément; Leroux, Delphine; Calvet, Jean-Christophe

2017-04-01

In the past decades, large efforts have been made to improve our understanding of the dynamics of the terrestrial water cycle, including vertical and horizontal water fluxes as well as water stored in the biosphere. The soil water content is closely related to the development of the vegetation, which is in turn closely related to the water and energy exchanges with the atmosphere (through evapotranspiration) as well as to carbon fluxes. Land Surface Models (LSMs) are usually designed to represent biogeophysical variables, such as Surface and Root Zone Soil Moisture (SSM, RZSM) or Leaf Area Index (LAI), in order to simulate water, energy and carbon fluxes at the interface between land and atmosphere. With the recent increase of satellite missions and derived products, LSMs can benefit from Earth Observations via Data Assimilation systems to improve their representation of different biogeophysical variables. This study, which is part of the eartH2Observe European project (http://www.earth2observe.eu), presents LDAS-Monde, a global Land Data Assimilation System using an implementation of the Simplified Extended Kalman Filter (SEKF) in the Météo-France's modelling platform (SURFEX). SURFEX is based on the coupling of the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (CTRIP). Two global operational datasets derived from satellite observations are assimilated simultaneously: (i) SSM from the ESA Climate Change Initiative and (ii) LAI from the Copernicus Global Land Service project. Atmospheric forcing used in SURFEX are derived from the ERA-Interim reanalysis and corrected from GPCC precipitations. The simulations are conducted at the global scale at a 1 degree spatial resolution over the period 2000-2014. An analysis of the model sensitivity to the assimilated observations is performed over different regions of the globe under various hydro-climatic conditions. The impact of the SEKF on different biogeophysical and hydrological variables is assessed. It is shown that the assimilation scheme greatly improves the representation of the observed variables (SSM and LAI) and that it effectively affects most of the other variables related to the terrestrial water and vegetation cycles. Future developments include the optimization of LDAS-Monde in order to improve the spatial resolution and then take full advantage of the potential of Earth Observations.

Uncertainties in modelling the climate impact of irrigation

NASA Astrophysics Data System (ADS)

de Vrese, Philipp; Hagemann, Stefan

2017-11-01

Irrigation-based agriculture constitutes an essential factor for food security as well as fresh water resources and has a distinct impact on regional and global climate. Many issues related to irrigation's climate impact are addressed in studies that apply a wide range of models. These involve substantial uncertainties related to differences in the model's structure and its parametrizations on the one hand and the need for simplifying assumptions for the representation of irrigation on the other hand. To address these uncertainties, we used the Max Planck Institute for Meteorology's Earth System model into which a simple irrigation scheme was implemented. In order to estimate possible uncertainties with regard to the model's more general structure, we compared the climate impact of irrigation between three simulations that use different schemes for the land-surface-atmosphere coupling. Here, it can be shown that the choice of coupling scheme does not only affect the magnitude of possible impacts but even their direction. For example, when using a scheme that does not explicitly resolve spatial subgrid scale heterogeneity at the surface, irrigation reduces the atmospheric water content, even in heavily irrigated regions. Contrarily, in simulations that use a coupling scheme that resolves heterogeneity at the surface or even within the lowest layers of the atmosphere, irrigation increases the average atmospheric specific humidity. A second experiment targeted possible uncertainties related to the representation of irrigation characteristics. Here, in four simulations the irrigation effectiveness (controlled by the target soil moisture and the non-vegetated fraction of the grid box that receives irrigation) and the timing of delivery were varied. The second experiment shows that uncertainties related to the modelled irrigation characteristics, especially the irrigation effectiveness, are also substantial. In general the impact of irrigation on the state of the land surface is more than three times larger when assuming a low irrigation effectiveness than when a high effectiveness is assumed. For certain variables, such as the vertically integrated water vapour, the impact is almost an order of magnitude larger. The timing of irrigation also has non-negligible effects on the simulated climate impacts and it can strongly alter their seasonality.

Reserve Design under Climate Change: From Land Facets Back to Ecosystem Representation

PubMed Central

Schneider, Richard R.; Bayne, Erin M.

2015-01-01

Ecosystem distributions are expected to shift as a result of global warming, raising concerns about the long-term utility of reserve systems based on coarse-filter ecosystem representation. We tested the extent to which proportional ecosystem representation targets would be maintained under a changing climate by projecting the distribution of the major ecosystems of Alberta, Canada, into the future using bioclimatic envelope models and then calculating the composition of reserves in successive periods. We used the Marxan conservation planning software to generate the suite of reserve systems for our test, varying the representation target and degree of reserve clumping. Our climate envelope projections for the 2080s indicate that virtually all reserves will, in time, be comprised of different ecosystem types than today. Nevertheless, our proportional targets for ecosystem representation were maintained across all time periods, with only minor exceptions. We hypothesize that this stability in representation arises because ecosystems may be serving as proxies for land facets, the stable abiotic landscape features that delineate major arenas of biological activity. The implication is that accommodating climate change may not require abandoning the conventional ecosystem-based approach to reserve design in favour of a strictly abiotic approach, since the two approaches may be largely synonymous. PMID:25978759

Uncertainty assessment of future land use in Brazil under increasing demand for bioenergy

NASA Astrophysics Data System (ADS)

van der Hilst, F.; Verstegen, J. A.; Karssenberg, D.; Faaij, A.

2013-12-01

Environmental impacts of a future increase in demand for bioenergy depend on the magnitude, location and pattern of the direct and indirect land use change of energy cropland expansion. Here we aim at 1) projecting the spatio-temporal pattern of sugar cane expansion and the effect on other land uses in Brazil towards 2030, and 2) assessing the uncertainty herein. For the spatio-temporal projection, three model components are used: 1) an initial land use map that shows the initial amount and location of sugar cane and all other relevant land use classes in the system, 2) a model to project the quantity of change of all land uses, and 3) a spatially explicit land use model that determines the location of change of all land uses. All three model components are sources of uncertainty, which is quantified by defining error models for all components and their inputs and propagating these errors through the chain of components. No recent accurate land use map is available for Brazil, so municipal census data and the global land cover map GlobCover are combined to create the initial land use map. The census data are disaggregated stochastically using GlobCover as a probability surface, to obtain a stochastic land use raster map for 2006. Since bioenergy is a global market, the quantity of change in sugar cane in Brazil depends on dynamics in both Brazil itself and other parts of the world. Therefore, a computable general equilibrium (CGE) model, MAGNET, is run to produce a time series of the relative change of all land uses given an increased future demand for bioenergy. A sensitivity analysis finds the upper and lower boundaries hereof, to define this component's error model. An initial selection of drivers of location for each land use class is extracted from literature. Using a Bayesian data assimilation technique and census data from 2007 to 2011 as observational data, the model is identified, meaning that the final selection and optimal relative importance of the drivers of location are determined. The data assimilation technique takes into account uncertainty in the observational data and yields a stochastic representation of the identified model. Using all stochastic inputs, this land use change model is run to find at which locations the future land use changes occur and to quantify the associated uncertainty. The results indicate that in the initial land use map especially the locations of pastures are uncertain. Since the dynamics in the livestock sector play a major role in the land use development of Brazil, the effect of this uncertainty on the model output is large. Results of the data assimilation indicate that the drivers of location of the land uses vary over time (variations up to 50% in the importance of the drivers) making it difficult to find a solid stationary system representation. Overall, we conclude that projection up to 2030 is only of use for quantifying impacts that act on a larger aggregation level, because at local level uncertainty is too large.

Improved protein surface comparison and application to low-resolution protein structure data

PubMed Central

2010-01-01

Background Recent advancements of experimental techniques for determining protein tertiary structures raise significant challenges for protein bioinformatics. With the number of known structures of unknown function expanding at a rapid pace, an urgent task is to provide reliable clues to their biological function on a large scale. Conventional approaches for structure comparison are not suitable for a real-time database search due to their slow speed. Moreover, a new challenge has arisen from recent techniques such as electron microscopy (EM), which provide low-resolution structure data. Previously, we have introduced a method for protein surface shape representation using the 3D Zernike descriptors (3DZDs). The 3DZD enables fast structure database searches, taking advantage of its rotation invariance and compact representation. The search results of protein surface represented with the 3DZD has showngood agreement with the existing structure classifications, but some discrepancies were also observed. Results The three new surface representations of backbone atoms, originally devised all-atom-surface representation, and the combination of all-atom surface with the backbone representation are examined. All representations are encoded with the 3DZD. Also, we have investigated the applicability of the 3DZD for searching protein EM density maps of varying resolutions. The surface representations are evaluated on structure retrieval using two existing classifications, SCOP and the CE-based classification. Conclusions Overall, the 3DZDs representing backbone atoms show better retrieval performance than the original all-atom surface representation. The performance further improved when the two representations are combined. Moreover, we observed that the 3DZD is also powerful in comparing low-resolution structures obtained by electron microscopy. PMID:21172052

Towards a realistic simulation of boreal summer tropical rainfall climatology in state-of-the-art coupled models: role of the background snow-free land albedo

NASA Astrophysics Data System (ADS)

Terray, P.; Sooraj, K. P.; Masson, S.; Krishna, R. P. M.; Samson, G.; Prajeesh, A. G.

2017-07-01

State-of-the-art global coupled models used in seasonal prediction systems and climate projections still have important deficiencies in representing the boreal summer tropical rainfall climatology. These errors include prominently a severe dry bias over all the Northern Hemisphere monsoon regions, excessive rainfall over the ocean and an unrealistic double inter-tropical convergence zone (ITCZ) structure in the tropical Pacific. While these systematic errors can be partly reduced by increasing the horizontal atmospheric resolution of the models, they also illustrate our incomplete understanding of the key mechanisms controlling the position of the ITCZ during boreal summer. Using a large collection of coupled models and dedicated coupled experiments, we show that these tropical rainfall errors are partly associated with insufficient surface thermal forcing and incorrect representation of the surface albedo over the Northern Hemisphere continents. Improving the parameterization of the land albedo in two global coupled models leads to a large reduction of these systematic errors and further demonstrates that the Northern Hemisphere subtropical deserts play a seminal role in these improvements through a heat low mechanism.

The effect of plant water stress approach on the modelled energy-, water and carbon balance for Mediterranean vegetation; implications for (agro)meteorological applications.

NASA Astrophysics Data System (ADS)

Verhoef, Anne; Egea, Gregorio; Garrigues, Sebastien; Vidale, Pier Luigi; Balan Sarojini, Beena

2017-04-01

Current land surface schemes in many crop, weather and climate models make use of the coupled photosynthesis-stomatal conductance (A-gs) models of plant function to determine the transpiration flux and gross primary productivity. Vegetation exchange is controlled by many environmental factors, and soil moisture control on root water uptake and stomatal function is a primary pathway for feedbacks in sub-tropical to temperate ecosystems. Representations of the above process of soil moisture control on plant function (often referred to as a 'beta' factor) vary among models. This matters because the simulated energy, water and carbon balances are very sensitive to the representation of water stress in these models. Building on Egea et al. (2011) and Verhoef and Egea (2014), we tested a range of 'beta' approaches in a leaf-level A-gs model (compatible with models such as JULES, CHTESSEL, ISBA, CLM), as well as some beta-approaches borrowed from the agronomic, and plant physiological communities (a combined soil-plant hydraulic approach, see Verhoef and Egea, 2014). Root zone soil moisture was allowed to limit plant function via individual routes (via CO2 assimilation, stomatal conductance, or mesophyll conductance) as well as combinations of that. The simulations were conducted for a typical Mediterranean field site (Avignon, France; Garrigues et al., 2015) which provides 14 years of near-continuous measurements of soil moisture and atmospheric driving data. Daytime (8-16 hrs local time) data between April-September were used. This allowed a broad range of atmospheric and soil moisture/vegetation states to be explored. A number of crops and tree types were investigated in this way. We evaluated the effect of choice of beta-function for Mediterranean climates in relation to stomatal conductance, transpiration, photosynthesis, and leaf surface temperature. We also studied the implications for a range of widely used agro-/micro-meteorological indicators such as Bowen ratio and the omega decoupling coefficient (which quantifies the degree of the aerodynamic coupling between a vegetated surface and the atmospheric boundary layer; Jacobs and de Bruin, 1992); and applications (e.g. the use of surface temperature based water stress indices). Results showed that choice of 'beta' function has far-reaching consequences. For certain widely used 'beta'-models the predicted key fluxes and state variables, predominantly compared using kernel density functions, showed considerable 'clumping' around narrow data ranges. This will have implications for the strength of land-surface feedback predicted by these models, and for any agrometeorological applications they are used for. Recommendations as to the most suitable 'beta'-functions, and related parameter sets, for Mediterranean climates were made. References Garrigues, S. et al. (2015) Evaluation of land surface model simulations of evapotranspiration over a 12-year crop succession: impact of soil hydraulic and vegetation properties, Hydrol. Earth Syst. Sci., 19, 3109-3131; Jacobs, C. M. J. and de Bruin, H. A. R. (1992) The sensitivity of regional transpiration to land-surface characteristics: Significance of feedback, J. Climate, 5(7), 683-698; Verhoef, A. and Egea, G. (2014) Agriculture and Forest Meteorology, 191, 22-32; Egea, G., Verhoef, A., and Vidale, P. L. (2011) Agricultural and Forest Meteorology, 151, 1370-1384

Effect of spatial resolution on remote sensing estimation of total evaporation in the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Clark, David; Mengistu, Michael; Dube, Timothy; Bulcock, Hartley

2015-01-01

This study evaluated the effect of two readily available multispectral sensors: the newly launched 30 m spatial resolution Landsat 8 and the long-serving 1000 m moderate resolution imaging spectroradiometer (MODIS) datasets in the spatial representation of total evaporation in the heterogeneous uMngeni catchment, South Africa, using the surface energy balance system model. The results showed that sensor spatial resolution plays a critical role in the accurate estimation of energy fluxes and total evaporation across a heterogeneous catchment. Landsat 8 estimates showed better spatial representation of the biophysical parameters and total evaporation for different land cover types, due to the relatively higher spatial resolution compared to the coarse spatial resolution MODIS sensor. Moreover, MODIS failed to capture the spatial variations of total evaporation estimates across the catchment. Analysis of variance (ANOVA) results showed that MODIS-based total evaporation estimates did not show any significant differences across different land cover types (one-way ANOVA; F1.924=1.412, p=0.186). However, Landsat 8 images yielded significantly different estimates between different land cover types (one-way ANOVA; F1.993=5.185, p<0.001). The validation results showed that Landsat 8 estimates were more comparable to eddy covariance (EC) measurements than the MODIS-based total evaporation estimates. EC measurement on May 23, 2013, was 3.8 mm/day, whereas the Landsat 8 estimate on the same day was 3.6 mm/day, with MODIS showing significantly lower estimates of 2.3 mm/day. The findings of this study underscore the importance of spatial resolution in estimating spatial variations of total evaporation at the catchment scale, thus, they provide critical information on the relevance of the readily available remote sensing products in water resources management in data-scarce environments.

Observations of land-atmosphere interactions using satellite data

NASA Astrophysics Data System (ADS)

Green, Julia; Gentine, Pierre; Konings, Alexandra; Alemohammad, Hamed; Kolassa, Jana

2016-04-01

Observations of land-atmosphere interactions using satellite data Julia Green (1), Pierre Gentine (1), Alexandra Konings (1,2), Seyed Hamed Alemohammad (3), Jana Kolassa (4) (1) Columbia University, Earth and Environmental Engineering, NY, NY, USA, (2) Stanford University, Environmental Earth System Science, Stanford, CA, USA, (3) Massachusetts Institute of Technology, Civil and Environmental Engineering, Cambridge, MA, USA, (4) National Aeronautics and Space Administration/Goddard Space Flight Center, Greenbelt, MD, USA. Previous studies of global land-atmosphere hotspots have often relied solely on data from global models with the consequence that they are sensitive to model error. On the other hand, by only analyzing observations, it can be difficult to distinguish causality from mere correlation. In this study, we present a general framework for investigating land-atmosphere interactions using Granger Causality analysis applied to remote sensing data. Based on the near linear relationship between chlorophyll sun induced fluorescence (SIF) and photosynthesis (and thus its relationship with transpiration), we use the GOME-2 fluorescence direct measurements to quantify the surface fluxes between the land and atmosphere. By using SIF data to represent the flux, we bypass the need to use soil moisture data from FLUXNET (limited spatially and temporally) or remote sensing (limited by spatial resolution, canopy interference, measurement depth, and radio frequency interference) thus eliminating additional uncertainty. The Granger Causality analysis allows for the determination of the strength of the two-way causal relationship between SIF and several climatic variables: precipitation, radiation and temperature. We determine that warm regions transitioning from water to energy limitation exhibit strong feedbacks between the land surface and atmosphere due to their high sensitivity to climate and weather variability. Tropical rainforest regions show low magnitudes of causal feedback likely due to other factors influencing the land surface such as phenological controls (e.g. leaf area index), nutrient limitations or soil texture. These results were then compared to CMIP5 GCM results using GPP in place of SIF. GCM results varied greatly between models as well as with the observational data analysis indicating deficiencies in the representation of certain modeled phenomena such as low level clouds and boundary layer development. This study highlights the need for GCM improvement to more accurately capture the feedbacks between the land and atmosphere. These results have the potential to improve our understanding of the underlying mechanisms between land and atmosphere coupling, which could ultimately be used to improve weather and climate predictions.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul

2016-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning retrospective predictions at the decadal (5-years), seasonal and sub-seasonal time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and sub-seasonal time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; van den Hurk, B.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2016-12-01

The European consortium earth system model (EC-Earth; http://www.ec-earth.org) has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

DOEpatents

Moody, Daniela; Wohlberg, Brendt

2018-01-02

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

A specific PFT and sub-canopy structure for simulating oil palm in the Community Land Model

NASA Astrophysics Data System (ADS)

Fan, Y.; Knohl, A.; Roupsard, O.; Bernoux, M.; LE Maire, G.; Panferov, O.; Kotowska, M.; Meijide, A.

2015-12-01

Towards an effort to quantify the effects of rainforests to oil palm conversion on land-atmosphere carbon, water and energy fluxes, a specific plant functional type (PFT) and sub-canopy structure are developed for simulating oil palm within the Community Land Model (CLM4.5). Current global land surface models only simulate annual crops beside natural vegetation. In this study, a multilayer oil palm subroutine is developed in CLM4.5 for simulating oil palm's phenology and carbon and nitrogen allocation. The oil palm has monopodial morphology and sequential phenology of around 40 stacked phytomers, each carrying a large leaf and a fruit bunch, forming a natural multilayer canopy. A sub-canopy phenological and physiological parameterization is thus introduced, so that multiple phytomer components develop simultaneously but according to their different phenological steps (growth, yield and senescence) at different canopy layers. This specific multilayer structure was proved useful for simulating canopy development in terms of leaf area index (LAI) and fruit yield in terms of carbon and nitrogen outputs in Jambi, Sumatra (Fan et al. 2015). The study supports that species-specific traits, such as palm's monopodial morphology and sequential phenology, are necessary representations in terrestrial biosphere models in order to accurately simulate vegetation dynamics and feedbacks to climate. Further, oil palm's multilayer structure allows adding all canopy-level calculations of radiation, photosynthesis, stomatal conductance and respiration, beside phenology, also to the sub-canopy level, so as to eliminate scale mismatch problem among different processes. A series of adaptations are made to the CLM model. Initial results show that the adapted multilayer radiative transfer scheme and the explicit represention of oil palm's canopy structure improve on simulating photosynthesis-light response curve. The explicit photosynthesis and dynamic leaf nitrogen calculations per canopy layer also enhance simulated CO2 flux when compared to eddy covariance flux data. More investigations on energy and water fluxes and nitrogen balance are being conducted. These new schemes would hopefully promote the understanding of climatic effects of the tropical land use transformation system.

One carbon cycle: Impacts of model integration, ecosystem process detail, model resolution, and initialization data, on projections of future climate mitigation strategies

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; le page, Y.; Patel, P. L.; Chini, L. P.; Sahajpal, R.; Dubayah, R.; Thomson, A. M.; Edmonds, J.; Janetos, A. C.

2013-12-01

Integrated assessment models (IAMs) simulate the interactions between human and natural systems at a global scale, representing a broad suite of phenomena across the global economy, energy system, land-use, and carbon cycling. Most proposed climate mitigation strategies rely on maintaining or enhancing the terrestrial carbon sink as a substantial contribution to restrain the concentration of greenhouse gases in the atmosphere, however most IAMs rely on simplified regional representations of terrestrial carbon dynamics. Our research aims to reduce uncertainties associated with forest modeling within integrated assessments, and to quantify the impacts of climate change on forest growth and productivity for integrated assessments of terrestrial carbon management. We developed the new Integrated Ecosystem Demography (iED) to increase terrestrial ecosystem process detail, resolution, and the utilization of remote sensing in integrated assessments. iED brings together state-of-the-art models of human society (GCAM), spatial land-use patterns (GLM) and terrestrial ecosystems (ED) in a fully coupled framework. The major innovative feature of iED is a consistent, process-based representation of ecosystem dynamics and carbon cycle throughout the human, terrestrial, land-use, and atmospheric components. One of the most challenging aspects of ecosystem modeling is to provide accurate initialization of land surface conditions to reflect non-equilibrium conditions, i.e., the actual successional state of the forest. As all plants in ED have an explicit height, it is one of the few ecosystem models that can be initialized directly with vegetation height data. Previous work has demonstrated that ecosystem model resolution and initialization data quality have a large effect on flux predictions at continental scales. Here we use a factorial modeling experiment to quantify the impacts of model integration, process detail, model resolution, and initialization data on projections of future climate mitigation strategies. We find substantial effects on key integrated assessment projections including the magnitude of emissions to mitigate, the economic value of ecosystem carbon storage, future land-use patterns, food prices and energy technology.

Characteristics of the ocean simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model

NASA Astrophysics Data System (ADS)

Jungclaus, J. H.; Fischer, N.; Haak, H.; Lohmann, K.; Marotzke, J.; Matei, D.; Mikolajewicz, U.; Notz, D.; von Storch, J. S.

2013-06-01

MPI-ESM is a new version of the global Earth system model developed at the Max Planck Institute for Meteorology. This paper describes the ocean state and circulation as well as basic aspects of variability in simulations contributing to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The performance of the ocean/sea-ice model MPIOM, coupled to a new version of the atmosphere model ECHAM6 and modules for land surface and ocean biogeochemistry, is assessed for two model versions with different grid resolution in the ocean. The low-resolution configuration has a nominal resolution of 1.5°, whereas the higher resolution version features a quasiuniform, eddy-permitting global resolution of 0.4°. The paper focuses on important oceanic features, such as surface temperature and salinity, water mass distribution, large-scale circulation, and heat and freshwater transports. In general, these integral quantities are simulated well in comparison with observational estimates, and improvements in comparison with the predecessor system are documented; for example, for tropical variability and sea ice representation. Introducing an eddy-permitting grid configuration in the ocean leads to improvements, in particular, in the representation of interior water mass properties in the Atlantic and in the representation of important ocean currents, such as the Agulhas and Equatorial current systems. In general, however, there are more similarities than differences between the two grid configurations, and several shortcomings, known from earlier versions of the coupled model, prevail.

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Starr, David (Technical Monitor)

2002-01-01

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (size about 2-200 km). The CRMs also allow explicit interaction between out-going longwave (cooling) and in-coming solar (heating) radiation with clouds. Observations can provide the initial conditions and validation for CRM results. The Goddard Cumulus Ensemble (GCE) Model, a CRM, has been developed and improved at NASA/Goddard Space Flight Center over the past two decades. The GCE model has been used to understand the following: 1) water and energy cycles and their roles in the tropical climate system; 2) the vertical redistribution of ozone and trace constituents by individual clouds and well organized convective systems over various spatial scales; 3) the relationship between the vertical distribution of latent heating (phase change of water) and the large-scale (pre-storm) environment; 4) the validity of assumptions used in the representation of cloud processes in climate and global circulation models; and 5) the representation of cloud microphysical processes and their interaction with radiative forcing over tropical and midlatitude regions. Four-dimensional cloud and latent heating fields simulated from the GCE model have been provided to the TRMM Science Data and Information System (TSDIS) to develop and improve algorithms for retrieving rainfall and latent heating rates for TRMM and the NASA Earth Observing System (EOS). More than 90 referred papers using the GCE model have been published in the last two decades. Also, more than 10 national and international universities are currently using the GCE model for research and teaching. In this talk, five specific major GCE improvements: (1) ice microphysics, (2) longwave and shortwave radiative transfer processes, (3) land surface processes, (4) ocean surface fluxes and (5) ocean mixed layer processes are presented. The performance of these new GCE improvements will be examined. Observations are used for model validation.

Final report on "Modeling Diurnal Variations of California Land Biosphere CO2 Fluxes"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fung, Inez

In Mediterranean climates, the season of water availability (winter) is out of phase with the season of light availability and atmospheric demand for moisture (summer). Multi-year half-hourly observations of sap flow velocities in 26 evergreen trees in a small watershed in Northern California show that different species of evergreen trees have different seasonalities of transpiration: Douglas-firs respond immediately to the first winter rain, while Pacific madrones have peak transpiration in the dry summer. Using these observations, we have derived species-specific parameterization of normalized sap flow velocities in terms of insolation, vapor pressure deficit and near-surface soil moisture. A simple 1-Dmore » boundary layer model showed that afternoon temperatures may be higher by 1 degree Celsius in an area with Douglas-firs than with Pacific madrones. The results point to the need to develop a new representation of subsurface moisture, in particular pools beneath the organic soil mantle and the vadose zone. Our ongoing and future work includes coupling our new parameterization of transpiration with new representation of sub-surface moisture in saprolite and weathered bedrock. The results will be implemented in a regional climate model to explore vegetation-climate feedbacks, especially in the dry season.« less

Analysis of the Intra-City Variation of Urban Heat Island and its Relation to Land Surface/cover Parameters

NASA Astrophysics Data System (ADS)

Gerçek, D.; Güven, İ. T.; Oktay, İ. Ç.

2016-06-01

Along with urbanization, sealing of vegetated land and evaporation surfaces by impermeable materials, lead to changes in urban climate. This phenomenon is observed as temperatures several degrees higher in densely urbanized areas compared to the rural land at the urban fringe particularly at nights, so-called Urban Heat Island. Urban Heat Island (UHI) effect is related with urban form, pattern and building materials so far as it is associated with meteorological conditions, air pollution, excess heat from cooling. UHI effect has negative influences on human health, as well as other environmental problems such as higher energy demand, air pollution, and water shortage. Urban Heat Island (UHI) effect has long been studied by observations of air temperature from thermometers. However, with the advent and proliferation of remote sensing technology, synoptic coverage and better representations of spatial variation of surface temperature became possible. This has opened new avenues for the observation capabilities and research of UHIs. In this study, "UHI effect and its relation to factors that cause it" is explored for İzmit city which has been subject to excess urbanization and industrialization during the past decades. Spatial distribution and variation of UHI effect in İzmit is analysed using Landsat 8 and ASTER day & night images of 2015 summer. Surface temperature data derived from thermal bands of the images were analysed for UHI effect. Higher temperatures were classified into 4 grades of UHIs and mapped both for day and night. Inadequate urban form, pattern, density, high buildings and paved surfaces at the expanse of soil ground and vegetation cover are the main factors that cause microclimates giving rise to spatial variations in temperatures across cities. These factors quantified as land surface/cover parameters for the study include vegetation index (NDVI), imperviousness (NDISI), albedo, solar insolation, Sky View Factor (SVF), building envelope, distance to sea, and traffic space density. These parameters that cause variation in intra-city temperatures were evaluated for their relationship with different grades of UHIs. Zonal statistics of UHI classes and variations in average value of parameters were interpreted. The outcomes that highlight local temperature peaks are proposed to the attention of the decision makers for mitigation of Urban Heat Island effect in the city at local and neighbourhood scale.

Wake Dynamics in the Atmospheric Boundary Layer Over Complex Terrain

NASA Astrophysics Data System (ADS)

Markfort, Corey D.

The goal of this research is to advance our understanding of atmospheric boundary layer processes over heterogeneous landscapes and complex terrain. The atmospheric boundary layer (ABL) is a relatively thin (˜ 1 km) turbulent layer of air near the earth's surface, in which most human activities and engineered systems are concentrated. Its dynamics are crucially important for biosphere-atmosphere couplings and for global atmospheric dynamics, with significant implications on our ability to predict and mitigate adverse impacts of land use and climate change. In models of the ABL, land surface heterogeneity is typically represented, in the context of Monin-Obukhov similarity theory, as changes in aerodynamic roughness length and surface heat and moisture fluxes. However, many real landscapes are more complex, often leading to massive boundary layer separation and wake turbulence, for which standard models fail. Trees, building clusters, and steep topography produce extensive wake regions currently not accounted for in models of the ABL. Wind turbines and wind farms also generate wakes that combine in complex ways to modify the ABL. Wind farms are covering an increasingly significant area of the globe and the effects of large wind farms must be included in regional and global scale models. Research presented in this thesis demonstrates that wakes caused by landscape heterogeneity must be included in flux parameterizations for momentum, heat, and mass (water vapor and trace gases, e.g. CO2 and CH4) in ABL simulation and prediction models in order to accurately represent land-atmosphere interactions. Accurate representation of these processes is crucial for the predictions of weather, air quality, lake processes, and ecosystems response to climate change. Objectives of the research reported in this thesis are: 1) to investigate turbulent boundary layer adjustment, turbulent transport and scalar flux in wind farms of varying configurations and develop an improved modeling framework for wind farm - atmosphere interaction, 2) to determine how heterogeneous patches of forest affect the structure of the ABL and its interactions with clearings and water bodies, 3) to investigate how landscape heterogeneity, including wakes, may be parameterized in regional-scale weather and climate models to improve the representation of surface fluxes, e.g. from lakes/wetlands and forest clearings. To achieve these objectives, this research employs an interdisciplinary strategy, utilizing concepts and methods from fluid mechanics, micrometeorology, ecosystem ecology and environmental sciences, and combines laboratory and field experiments. In particular, a) wind tunnel experiments of flow through and over model wind farms and model forest canopies were used to improve our fundamental understanding of how wakes affect land-atmosphere coupling, including surface fluxes, after wind farm installation and for heterogeneous landscapes of canopies and clearings or lakes, and b) extensive field studies over lakes and wetlands were undertaken to study the effects of wakes downwind of forest canopies and the effect of wind sheltering on lake stratification dynamics and gas fluxes. These experiments were also used to improve and validate numerical simulation techniques for the atmospheric boundary layer, specifically the large eddy simulation technique, which is used to simulate flow in wind farms and flow over heterogeneous terrain.

Towards a simple representation of chalk hydrology in land surface modelling

NASA Astrophysics Data System (ADS)

Rahman, Mostaquimur; Rosolem, Rafael

2017-01-01

Modelling and monitoring of hydrological processes in the unsaturated zone of chalk, a porous medium with fractures, is important to optimize water resource assessment and management practices in the United Kingdom (UK). However, incorporating the processes governing water movement through a chalk unsaturated zone in a numerical model is complicated mainly due to the fractured nature of chalk that creates high-velocity preferential flow paths in the subsurface. In general, flow through a chalk unsaturated zone is simulated using the dual-porosity concept, which often involves calibration of a relatively large number of model parameters, potentially undermining applications to large regions. In this study, a simplified parameterization, namely the Bulk Conductivity (BC) model, is proposed for simulating hydrology in a chalk unsaturated zone. This new parameterization introduces only two additional parameters (namely the macroporosity factor and the soil wetness threshold parameter for fracture flow activation) and uses the saturated hydraulic conductivity from the chalk matrix. The BC model is implemented in the Joint UK Land Environment Simulator (JULES) and applied to a study area encompassing the Kennet catchment in the southern UK. This parameterization is further calibrated at the point scale using soil moisture profile observations. The performance of the calibrated BC model in JULES is assessed and compared against the performance of both the default JULES parameterization and the uncalibrated version of the BC model implemented in JULES. Finally, the model performance at the catchment scale is evaluated against independent data sets (e.g. runoff and latent heat flux). The results demonstrate that the inclusion of the BC model in JULES improves simulated land surface mass and energy fluxes over the chalk-dominated Kennet catchment. Therefore, the simple approach described in this study may be used to incorporate the flow processes through a chalk unsaturated zone in large-scale land surface modelling applications.

Progress in and prospects for fluvial flood modelling.

PubMed

Wheater, H S

2002-07-15

Recent floods in the UK have raised public and political awareness of flood risk. There is an increasing recognition that flood management and land-use planning are linked, and that decision-support modelling tools are required to address issues of climate and land-use change for integrated catchment management. In this paper, the scientific context for fluvial flood modelling is discussed, current modelling capability is considered and research challenges are identified. Priorities include (i) appropriate representation of spatial precipitation, including scenarios of climate change; (ii) development of a national capability for continuous hydrological simulation of ungauged catchments; (iii) improved scientific understanding of impacts of agricultural land-use and land-management change, and the development of new modelling approaches to represent those impacts; (iv) improved representation of urban flooding, at both local and catchment scale; (v) appropriate parametrizations for hydraulic simulation of in-channel and flood-plain flows, assimilating available ground observations and remotely sensed data; and (vi) a flexible decision-support modelling framework, incorporating developments in computing, data availability, data assimilation and uncertainty analysis.

Workshop on Aircraft Surface Representation for Aerodynamic Computation

NASA Technical Reports Server (NTRS)

Gregory, T. J. (Editor); Ashbaugh, J. (Editor)

1980-01-01

Papers and discussions on surface representation and its integration with aerodynamics, computers, graphics, wind tunnel model fabrication, and flow field grid generation are presented. Surface definition is emphasized.

Precision Gas Sampling (PGS) Validation2011-2014 Final Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tom, M. S.; Fischer, M. L.; Biraud, S. C.

In this field campaign, we used eddy covariance towers to quantify carbon, water, and energy fluxes from a pasture and a wheat field that were converted to switchgrass. The U.S. Department of Energy is investing in switchgrass as a cellulosic bioenergy crop, but there is little data available that could be used to develop or test land surface model representations of the crop. This campaign was a collaboration between Lawrence Berkeley National Laboratory and the U.S. Department of Agriculture Agricultural Research Service. Unfortunately, in 2011, Oklahoma had one of the most severe droughts on record, and the crop in onemore » of the switchgrass fields experienced almost complete die-off. The crop was replanted, but subsequent drought conditions prevented its establishment. Then, in April 2012, a large tornado demolished the instruments at our site in Woodward, Oklahoma. These two events meant that we have some interesting data on land response to extreme weather; however, we were not able to collect continuous data for annual sums as originally intended. We did observe that, because of the drought, the net ecosystem exchange of CO 2 was much lower in 2011 than in 2010. Concomitantly, sensible heat fluxes increased and latent heat fluxes decreased. These conditions would have large consequences for land surface forcing of convection. Data from all years were submitted to the Atmospheric Radiation Measurement Climate Research Facility Data Archive, and the sites were registered in AmeriFlux.« less

Synergies Between Grace and Regional Atmospheric Modeling Efforts

NASA Astrophysics Data System (ADS)

Kusche, J.; Springer, A.; Ohlwein, C.; Hartung, K.; Longuevergne, L.; Kollet, S. J.; Keune, J.; Dobslaw, H.; Forootan, E.; Eicker, A.

2014-12-01

In the meteorological community, efforts converge towards implementation of high-resolution (< 12km) data-assimilating regional climate modelling/monitoring systems based on numerical weather prediction (NWP) cores. This is driven by requirements of improving process understanding, better representation of land surface interactions, atmospheric convection, orographic effects, and better forecasting on shorter timescales. This is relevant for the GRACE community since (1) these models may provide improved atmospheric mass separation / de-aliasing and smaller topography-induced errors, compared to global (ECMWF-Op, ERA-Interim) data, (2) they inherit high temporal resolution from NWP models, (3) parallel efforts towards improving the land surface component and coupling groundwater models; this may provide realistic hydrological mass estimates with sub-diurnal resolution, (4) parallel efforts towards re-analyses, with the aim of providing consistent time series. (5) On the other hand, GRACE can help validating models and aids in the identification of processes needing improvement. A coupled atmosphere - land surface - groundwater modelling system is currently being implemented for the European CORDEX region at 12.5 km resolution, based on the TerrSysMP platform (COSMO-EU NWP, CLM land surface and ParFlow groundwater models). We report results from Springer et al. (J. Hydromet., accept.) on validating the water cycle in COSMO-EU using GRACE and precipitation, evapotranspiration and runoff data; confirming that the model does favorably at representing observations. We show that after GRACE-derived bias correction, basin-average hydrological conditions prior to 2002 can be reconstructed better than before. Next, comparing GRACE with CLM forced by EURO-CORDEX simulations allows identifying processes needing improvement in the model. Finally, we compare COSMO-EU atmospheric pressure, a proxy for mass corrections in satellite gravimetry, with ERA-Interim over Europe at timescales shorter/longer than 1 month, and spatial scales below/above ERA resolution. We find differences between regional and global model more pronounced at high frequencies, with magnitude at sub-grid scale and larger scale corresponding to 1-3 hPa (1-3 cm EWH); relevant for the assessment of post-GRACE concepts.

Prediction Activities at NASA's Global Modeling and Assimilation Office

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2010-01-01

The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the climate community. An improved understanding of the nature of decadal variability and its predictability has important implications for efforts to assess the impacts of global change in the coming decades. In fact, the GMAO has taken on the challenge of carrying out experimental decadal predictions in support of the IPCC AR5 effort.

Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins: SOIL MOISTURE SCALE GAP

DOE PAGES

Baker, I. T.; Sellers, P. J.; Denning, A. S.; ...

2017-03-01

The interaction of land with the atmosphere is sensitive to soil moisture (W). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f(W), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell-average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed tomore » represent subgrid scale heterogeneity, including: (1) statistical-dynamical representations of grid subelements of varying wetness, (2) relaxation of f(W), (3) moderating f(W) with approximations of catchment hydrology, (4) “tiling” the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape-scale W is represented as a series of “Bins” of increasing wetness from dry to saturated. The grid cell-level f(W) is defined by the integral of the fractional area of the wetness bins and the value of f(W) associated with each. This approach accounts for the spatiotemporal dynamics of W. We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W. We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs.« less

A Systematic Evaluation of Noah-MP in Simulating Land-Atmosphere Energy, Water, and Carbon Exchanges Over the Continental United States

NASA Astrophysics Data System (ADS)

Ma, Ning; Niu, Guo-Yue; Xia, Youlong; Cai, Xitian; Zhang, Yinsheng; Ma, Yaoming; Fang, Yuanhao

2017-11-01

Accurate simulation of energy, water, and carbon fluxes exchanging between the land surface and the atmosphere is beneficial for improving terrestrial ecohydrological and climate predictions. We systematically assessed the Noah land surface model (LSM) with mutiparameterization options (Noah-MP) in simulating these fluxes and associated variations in terrestrial water storage (TWS) and snow cover fraction (SCF) against various reference products over 18 United States Geological Survey two-digital hydrological unit code regions of the continental United States (CONUS). In general, Noah-MP captures better the observed seasonal and interregional variability of net radiation, SCF, and runoff than other variables. With a dynamic vegetation model, it overestimates gross primary productivity by 40% and evapotranspiration (ET) by 22% over the whole CONUS domain; however, with a prescribed climatology of leaf area index, it greatly improves ET simulation with relative bias dropping to 4%. It accurately simulates regional TWS dynamics in most regions except those with large lakes or severely affected by irrigation and/or impoundments. Incorporating the lake water storage variations into the modeled TWS variations largely reduces the TWS simulation bias more obviously over the Great Lakes with model efficiency increasing from 0.18 to 0.76. Noah-MP simulates runoff well in most regions except an obvious overestimation (underestimation) in the Rio Grande and Lower Colorado (New England). Compared with North American Land Data Assimilation System Phase 2 (NLDAS-2) LSMs, Noah-MP shows a better ability to simulate runoff and a comparable skill in simulating Rn but a worse skill in simulating ET over most regions. This study suggests that future model developments should focus on improving the representations of vegetation dynamics, lake water storage dynamics, and human activities including irrigation and impoundments.

Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins: SOIL MOISTURE SCALE GAP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, I. T.; Sellers, P. J.; Denning, A. S.

The interaction of land with the atmosphere is sensitive to soil moisture (W). Evapotranspiration (ET) reacts to soil moisture in a nonlinear way, f(W), as soils dry from saturation to wilt point. This nonlinear behavior and the fact that soil moisture varies on scales as small as 1–10 m in nature, while numerical general circulation models (GCMs) have grid cell sizes on the order of 1 to 100s of kilometers, makes the calculation of grid cell-average ET problematic. It is impractical to simulate the land in GCMs on the small scales seen in nature, so techniques have been developed tomore » represent subgrid scale heterogeneity, including: (1) statistical-dynamical representations of grid subelements of varying wetness, (2) relaxation of f(W), (3) moderating f(W) with approximations of catchment hydrology, (4) “tiling” the landscape into vegetation types, and (5) hyperresolution. Here we present an alternative method for representing subgrid variability in W, one proven in a conceptual framework where landscape-scale W is represented as a series of “Bins” of increasing wetness from dry to saturated. The grid cell-level f(W) is defined by the integral of the fractional area of the wetness bins and the value of f(W) associated with each. This approach accounts for the spatiotemporal dynamics of W. We implemented this approach in the SiB3 land surface parameterization and then evaluated its performance against a control, which assumes a horizontally uniform field of W. We demonstrate that the Bins method, with a physical basis, attenuates unrealistic jumps in model state and ET seen in the control runs.« less

SUMMA and Model Mimicry: Understanding Differences Among Land Models

NASA Astrophysics Data System (ADS)

Nijssen, B.; Nearing, G. S.; Ou, G.; Clark, M. P.

2016-12-01

Model inter-comparison and model ensemble experiments suffer from an inability to explain the mechanisms behind differences in model outcomes. We can clearly demonstrate that the models are different, but we cannot necessarily identify the reasons why, because most models exhibit myriad differences in process representations, model parameterizations, model parameters and numerical solution methods. This inability to identify the reasons for differences in model performance hampers our understanding and limits model improvement, because we cannot easily identify the most promising paths forward. We have developed the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to allow for controlled experimentation with model construction, numerical techniques, and parameter values and therefore isolate differences in model outcomes to specific choices during the model development process. In developing SUMMA, we recognized that hydrologic models can be thought of as individual instantiations of a master modeling template that is based on a common set of conservation equations for energy and water. Given this perspective, SUMMA provides a unified approach to hydrologic modeling that integrates different modeling methods into a consistent structure with the ability to instantiate alternative hydrologic models at runtime. Here we employ SUMMA to revisit a previous multi-model experiment and demonstrate its use for understanding differences in model performance. Specifically, we implement SUMMA to mimic the spread of behaviors exhibited by the land models that participated in the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) and draw conclusions about the relative performance of specific model parameterizations for water and energy fluxes through the soil-vegetation continuum. SUMMA's ability to mimic the spread of model ensembles and the behavior of individual models can be an important tool in focusing model development and improvement efforts.

Cortical dynamics of three-dimensional figure-ground perception of two-dimensional pictures.

PubMed

Grossberg, S

1997-07-01

This article develops the FACADE theory of 3-dimensional (3-D) vision and figure-ground separation to explain data concerning how 2-dimensional pictures give rise to 3-D percepts of occluding and occluded objects. The model describes how geometrical and contrastive properties of a picture can either cooperate or compete when forming the boundaries and surface representation that subserve conscious percepts. Spatially long-range cooperation and spatially short-range competition work together to separate the boundaries of occluding figures from their occluded neighbors. This boundary ownership process is sensitive to image T junctions at which occluded figures contact occluding figures. These boundaries control the filling-in of color within multiple depth-sensitive surface representations. Feedback between surface and boundary representations strengthens consistent boundaries while inhibiting inconsistent ones. Both the boundary and the surface representations of occluded objects may be amodally completed, while the surface representations of unoccluded objects become visible through modal completion. Functional roles for conscious modal and amodal representations in object recognition, spatial attention, and reaching behaviors are discussed. Model interactions are interpreted in terms of visual, temporal, and parietal cortices.

Investigation of environmental change pattern in Japan: A study on change detection of land cover in Tokyo districts using multi-dates LANDSAT CCT

NASA Technical Reports Server (NTRS)

Maruyasu, T.; Murai, S. (Principal Investigator)

1976-01-01

The author has identified the following significant results. The software program, which enables the geographically corrected LANDSAT digital data base, was developed. The data base could provide land use planners with land cover information and the environmental change pattern. Land cover was evaluated by the color representation for ratio of three primary components, water vegetation, and nonorganic matter. Software was also developed for the change detection within multidates LANDSAT MSS data.

A novel representation of chalk hydrology in a land surface model

NASA Astrophysics Data System (ADS)

Rahman, Mostaquimur; Rosolem, Rafael

2016-04-01

Unconfined chalk aquifers contain a significant portion of water in the United Kingdom. In order to optimize the assessment and management practices of water resources in the region, modelling and monitoring of soil moisture in the unsaturated zone of the chalk aquifers are of utmost importance. However, efficient simulation of soil moisture in such aquifers is difficult mainly due to the fractured nature of chalk, which creates high-velocity preferential flow paths in the unsaturated zone. In this study, the Joint UK Land Environment Simulator (JULES) is applied on a study area encompassing the Kennet catchment in Southern England. The fluxes and states of the coupled water and energy cycles are simulated for 10 consecutive years (2001-2010). We hypothesize that explicit representation for the soil-chalk layers and the inclusion of preferential flow in the fractured chalk aquifers improves the reproduction of the hydrological processes in JULES. In order to test this hypothesis, we propose a new parametrization for preferential flow in JULES. This parametrization explicitly describes the flow of water in soil matrices and preferential flow paths using a simplified approach which can be beneficial for large-scale hydrometeorological applications. We also define the overlaying soil properties obtained from the Harmonized World Soil Database (HWSD) in the model. Our simulation results are compared across spatial scales with measured soil moisture and river discharge, indicating the importance of accounting for the physical properties of the medium while simulating hydrological processes in the chalk aquifers.

32 CFR 644.530 - Conditions in conveying land suspected of contamination.

Code of Federal Regulations, 2011 CFR

2011-07-01

... representations or warranties pertaining to the condition of the land; and Whereas, the hereinafter-designated grantee has entered into a contract to purchase said property with full knowledge of, and notwithstanding... confesses to full knowledge with respect to the facts contained in the foregoing recitals as to possible...

43 CFR 2091.0-5 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Tract Books, Master Title Plats and Historical Indices maintained by the Bureau of Land Management, or automated representation of these books, plats and indices on which are recorded information relating to the... language in the opening order, an opening may restore the lands to the operation of all or some of the...

43 CFR 2091.0-5 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Tract Books, Master Title Plats and Historical Indices maintained by the Bureau of Land Management, or automated representation of these books, plats and indices on which are recorded information relating to the... language in the opening order, an opening may restore the lands to the operation of all or some of the...

43 CFR 2091.0-5 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Tract Books, Master Title Plats and Historical Indices maintained by the Bureau of Land Management, or automated representation of these books, plats and indices on which are recorded information relating to the... language in the opening order, an opening may restore the lands to the operation of all or some of the...

Uncertainty in Land Cover observations and its impact on near surface climate

NASA Astrophysics Data System (ADS)

Georgievski, Goran; Hagemann, Stefan

2017-04-01

Land Cover (LC) and its bio-geo-physical feedbacks are important for the understanding of climate and its vulnerability to changes on the surface of the Earth. Recently ESA has published a new LC map derived by combining remotely sensed surface reflectance and ground-truth observations. For each grid-box at 300m resolution, an estimate of confidence is provided. This LC data set can be used in climate modelling to derive land surface boundary parameters for the respective Land Surface Model (LSM). However, the ESA LC classes are not directly suitable for LSMs, therefore they need to be converted into the model specific surface presentations. Due to different design and processes implemented in various climate models they might differ in the treatment of artificial, water bodies, ice, bare or vegetated surfaces. Nevertheless, usually vegetation distribution in models is presented by means of plant functional types (PFT), which is a classification system used to simplify vegetation representation and group different vegetation types according to their biophysical characteristics. The method of LC conversion into PFT is also called "cross-walking" (CW) procedure. The CW procedure is another source of uncertainty, since it depends on model design and processes implemented and resolved by LSMs. These two sources of uncertainty, (i) due to surface reflectance conversion into LC classes, (ii) due to CW procedure, have been studied by Hartley et al (2016) to investigate their impact on LSM state variables (albedo, evapotranspiration (ET) and primary productivity) by using three standalone LSMs. The present study is a follow up to that work and aims at quantifying the impact of these two uncertainties on climate simulations performed with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) using prescribed sea surface temperature and sea ice. The main focus is on the terrestrial water cycle, but the impacts on surface albedo, wind patterns, 2m temperatures, as well as plant productivity are also examined. The analysis of vegetation covered area indicates that the range of uncertainty might be about the same order of magnitude as the estimated historical anthropogenic LC change. For example, the area covered with managed grasses (crops and pasture in MPI-ESM PFT classification) varies from 17 to 26 million km2, and area covered with trees ranges from 15 million km2 up to 51 million km2. These uncertainties in vegetation distribution lead to noticeable variations in atmospheric temperature, humidity, cloud cover, circulation, and precipitation as well as local, regional and global climate forcing. For example, the amount of terrestrial ET ranges from 73 to 77 × 103 km3yr-1in MPI-ESM simulations and this range has about the same order of magnitude as the current estimate of the reduction of annual ET due to recent anthropogenic LC change. This and more impacts of LC uncertainty on the near surface climate will be presented and discussed in the context of LC change. Hartley, A.J., MacBean, N., Georgievski, G., Bontemps, S.: Uncertainty in plant functional type distributions and its impact on land surface models (in review with Remote Sensing of Environment Special Issue)

Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation

DOE PAGES

Luo, Xiangyu; Li, Hong -Yi; Leung, L. Ruby; ...

2017-03-23

In the Amazon Basin, floodplain inundation is a key component of surface water dynamics and plays an important role in water, energy and carbon cycles. The Model for Scale Adaptive River Transport (MOSART) was extended with a macroscale inundation scheme for representing floodplain inundation. The extended model, named MOSART-Inundation, was used to simulate surface hydrology of the entire Amazon Basin. Previous hydrologic modeling studies in the Amazon Basin identified and addressed a few challenges in simulating surface hydrology of this basin, including uncertainties of floodplain topography and channel geometry, and the representation of river flow in reaches with mild slopes.more » This study further addressed four aspects of these challenges. First, the spatial variability of vegetation-caused biases embedded in the HydroSHEDS digital elevation model (DEM) data was explicitly addressed. A vegetation height map of about 1 km resolution and a land cover dataset of about 90 m resolution were used in a DEM correction procedure that resulted in an average elevation reduction of 13.2 m for the entire basin and led to evident changes in the floodplain topography. Second, basin-wide empirical formulae for channel cross-sectional dimensions were refined for various subregions to improve the representation of spatial variability in channel geometry. Third, the channel Manning roughness coefficient was allowed to vary with the channel depth, as the effect of riverbed resistance on river flow generally declines with increasing river size. Lastly, backwater effects were accounted for to better represent river flow in mild-slope reaches. The model was evaluated against in situ streamflow records and remotely sensed Envisat altimetry data and Global Inundation Extent from Multi-Satellites (GIEMS) inundation data. In a sensitivity study, seven simulations were compared to evaluate the impacts of the five modeling aspects addressed in this study. The comparisons showed that representing floodplain inundation could significantly improve the simulated streamflow and river stages. Refining floodplain topography, channel geometry and Manning roughness coefficients, as well as accounting for backwater effects had notable impacts on the simulated surface water dynamics in the Amazon Basin. As a result, the understanding obtained in this study could be helpful in improving modeling of surface hydrology in basins with evident inundation, especially at regional to continental scales.« less

Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Xiangyu; Li, Hong -Yi; Leung, L. Ruby

In the Amazon Basin, floodplain inundation is a key component of surface water dynamics and plays an important role in water, energy and carbon cycles. The Model for Scale Adaptive River Transport (MOSART) was extended with a macroscale inundation scheme for representing floodplain inundation. The extended model, named MOSART-Inundation, was used to simulate surface hydrology of the entire Amazon Basin. Previous hydrologic modeling studies in the Amazon Basin identified and addressed a few challenges in simulating surface hydrology of this basin, including uncertainties of floodplain topography and channel geometry, and the representation of river flow in reaches with mild slopes.more » This study further addressed four aspects of these challenges. First, the spatial variability of vegetation-caused biases embedded in the HydroSHEDS digital elevation model (DEM) data was explicitly addressed. A vegetation height map of about 1 km resolution and a land cover dataset of about 90 m resolution were used in a DEM correction procedure that resulted in an average elevation reduction of 13.2 m for the entire basin and led to evident changes in the floodplain topography. Second, basin-wide empirical formulae for channel cross-sectional dimensions were refined for various subregions to improve the representation of spatial variability in channel geometry. Third, the channel Manning roughness coefficient was allowed to vary with the channel depth, as the effect of riverbed resistance on river flow generally declines with increasing river size. Lastly, backwater effects were accounted for to better represent river flow in mild-slope reaches. The model was evaluated against in situ streamflow records and remotely sensed Envisat altimetry data and Global Inundation Extent from Multi-Satellites (GIEMS) inundation data. In a sensitivity study, seven simulations were compared to evaluate the impacts of the five modeling aspects addressed in this study. The comparisons showed that representing floodplain inundation could significantly improve the simulated streamflow and river stages. Refining floodplain topography, channel geometry and Manning roughness coefficients, as well as accounting for backwater effects had notable impacts on the simulated surface water dynamics in the Amazon Basin. As a result, the understanding obtained in this study could be helpful in improving modeling of surface hydrology in basins with evident inundation, especially at regional to continental scales.« less

Model Meets Data: Challenges and Opportunities to Implement Land Management in Earth System Models

NASA Astrophysics Data System (ADS)

Pongratz, J.; Dolman, A. J.; Don, A.; Erb, K. H.; Fuchs, R.; Herold, M.; Jones, C.; Luyssaert, S.; Kuemmerle, T.; Meyfroidt, P.

2016-12-01

Land-based demand for food and fibre is projected to increase in the future. In light of global sustainability challenges only part of this increase will be met by expansion of land use into relatively untouched regions. Additional demand will have to be fulfilled by intensification and other adjustments in management of land that already is under agricultural and forestry use. Such land management today occurs on about half of the ice-free land surface, as compared to only about one quarter that has undergone a change in land cover. As the number of studies revealing substantial biogeophysical and biogeochemical effects of land management is increasing, moving beyond land cover change towards including land management has become a key focus for Earth system modeling. However, a basis for prioritizing land management activities for implementation in models is lacking. We lay this basis for prioritization in a collaborative project across the disciplines of Earth system modeling, land system science, and Earth observation. We first assess the status and plans of implementing land management in Earth system and dynamic global vegetation models. A clear trend towards higher complexity of land use representation is visible. We then assess five criteria for prioritizing the implementation of land management activities: (1) spatial extent, (2) evidence for substantial effects on the Earth system, (3) process understanding, (4) possibility to link the management activity to existing concepts and structures of models, (5) availability of data required as model input. While the first three criteria have been assessed by an earlier study for ten common management activities, we review strategies for implementation in models and the availability of required datasets. We can thus evaluate the management activities for their performance in terms of importance for the Earth system, possibility of technical implementation in models, and data availability. This synthesis reveals some "low-hanging" fruits for model implementation, but also challenges for the assessment of land management effects by modeling. The identified gaps can guide prioritization within the data community from the Earth system and Earth system modeling perspective.

Model meets data: Challenges and opportunities to implement land management in Earth System Models

NASA Astrophysics Data System (ADS)

Pongratz, Julia; Dolman, Han; Don, Axel; Erb, Karl-Heinz; Fuchs, Richard; Herold, Martin; Jones, Chris; Luyssaert, Sebastiaan; Kuemmerle, Tobias; Meyfroidt, Patrick; Naudts, Kim

2017-04-01

Land-based demand for food and fibre is projected to increase in the future. In light of global sustainability challenges only part of this increase will be met by expansion of land use into relatively untouched regions. Additional demand will have to be fulfilled by intensification and other adjustments in management of land that already is under agricultural and forestry use. Such land management today occurs on about half of the ice-free land surface, as compared to only about one quarter that has undergone a change in land cover. As the number of studies revealing substantial biogeophysical and biogeochemical effects of land management is increasing, moving beyond land cover change towards including land management has become a key focus for Earth system modeling. However, a basis for prioritizing land management activities for implementation in models is lacking. We lay this basis for prioritization in a collaborative project across the disciplines of Earth system modeling, land system science, and Earth observation. We first assess the status and plans of implementing land management in Earth system and dynamic global vegetation models. A clear trend towards higher complexity of land use representation is visible. We then assess five criteria for prioritizing the implementation of land management activities: (1) spatial extent, (2) evidence for substantial effects on the Earth system, (3) process understanding, (4) possibility to link the management activity to existing concepts and structures of models, (5) availability of data required as model input. While the first three criteria have been assessed by an earlier study for ten common management activities, we review strategies for implementation in models and the availability of required datasets. We can thus evaluate the management activities for their performance in terms of importance for the Earth system, possibility of technical implementation in models, and data availability. This synthesis reveals some "low-hanging" fruits for model implementation, but also challenges for the assessment of land management effects by modeling. The identified gaps can guide prioritization within the data community from the Earth system and Earth system modeling perspective.

Effects of Explicit Urban-Canopy Representation on Local Circulations Above a Tropical Mega-City

NASA Astrophysics Data System (ADS)

Flores Rojas, José L.; Pereira Filho, Augusto J.; Karam, Hugo A.; Vemado, Felipe; Masson, Valéry

2018-01-01

The Advanced Regional Prediction System (ARPS) is coupled with the tropical town energy budget (tTEB) scheme to analyze the effects of the urban canopy circulation over the metropolitan area of São Paulo and its interactions with the sea breeze and mountain-valley circulation in the eastern state of São Paulo, Brazil. Two experiments are carried out for the typical sea-breeze event occurring on 22 August 2014 under weak synoptic forcing and clear-sky conditions: (a) a control run with the default semi-desert surface parametrization and; (b) a tTEB run for the urban canopy of São Paulo. A realistic land-use database over the south-eastern domain of Brazil is used in the downscaling simulation to a horizontal grid resolution of 3 km. Our results indicate that ARPS effectively simulates features of the nighttime and early morning land-breeze circulation, which is affected by the surrounding hills and the nocturnal heat island of São Paulo. By early afternoon, the south-eastern sea-breeze circulation moves inland perpendicular to the upslope of the Serra do Mar scarp, which generates a line of moisture convergence and updrafts further inland. Later, the convergence line reaches São Paulo and interacts with the circulation arising from the urban heat island (UHI), which increases the moisture convergence and strength of updrafts. The surface energy balance indicates that the UHI is caused by large sensible heat storage within the urban canopy during the day, which is later released in the afternoon and at night. The simulations are verified with available radiosonde and surface weather station data, land-surface-temperature estimates from the moderate resolution imaging spectroradiometer, as well as the National Center for Atmospheric Research reanalysis databases. The three-dimensional geometry of the urban canyons within the tTEB scheme consistently improves the thermodynamically-induced circulation over São Paulo.

Vector-Based Ground Surface and Object Representation Using Cameras

DTIC Science & Technology

2009-12-01

representations and it is a digital data structure used for the representation of a ground surface in geographical information systems ( GIS ). Figure...Vision API library, and the OpenCV library. Also, the Posix thread library was utilized to quickly capture the source images from cameras. Both

The Goddard Cumulus Ensemble Model (GCE): Improvements and Applications for Studying Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, Stephen E.; Zeng, Xiping; Li, Xiaowen; Matsui, Toshi; Mohr, Karen; Posselt, Derek; Chern, Jiundar; Peters-Lidard, Christa; Norris, Peter M.;

Investigatigating inter-/intra-annual variability of surface hydrology at northern high latitude from spaceborne measurements

NASA Astrophysics Data System (ADS)

Kang, K.; Duguay, C. R.

2014-12-01

Lakes encompass a large part of the surface cover in the northern boreal and tundra areas of northern Canada and are therefore a significant component of the terrestrial hydrological system. To understand the hydrologic cycle over subarctic and arctic landscapes, estimating surface parameters such as surface net radiation, soil moisture, and surface albedo is important. Although ground-based field measurements provide a good temporal resolution, these data provide a limited spatial representation and are often restricted to the summer period (from June to August), and few surface-based stations are located in high-latitude regions. In this respect, spaceborne remote sensing provides the means to monitor surface hydrology and to estimate components of the surface energy balance with reasonable spatial and temporal resolutions required for hydrological investigations, as well as for providing more spatially representative lake-relevant information than available from in situ measurements. The primary objective of this study is to quantify the sources of temporal and spatial variability in surface albedo over subarctic wetland from satellite derived albedo measurements in the Hudson Bay Lowlands near Churchill, Manitoba. The spatial variability in albedo within each land-cover type is investigated through optical satellite imagery from Landsat-5 Thematic Mapper, Landsat-7 Enhanced Thematic Mapper Plus, and Landsat-8 Operational Land Imager obtained in different seasons from spring into fall (April and October) over a 30-year period (1984-2013). These data allowed for an examination of the spatial variability of surface albedo under relatively dry and wet summer conditions (i.e. 1984, 1998 versus 1991, 2005). A detailed analysis of Landsat-derived surface albedo (ranging from 0.09 to 0.15) conducted in the Churchill region for August is inversely related to surface water fraction calculated from Landsat images. Preliminary analysis of surface albedo observed between July and August are 0.10 to 0.15, and vary due to differences in meteorological parameters such as rainfall, surface moisture and surface air temperature. Overall, spaceborne optical data are an invaluable source for investigating changes and variability in surface albedo in relation to surface hydrology over subarctic regions.

Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau

USGS Publications Warehouse

Yi, S.; Li, N.; Xiang, B.; Wang, X.; Ye, B.; McGuire, A.D.

2013-01-01

Soil surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the Qinghai-Tibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.

Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau

NASA Astrophysics Data System (ADS)

Yi, S.; Li, N.; Xiang, B.; Wang, X.; Ye, B.; McGuire, A. D.

2013-07-01

surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the Qinghai-Tibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.

RESEARCH: Theory in Practice: Applying Participatory Democracy Theory to Public Land Planning

PubMed

Moote; Mcclaran; Chickering

1997-11-01

/ Application of participatory democracy theory to public participation in public land planning, while widely advocated, has not been closely examined. A case study is used here to explicate the application of participatory democracy concepts to public participation in public land planning and decision making. In this case, a Bureau of Land Management resource area manager decided to make a significant shift from the traditional public involvement process to a more participatory method-coordinated resource management (CRM). This case was assessed using document analysis, direct observation of CRM meetings, questionnaires, and interviews of key participants. These sources were used to examine the CRM case using participatory democracy concepts of efficacy, access and representation, continuous participation throughout planning, information exchange and learning, and decision-making authority. The case study suggests that social deliberation in itself does not ensure successful collaboration and that establishing rules of operation and decision making within the group is critical. Furthermore, conflicts between the concept of shared decision-making authority and the public land management agencies' accountability to Congress, the President, and the courts need further consideration.KEY WORDS: Case study; Coordinated resource management; Public participation; Administrative discretion; Representation; Consensus; Collaboration

The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0

NASA Astrophysics Data System (ADS)

Valdes, Paul J.; Armstrong, Edward; Badger, Marcus P. S.; Bradshaw, Catherine D.; Bragg, Fran; Crucifix, Michel; Davies-Barnard, Taraka; Day, Jonathan J.; Farnsworth, Alex; Gordon, Chris; Hopcroft, Peter O.; Kennedy, Alan T.; Lord, Natalie S.; Lunt, Dan J.; Marzocchi, Alice; Parry, Louise M.; Pope, Vicky; Roberts, William H. G.; Stone, Emma J.; Tourte, Gregory J. L.; Williams, Jonny H. T.

2017-10-01

Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing with observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.

Digital representation of oil and natural gas well pad scars in southwest Wyoming

USGS Publications Warehouse

Garman, Steven L.; McBeth, Jamie L.

2014-01-01

The recent proliferation of oil and natural gas energy development in southwest Wyoming has stimulated the need to understand wildlife responses to this development. Central to many wildlife assessments is the use of geospatial methods that rely on digital representation of energy infrastructure. Surface disturbance of the well pad scars associated with oil and natural gas extraction has been an important but unavailable infrastructure layer. To provide a digital baseline of this surface disturbance, we extracted visible oil and gas well pad scars from 1-meter National Agriculture Imagery Program imagery (NAIP) acquired in 2009 for a 7.7 million-hectare region of southwest Wyoming. Scars include the pad area where wellheads, pumps, and storage facilities reside, and the surrounding area that was scraped and denuded of vegetation during the establishment of the pad. Scars containing tanks, compressors, and the storage of oil and gas related equipment, and produced-water ponds were also collected on occasion. Our extraction method was a two-step process starting with automated extraction followed by manual inspection and clean up. We used available well-point information to guide manual clean up and to derive estimates of year of origin and duration of activity on a pad scar. We also derived estimates of the proportion of non-vegetated area on a scar using a Normalized Difference Vegetation Index derived using 1-meter NAIP imagery. We extracted 16,973 pad scars of which 15,318 were oil and gas well pads. Digital representation of pad scars along with time-stamps of activity and estimates of non-vegetated area provides important baseline (circa 2009) data for assessments of wildlife responses, land-use trends, and disturbance-mediated pattern assessments.

Simulation of High-Latitude Hydrological Processes in the Torne-Kalix Basin: PILPS Phase 2(e). 3; Equivalent Model Representation and Sensitivity Experiments

NASA Technical Reports Server (NTRS)

Bowling, Laura C.; Lettenmaier, Dennis P.; Nijssen, Bart; Polcher, Jan; Koster, Randal D.; Lohmann, Dag; Houser, Paul R. (Technical Monitor)

2002-01-01

The Project for Intercomparison of Land Surface Parameterization Schemes (PILPS) Phase 2(e) showed that in cold regions the annual runoff production in Land Surface Schemes (LSSs) is closely related to the maximum snow accumulation, which in turn is controlled in large part by winter sublimation. To help further explain the relationship between snow cover, turbulent exchanges and runoff production, a simple equivalent model-(SEM) was devised to reproduce the seasonal and annual fluxes simulated by 13 LSSs that participated in PILPS Phase 2(e). The design of the SEM relates the annual partitioning of precipitation and energy in the LSSs to three primary parameters: snow albedo, effective aerodynamic resistance and evaporation efficiency. Isolation of each of the parameters showed that the annual runoff production was most sensitive to the aerodynamic resistance. The SEM was somewhat successful in reproducing the observed LSS response to a decrease in shortwave radiation and changes in wind speed forcings. SEM parameters derived from the reduced shortwave forcings suggested that increased winter stability suppressed turbulent heat fluxes over snow. Because winter sensible heat fluxes were largely negative, reductions in winter shortwave radiation imply an increase in annual average sensible heat.

Effect of mosaic representation of vegetation in land surface schemes on simulated energy and carbon balances

NASA Astrophysics Data System (ADS)

Li, R.; Arora, V. K.

2011-06-01

Energy and carbon balance implications of representing vegetation using a composite or mosaic approach in a land surface scheme are investigated. In the composite approach the attributes of different plant functional types (PFTs) present in a grid cell are aggregated in some fashion for energy and water balance calculations. The resulting physical environmental conditions (including net radiation, soil moisture and soil temperature) are common to all PFTs and affect their ecosystem processes. In the mosaic approach energy and water balance calculations are performed separately for each PFT tile using its own vegetation attributes, so each PFT "sees" different physical environmental conditions and its carbon balance evolves somewhat differently from that in the composite approach. Simulations are performed at selected boreal, temperate and tropical locations to illustrate the differences caused by using the composite versus the mosaic approaches of representing vegetation. Differences in grid averaged primary energy fluxes are generally less than 5 % between the two approaches. Grid-averaged carbon fluxes and pool sizes can, however, differ by as much as 46 %. Simulation results suggest that differences in carbon balance between the two approaches arise primarily through differences in net radiation which directly affects net primary productivity, and thus leaf area index and vegetation biomass.

Improving Land-Surface Model Hydrology: Is an Explicit Aquifer Model Better than a Deeper Soil Profile?

NASA Technical Reports Server (NTRS)

Gulden, L. E.; Rosero, E.; Yang, Z.-L.; Rodell, Matthew; Jackson, C. S.; Niu, G.-Y.; Yeh, P. J.-F.; Famiglietti, J. S.

2007-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the storage and movement of water (including soil moisture, snow, evaporation, and runoff) after it falls to the ground as precipitation. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy. Hence LSMs have been developed to integrate the available information, including satellite observations, using powerful computers, in order to track water storage and redistribution. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. Recently, the models have begun to simulate groundwater storage. In this paper, we compare several possible approaches, and examine the pitfalls associated with trying to estimate aquifer parameters (such as porosity) that are required by the models. We find that explicit representation of groundwater, as opposed to the addition of deeper soil layers, considerably decreases the sensitivity of modeled terrestrial water storage to aquifer parameter choices. We also show that approximate knowledge of parameter values is not sufficient to guarantee realistic model performance: because interaction among parameters is significant, they must be prescribed as a harmonious set.

Substantial impacts of landscape changes on summer climate with major regional differences: The case of China.

PubMed

Cao, Qian; Yu, Deyong; Georgescu, Matei; Wu, Jianguo

2018-06-01

China's rapid socioeconomic development during the past few decades has resulted in large-scale landscape changes across the country. However, the impacts of these land surface modifications on climate are yet to be adequately understood. Using a coupled process-based land-atmospheric model, therefore, we quantified the climatic effects of land cover and land management changes over mainland China from 2001 to 2010, via incorporation of real-time and high-quality satellite-derived landscape representation (i.e., vegetation fraction, leaf area index, and albedo) into numerical modeling. Our results show that differences in landscape patterns due to changes in land cover and land management have exerted a strong influence on summer climate in China. During 2001 and 2010, extensive cooling of up to 1.5°C was found in the Loess Plateau and 1.0°C in northeastern China. In contrast, regional-scale warming was detected in the Tibetan Plateau (0.3°C), Yunnan province (0.4°C), and rapidly expanding urban centers across China (as high as 2°C). Summer precipitation decreased in the northeastern region, with patchy reduction generally <1.8mm/day, but increased in the Loess Plateau, with local spikes up to 2.4mm/day. Our study highlights that human alterations of landscapes have had substantial impacts on summer climate over the entire mainland China, but these impacts varied greatly on the regional scale, including changes in opposite directions. Therefore, effective national-level policies and regional land management strategies for climate change mitigation and adaptation should take explicit account of the spatial heterogeneity of landscape-climate interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

Cloud Resolving Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2007-01-01

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with cloud-resolving models (CRMs). CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (with sizes ranging from about 2-200 km). CRMs also allow for explicit interaction between clouds, outgoing longwave (cooling) and incoming solar (heating) radiation, and ocean and land surface processes. Observations are required to initialize CRMs and to validate their results. This paper provides a brief discussion and review of the main characteristics of CRMs as well as some of their major applications. These include the use of CRMs to improve our understanding of: (1) convective organization, (2) cloud temperature and water vapor budgets, and convective momentum transport, (3) diurnal variation of precipitation processes, (4) radiative-convective quasi-equilibrium states, (5) cloud-chemistry interaction, (6) aerosol-precipitation interaction, and (7) improving moist processes in large-scale models. In addition, current and future developments and applications of CRMs will be presented.

Quantifying the effect of ecological restoration on soil erosion in China's Loess Plateau region: an application of the MMF approach.

PubMed

Li, Changbin; Qi, Jiaguo; Feng, Zhaodong; Yin, Runsheng; Guo, Biyun; Zhang, Feng; Zou, Songbing

2010-03-01

Land degradation due to erosion is one of the most serious environmental problems in China. To reduce land degradation, the government has taken a number of conservation and restoration measures, including the Sloping Land Conversion Program (SLCP), which was launched in 1999. A logical question is whether these measures have reduced soil erosion at the regional level. The objective of this article is to answer this question by assessing soil erosion dynamics in the Zuli River basin in the Loess Plateau of China from 1999 to 2006. The MMF (Morgan, Morgan and Finney) model was used to simulate changes in runoff and soil erosion over the period of time during which ecological restoration projects were implemented. Some model variables were derived from remotely sensed images to provide improved land surface representation. With an overall accuracy rate of 0.67, our simulations show that increased ground vegetation cover, especially in forestlands and grasslands, has reduced soil erosion by 38.8% on average from 1999 to 2006. During the same time period, however, the change in rainfall pattern has caused a 13.1% +/- 4.3% increase in soil erosion, resulting in a net 25.7% +/- 8.5% reduction in soil erosion. This suggests that China's various ecological restoration efforts have been effective in reducing soil loss.

Characterizing hydrological hazards and trends with the NASA South Asia Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Ghatak, D.; Zaitchik, B. F.; Limaye, A. S.; Searby, N. D.; Doorn, B.; Bolten, J. D.; Toll, D. L.; Lee, S.; Mourad, B.; Narula, K.; Nischal, S.; Iceland, C.; Bajracharya, B.; Kumar, S.; Shrestha, B. R.; Murthy, M.; Hain, C.; Anderson, M. C.

2015-12-01

South Asia faces severe challenges to meet the need of water for agricultural, domestic and industrial purposes while coping with the threats posed by climate and land use/cover changes on regional hydrology. South Asia is also characterized by extreme climate contrasts, remote and poorly-monitored headwaters regions, and large uncertainties in estimates of consumptive water withdrawals. Here, we present results from the South Asia Land Data Assimilation System (South Asia LDAS) that apply multiple simulations involving different combination of forcing datasets, land surface models, and satellite-derived parameter datasets to characterize the distributed water balance of the subcontinent. The South Asia LDAS ensemble of simulations provides a range of uncertainty associated with model products. The system includes customized irrigation schemes to capture water use and HYMAP streamflow routing for application to floods. This presentation focuses on two key application areas for South Asia LDAS: the representation of extreme floods in transboundary rivers, and the estimate of water use in irrigated agriculture. We show that South Asia LDAS captures important features of both phenomena, address opportunities and barriers for the use of South Asia LDAS in decision support, and review uncertainties and limitations.This work is being performed by an interdisciplinary team of scientists and decision makers, to ensure that the modeling system meets the needs of decision makers at national and regional levels.

Evaluation of the 7-km GEOS-5 Nature Run

NASA Technical Reports Server (NTRS)

Gelaro, Ronald; Putman, William M.; Pawson, Steven; Draper, Clara; Molod, Andrea; Norris, Peter M.; Ott, Lesley; Prive, Nikki; Reale, Oreste; Achuthavarier, Deepthi;

Using semi-variogram analysis for providing spatially distributed information on soil surface condition for land surface modeling

NASA Astrophysics Data System (ADS)

Croft, Holly; Anderson, Karen; Kuhn, Nikolaus J.

2010-05-01

The ability to quantitatively and spatially assess soil surface roughness is important in geomorphology and land degradation studies. Soils can experience rapid structural degradation in response to land cover changes, resulting in increased susceptibility to erosion and a loss of Soil Organic Matter (SOM). Changes in soil surface condition can also alter sediment detachment, transport and deposition processes, infiltration rates and surface runoff characteristics. Deriving spatially distributed quantitative information on soil surface condition for inclusion in hydrological and soil erosion models is therefore paramount. However, due to the time and resources involved in using traditional field sampling techniques, there is a lack of spatially distributed information on soil surface condition. Laser techniques can provide data for a rapid three dimensional representation of the soil surface at a fine spatial resolution. This provides the ability to capture changes at the soil surface associated with aggregate breakdown, flow routing, erosion and sediment re-distribution. Semi-variogram analysis of the laser data can be used to represent spatial dependence within the dataset; providing information about the spatial character of soil surface structure. This experiment details the ability of semi-variogram analysis to spatially describe changes in soil surface condition. Soil for three soil types (silt, silt loam and silty clay) was sieved to produce aggregates between 1 mm and 16 mm in size and placed evenly in sample trays (25 x 20 x 2 cm). Soil samples for each soil type were exposed to five different durations of artificial rainfall, to produce progressively structurally degraded soil states. A calibrated laser profiling instrument was used to measure surface roughness over a central 10 x 10 cm plot of each soil state, at 2 mm sample spacing. The laser data were analysed within a geostatistical framework, where semi-variogram analysis quantitatively represented the change in soil surface structure during crusting. The laser data were also used to create digital surface models (DSM) of the soil states for visual comparison. This research has shown that aggregate breakdown and soil crusting can be shown quantitatively by a decrease in sill variance (silt soil: 11.67 (control) to 1.08 (after 90 mins rainfall)). Features present within semi-variograms were spatially linked to features at the soil surface, such as soil cracks, tillage lines and areas of deposition. Directional semi-variograms were used to provide a spatially orientated component, where the directional sill variance associated with a soil crack was shown to increase from 7.95 to 19.33. Periodicity within semi-variogram was also shown to quantify the spatial scale of soil cracking networks and potentially surface flowpaths; an average distance between soil cracks of 37 mm closely corresponded to the distance of 38 mm shown in the semi-variogram. The results provide a strong basis for the future retrieval of spatio-temporal variations in soil surface condition. Furthermore, the presence of process-based information on hydrological pathways within semi-variograms may work towards an inclusion of geostatisically-derived information in land surface models and the understanding of complex surface processes at different spatial scales.

The impact of changing the land surface scheme in ACCESS(v1.0/1.1) on the surface climatology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kowalczyk, Eva A.; Stevens, Lauren E.; Law, Rachel M.

The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present-day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. The cooler NH summer temperatures in canopy-covered regions aremore » more consistent with observations and are attributed to two factors. Firstly, CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below; this placement of the canopy above the ground eliminates the need for a separate bare ground tile in canopy-covered areas. Secondly, CABLE simulates larger evapotranspiration fluxes and a slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow-covered areas. In particular, prognostic snow density increases through the winter and lowers the diurnally resolved snow albedo; variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses; liquid precipitation freezing within the snowpack delays the building of the snowpack in autumn and accelerates snow melting in spring. Altogether we find that the ACCESS simulation of surface air temperature benefits from the specific representation of the turbulent transport within and just above the canopy in the roughness sublayer as well as the more complex snow scheme in CABLE relative to MOSES.« less

The impact of changing the land surface scheme in ACCESS(v1.0/1.1) on the surface climatology

DOE PAGES

Kowalczyk, Eva A.; Stevens, Lauren E.; Law, Rachel M.; ...

2016-08-23

The Community Atmosphere Biosphere Land Exchange (CABLE) model has been coupled to the UK Met Office Unified Model (UM) within the existing framework of the Australian Community Climate and Earth System Simulator (ACCESS), replacing the Met Office Surface Exchange Scheme (MOSES). Here we investigate how features of the CABLE model impact on present-day surface climate using ACCESS atmosphere-only simulations. The main differences attributed to CABLE include a warmer winter and a cooler summer in the Northern Hemisphere (NH), earlier NH spring runoff from snowmelt, and smaller seasonal and diurnal temperature ranges. The cooler NH summer temperatures in canopy-covered regions aremore » more consistent with observations and are attributed to two factors. Firstly, CABLE accounts for aerodynamic and radiative interactions between the canopy and the ground below; this placement of the canopy above the ground eliminates the need for a separate bare ground tile in canopy-covered areas. Secondly, CABLE simulates larger evapotranspiration fluxes and a slightly larger daytime cloud cover fraction. Warmer NH winter temperatures result from the parameterization of cold climate processes in CABLE in snow-covered areas. In particular, prognostic snow density increases through the winter and lowers the diurnally resolved snow albedo; variable snow thermal conductivity prevents early winter heat loss but allows more heat to enter the ground as the snow season progresses; liquid precipitation freezing within the snowpack delays the building of the snowpack in autumn and accelerates snow melting in spring. Altogether we find that the ACCESS simulation of surface air temperature benefits from the specific representation of the turbulent transport within and just above the canopy in the roughness sublayer as well as the more complex snow scheme in CABLE relative to MOSES.« less

Influence of Aerosols And Surface Reflectance On NO2 Retrieval Over China From 2005 to 2015

NASA Astrophysics Data System (ADS)

Liu, M.; Lin, J.

2016-12-01

Satellite observation is a powerful way to analysis annual and seasonal variations of nitrogen dioxide (NO2). However, much retrieval of vertical column densities (VCDs) of normally do not explicitly account for aerosol optical effects and surface reflectance anisotropy that vary with space and time. In traditional retrieval, aerosols' effects are often considered as cloud. However, China has complicated aerosols type and aerosol loading. Their optical properties may be very different from the cloud. Furthermore, China has undergone big changes in land use type in recent 10 years. Traditional climatology surface reflectance data may not have representation. In order to study spatial-temporal variation of and influences of these two factors on variations and trends, we use an improved retrieval method of VCDs over China, called the POMINO, based on measurements from the Ozone Monitoring Instrument (OMI), and we compare the results of without aerosol, without surface reflectance treatments and without both to the original POMINO product from 2005 to 2015. Furthermore, we will study correspondent spatial-temporal variations of aerosols, represented by MODIS aerosol optical depth (AOD) data and CALIOP extinction data; surface reflectance, represented by MODIS bidirectional reflectance distribution function (BRDF) data.

The Community Climate System Model Version 4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gent, Peter R.; Danabasoglu, Gokhan; Donner, Leo J.

The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all the CCSM components, and documents fully coupled pre-industrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1{sup o} results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4{sup o} resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in the CCSM4 producing El Nino/Southern Oscillation variability with a much more realistic frequency distribution than themore » CCSM3, although the amplitude is too large compared to observations. They also improve the representation of the Madden-Julian Oscillation, and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the deep ocean density structure, especially in the North Atlantic. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than the CCSM3, and the Arctic sea ice concentration is improved in the CCSM4. An ensemble of 20th century simulations runs produce an excellent match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally-averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4 C. This is consistent with the fact that the CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of short-wave and long-wave cloud forcings.« less

Distributed HUC-based modeling with SUMMA for ensemble streamflow forecasting over large regional domains.

NASA Astrophysics Data System (ADS)

Saharia, M.; Wood, A.; Clark, M. P.; Bennett, A.; Nijssen, B.; Clark, E.; Newman, A. J.

2017-12-01

Most operational streamflow forecasting systems rely on a forecaster-in-the-loop approach in which some parts of the forecast workflow require an experienced human forecaster. But this approach faces challenges surrounding process reproducibility, hindcasting capability, and extension to large domains. The operational hydrologic community is increasingly moving towards `over-the-loop' (completely automated) large-domain simulations yet recent developments indicate a widespread lack of community knowledge about the strengths and weaknesses of such systems for forecasting. A realistic representation of land surface hydrologic processes is a critical element for improving forecasts, but often comes at the substantial cost of forecast system agility and efficiency. While popular grid-based models support the distributed representation of land surface processes, intermediate-scale Hydrologic Unit Code (HUC)-based modeling could provide a more efficient and process-aligned spatial discretization, reducing the need for tradeoffs between model complexity and critical forecasting requirements such as ensemble methods and comprehensive model calibration. The National Center for Atmospheric Research is collaborating with the University of Washington, the Bureau of Reclamation and the USACE to implement, assess, and demonstrate real-time, over-the-loop distributed streamflow forecasting for several large western US river basins and regions. In this presentation, we present early results from short to medium range hydrologic and streamflow forecasts for the Pacific Northwest (PNW). We employ a real-time 1/16th degree daily ensemble model forcings as well as downscaled Global Ensemble Forecasting System (GEFS) meteorological forecasts. These datasets drive an intermediate-scale configuration of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) model, which represents the PNW using over 11,700 HUCs. The system produces not only streamflow forecasts (using the MizuRoute channel routing tool) but also distributed model states such as soil moisture and snow water equivalent. We also describe challenges in distributed model-based forecasting, including the application and early results of real-time hydrologic data assimilation.

Forest management in Earth system modelling: a vertically discretised canopy description for ORCHIDEE and the modifications to the energy, water and carbon fluxes

NASA Astrophysics Data System (ADS)

Naudts, Kim; Ryder, James; McGrath, Matthew J.; Otto, Juliane; Chen, Yiying; Valade, Aude; Bellasen, Valentin; Ghattas, Josefine; Haverd, Vanessa; MacBean, Natasha; Maignan, Fabienne; Peylin, Philippe; Pinty, Bernard; Solyga, Didier; Vuichard, Nicolas; Luyssaert, Sebastiaan

2015-04-01

Since 70% of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land surface models used in Earth system models, and therefore none of today's predictions of future climate, account for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrizing a version of the land surface model ORCHIDEE to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new model called ORCHIDEE-CAN and the standard version of ORCHIDEE are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes towards a better process representation occurred for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrization was revisited after introducing twelve new parameter sets that represent specific tree species or genera rather than a group of unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, GPP, albedo and evapotranspiration over Europe. For all tested variables ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92% chance to reproduce the spatial and temporal variability of the validation data.

A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes

NASA Astrophysics Data System (ADS)

Naudts, K.; Ryder, J.; McGrath, M. J.; Otto, J.; Chen, Y.; Valade, A.; Bellasen, V.; Berhongaray, G.; Bönisch, G.; Campioli, M.; Ghattas, J.; De Groote, T.; Haverd, V.; Kattge, J.; MacBean, N.; Maignan, F.; Merilä, P.; Penuelas, J.; Peylin, P.; Pinty, B.; Pretzsch, H.; Schulze, E. D.; Solyga, D.; Vuichard, N.; Yan, Y.; Luyssaert, S.

2015-07-01

Since 70 % of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land-surface models used in Earth system models, and therefore none of today's predictions of future climate, accounts for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrising a version of the ORCHIDEE land-surface model to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes were introduced towards a better process representation for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrisation was revisited after introducing 12 new parameter sets that represent specific tree species or genera rather than a group of often distantly related or even unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, gross primary production (GPP), albedo and evapotranspiration over Europe. For all tested variables, ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92 % chance to reproduce the spatial and temporal variability of the validation data.

L-band microwave remote sensing and land data assimilation improve the representation of pre-storm soil moisture conditions for hydrologic forecasting

USDA-ARS?s Scientific Manuscript database

Recent advances in remote sensing and land data assimilation purport to improve the quality of antecedent soil moisture information available for operational hydrologic forecasting. We objectively validate this claim by calculating the strength of the relationship between storm-scale runoff ratio (i...

Evaluating the Community Land Model (CLM4.5) at a coniferous forest site in northwestern United States using flux and carbon-isotope measurements

Treesearch

Henrique F. Duarte; Brett M. Raczka; Daniel M. Ricciuto; John C. Lin; Charles D. Koven; Peter E. Thornton; David R. Bowling; Chun-Ta Lai; Kenneth J. Bible; James R. Ehleringer

2017-01-01

Droughts in the western United States are expected to intensify with climate change. Thus, an adequate representation of ecosystem response to water stress in land models is critical for predicting carbon dynamics. The goal of this study was to evaluate the performance of the Community Land Model (CLM) version 4.5 against observations at an old-growth coniferous forest...

Land cover characterization and land surface parameterization research

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Parton, William J.

1997-01-01

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Application and Evaluation of MODIS LAI, FPAR, and Albedo ...

EPA Pesticide Factsheets

MODIS vegetation and albedo products provide a more realistic representation of surface conditions for input to the WRF/CMAQ modeling system. However, the initial evaluation of ingesting MODIS data into the system showed mixed results, with increased bias and error for 2-m temperature and reduced bias and error for 2-m mixing ratio. Recently, the WRF/CMAQ land surface and boundary laywer processes have been updated. In this study, MODIS vegetation and albedo data are input to the updated WRF/CMAQ meteorology and air quality simulations for 2006 over a North American (NA) 12-km domain. The evaluation of the simulation results shows that the updated WRF/CMAQ system improves 2-m temperature estimates over the pre-update base modeling system estimates. The MODIS vegetation input produces a realistic spring green-up that progresses through time from the south to north. Overall, MODIS input reduces 2-m mixing ration bias during the growing season. The NA west shows larger positive O3 bias during the growing season because of reduced gas phase deposition resulting from lower O3 deposition velocities driven by reduced vegetation cover. The O3 bias increase associated with the realistic vegetation representation indicates that further improvement may be needed in the WRF/CMAQ system. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment. AMAD’s rese

Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Goldberg, Richard; Chryssanthacopoulos, James

2014-01-01

The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

System for conversion between the boundary representation model and a constructive solid geometry model of an object

DOEpatents

Christensen, Noel C.; Emery, James D.; Smith, Maurice L.

1988-04-05

A system converts from the boundary representation of an object to the constructive solid geometry representation thereof. The system converts the boundary representation of the object into elemental atomic geometrical units or I-bodies which are in the shape of stock primitives or regularized intersections of stock primitives. These elemental atomic geometrical units are then represented in symbolic form. The symbolic representations of the elemental atomic geometrical units are then assembled heuristically to form a constructive solid geometry representation of the object usable for manufacturing thereof. Artificial intelligence is used to determine the best constructive solid geometry representation from the boundary representation of the object. Heuristic criteria are adapted to the manufacturing environment for which the device is to be utilized. The surface finish, tolerance, and other information associated with each surface of the boundary representation of the object are mapped onto the constructive solid geometry representation of the object to produce an enhanced solid geometry representation, particularly useful for computer-aided manufacture of the object.

Calculating and controlling the error of discrete representations of Pareto surfaces in convex multi-criteria optimization.

PubMed

Craft, David

2010-10-01

A discrete set of points and their convex combinations can serve as a sparse representation of the Pareto surface in multiple objective convex optimization. We develop a method to evaluate the quality of such a representation, and show by example that in multiple objective radiotherapy planning, the number of Pareto optimal solutions needed to represent Pareto surfaces of up to five dimensions grows at most linearly with the number of objectives. The method described is also applicable to the representation of convex sets. Copyright © 2009 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

The Effect of Landing Surface on the Plantar Kinetics of Chinese Paratroopers Using Half-Squat Landing

PubMed Central

Li, Yi; Wu, Ji; Zheng, Chao; Huang, Rong Rong; Na, Yuhong; Yang, Fan; Wang, Zengshun; Wu, Di

2013-01-01

The objective of the study was to determine the effect of landing surface on plantar kinetics during a half-squat landing. Twenty male elite paratroopers with formal parachute landing training and over 2 years of parachute jumping experience were recruited. The subjects wore parachuting boots in which pressure sensing insoles were placed. Each subject was instructed to jump off a platform with a height of 60 cm, and land on either a hard or soft surface in a half-squat posture. Outcome measures were maximal plantar pressure, time to maximal plantar pressure (T-MPP), and pressure-time integral (PTI) upon landing on 10 plantar regions. Compared to a soft surface, hard surface produced higher maximal plantar pressure in the 1st to 4th metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5th metatarsal region. Shorter T- MPP was found during hard surface landing in the 1st and 2nd metatarsal and medial rear foot. Landing on a hard surface landing resulted in a lower PTI than a soft surface in the 1stphalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the1st to 4thmetatarsal region for hard surface landing, and the 1stphalangeal and 5thmetatarsal region for soft surface landing. Key Points Understanding plantar kinetics during the half-squat landing used by Chinese paratroopers can assist in the design of protective footwear. Compared to landing on a soft surface, a hard surface produced higher maximal plantar pressure in the 1st to 4th metatarsal and mid-foot regions, but lower maximal plantar pressure in the 5th metatarsal region. A shorter time to maximal plantar pressure was found during a hard surface landing in the 1st and 2nd metatarsals and medial rear foot. Landing on a hard surface resulted in a lower pressure-time integral than landing on a soft surface in the 1st phalangeal region. For Chinese paratroopers, specific foot prosthesis should be designed to protect the 1st to 4th metatarsal region for a hard surface landing, and the 1st phalangeal and 5th metatarsal region for a soft surface landing. PMID:24149145

Analysis of relationships between land surface temperature and land use changes in the Yellow River Delta

NASA Astrophysics Data System (ADS)

Ning, Jicai; Gao, Zhiqiang; Meng, Ran; Xu, Fuxiang; Gao, Meng

2018-06-01

This study analyzed land use and land cover changes and their impact on land surface temperature using Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager and Thermal Infrared Sensor imagery of the Yellow River Delta. Six Landsat images comprising two time series were used to calculate the land surface temperature and correlated vegetation indices. The Yellow River Delta area has expanded substantially because of the deposited sediment carried from upstream reaches of the river. Between 1986 and 2015, approximately 35% of the land use area of the Yellow River Delta has been transformed into salterns and aquaculture ponds. Overall, land use conversion has occurred primarily from poorly utilized land into highly utilized land. To analyze the variation of land surface temperature, a mono-window algorithm was applied to retrieve the regional land surface temperature. The results showed bilinear correlation between land surface temperature and the vegetation indices (i.e., Normalized Difference Vegetation Index, Adjusted-Normalized Vegetation Index, Soil-Adjusted Vegetation Index, and Modified Soil-Adjusted Vegetation Index). Generally, values of the vegetation indices greater than the inflection point mean the land surface temperature and the vegetation indices are correlated negatively, and vice versa. Land surface temperature in coastal areas is affected considerably by local seawater temperature and weather conditions.

Revising Hydrology of a Land Surface Model

NASA Astrophysics Data System (ADS)

Le Vine, Nataliya; Butler, Adrian; McIntyre, Neil; Jackson, Christopher

2015-04-01

Land Surface Models (LSMs) are key elements in guiding adaptation to the changing water cycle and the starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, before this potential is realised, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. An important limitation is the simplistic or non-existent representation of the deep subsurface in LSMs; and another is the lack of connection of LSM parameterisations to relevant hydrological information. In this context, the paper uses a case study of the JULES (Joint UK Land Environmental Simulator) LSM applied to the Kennet region in Southern England. The paper explores the assumptions behind JULES hydrology, adapts the model structure and optimises the coupling with the ZOOMQ3D regional groundwater model. The analysis illustrates how three types of information can be used to improve the model's hydrology: a) observations, b) regionalized information, and c) information from an independent physics-based model. It is found that: 1) coupling to the groundwater model allows realistic simulation of streamflows; 2) a simple dynamic lower boundary improves upon JULES' stationary unit gradient condition; 3) a 1D vertical flow in the unsaturated zone is sufficient; however there is benefit in introducing a simple dual soil moisture retention curve; 4) regionalized information can be used to describe soil spatial heterogeneity. It is concluded that relatively simple refinements to the hydrology of JULES and its parameterisation method can provide a substantial step forward in realising its potential as a high-resolution multi-purpose model.

Synergy of the SimSphere land surface process model with ASTER imagery for the retrieval of spatially distributed estimates of surface turbulent heat fluxes and soil moisture content

NASA Astrophysics Data System (ADS)

Petropoulos, George; Wooster, Martin J.; Carlson, Toby N.; Drake, Nick

2010-05-01

Accurate information on spatially explicit distributed estimates of key land-atmosphere fluxes and related land surface parameters is of key importance in a range of disciplines including hydrology, meteorology, agriculture and ecology. Estimation of those parameters from remote sensing frequently employs the integration of such data with mathematical representations of the transfers of energy, mass and radiation between soil, vegetation and atmosphere continuum, known as Soil Vegetation Atmosphere Transfer (SVAT) models. The ability of one such inversion modelling scheme to resolve for key surface energy fluxes and of soil surface moisture content is examined here using data from a multispectral high spatial resolution imaging instrument, the Advanced Spaceborne Thermal Emission and Reflection Scanning Radiometer (ASTER) and SimSphere one-dimensional SVAT model. Accuracy of the investigated methodology, so-called as the "triangle" method, is verified using validated ground observations obtained from selected days collected from nine CARBOEUROPE IP sites representing a variety of climatic, topographic and environmental conditions. Subsequently, a new framework is suggested for the retrieval of two additional parameters by the investigated method, namely the Evaporative (EF) and the Non-Evaporative (NEF) Fractions. Results indicated a close agreement between the inverted surface fluxes and surface moisture availability maps as well as of the EF and NEF parameters with the observations both spatially and temporally with accuracies comparable to those obtained in similar experiments with high spatial resolution data. Inspection of the inverted surface fluxes maps regionally, showed an explainable distribution in the range of the inverted parameters in relation with the surface heterogeneity. Overall performance of the "triangle" inversion methodology was found to be affected predominantly by the SVAT model "correct" initialisation representative of the test site environment, most importantly the atmospheric conditions required in the SVAT model initial conditions. This study represents the first comprehensive evaluation of the performance of this particular methodological implementation at a European setting using the SimSphere SVAT with the ASTER data. The present work is also very timely in that, a variation of this specific inversion methodology has been proposed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2012. KEYWORDS: micrometeorology, surface heat fluxes, soil moisture content, ASTER, triangle method, SimSphere, CarboEurope IP

Relationships between aerodynamic roughness and land use and land cover in Baltimore, Maryland

USGS Publications Warehouse

Nicholas, F.W.; Lewis, J.E.

1980-01-01

Urbanization changes the radiative, thermal, hydrologic, and aerodynamic properties of the Earth's surface. Knowledge of these surface characteristics, therefore, is essential to urban climate analysis. Aerodynamic or surface roughness of urban areas is not well documented, however, because of practical constraints in measuring the wind profile in the presence of large buildings. Using an empirical method designed by Lettau, and an analysis of variance of surface roughness values calculated for 324 samples averaging 0.8 hectare (ha) of land use and land cover sample in Baltimore, Md., a strong statistical relation was found between aerodynamic roughness and urban land use and land cover types. Assessment of three land use and land cover systems indicates that some of these types have significantly different surface roughness characteristics. The tests further indicate that statistically significant differences exist in estimated surface roughness values when categories (classes) from different land use and land cover classification systems are used as surrogates. A Level III extension of the U.S. Geological Survey Level II land use and land cover classification system provided the most reliable results. An evaluation of the physical association between the aerodynamic properties of land use and land cover and the surface climate by numerical simulation of the surface energy balance indicates that changes in surface roughness within the range of values typical of the Level III categories induce important changes in the surface climate.

Satellite remotely-sensed land surface parameters and their climatic effects for three metropolitan regions

USGS Publications Warehouse

Xian, George

2008-01-01

By using both high-resolution orthoimagery and medium-resolution Landsat satellite imagery with other geospatial information, several land surface parameters including impervious surfaces and land surface temperatures for three geographically distinct urban areas in the United States – Seattle, Washington, Tampa Bay, Florida, and Las Vegas, Nevada, are obtained. Percent impervious surface is used to quantitatively define the spatial extent and development density of urban land use. Land surface temperatures were retrieved by using a single band algorithm that processes both thermal infrared satellite data and total atmospheric water vapor content. Land surface temperatures were analyzed for different land use and land cover categories in the three regions. The heterogeneity of urban land surface and associated spatial extents were shown to influence surface thermal conditions because of the removal of vegetative cover, the introduction of non-transpiring surfaces, and the reduction in evaporation over urban impervious surfaces. Fifty years of in situ climate data were integrated to assess regional climatic conditions. The spatial structure of surface heating influenced by landscape characteristics has a profound influence on regional climate conditions, especially through urban heat island effects.

Impact of high resolution land surface initialization in Indian summer monsoon simulation using a regional climate model

NASA Astrophysics Data System (ADS)

Unnikrishnan, C. K.; Rajeevan, M.; Rao, S. Vijaya Bhaskara

2016-06-01

The direct impact of high resolution land surface initialization on the forecast bias in a regional climate model in recent years over Indian summer monsoon region is investigated. Two sets of regional climate model simulations are performed, one with a coarse resolution land surface initial conditions and second one used a high resolution land surface data for initial condition. The results show that all monsoon years respond differently to the high resolution land surface initialization. The drought monsoon year 2009 and extended break periods were more sensitive to the high resolution land surface initialization. These results suggest that the drought monsoon year predictions can be improved with high resolution land surface initialization. Result also shows that there are differences in the response to the land surface initialization within the monsoon season. Case studies of heat wave and a monsoon depression simulation show that, the model biases were also improved with high resolution land surface initialization. These results show the need for a better land surface initialization strategy in high resolution regional models for monsoon forecasting.

Using reactive transport codes to provide mechanistic biogeochemistry representations in global land surface models: CLM-PFLOTRAN 1.0

DOE PAGES

Tang, G.; Yuan, F.; Bisht, G.; ...

2015-12-17

We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models; our goal is to facilitate testing of alternative models and incorporation of new understanding. A reaction network with the CLM-CN decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN code, coupled with the Community Land Model (CLM), and test at Arctic, temperate, and tropical sites. To make the reaction network designed for use in explicit time stepping in CLM compatible with the implicit time stepping used in PFLOTRAN,more » the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. To achieve accurate, efficient, and robust numerical solutions, care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60–100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10 −3 to 10 −9 mol m −3, which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %; computing time can be doubled for log transformation. Caution needs to be taken in choosing the appropriate scaling factor because a small value caused by a negative update to a small concentration may diminish the update and result in false convergence even with very tight relative update tolerance. As some biogeochemical processes (e.g., methane and nitrous oxide production and consumption) involve very low half saturation and threshold concentrations, this work provides insights for addressing nonphysical negativity issues and facilitates the representation of a mechanistic biogeochemical description in earth system models to reduce climate prediction uncertainty.« less

Modeling Surface Water Dynamics in the Amazon Basin Using Mosart-Inundation-v1.0: Impacts of Geomorphological Parameters and River Flow Representation

NASA Technical Reports Server (NTRS)

Luo, Xiangyu; Li, Hong-Yi; Leung, Ruby; Tesfa, Teklu K.; Getirana, Augusto; Papa, Fabrice; Hess, Laura L.

2017-01-01

Surface water dynamics play an important role in water, energy and carbon cycles of the Amazon Basin. A macro-scale inundation scheme was integrated with a surface-water transport model and the extended model was applied in this vast basin. We addressed the challenges of improving basin-wide geomorphological parameters and river flow representation for 15 large-scale applications. Vegetation-caused biases embedded in the HydroSHEDS DEM data were alleviated by using a vegetation height map of about 1-km resolution and a land cover dataset of about 90-m resolution. The average elevation deduction from the DEM correction was about 13.2 m for the entire basin. Basin-wide empirical formulae for channel cross-sectional geometry were adjusted based on local information for the major portion of the basin, which could significantly reduce the cross-sectional area for the channels of some subregions. The Manning roughness coefficient of the channel 20 varied with the channel depth to reflect the general rule that the relative importance of riverbed resistance in river flow declined with the increase of river size. The entire basin was discretized into 5395 subbasins (with an average area of 1091.7 km2), which were used as computation units. The model was driven by runoff estimates of 14 years (1994 2007) generated by the ISBA land surface model. The simulated results were evaluated against in situ streamflow records, and remotely sensed Envisat altimetry data and GIEMS inundation data. The hydrographs were reproduced fairly well for the majority of 25 13 major stream gauges. For the 11 subbasins containing or close to 11 of the 13 gauges, the timing of river stage fluctuations was captured; for most of the 11 subbasins, the magnitude of river stage fluctuations was represented well. The inundation estimates were comparable to the GIEMS observations. Sensitivity analyses demonstrated that refining floodplain topography, channel morphology and Manning roughness coefficients, as well as accounting for backwater effects could evidently affect local and upstream inundation, which consequently affected flood waves and inundation of the downstream 30 area. It was also shown that the river stage was sensitive to local channel morphology and Manning roughness coefficients, as well as backwater effects. The understanding obtained in this study could be helpful to improving modeling of surface hydrology in basins with evident inundation, especially at regional or larger scales.

Exploration Geophysics

ERIC Educational Resources Information Center

Espey, H. R.

1977-01-01

Describes geophysical techniques such as seismic, gravity, and magnetic surveys of offshare acreage, and land-data gathering from a three-dimensional representation made from closely spaced seismic lines. (MLH)

Surface similarity-based molecular query-retrieval

PubMed Central

Singh, Rahul

2007-01-01

Background Discerning the similarity between molecules is a challenging problem in drug discovery as well as in molecular biology. The importance of this problem is due to the fact that the biochemical characteristics of a molecule are closely related to its structure. Therefore molecular similarity is a key notion in investigations targeting exploration of molecular structural space, query-retrieval in molecular databases, and structure-activity modelling. Determining molecular similarity is related to the choice of molecular representation. Currently, representations with high descriptive power and physical relevance like 3D surface-based descriptors are available. Information from such representations is both surface-based and volumetric. However, most techniques for determining molecular similarity tend to focus on idealized 2D graph-based descriptors due to the complexity that accompanies reasoning with more elaborate representations. Results This paper addresses the problem of determining similarity when molecules are described using complex surface-based representations. It proposes an intrinsic, spherical representation that systematically maps points on a molecular surface to points on a standard coordinate system (a sphere). Molecular surface properties such as shape, field strengths, and effects due to field super-positioningcan then be captured as distributions on the surface of the sphere. Surface-based molecular similarity is subsequently determined by computing the similarity of the surface-property distributions using a novel formulation of histogram-intersection. The similarity formulation is not only sensitive to the 3D distribution of the surface properties, but is also highly efficient to compute. Conclusion The proposed method obviates the computationally expensive step of molecular pose-optimisation, can incorporate conformational variations, and facilitates highly efficient determination of similarity by directly comparing molecular surfaces and surface-based properties. Retrieval performance, applications in structure-activity modeling of complex biological properties, and comparisons with existing research and commercial methods demonstrate the validity and effectiveness of the approach. PMID:17634096

To Hell with the Wigs! Native American Representation and Resistance at the World's Columbian Exposition

ERIC Educational Resources Information Center

Rinehart, Melissa

2012-01-01

The World's Columbian Exposition of 1893, in celebration of the quadricentennial anniversary of Columbus's landing in the Americas, spread over six hundred acres of reclaimed marsh lands in Chicago's South Side. Fourteen great buildings and two hundred additional buildings stood on the fairgrounds, and if tourists had visited every exhibit, they…

Estimation of Surface Air Temperature from MODIS 1km Resolution Land Surface Temperature Over Northern China

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina

2010-01-01

Surface air temperature is a critical variable to describe the energy and water cycle of the Earth-atmosphere system and is a key input element for hydrology and land surface models. It is a very important variable in agricultural applications and climate change studies. This is a preliminary study to examine statistical relationships between ground meteorological station measured surface daily maximum/minimum air temperature and satellite remotely sensed land surface temperature from MODIS over the dry and semiarid regions of northern China. Studies were conducted for both MODIS-Terra and MODIS-Aqua by using year 2009 data. Results indicate that the relationships between surface air temperature and remotely sensed land surface temperature are statistically significant. The relationships between the maximum air temperature and daytime land surface temperature depends significantly on land surface types and vegetation index, but the minimum air temperature and nighttime land surface temperature has little dependence on the surface conditions. Based on linear regression relationship between surface air temperature and MODIS land surface temperature, surface maximum and minimum air temperatures are estimated from 1km MODIS land surface temperature under clear sky conditions. The statistical errors (sigma) of the estimated daily maximum (minimum) air temperature is about 3.8 C(3.7 C).

The Spatial Resolution in the Computer Modelling of Atmospheric Flow over a Double-Hill Forested Region

NASA Astrophysics Data System (ADS)

Palma, J. L.; Rodrigues, C. V.; Lopes, A. S.; Carneiro, A. M. C.; Coelho, R. P. C.; Gomes, V. C.

2017-12-01

With the ever increasing accuracy required from numerical weather forecasts, there is pressure to increase the resolution and fidelity employed in computational micro-scale flow models. However, numerical studies of complex terrain flows are fundamentally bound by the digital representation of the terrain and land cover. This work assess the impact of the surface description on micro-scale simulation results at a highly complex site in Perdigão, Portugal, characterized by a twin parallel ridge topography, densely forested areas and an operating wind turbine. Although Coriolis and stratification effects cannot be ignored, the study is done under neutrally stratified atmosphere and static inflow conditions. The understanding gained here will later carry over to WRF-coupled simulations, where those conditions do not apply and the flow physics is more accurately modelled. With access to very fine digital mappings (<1m horizontal resolution) of both topography and land cover (roughness and canopy cover, both obtained through aerial LIDAR scanning of the surface) the impact of each element of the surface description on simulation results can be individualized, in order to estimate the resolution required to satisfactorily resolve them. Starting from the bare topographic description, in its coursest form, these include: a) the surface roughness mapping, b) the operating wind turbine, c) the canopy cover, as either body forces or added surface roughness (akin to meso-scale modelling), d) high resolution topography and surface cover mapping. Each of these individually will have an impact near the surface, including the rotor swept area of modern wind turbines. Combined they will considerably change flow up to boundary layer heights. Sensitivity to these elements cannot be generalized and should be assessed case-by-case. This type of in-depth study, unfeasible using WRF-coupled simulations, should provide considerable insight when spatially allocating mesh resolution for accurate resolution of complex flows.

Evaluation of improved land use and canopy representation in ...

EPA Pesticide Factsheets

Biogenic volatile organic compounds (BVOC) participate in reactions that can lead to secondarily formed ozone and particulate matter (PM) impacting air quality and climate. BVOC emissions are important inputs to chemical transport models applied on local to global scales but considerable uncertainty remains in the representation of canopy parameterizations and emission algorithms from different vegetation species. The Biogenic Emission Inventory System (BEIS) has been used to support both scientific and regulatory model assessments for ozone and PM. Here we describe a new version of BEIS which includes updated input vegetation data and canopy model formulation for estimating leaf temperature and vegetation data on estimated BVOC. The Biogenic Emission Landuse Database (BELD) was revised to incorporate land use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) land product and 2006 National Land Cover Database (NLCD) land coverage. Vegetation species data are based on the US Forest Service (USFS) Forest Inventory and Analysis (FIA) version 5.1 for 2002–2013 and US Department of Agriculture (USDA) 2007 census of agriculture data. This update results in generally higher BVOC emissions throughout California compared with the previous version of BEIS. Baseline and updated BVOC emission estimates are used in Community Multiscale Air Quality (CMAQ) Model simulations with 4 km grid resolution and evaluated with measurements of isoprene and monoterp

Land Surface Microwave Emissivity Dynamics: Observations, Analysis and Modeling

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Kumar, Sujay; Ringerud, Sarah

2014-01-01

Land surface microwave emissivity affects remote sensing of both the atmosphere and the land surface. The dynamical behavior of microwave emissivity over a very diverse sample of land surface types is studied. With seven years of satellite measurements from AMSR-E, we identified various dynamical regimes of the land surface emission. In addition, we used two radiative transfer models (RTMs), the Community Radiative Transfer Model (CRTM) and the Community Microwave Emission Modeling Platform (CMEM), to simulate land surface emissivity dynamics. With both CRTM and CMEM coupled to NASA's Land Information System, global-scale land surface microwave emissivities were simulated for five years, and evaluated against AMSR-E observations. It is found that both models have successes and failures over various types of land surfaces. Among them, the desert shows the most consistent underestimates (by approx. 70-80%), due to limitations of the physical models used, and requires a revision in both systems. Other snow-free surface types exhibit various degrees of success and it is expected that parameter tuning can improve their performances.

Representation of regional urban development conditions using a watershed-based gradient study design

USGS Publications Warehouse

Terziotti, Silvia; McMahon, Gerard; Bell, Amanda H.

2012-01-01

As part of the U.S. Geological Survey National Water-Quality Assessment Program, the effects of urbanization on stream ecosystems (EUSE) have been intensively investigated in nine metropolitan areas in the United States, including Boston, Massachusetts; Atlanta, Georgia; Birmingham, Alabama; Raleigh, North Carolina; Salt Lake City, Utah; Denver, Colorado; Dallas–Fort Worth, Texas; Portland, Oregon; and Milwaukee–Green Bay, Wisconsin. Each of the EUSE study area watersheds was associated with one ecological region of the United States. This report evaluates whether each metropolitan area can be generalized across the ecological regions (ecoregions) within which the EUSE study watersheds are located. Seven characteristics of the EUSE watersheds that affect stream ecosystems were examined to determine the similarities in the same seven characteristics of the watersheds in the entire ecoregion. Land cover (percentage developed, forest and shrubland, and herbaceous and cultivated classes), average annual temperature, average annual precipitation, average surface elevation, and average percentage slope were selected as human-influenced, climate, and topography characteristics. Three findings emerged from this comparison that have implications for the use of EUSE data in models used to predict stream ecosystem condition. One is that the predominant or "background" land-cover type (either forested or agricultural land) in each ecoregion also is the predominant land-cover type within the associated EUSE study watersheds. The second finding is that in all EUSE study areas, the watersheds account for the range of developed land conditions that exist in the corresponding ecoregion watersheds. However, six of the nine EUSE study area watersheds have significantly different distributions of developed land from the ecoregion watersheds. Finally, in seven of the nine EUSE/ecoregion comparisons, the distributions of the values of climate variables in the EUSE watersheds are different from the distributions for watersheds in the corresponding ecoregions.

OCO-2 Column Carbon Dioxide and Biometric Data Jointly Constrain Parameterization and Projection of a Global Land Model

NASA Astrophysics Data System (ADS)

Shi, Z.; Crowell, S.; Luo, Y.; Rayner, P. J.; Moore, B., III

2015-12-01

Uncertainty in predicted carbon-climate feedback largely stems from poor parameterization of global land models. However, calibration of global land models with observations has been extremely challenging at least for two reasons. First we lack global data products from systematical measurements of land surface processes. Second, computational demand is insurmountable for estimation of model parameter due to complexity of global land models. In this project, we will use OCO-2 retrievals of dry air mole fraction XCO2 and solar induced fluorescence (SIF) to independently constrain estimation of net ecosystem exchange (NEE) and gross primary production (GPP). The constrained NEE and GPP will be combined with data products of global standing biomass, soil organic carbon and soil respiration to improve the community land model version 4.5 (CLM4.5). Specifically, we will first develop a high fidelity emulator of CLM4.5 according to the matrix representation of the terrestrial carbon cycle. It has been shown that the emulator fully represents the original model and can be effectively used for data assimilation to constrain parameter estimation. We will focus on calibrating those key model parameters (e.g., maximum carboxylation rate, turnover time and transfer coefficients of soil carbon pools, and temperature sensitivity of respiration) for carbon cycle. The Bayesian Markov chain Monte Carlo method (MCMC) will be used to assimilate the global databases into the high fidelity emulator to constrain the model parameters, which will be incorporated back to the original CLM4.5. The calibrated CLM4.5 will be used to make scenario-based projections. In addition, we will conduct observing system simulation experiments (OSSEs) to evaluate how the sampling frequency and length could affect the model constraining and prediction.

Assessment of the potential enhancement of rural food security in Mexico using decision tree land use classification on medium resolution satellite imagery

NASA Astrophysics Data System (ADS)

Bermeo, A.; Couturier, S.

2017-01-01

Because of its renewed importance in international agendas, food security in sub-tropical countries has been the object of studies at different scales, although the spatial components of food security are still largely undocumented. Among other aspects, food security can be assessed using a food selfsufficiency index. We propose a spatial representation of this assessment in the densely populated rural area of the Huasteca Poblana, Mexico, where there is a known tendency towards the loss of selfsufficiency of basic grains. The main agricultural systems in this area are the traditional milpa (a multicrop practice with maize as the main basic crop) system, coffee plantations and grazing land for bovine livestock. We estimate a potential additional milpa - based maize production by smallholders identifying the presence of extensive coffee and pasture systems in the production data of the agricultural census. The surface of extensive coffee plantations and pasture land were estimated using the detailed coffee agricultural census data, and a decision tree combining unsupervised and supervised spectral classification techniques of medium scale (Landsat) satellite imagery. We find that 30% of the territory would benefit more than 50% increment in food security and 13% could theoretically become maize self-sufficient from the conversion of extensive systems to the traditional multicrop milpa system.

Land Survey from Unmaned Aerial Veichle

NASA Astrophysics Data System (ADS)

Peterman, V.; Mesarič, M.

2012-07-01

In this paper we present, how we use a quadrocopter unmanned aerial vehicle with a camera attached to it, to do low altitude photogrammetric land survey. We use the quadrocopter to take highly overlapping photos of the area of interest. A "structure from motion" algorithm is implemented to get parameters of camera orientations and to generate a sparse point cloud representation of objects in photos. Than a patch based multi view stereo algorithm is applied to generate a dense point cloud. Ground control points are used to georeference the data. Further processing is applied to generate digital orthophoto maps, digital surface models, digital terrain models and assess volumes of various types of material. Practical examples of land survey from a UAV are presented in the paper. We explain how we used our system to monitor the reconstruction of commercial building, then how our UAV was used to assess the volume of coal supply for Ljubljana heating plant. Further example shows the usefulness of low altitude photogrammetry for documentation of archaeological excavations. In the final example we present how we used our UAV to prepare an underlay map for natural gas pipeline's route planning. In the final analysis we conclude that low altitude photogrammetry can help bridge the gap between laser scanning and classic tachymetric survey, since it offers advantages of both techniques.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impactmore » on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.« less

Present-day irrigation mitigates heat extremes

NASA Astrophysics Data System (ADS)

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.; Hirsch, Annette L.; Hauser, Mathias; Seneviratne, Sonia I.

2017-02-01

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. Our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.

A New Metric for Land-Atmosphere Coupling Strength: Applications on Observations and Modeling

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Zhang, Y.; Phillips, T. J.; Santanello, J. A., Jr.; Cook, D. R.; Riihimaki, L.; Gaustad, K.

2017-12-01

A new metric is proposed to quantify the land-atmosphere (LA) coupling strength and is elaborated by correlating the surface evaporative fraction and impacting land and atmosphere variables (e.g., soil moisture, vegetation, and radiation). Based upon multiple linear regression, this approach simultaneously considers multiple factors and thus represents complex LA coupling mechanisms better than existing single variable metrics. The standardized regression coefficients quantify the relative contributions from individual drivers in a consistent manner, avoiding the potential inconsistency in relative influence of conventional metrics. Moreover, the unique expendable feature of the new method allows us to verify and explore potentially important coupling mechanisms. Our observation-based application of the new metric shows moderate coupling with large spatial variations at the U.S. Southern Great Plains. The relative importance of soil moisture vs. vegetation varies by location. We also show that LA coupling strength is generally underestimated by single variable methods due to their incompleteness. We also apply this new metric to evaluate the representation of LA coupling in the Accelerated Climate Modeling for Energy (ACME) V1 Contiguous United States (CONUS) regionally refined model (RRM). This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-734201

Application of Suomi-NPP Green Vegetation Fraction and NUCAPS for Improving Regional Numerical Weather Prediction

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Berndt, Emily B.; Srikishen, Jayanthi; Zavodsky, Bradley T.

2014-01-01

The NASA SPoRT Center is working to incorporate Suomi-NPP products into its research and transition activities to improve regional numerical weather prediction (NWP). Specifically, SPoRT seeks to utilize two data products from NOAA/NESDIS: (1) daily global VIIRS green vegetation fraction (GVF), and (2) NOAA Unique CrIS and ATMS Processing System (NUCAPS) temperature and moisture retrieved profiles. The goal of (1) is to improve the representation of vegetation in the Noah land surface model (LSM) over existing climatological GVF datasets in order to improve the land-atmosphere energy exchanges in NWP models and produce better temperature, moisture, and precipitation forecasts. The goal of (2) is to assimilate NUCAPS retrieved profiles into the Gridpoint Statistical Interpolation (GSI) data assimilation system to assess the impact on a summer pre-frontal convection case. Most regional NWP applications make use of a monthly GVF climatology for use in the Noah LSM within the Weather Research and Forecasting (WRF) model. The GVF partitions incoming energy into direct surface heating/evaporation over bare soil versus evapotranspiration processes over vegetated surfaces. Misrepresentations of the fractional coverage of vegetation during anomalous weather/climate regimes (e.g., early/late bloom or freeze; drought) can lead to poor NWP model results when land-atmosphere feedback is important. SPoRT has been producing a daily MODIS GVF product based on the University of Wisconsin Direct Broadcast swaths of Normalized Difference Vegetation Index (NDVI). While positive impacts have been demonstrated in the WRF model for some cases, the reflectances composing these NDVI do not correct for atmospheric aerosols nor satellite view angle, resulting in temporal noisiness at certain locations (especially heavy vegetation). The method behind the NESDIS VIIRS GVF is expected to alleviate the issues seen in the MODIS GVF real-time product, thereby offering a higher-quality dataset for modeling applications. SPoRT is evaluating the VIIRS GVF data against the MODIS real-time and climatology GVF in both WRF and the NASA Land Information System. SPoRT has a history of assimilating hyperspectral infrared retrieved profiles

Capture and Three Dimensional Projection of New South Wales Strata Plans in Landxml Format

NASA Astrophysics Data System (ADS)

Harding, B.; Foreman, A.

2017-10-01

New South Wales is embarking on a major reform program named Cadastre NSW. This reform aims to move to a single source of truth for the digital representation of cadastre. The current lack of a single source cadastre has hindered users from government and industry due to duplication of effort and misalignment between databases from different sources. For this reform to be successful, there are some challenges that need to be addressed. "Cadastre 2034 - Powering Land & Real Property" (2015) published by the Intergovernmental Committee on Surveying and Mapping (ICSM) identifies that current cadastres do not represent real property in three dimensions. In future vertical living lifestyles will create complex property scenarios that the Digital Cadastral Database (DCDB) will need to contend with. While the NSW DCDB currently holds over 3 million lots and 5 million features, one of its limitations is that it does not indicate land ownership above or below the ground surface. NSW Spatial Services is currently capturing survey plans into LandXML format. To prepare for the future, research is being undertaken to also capture multi-level Strata Plans through a modified recipe. During this research, multiple Strata Plans representing a range of ages and development types have been investigated and converted to LandXML. Since it is difficult to visualise the plans in a two dimensional format, quality control purposes require a method to display these plans in three dimensions. Overall investigations have provided Spatial Services with enough information to confirm that the capture and display of Strata Plans in the LandXML format is possible.

System for conversion between the boundary representation model and a constructive solid geometry model of an object

DOEpatents

Christensen, N.C.; Emery, J.D.; Smith, M.L.

1985-04-29

A system converts from the boundary representation of an object to the constructive solid geometry representation thereof. The system converts the boundary representation of the object into elemental atomic geometrical units or I-bodies which are in the shape of stock primitives or regularized intersections of stock primitives. These elemental atomic geometrical units are then represented in symbolic form. The symbolic representations of the elemental atomic geometrical units are then assembled heuristically to form a constructive solid geometry representation of the object usable for manufacturing thereof. Artificial intelligence is used to determine the best constructive solid geometry representation from the boundary representation of the object. Heuristic criteria are adapted to the manufacturing environment for which the device is to be utilized. The surface finish, tolerance, and other information associated with each surface of the boundary representation of the object are mapped onto the constructive solid geometry representation of the object to produce an enhanced solid geometry representation, particularly useful for computer-aided manufacture of the object. 19 figs.

Land Surface Modeling and Data Assimilation to Support Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Tian. Yudong; Kumar, Sujay; Geiger, James; Choudhury, Bhaskar

2010-01-01

Objective: The objective of this proposal is to provide a routine land surface modeling and data assimilation capability for GPM in order to provide global land surface states that are necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in GPM, is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. Therefore, providing a robust capability to routinely provide these critical land states is essential to support GPM-era physical retrieval algorithms over land.

Investigation of Skylab imagery for regional planning. [New York, New Jersey, and Connecticut

NASA Technical Reports Server (NTRS)

Harting, W. (Principal Investigator)

1975-01-01

The author has identified the following significant results. It is feasible to use earth terrain camera imagery to detect four land uses (vacant land, developed land, streets, and water) for general regional planning purposes. Multispectral imagery is suitable for detecting, mapping, and measuring water bodies as small as two acres. Sufficient information can be extracted to prepare graphic and pictorial representations of the general growth and development patterns, but cannot be incorporated into an inventory file for predictive models.

Progress in remote sensing of global land surface heat fluxes and evaporations with a turbulent heat exchange parameterization method

NASA Astrophysics Data System (ADS)

Chen, Xuelong; Su, Bob

2017-04-01

Remote sensing has provided us an opportunity to observe Earth land surface with a much higher resolution than any of GCM simulation. Due to scarcity of information for land surface physical parameters, up-to-date GCMs still have large uncertainties in the coupled land surface process modeling. One critical issue is a large amount of parameters used in their land surface models. Thus remote sensing of land surface spectral information can be used to provide information on these parameters or assimilated to decrease the model uncertainties. Satellite imager could observe the Earth land surface with optical, thermal and microwave bands. Some basic Earth land surface status (land surface temperature, canopy height, canopy leaf area index, soil moisture etc.) has been produced with remote sensing technique, which already help scientists understanding Earth land and atmosphere interaction more precisely. However, there are some challenges when applying remote sensing variables to calculate global land-air heat and water exchange fluxes. Firstly, a global turbulent exchange parameterization scheme needs to be developed and verified, especially for global momentum and heat roughness length calculation with remote sensing information. Secondly, a compromise needs to be innovated to overcome the spatial-temporal gaps in remote sensing variables to make the remote sensing based land surface fluxes applicable for GCM model verification or comparison. A flux network data library (more 200 flux towers) was collected to verify the designed method. Important progress in remote sensing of global land flux and evaporation will be presented and its benefits for GCM models will also be discussed. Some in-situ studies on the Tibetan Plateau and problems of land surface process simulation will also be discussed.

Spatial wavefield gradient-based seismic wavefield separation

NASA Astrophysics Data System (ADS)

Van Renterghem, C.; Schmelzbach, C.; Sollberger, D.; Robertsson, J. OA

2018-03-01

Measurements of the horizontal and vertical components of particle motion combined with estimates of the spatial gradients of the seismic wavefield enable seismic data to be acquired and processed using single dedicated multicomponent stations (e.g. rotational sensors) and/or small receiver groups instead of large receiver arrays. Here, we present seismic wavefield decomposition techniques that use spatial wavefield gradient data to separate land and ocean bottom data into their upgoing/downgoing and P/S constituents. Our method is based on the elastodynamic representation theorem with the derived filters requiring local measurements of the wavefield and its spatial gradients only. We demonstrate with synthetic data and a land seismic field data example that combining translational measurements with spatial wavefield gradient estimates allows separating seismic data recorded either at the Earth's free-surface or at the sea bottom into upgoing/downgoing and P/S wavefield constituents for typical incidence angle ranges of body waves. A key finding is that the filter application only requires knowledge of the elastic properties exactly at the recording locations and is valid for a wide elastic property range.

Simulating the effects of fire disturbance and vegetation recovery on boreal ecosystem carbon fluxes

NASA Astrophysics Data System (ADS)

Yi, Y.; Kimball, J. S.; Jones, L. A.; Zhao, M.

2011-12-01

Fire related disturbance and subsequent vegetation recovery has a major influence on carbon storage and land-atmosphere CO2 fluxes in boreal ecosystems. We applied a synthetic approach combining tower eddy covariance flux measurements, satellite remote sensing and model reanalysis surface meteorology within a terrestrial carbon model framework to estimate fire disturbance and recovery effects on boreal ecosystem carbon fluxes including gross primary production (GPP), ecosystem respiration and net CO2 exchange (NEE). A disturbance index based on MODIS land surface temperature and NDVI was found to coincide with vegetation recovery status inferred from tower chronosequence sites. An empirical algorithm was developed to track ecosystem recovery status based on the disturbance index and used to nudge modeled net primary production (NPP) and surface soil organic carbon stocks from baseline steady-state conditions. The simulations were conducted using a satellite based terrestrial carbon flux model driven by MODIS NDVI and MERRA reanalysis daily surface meteorology inputs. The MODIS (MCD45) burned area product was then applied for mapping recent (post 2000) regional disturbance history, and used with the disturbance index to define vegetation disturbance and recovery status. The model was then applied to estimate regional patterns and temporal changes in terrestrial carbon fluxes across the entire northern boreal forest and tundra domain. A sensitivity analysis was conducted to assess the relative importance of fire disturbance and recovery on regional carbon fluxes relative to assumed steady-state conditions. The explicit representation of disturbance and recovery effects produces more accurate NEE predictions than the baseline steady-state simulations and reduces uncertainty regarding the purported missing carbon sink in the high latitudes.

Comparing alternative tree canopy cover estimates derived from digital aerial photography and field-based assessments

Treesearch

Tracey S. Frescino; Gretchen G. Moisen

2012-01-01

A spatially-explicit representation of live tree canopy cover, such as the National Land Cover Dataset (NLCD) percent tree canopy cover layer, is a valuable tool for many applications, such as defining forest land, delineating wildlife habitat, estimating carbon, and modeling fire risk and behavior. These layers are generated by predictive models wherein their accuracy...

Assessment of MERRA-2 Land Surface Energy Flux Estimates

NASA Technical Reports Server (NTRS)

Draper, Clara; Reichle, Rolf; Koster, Randal

2017-01-01

In MERRA-2, observed precipitation is inserted in place of model-generated precipitation at the land surface. The use of observed precipitation was originally developed for MERRA-Land(a land-only replay of MERRA with model-generated precipitation replaced with observations).Previously shown that the land hydrology in MERRA-2 and MERRA-Land is better than MERRA. We test whether the improved land surface hydrology in MERRA-2 leads to the expected improvements in the land surface energy fluxes and 2 m air temperatures (T2m).

Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin

NASA Astrophysics Data System (ADS)

Mallick, Kaniska; Trebs, Ivonne; Boegh, Eva; Giustarini, Laura; Schlerf, Martin; Drewry, Darren T.; Hoffmann, Lucien; von Randow, Celso; Kruijt, Bart; Araùjo, Alessandro; Saleska, Scott; Ehleringer, James R.; Domingues, Tomas F.; Ometto, Jean Pierre H. B.; Nobre, Antonio D.; Leal de Moraes, Osvaldo Luiz; Hayek, Matthew; Munger, J. William; Wofsy, Steven C.

2016-10-01

Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman-Monteith and Shuttleworth-Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy-atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land-surface-atmosphere exchange parameterizations across a range of spatial scales.

The Jena Diversity Model: Towards a Richer Representation of the Terrestrial Biosphere for Earth System Modelling

NASA Astrophysics Data System (ADS)

Pavlick, R.; Reu, B.; Bohn, K.; Dyke, J.; Kleidon, A.

2010-12-01

The terrestrial biosphere is a complex, self-organizing system which is continually both adapting to and altering its global environment. It also exhibits a vast diversity of vegetation forms and functioning. However, the terrestrial biosphere components within current state-of-the-art Earth System Models abstract this diversity in to a handful of relatively static plant functional types. These coarse and static representations of functional diversity might contribute to overly pessimistic projections regarding terrestrial ecosystem responses to scenarios of global change (e.g. Amazonian and boreal forest diebacks). In the Jena Diversity (JeDi) model, we introduce a new approach to vegetation modelling with a richer representation of functional diversity, based not on plant functional types, but on unavoidable plant ecophysiological trade-offs, which we hypothesize should be more stable in time. The JeDi model tests a large number of plant growth strategies. Each growth strategy is simulated using a set of randomly generated parameter values, which characterize its functioning in terms of carbon allocation, ecophysiology, and phenology, which are then linked to the growing conditions at the land surface. The model is constructed in such a way that these parameters inherently lead to ecophysiological trade-offs, which determine whether a growth strategy is able to survive and reproduce under the prevalent climatic conditions. Kleidon and Mooney (2000) demonstrated that this approach is capable of reproducing the geographic distribution of species richness. More recently, we have shown the JeDi model can explain other biogeographical phenomena including the present-day global pattern of biomes (Reu et al., accepted), ecosystem evenness (Kleidon et al. 2009), and possible mechanisms for biome shifts and biodiversity changes under scenarios of global warming (Reu et al., submitted). We have also evaluated the simulated biogeochemical fluxes from JeDi against a variety of site, field, and satellite observations (Pavlick et al., submitted) following a protocol established by the Carbon-Land Model Intercomparison Project (Randerson et al. 2009). We found that the global patterns of biogeochemical fluxes and land surface properties are reasonably well simulated using this bottom-up trade-off approach and compare favorably with other state of the art terrestrial biosphere models. Here, we present some results from JeDi simulations, wherein we varied the modelled functional diversity to quantify its impact on terrestrial biogeochemical fluxes under both present-day conditions and projected scenarios of global change. We also present results from a set of simulations wherein we vary the ability of the modelled ecosystems to adapt through changes in functional composition, leading to different projection responses of the carbon cycle to global warming. This plant functional tradeoff approach sets the foundation for many applications, including exploring the emergence and climatic impacts of major vegetation transitions throughout the last 400 million years as well as quantifying the significance of preserving functional diversity to hedge against uncertain climates in the future.

Effect of mosaic representation of vegetation in land surface schemes on simulated energy and carbon balances

NASA Astrophysics Data System (ADS)

Li, R.; Arora, V. K.

2012-01-01

Energy and carbon balance implications of representing vegetation using a composite or mosaic approach in a land surface scheme are investigated. In the composite approach the attributes of different plant functional types (PFTs) present in a grid cell are aggregated in some fashion for energy and water balance calculations. The resulting physical environmental conditions (including net radiation, soil moisture and soil temperature) are common to all PFTs and affect their ecosystem processes. In the mosaic approach energy and water balance calculations are performed separately for each PFT tile using its own vegetation attributes, so each PFT "sees" different physical environmental conditions and its carbon balance evolves somewhat differently from that in the composite approach. Simulations are performed at selected boreal, temperate and tropical locations to illustrate the differences caused by using the composite versus mosaic approaches of representing vegetation. These idealized simulations use 50% fractional coverage for each of the two dominant PFTs in a grid cell. Differences in simulated grid averaged primary energy fluxes at selected sites are generally less than 5% between the two approaches. Simulated grid-averaged carbon fluxes and pool sizes at these sites can, however, differ by as much as 46%. Simulation results suggest that differences in carbon balance between the two approaches arise primarily through differences in net radiation which directly affects net primary productivity, and thus leaf area index and vegetation biomass.

Asymmetric Responses of Primary Productivity to Altered Precipitation Simulated by Land Surface Models across Three Long-term Grassland Sites

NASA Astrophysics Data System (ADS)

Wu, D.; Ciais, P.; Viovy, N.; Knapp, A.; Wilcox, K.; Bahn, M.; Smith, M. D.; Ito, A.; Arneth, A.; Harper, A. B.; Ukkola, A.; Paschalis, A.; Poulter, B.; Peng, C.; Reick, C. H.; Hayes, D. J.; Ricciuto, D. M.; Reinthaler, D.; Chen, G.; Tian, H.; Helene, G.; Zscheischler, J.; Mao, J.; Ingrisch, J.; Nabel, J.; Pongratz, J.; Boysen, L.; Kautz, M.; Schmitt, M.; Krohn, M.; Zeng, N.; Meir, P.; Zhang, Q.; Zhu, Q.; Hasibeder, R.; Vicca, S.; Sippel, S.; Dangal, S. R. S.; Fatichi, S.; Sitch, S.; Shi, X.; Wang, Y.; Luo, Y.; Liu, Y.; Piao, S.

2017-12-01

Changes in precipitation variability including the occurrence of extreme events strongly influence plant growth in grasslands. Field measurements of aboveground net primary production (ANPP) in temperate grasslands suggest a positive asymmetric response with wet years resulting in ANPP gains larger than ANPP declines in dry years. Whether land surface models used for historical simulations and future projections of the coupled carbon-water system in grasslands are capable to simulate such non-symmetrical ANPP responses remains an important open research question. In this study, we evaluate the simulated responses of grassland primary productivity to altered precipitation with fourteen land surface models at the three sites of Colorado Shortgrass Steppe (SGS), Konza prairie (KNZ) and Stubai Valley meadow (STU) along a rainfall gradient from dry to wet. Our results suggest that: (i) Gross primary production (GPP), NPP, ANPP and belowground NPP (BNPP) show nonlinear response curves (concave-down) in all the models, but with different curvatures and mean values. In contrast across the sites, primary production increases and then saturates along increasing precipitation with a flattening at the wetter site. (ii) Slopes of spatial relationships between modeled primary production and precipitation are steeper than the temporal slopes (obtained from inter-annual variations). (iii) Asymmetric responses under nominal precipitation range with modeled inter-annual primary production show large uncertainties, and model-ensemble median generally suggests negative asymmetry (greater declines in dry years than increases in wet years) across the three sites. (iv) Primary production at the drier site is predicted to more sensitive to precipitation compared to wetter site, and median sensitivity consistently indicates greater negative impacts of reduced precipitation than positive effects of increased precipitation under extreme conditions. This study implies that most models overemphasize the drought effects or underestimate the watering impacts on primary production in the normal-state, with the direct consequence that carbon-water interactions need to be improved in future model generations with improved mechanistic representations.

Global simulation of interactions between groundwater and terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Braakhekke, M. C.; Rebel, K.; Dekker, S. C.; Smith, B.; Van Beek, L. P.; Sutanudjaja, E.; van Kampenhout, L.; Wassen, M. J.

2016-12-01

In many places in the world ecosystems are influenced by the presence of a shallow groundwater table. In these regions upward water flux due to capillary rise increases soil moisture availability in the root zone, which has strong positive effect on evapotranspiration. Additionally it has important consequences for vegetation dynamics and fluxes of carbon and nitrogen. Under water limited conditions shallow groundwater stimulates vegetation productivity, and soil organic matter decomposition while under saturated conditions groundwater may have a negative effect on these processes due to lack of oxygen. Furthermore, since plant species differ with respect to their root distribution, preference for moisture conditions, and resistance to oxygen stress, shallow groundwater also influences vegetation type. Finally, processes such as denitrification and methane production occur under strictly anaerobic conditions and are thus strongly influenced by moisture availability. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure and are therefore less suitable to represent effects of groundwater on biogeochemical fluxes. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure and biogeochemical processes. These models are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB. Using this coupled model we aim to study the influence of shallow groundwater on terrestrial ecosystem processes. We will present results of global simulations to demonstrate the effects on C, N, and water fluxes.

Diving into Cold Pools

NASA Astrophysics Data System (ADS)

van den Heever, S. C.; Grant, L. D.; Drager, A. J.

2017-12-01

Cold pools play a significant role in convective storm initiation, organization and longevity. Given their role in convective life cycles, recent efforts have been focused on improving the representation of cold pool processes within weather forecast models, as well as on developing cold pool parameterizations in order to better represent their impacts within global climate models. Understanding the physical processes governing cold pool formation, intensity and dissipation is therefore critical to these efforts. Cold pool characteristics are influenced by numerous factors, including those associated with precipitation formation and evaporation, variations in the environmental moisture and shear, and land surface interactions. The focus of this talk will be on the manner in which the surface characteristics and associated processes impact cold pool genesis and dissipation. In particular, the results from high-resolution modeling studies focusing on the role of sensible and latent heat fluxes, soil moisture and SST will be presented. The results from a recent field campaign examining cold pools over northern Colorado will also be discussed.

Multi Seasonal and Diurnal Characterization of Sensible Heat Flux in an Arid Land Environment

NASA Astrophysics Data System (ADS)

Al-Mashharawi, S.; Aragon, B.; McCabe, M.

2017-12-01

In sparsely vegetated arid and semi-arid regions, the available energy is transformed primarily into sensible heat, with little to no energy partitioned into latent heat. The characterization of bare soil arid environments are rather poorly understood in the context of both local, regional and global energy budgets. Using data from a long-term surface layer scintillometer and co-located meteorological installation, we examine the diurnal and seasonal patterns of sensible heat flux and the net radiation to soil heat flux ratio. We do this over a bare desert soil located adjacent to an irrigated agricultural field in the central region of Saudi Arabia. The results of this exploratory analysis can be used to inform upon remote sensing techniques for surface flux estimation, to derive and monitor soil heat flux dynamics, estimate the heat transfer resistance and the thermal roughness length over bare soils, and to better inform efforts that model the advective effects that complicate the accurate representation of agricultural energy budgets in the arid zone.

Advances in land modeling of KIAPS based on the Noah Land Surface Model

NASA Astrophysics Data System (ADS)

Koo, Myung-Seo; Baek, Sunghye; Seol, Kyung-Hee; Cho, Kyoungmi

2017-08-01

As of 2013, the Noah Land Surface Model (LSM) version 2.7.1 was implemented in a new global model being developed at the Korea Institute of Atmospheric Prediction Systems (KIAPS). This land surface scheme is further refined in two aspects, by adding new physical processes and by updating surface input parameters. Thus, the treatment of glacier land, sea ice, and snow cover are addressed more realistically. Inconsistencies in the amount of absorbed solar flux at ground level by the land surface and radiative processes are rectified. In addition, new parameters are available by using 1-km land cover data, which had usually not been possible at a global scale. Land surface albedo/emissivity climatology is newly created using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellitebased data and adjusted parameterization. These updates have been applied to the KIAPS-developed model and generally provide a positive impact on near-surface weather forecasting.

An enhanced forest classification scheme for modeling vegetation-climate interactions based on national forest inventory data

NASA Astrophysics Data System (ADS)

Majasalmi, Titta; Eisner, Stephanie; Astrup, Rasmus; Fridman, Jonas; Bright, Ryan M.

2018-01-01

Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAImax), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products (https://doi.org/10.21350/7zZEy5w3) showed that forest extent notably (κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAImax) of managed forests in Fennoscandia, we compared our LAImax map with reference LAImax maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAImax values used in three leading land models. Comparison of the LAImax maps showed that our product provides a spatially more realistic description of LAImax in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.

Change detection and change monitoring of natural and man-made features in multispectral and hyperspectral satellite imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moody, Daniela Irina

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. A Hebbian learning rule may be used to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of pixel patches over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detectmore » geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.« less

On the use of a physically-based baseflow timescale in land surface models.

NASA Astrophysics Data System (ADS)

Jost, A.; Schneider, A. C.; Oudin, L.; Ducharne, A.

2017-12-01

Groundwater discharge is an important component of streamflow and estimating its spatio-temporal variation in response to changes in recharge is of great value to water resource planning, and essential for modelling accurate large scale water balance in land surface models (LSMs). First-order representation of groundwater as a single linear storage element is frequently used in LSMs for the sake of simplicity, but requires a suitable parametrization of the aquifer hydraulic behaviour in the form of the baseflow characteristic timescale (τ). Such a modelling approach can be hampered by the lack of available calibration data at global scale. Hydraulic groundwater theory provides an analytical framework to relate the baseflow characteristics to catchment descriptors. In this study, we use the long-time solution of the linearized Boussinesq equation to estimate τ at global scale, as a function of groundwater flow length and aquifer hydraulic diffusivity. Our goal is to evaluate the use of this spatially variable and physically-based τ in the ORCHIDEE surface model in terms of simulated river discharges across large catchments. Aquifer transmissivity and drainable porosity stem from GLHYMPS high-resolution datasets whereas flow length is derived from an estimation of drainage density, using the GRIN global river network. ORCHIDEE is run in offline mode and its results are compared to a reference simulation using an almost spatially constant topographic-dependent τ. We discuss the limits of our approach in terms of both the relevance and accuracy of global estimates of aquifer hydraulic properties and the extent to which the underlying assumptions in the analytical method are valid.

Improving the representation of photosynthesis in Earth system models

NASA Astrophysics Data System (ADS)

Rogers, A.; Medlyn, B. E.; Dukes, J.; Bonan, G. B.; von Caemmerer, S.; Dietze, M.; Kattge, J.; Leakey, A. D.; Mercado, L. M.; Niinemets, U.; Prentice, I. C. C.; Serbin, S.; Sitch, S.; Way, D. A.; Zaehle, S.

2015-12-01

Continued use of fossil fuel drives an accelerating increase in atmospheric CO2 concentration ([CO2]) and is the principal cause of global climate change. Many of the observed and projected impacts of rising [CO2] portend increasing environmental and economic risk, yet the uncertainty surrounding the projection of our future climate by Earth System Models (ESMs) is unacceptably high. Improving confidence in our estimation of future [CO2] is essential if we seek to project global change with greater confidence. There are critical uncertainties over the long term response of terrestrial CO2 uptake to global change, more specifically, over the size of the terrestrial carbon sink and over its sensitivity to rising [CO2] and temperature. Reducing the uncertainty associated with model representation of the largest CO2 flux on the planet is therefore an essential part of improving confidence in projections of global change. Here we have examined model representation of photosynthesis in seven process models including several global models that underlie the representation of photosynthesis in the land surface model component of ESMs that were part of the recent Fifth Assessment Report from the IPCC. Our approach was to focus on how physiological responses are represented by these models, and to better understand how structural and parametric differences drive variation in model responses to light, CO2, nutrients, temperature, vapor pressure deficit and soil moisture. We challenged each model to produce leaf and canopy responses to these factors to help us identify areas in which current process knowledge and emerging data sets could be used to improve model skill, and also identify knowledge gaps in current understanding that directly impact model outputs. We hope this work will provide a roadmap for the scientific activity that is necessary to advance process representation, parameterization and scaling of photosynthesis in the next generation of Earth System Models.

Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS)

NASA Astrophysics Data System (ADS)

Jing, Miao; Heße, Falk; Kumar, Rohini; Wang, Wenqing; Fischer, Thomas; Walther, Marc; Zink, Matthias; Zech, Alraune; Samaniego, Luis; Kolditz, Olaf; Attinger, Sabine

2018-06-01

Most large-scale hydrologic models fall short in reproducing groundwater head dynamics and simulating transport process due to their oversimplified representation of groundwater flow. In this study, we aim to extend the applicability of the mesoscale Hydrologic Model (mHM v5.7) to subsurface hydrology by coupling it with the porous media simulator OpenGeoSys (OGS). The two models are one-way coupled through model interfaces GIS2FEM and RIV2FEM, by which the grid-based fluxes of groundwater recharge and the river-groundwater exchange generated by mHM are converted to fixed-flux boundary conditions of the groundwater model OGS. Specifically, the grid-based vertical reservoirs in mHM are completely preserved for the estimation of land-surface fluxes, while OGS acts as a plug-in to the original mHM modeling framework for groundwater flow and transport modeling. The applicability of the coupled model (mHM-OGS v1.0) is evaluated by a case study in the central European mesoscale river basin - Nägelstedt. Different time steps, i.e., daily in mHM and monthly in OGS, are used to account for fast surface flow and slow groundwater flow. Model calibration is conducted following a two-step procedure using discharge for mHM and long-term mean of groundwater head measurements for OGS. Based on the model summary statistics, namely the Nash-Sutcliffe model efficiency (NSE), the mean absolute error (MAE), and the interquartile range error (QRE), the coupled model is able to satisfactorily represent the dynamics of discharge and groundwater heads at several locations across the study basin. Our exemplary calculations show that the one-way coupled model can take advantage of the spatially explicit modeling capabilities of surface and groundwater hydrologic models and provide an adequate representation of the spatiotemporal behaviors of groundwater storage and heads, thus making it a valuable tool for addressing water resources and management problems.

Vegetation Demographics in Earth System Models: a review of progress and priorities

DOE PAGES

Fisher, Rosie A.; Koven, Charles D.; Anderegg, William R. L.; ...

2017-09-18

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections butmore » also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.« less

Vegetation Demographics in Earth System Models: a review of progress and priorities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisher, Rosie A.; Koven, Charles D.; Anderegg, William R. L.

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections butmore » also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fu, Congsheng; Wang, Guiling; Goulden, Michael L.

Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) have done cross-site comparisons for contrasting climate regimes and multiple vegetation types via the integration of measurement and modeling. Here, we incorporated the HR scheme of Ryel et al. (2002) into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture themore » magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on land surface water and energy budgets, and to explore how the impact may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites with contrasting climate regimes and multiple vegetation types were studied, including the Wind River Crane site in Washington State, the Santa Rita Mesquite savanna site in southern Arizona, and six sites along the Southern California Climate Gradient. HR flux, evapotranspiration (ET), and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement matches of evapotranspiration, Bowen ratio, and soil moisture particularly during dry seasons. Lastly, our results also reveal that HR has important hydrological impact in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.« less

Combined measurement and modeling of the hydrological impact of hydraulic redistribution using CLM4.5 at eight AmeriFlux sites

NASA Astrophysics Data System (ADS)

Fu, Congsheng; Wang, Guiling; Goulden, Michael L.; Scott, Russell L.; Bible, Kenneth; Cardon, Zoe G.

2016-05-01

Effects of hydraulic redistribution (HR) on hydrological, biogeochemical, and ecological processes have been demonstrated in the field, but the current generation of standard earth system models does not include a representation of HR. Though recent studies have examined the effect of incorporating HR into land surface models, few (if any) have done cross-site comparisons for contrasting climate regimes and multiple vegetation types via the integration of measurement and modeling. Here, we incorporated the HR scheme of Ryel et al. (2002) into the NCAR Community Land Model Version 4.5 (CLM4.5), and examined the ability of the resulting hybrid model to capture the magnitude of HR flux and/or soil moisture dynamics from which HR can be directly inferred, to assess the impact of HR on land surface water and energy budgets, and to explore how the impact may depend on climate regimes and vegetation conditions. Eight AmeriFlux sites with contrasting climate regimes and multiple vegetation types were studied, including the Wind River Crane site in Washington State, the Santa Rita Mesquite savanna site in southern Arizona, and six sites along the Southern California Climate Gradient. HR flux, evapotranspiration (ET), and soil moisture were properly simulated in the present study, even in the face of various uncertainties. Our cross-ecosystem comparison showed that the timing, magnitude, and direction (upward or downward) of HR vary across ecosystems, and incorporation of HR into CLM4.5 improved the model-measurement matches of evapotranspiration, Bowen ratio, and soil moisture particularly during dry seasons. Our results also reveal that HR has important hydrological impact in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.

Representing Reservoir Stratification in Land Surface and Earth System Models

NASA Astrophysics Data System (ADS)

Yigzaw, W.; Li, H. Y.; Leung, L. R.; Hejazi, M. I.; Voisin, N.; Payn, R. A.; Demissie, Y.

2017-12-01

A one-dimensional reservoir stratification modeling has been developed as part of Model for Scale Adaptive River Transport (MOSART), which is the river transport model used in the Accelerated Climate Modeling for Energy (ACME) and Community Earth System Model (CESM). Reservoirs play an important role in modulating the dynamic water, energy and biogeochemical cycles in the riverine system through nutrient sequestration and stratification. However, most earth system models include lake models that assume a simplified geometry featuring a constant depth and a constant surface area. As reservoir geometry has important effects on thermal stratification, we developed a new algorithm for deriving generic, stratified area-elevation-storage relationships that are applicable at regional and global scales using data from Global Reservoir and Dam database (GRanD). This new reservoir geometry dataset is then used to support the development of a reservoir stratification module within MOSART. The mixing of layers (energy and mass) in the reservoir is driven by eddy diffusion, vertical advection, and reservoir inflow and outflow. Upstream inflow into a reservoir is treated as an additional source/sink of energy, while downstream outflow represented a sink. Hourly atmospheric forcing from North American Land Assimilation System (NLDAS) Phase II and simulated daily runoff by ACME land component are used as inputs for the model over the contiguous United States for simulations between 2001-2010. The model is validated using selected observed temperature profile data in a number of reservoirs that are subject to various levels of regulation. The reservoir stratification module completes the representation of riverine mass and heat transfer in earth system models, which is a major step towards quantitative understanding of human influences on the terrestrial hydrological, ecological and biogeochemical cycles.

JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

NASA Astrophysics Data System (ADS)

Osborne, T.; Gornall, J.; Hooker, J.; Williams, K.; Wiltshire, A.; Betts, R.; Wheeler, T.

2014-10-01

Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soy bean, maize and rice is presented. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soy bean at the global level, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index and canopy height better than in standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an earth system and crop yield model perspective is encouraging however, more effort is needed to develop the parameterisation of the model for specific applications. Key future model developments identified include the specification of the yield gap to enable better representation of the spatial variability in yield.

Impact of urban canopy models and external parameters on the modelled urban energy balance in a tropical city

NASA Astrophysics Data System (ADS)

Demuzere, Matthias; Harshan, Suraj; Järvi, Leena; Roth, Matthias; Betham Grimmond, Christine Susan; Masson, Valéry; Oleson, Keith; Velasco Saldana, Hector Erik; Wouters, Hendrik

2017-04-01

This paper provides the first comparative evaluation of four urban land surface models for a tropical residential neighbourhood in Singapore. The simulations are performed offline, for an 11-month period, using the bulk scheme TERRA_URB and three models of intermediate complexity (CLM, SURFEX and SUEWS). In addition, information from three different parameter lists are added to quantify the impact (interaction) of (between) external parameter settings and model formulations on the modelled urban energy balance components. Overall, the models' performance using the reference parameters aligns well with previous findings for mid- and high-latitude sites against (for) which the models are generally optimised (evaluated). The various combinations of models and different parameter values suggest that error statistics tend to be more dominated by the choice of the latter than the choice of model. Stratifying the observation period into dry / wet periods and hours since selected precipitation events reveals that the models' skill generally deteriorates during dry periods while e.g. CLM/SURFEX has a positive bias in the latent heat flux directly after a precipitation event. It is shown that the latter is due to simple representation of water intercepted on the impervious surfaces. In addition, the positive bias in modelled outgoing longwave radiation is attributed to neglecting the interactions between water vapor and radiation between the surface and the tower sensor. These findings suggest that future developments in urban climate research should continue the integration of more physically-based processes in urban canopy models, ensure the consistency between the observed and modelled atmospheric properties and focus on the correct representation of urban morphology and thermal and radiative characteristics.

Sub-kilometer Numerical Weather Prediction in complex urban areas

NASA Astrophysics Data System (ADS)

Leroyer, S.; Bélair, S.; Husain, S.; Vionnet, V.

2013-12-01

A Sub-kilometer atmospheric modeling system with grid-spacings of 2.5 km, 1 km and 250 m and including urban processes is currently being developed at the Meteorological Service of Canada (MSC) in order to provide more accurate weather forecasts at the city scale. Atmospheric lateral boundary conditions are provided with the 15-km Canadian Regional Deterministic Prediction System (RDPS). Surface physical processes are represented with the Town Energy Balance (TEB) model for the built-up covers and with the Interactions between the Surface, Biosphere, and Atmosphere (ISBA) land surface model for the natural covers. In this study, several research experiments over large metropolitan areas and using observational networks at the urban scale are presented, with a special emphasis on the representation of local atmospheric circulations and their impact on extreme weather forecasting. First, numerical simulations are performed over the Vancouver metropolitan area during a summertime Intense Observing Period (IOP of 14-15 August 2008) of the Environmental Prediction in Canadian Cities (EPiCC) observational network. The influence of the horizontal resolution on the fine-scale representation of the sea-breeze development over the city is highlighted (Leroyer et al., 2013). Then severe storms cases occurring in summertime within the Greater Toronto Area (GTA) are simulated. In view of supporting the 2015 PanAmerican and Para-Pan games to be hold in GTA, a dense observational network has been recently deployed over this region to support model evaluations at the urban and meso scales. In particular, simulations are conducted for the case of 8 July 2013 when exceptional rainfalls were recorded. Leroyer, S., S. Bélair, J. Mailhot, S.Z. Husain, 2013: Sub-kilometer Numerical Weather Prediction in an Urban Coastal Area: A case study over the Vancouver Metropolitan Area, submitted to Journal of Applied Meteorology and Climatology.

Towards integrated modelling of soil organic carbon cycling at landscape scale

NASA Astrophysics Data System (ADS)

Viaud, V.

2009-04-01

Soil organic carbon (SOC) is recognized as a key factor of the chemical, biological and physical quality of soil. Numerous models of soil organic matter turnover have been developed since the 1930ies, most of them dedicated to plot scale applications. More recently, they have been applied to national scales to establish the inventories of carbon stocks directed by the Kyoto protocol. However, only few studies consider the intermediate landscape scale, where the spatio-temporal pattern of land management practices, its interactions with the physical environment and its impacts on SOC dynamics can be investigated to provide guidelines for sustainable management of soils in agricultural areas. Modelling SOC cycling at this scale requires accessing accurate spatially explicit input data on soils (SOC content, bulk density, depth, texture) and land use (land cover, farm practices), and combining both data in a relevant integrated landscape representation. The purpose of this paper is to present a first approach to modelling SOC evolution in a small catchment. The impact of the way landscape is represented on SOC stocks in the catchment was more specifically addressed. This study was based on the field map, the soil survey, the crop rotations and land management practices of an actual 10-km² agricultural catchment located in Brittany (France). RothC model was used to drive soil organic matter dynamics. Landscape representation in the form of a systematic regular grid, where driving properties vary continuously in space, was compared to a representation where landscape is subdivided into a set of homogeneous geographical units. This preliminary work enabled to identify future needs to improve integrated soil-landscape modelling in agricultural areas.

Impact of Land Surface Initialization Approach on Subseasonal Forecast Skill: a Regional Analysis in the Southern Hemisphere

NASA Technical Reports Server (NTRS)

Hirsch, Annette L.; Kala, Jatin; Pitman, Andy J.; Carouge, Claire; Evans, Jason P.; Haverd, Vanessa; Mocko, David

2014-01-01

The authors use a sophisticated coupled land-atmosphere modeling system for a Southern Hemisphere subdomain centered over southeastern Australia to evaluate differences in simulation skill from two different land surface initialization approaches. The first approach uses equilibrated land surface states obtained from offline simulations of the land surface model, and the second uses land surface states obtained from reanalyses. The authors find that land surface initialization using prior offline simulations contribute to relative gains in subseasonal forecast skill. In particular, relative gains in forecast skill for temperature of 10%-20% within the first 30 days of the forecast can be attributed to the land surface initialization method using offline states. For precipitation there is no distinct preference for the land surface initialization method, with limited gains in forecast skill irrespective of the lead time. The authors evaluated the asymmetry between maximum and minimum temperatures and found that maximum temperatures had the largest gains in relative forecast skill, exceeding 20% in some regions. These results were statistically significant at the 98% confidence level at up to 60 days into the forecast period. For minimum temperature, using reanalyses to initialize the land surface contributed to relative gains in forecast skill, reaching 40% in parts of the domain that were statistically significant at the 98% confidence level. The contrasting impact of the land surface initialization method between maximum and minimum temperature was associated with different soil moisture coupling mechanisms. Therefore, land surface initialization from prior offline simulations does improve predictability for temperature, particularly maximum temperature, but with less obvious improvements for precipitation and minimum temperature over southeastern Australia.

On the appropriate definition of soil profile configuration and initial conditions for land surface-hydrology models in cold regions

NASA Astrophysics Data System (ADS)

Sapriza-Azuri, Gonzalo; Gamazo, Pablo; Razavi, Saman; Wheater, Howard S.

2018-06-01

Arctic and subarctic regions are amongst the most susceptible regions on Earth to global warming and climate change. Understanding and predicting the impact of climate change in these regions require a proper process representation of the interactions between climate, carbon cycle, and hydrology in Earth system models. This study focuses on land surface models (LSMs) that represent the lower boundary condition of general circulation models (GCMs) and regional climate models (RCMs), which simulate climate change evolution at the global and regional scales, respectively. LSMs typically utilize a standard soil configuration with a depth of no more than 4 m, whereas for cold, permafrost regions, field experiments show that attention to deep soil profiles is needed to understand and close the water and energy balances, which are tightly coupled through the phase change. To address this gap, we design and run a series of model experiments with a one-dimensional LSM, called CLASS (Canadian Land Surface Scheme), as embedded in the MESH (Modélisation Environmentale Communautaire - Surface and Hydrology) modelling system, to (1) characterize the effect of soil profile depth under different climate conditions and in the presence of parameter uncertainty; (2) assess the effect of including or excluding the geothermal flux in the LSM at the bottom of the soil column; and (3) develop a methodology for temperature profile initialization in permafrost regions, where the system has an extended memory, by the use of paleo-records and bootstrapping. Our study area is in Norman Wells, Northwest Territories of Canada, where measurements of soil temperature profiles and historical reconstructed climate data are available. Our results demonstrate a dominant role for parameter uncertainty, that is often neglected in LSMs. Considering such high sensitivity to parameter values and dependency on the climate condition, we show that a minimum depth of 20 m is essential to adequately represent the temperature dynamics. We further show that our proposed initialization procedure is effective and robust to uncertainty in paleo-climate reconstructions and that more than 300 years of reconstructed climate time series are needed for proper model initialization.

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

NASA Technical Reports Server (NTRS)

Tao, W. K.; Wang, Y.; Qian, J.; Shie, C. -L.; Lau, W. K. -M.; Kakar, R.; Starr, David O' C. (Technical Monitor)

2002-01-01

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Geometrical considerations in analyzing isotropic or anisotropic surface reflections.

PubMed

Simonot, Lionel; Obein, Gael

2007-05-10

The bidirectional reflectance distribution function (BRDF) represents the evolution of the reflectance with the directions of incidence and observation. Today BRDF measurements are increasingly applied and have become important to the study of the appearance of surfaces. The representation and the analysis of BRDF data are discussed, and the distortions caused by the traditional representation of the BRDF in a Fourier plane are pointed out and illustrated for two theoretical cases: an isotropic surface and a brushed surface. These considerations will help characterize either the specular peak width of an isotropic rough surface or the main directions of the light scattered by an anisotropic rough surface without misinterpretations. Finally, what is believed to be a new space is suggested for the representation of the BRDF, which avoids the geometrical deformations and in numerous cases is more convenient for BRDF analysis.

Advancing the Explicit Representation of Lake Processes in WRF-Hydro

NASA Astrophysics Data System (ADS)

Yates, D. N.; Read, L.; Barlage, M. J.; Gochis, D.

2017-12-01

Realistic simulation of physical processes in lakes is essential for closing the water and energy budgets in a coupled land-surface and hydrologic model, such as the Weather Research and Forecasting (WRF) model's WRF-Hydro framework. A current version of WRF-Hydro, the National Water Model (NWM), includes 1,506 waterbodies derived from the National Hydrography Database, each of which is modeled using a level-pool routing scheme. This presentation discusses the integration of WRF's one-dimensional lake model into WRF-Hydro, which is used to estimate waterbody fluxes and thus explicitly represent latent and sensible heat and the mass balance occurring over the lakes. Results of these developments are presented through a case study from Lake Winnebago, Wisconsin. Scalability and computational benchmarks to expand to the continental-scale NWM are discussed.

3D Printed Potential and Free Energy Surfaces for Teaching Fundamental Concepts in Physical Chemistry

ERIC Educational Resources Information Center

Kaliakin, Danil S.; Zaari, Ryan R.; Varganov, Sergey A.

2015-01-01

Teaching fundamental physical chemistry concepts such as the potential energy surface, transition state, and reaction path is a challenging task. The traditionally used oversimplified 2D representation of potential and free energy surfaces makes this task even more difficult and often confuses students. We show how this 2D representation can be…

Impact of Land Model Calibration on Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry and wet land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystem in NASA's Land Information System (LIS-OPT/UE). The impact of the calibration on the a) spinup of the land surface used as initial conditions, and b) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. Changes in ambient weather and land-atmosphere coupling are evaluated along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Results indicate that the offline calibration leads to systematic improvements in land-PBL fluxes and near-surface temperature and humidity, and in the process provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.

Description and evaluation of the Earth System Regional Climate Model (RegCM-ES)

NASA Astrophysics Data System (ADS)

Farneti, Riccardo; Sitz, Lina; Di Sante, Fabio; Fuentes-Franco, Ramon; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Giorgi, Filippo

2017-04-01

The increasing availability of satellite remote sensing data, of high temporal frequency and spatial resolution, has provided a new and enhanced view of the global ocean and atmosphere, revealing strong air-sea coupling processes throughout the ocean basins. In order to obtain an accurate representation and better understanding of the climate system, its variability and change, the inclusion of all mechanisms of interaction among the different sub-components, at high temporal and spatial resolution, becomes ever more desirable. Recently, global coupled models have been able to progressively refine their horizontal resolution to attempt to resolve smaller-scale processes. However, regional coupled ocean-atmosphere models can achieve even finer resolutions and provide additional information on the mechanisms of air-sea interactions and feedbacks. Here we describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES). RegCM-ES presently includes the coupling between atmosphere, ocean, land surface and sea-ice components, as well as an hydrological and ocean biogeochemistry model. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains. RegCM-ES has shown improvements in the representation of precipitation and SST fields over the tested domains, as well as realistic representations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source making it suitable for usage by the large scientific community.

Tropical convection regimes in climate models: evaluation with satellite observations

NASA Astrophysics Data System (ADS)

Steiner, Andrea K.; Lackner, Bettina C.; Ringer, Mark A.

2018-04-01

High-quality observations are powerful tools for the evaluation of climate models towards improvement and reduction of uncertainty. Particularly at low latitudes, the most uncertain aspect lies in the representation of moist convection and interaction with dynamics, where rising motion is tied to deep convection and sinking motion to dry regimes. Since humidity is closely coupled with temperature feedbacks in the tropical troposphere, a proper representation of this region is essential. Here we demonstrate the evaluation of atmospheric climate models with satellite-based observations from Global Positioning System (GPS) radio occultation (RO), which feature high vertical resolution and accuracy in the troposphere to lower stratosphere. We focus on the representation of the vertical atmospheric structure in tropical convection regimes, defined by high updraft velocity over warm surfaces, and investigate atmospheric temperature and humidity profiles. Results reveal that some models do not fully capture convection regions, particularly over land, and only partly represent strong vertical wind classes. Models show large biases in tropical mean temperature of more than 4 K in the tropopause region and the lower stratosphere. Reasonable agreement with observations is given in mean specific humidity in the lower to mid-troposphere. In moist convection regions, models tend to underestimate moisture by 10 to 40 % over oceans, whereas in dry downdraft regions they overestimate moisture by 100 %. Our findings provide evidence that RO observations are a unique source of information, with a range of further atmospheric variables to be exploited, for the evaluation and advancement of next-generation climate models.

The Urban Heat Island Impact in Consideration of Spatial Pattern of Urban Landscape and Structure

NASA Astrophysics Data System (ADS)

Kim, J.; Lee, D. K.; Jeong, W.; Sung, S.; Park, J.

2015-12-01

Preceding study has established a clear relationship between land surface temperature and area of land covers. However, only few studies have specifically examined the effects of spatial patterns of land covers and urban structure. To examine how much the local climate is affected by the spatial pattern in highly urbanized city, we investigated the correlation between land surface temperature and spatial patterns of land covers. In the analysis of correlation, we categorized urban structure to four different land uses: Apartment residential area, low rise residential area, industrial area and central business district. Through this study, we aims to examine the types of residential structure and land cover pattern for reducing urban heat island and sustainable development. Based on land surface temperature, we investigated the phenomenon of urban heat island through using the data of remote sensing. This study focused on Daegu in Korea. This city, one of the hottest city in Korea has basin form. We used high-resolution land cover data and land surface temperature by using Landsat8 satellite image to examine 100 randomly selected sample sites of 884.15km2 (1)In each land use, we quantified several landscape-levels and class-level landscape metrics for the sample study sites. (2)In addition, we measured the land surface temperature in 3 year hot summer seasons (July to September). Then, we investigated the pattern of land surface temperature for each land use through Ecognition package. (3)We deducted the Pearson correlation coefficients between land surface temperature and each landscape metrics. (4)We analyzed the variance among the four land uses. (5)Using linear regression, we determined land surface temperature model for each land use. (6)Through this analysis, we aims to examine the best pattern of land cover and artificial structure for reducing urban heat island effect in highly urbanized city. The results of linear regression showed that proportional land cover of grass, tree, water and impervious surfaces well explained the temperature in apartment residential areas. In contrast, the changes in the pattern of water, grass, tree and impervious surfaces were the best to determine the temperature in low rise residential area, central business district and industrial area.

Impacts of rural land-use on overland flow and sediment transport

NASA Astrophysics Data System (ADS)

Fraser, S. L.; Jackson, B. M.; Norton, K. P.

2013-12-01

The loss of fertile topsoil over time, due to erosive processes, could have a major impact on New Zealand's economy as well as being devastating to individual land owners. Improved management of land use is needed to provide protection of soil from erosion by overland flow and aeolian processes. Effects of soil erosion and sedimentation result in an annual nationwide cost of NZ$123 million. Many previous New Zealand studies have focused on large scale soil movement from land sliding and gully erosion, including identifying risk areas. However, long term small scale erosion and degradation has been largely overlooked in the literature. Although small scale soil erosion is less apparent than mass movement, cumulative small scale soil loss over many years may have a significant impact for future land productivity. One approach to assessing the role of soil degradation is through the application of landscape models. Due to the time consuming collection of data and limited scales over which data can be collected, many models created are unique to a particular land type, land use or locality. Collection of additional datasets can broaden the use of such models by informing model representation and enhancing parameterisation. The Land Use Capability Index (LUCI), developed by Jackson et al (2013) is an example of a model that will benefit from additional data sets. LUCI is a multi-criteria GIS tool, designed to inform land management decisions by identifying areas of potential change, based on land characteristics and land use options. LUCI topographically routes overland flow and sediment using existing land characteristic maps and additionally incorporating sub-field scale data. The model then has the ability to utilise these data to enhance prediction at landscape scale. This study focuses on the influence of land use on small scale sediment transport and enhancing process representation and parameterisation to improve predictive ability of models, such as LUCI. Data are currently being collected in a small catchment at the foothills of the Tararua ranges, lower North Island of New Zealand. Gurlach traps are utilised in a step like array on a number of hillslopes to provide a comprehensive dataset of overland flow and sediment volume for different magnitude rainfall events. ArcGIS is used to calculate a contributing area to each trap. The study provides quantitative data linking overland flow to event magnitude for the rural land uses of pasture versus regenerating native forest at multiple slope angles. These data along with measured soil depth/slope relationships and stream monitoring data are used to inform process representation and parameterisation of LUCI at hillslope scale. LUCI is then used to explore implications at landscape scale. The data and modelling are intended to provide information to help in long-term land management decisions. Jackson, B., Pagella, T., Sinclair, F., Orellana, B., Henshaw, A., Reynolds, B., McIntyre, N., Wheater, H., and Eycott, A. 2013. Polyscape: A GIS mapping framework providing efficient and spatially explicit landscape-scale valuation of multiple ecosystem services. Landscape and Urban Planning, 112(0): 74-88

Consequences of land-cover misclassification in models of impervious surface

USGS Publications Warehouse

McMahon, G.

2007-01-01

Model estimates of impervious area as a function of landcover area may be biased and imprecise because of errors in the land-cover classification. This investigation of the effects of land-cover misclassification on impervious surface models that use National Land Cover Data (NLCD) evaluates the consequences of adjusting land-cover within a watershed to reflect uncertainty assessment information. Model validation results indicate that using error-matrix information to adjust land-cover values used in impervious surface models does not substantially improve impervious surface predictions. Validation results indicate that the resolution of the landcover data (Level I and Level II) is more important in predicting impervious surface accurately than whether the land-cover data have been adjusted using information in the error matrix. Level I NLCD, adjusted for land-cover misclassification, is preferable to the other land-cover options for use in models of impervious surface. This result is tied to the lower classification error rates for the Level I NLCD. ?? 2007 American Society for Photogrammetry and Remote Sensing.

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidar, Christa D.; Tian, Yudong; Kenneth, Tian; Harrison, Kenneth; Kumar, Sujay

2011-01-01

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Impact of Changes in Diffuse Radiation on the Global Land Carbon Sink, 1901-2100

NASA Astrophysics Data System (ADS)

Mercado, L.; Bellouin, N.; Sitch, S.; Boucher, O.; Huntingford, C.; Wild, M.; Cox, P. M.

2009-04-01

Recent observational and theoretical studies have shown that changes in surface radiation that lead to increasing diffuse surface irradiance, enhance plant photosynthesis (Gu et al., 2003, Niyogi et al., 2004, Oliveira et al., 2007, Roderick et al., 2001). Solar radiation reaching the land surface has changed over the industrial era due to aerosols emitted from volcanoes and various anthropogenic sources (Kvalevag and Myhre, 2007). Such changes in total surface radiation are accompanied by changes in direct and diffuse surface solar radiation. Current global climate-carbon models do include the effects of changes in total surface radiation on the land biosphere but neglect the positive effects of increasing diffuse fraction on plant photosynthesis. In this study we estimate for the first time, the impact of variations in diffuse fraction on the land carbon sink using a global model (Mercado et al., 2007) modified to account for the effects of variations in both direct and diffuse radiation on canopy photosynthesis. We use meteorological forcing from the Climate Research Unit Data set. Additionally short wave and photosynthetic active radiation are reconstructed from the Hadley centre climate model, which accounts for the scattering and absorption of light by tropospheric and stratospheric aerosols and change in cloud properties due to indirect aerosol effects. References Gu L.H., Baldocchi D.D., Wofsy S.C., Munger J.W., Michalsky J.J., Urbanski S.P. & Boden T.A. (2003) Response of a deciduous forest to the Mount Pinatubo eruption: Enhanced photosynthesis. Science, 299, 2035-2038. M. M. Kvalevag and G. Myhre, J. Clim. 20, 4874 (2007). Mercado L.M., Huntingford C., Gash J.H.C., Cox P.M. & Jogireddy V. (2007) Improving the representation of radiation interception and photosynthesis for climate model applications. Tellus Series B-Chemical and Physical Meteorology, 59, 553-565. Niyogi D., Chang H.I., Saxena V.K., Holt T., Alapaty K., Booker F., Chen F., Davis K.J., Holben B., Matsui T., Meyers T., Oechel W.C., Pielke R.A., Wells R., Wilson K. & Xue Y.K. (2004) Direct observations of the effects of aerosol loading on net ecosystem CO2 exchanges over different landscapes. Geophysical Research Letters, 31. Oliveira P.H.F., Artaxo P., Pires C., De Lucca S., Procopio A., Holben B., Schafer J., Cardoso L.F., Wofsy S.C. & Rocha H.R. (2007) The effects of biomass burning aerosols and clouds on the CO2 flux in Amazonia. Tellus Series B-Chemical and Physical Meteorology, 59, 338-349. Roderick M.L., Farquhar G.D., Berry S.L. & Noble I.R. (2001) On the direct effect of clouds and atmospheric particles on the productivity and structure of vegetation. Oecologia, 129, 21-30.

Global off-line evaluation of the ISBA-TRIP continental hydrological system used in the CNRM-CM6 climate model for the next CMIP6 exercise

NASA Astrophysics Data System (ADS)

Decharme, Bertrand; Vergnes, Jean-Pierre; Minvielle, Marie; Colin, Jeanne; Delire, Christine

2016-04-01

The land surface hydrology represents an active component of the climate system. It is likely to influence the water and energy exchanges at the land surface, the ocean salinity and temperature at the mouth of the largest rivers, and the climate at least at the regional scale. In climate models, the continental hydrology is simulated via Land Surface Models (LSM), which compute water and energy budgets at the surface, coupled to River Routing Model (RRM), which convert the runoff simulated by the LSMs into river discharge in order to transfer the continental fresh water into the oceans and then to close the global hydrological cycle. Validating these Continental Hydrological Systems (CHS) at the global scale is therefore a crucial task, which requires off-line simulations driven by realistic atmospheric fluxes to avoid the systematic biases commonly found in the atmospheric models. In the CNRM-CM6 climate model of Météo-France, that will be used for the next Coupled Climate Intercomparison Project phase 6 (CMIP6) exercise, the land surface hydrology is simulated using the ISBA-TRIP CHS coupled via the OASIS-MCT coupler. The ISBA LSM solves explicitly the one dimensional Fourier law for soil temperature and the mixed form of the Richards equation for soil moisture using a 14-layers discretization over 12m depths. For the snowpack, a discretization using 12 layers allows the explicit representation of some snow key processes as its viscosity, its compaction due to wind, its age and its albedo on the visible and near infrared spectra. The TRIP RRM uses a global river channel network at 0.5° resolution. It is based on a three prognostic equations for the surface stream water, the seasonal floodplains, and the groundwater. The streamflow velocity is computed using the Maning's formula. The floodplain reservoir fills when the river height exceeds the river bankfull height and vice-versa. The flood interacts with the ISBA soil hydrology through infiltration and with the overlying atmosphere through precipitation interception and free water surface evaporation. Finally, the groundwater scheme is based on the two-dimensional groundwater flow equation for the piezometric head. Its coupling with ISBA permits to account for the presence of a water table under the soil moisture column allowing upward capillarity fluxes into the soil. In this study, we will present the off-line evaluation at the global scale of the ISBA-TRIP CHS over a recent period (1979-2010). The system will be compared to observations such as GRACE (Gravity Recovery and Climate Experiment) terrestrial water storage data, snow and permafrost extents from NSIDC (National Snow and Ice Data Center), or in-situ river discharge measurements from several sources. In addition we will also explore the impacts on the simulated water budget to account for some processes such as upward capillarity fluxes from groundwaters or seasonal floodplains. At last, it is envisaged to discuss some results about land/atmosphere interactions induced by these processes in the CNRM-CM6 climate model.

Upper Blue Nile basin water budget from a multi-model perspective

NASA Astrophysics Data System (ADS)

Jung, Hahn Chul; Getirana, Augusto; Policelli, Frederick; McNally, Amy; Arsenault, Kristi R.; Kumar, Sujay; Tadesse, Tsegaye; Peters-Lidard, Christa D.

2017-12-01

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.

Impacts of land cover transitions on surface temperature in China based on satellite observations

NASA Astrophysics Data System (ADS)

Zhang, Yuzhen; Liang, Shunlin

2018-02-01

China has experienced intense land use and land cover changes during the past several decades, which have exerted significant influences on climate change. Previous studies exploring related climatic effects have focused mainly on one or two specific land use changes, or have considered all land use and land cover change types together without distinguishing their individual impacts, and few have examined the physical processes of the mechanism through which land use changes affect surface temperature. However, in this study, we considered satellite-derived data of multiple land cover changes and transitions in China. The objective was to obtain observational evidence of the climatic effects of land cover transitions in China by exploring how they affect surface temperature and to what degree they influence it through the modification of biophysical processes, with an emphasis on changes in surface albedo and evapotranspiration (ET). To achieve this goal, we quantified the changes in albedo, ET, and surface temperature in the transition areas, examined their correlations with temperature change, and calculated the contributions of different land use transitions to surface temperature change via changes in albedo and ET. Results suggested that land cover transitions from cropland to urban land increased land surface temperature (LST) during both daytime and nighttime by 0.18 and 0.01 K, respectively. Conversely, the transition of forest to cropland tended to decrease surface temperature by 0.53 K during the day and by 0.07 K at night, mainly through changes in surface albedo. Decreases in both daytime and nighttime LST were observed over regions of grassland to forest transition, corresponding to average values of 0.44 and 0.20 K, respectively, predominantly controlled by changes in ET. These results highlight the necessity to consider the individual climatic effects of different land cover transitions or conversions in climate research studies. This short-term analysis of land cover transitions in China means our estimates should represent local temperature effects. Changes in ET and albedo explained <60% of the variation in LST change caused by land cover transitions; thus, additional factors that affect surface climate need consideration in future studies.

Investigating Bidirectional Reflectance in the Los Angeles Megacity Using CLARS Multiangle and Hyperspectral Measurements

NASA Astrophysics Data System (ADS)

Zeng, Z. C.; Natraj, V.; Pongetti, T.; Shia, R. L.; Sander, S. P.; Yung, Y. L.

2017-12-01

The surface reflectance is a key ingredient in the remote sensing of surface and atmospheric properties from space. The determination of atmospheric composition, including greenhouse gas (GHG) and aerosol concentrations, from reflected sunlight requires accurate knowledge of the contribution from the underlying surface. Over megacity areas, such as the Los Angeles (LA) basin, which are major sources of GHGs and anthropogenic aerosols, the quantification of surface reflectance is challenging due to the associated complex land use types. In this study, we investigate the bidirectional reflectance in the Los Angeles megacity area using multiangle and hyperspectral radiance measurements from the California Laboratory for Atmospheric Remote Sensing (CLARS). The CLARS facility is located near the top of Mt. Wilson, at an altitude of 1670 m a.s.l., overlooking the LA megacity area with an FTS operating since 2011 to continuously monitor the GHGs and near-surface aerosols in the basin. The CLARS-FTS offers continuous high-resolution spectral measurements in the visible, near infrared and shortwave infrared spectral regions. The CLARS measurements mimic the off-nadir viewing of a low-Earth orbiting instrument, such as GOSAT and OCO-2, but with daily viewing capability. Eight surface targets with different land use types, including urban parks, industrial and residential areas, are selected in this study. The surface reflectance for specific solar incident and viewing angles is calculated by dividing, for non-absorbing spectral channels on clear days (such that gas and aerosol extinction can be ignored), the observed radiance reflected from surface targets by the observed irradiance. The non-linear Rahman-Pinty-Verstraete (RPV) model is used to model the Bidirectional Reflectance Distribution Function (BRDF) by fitting the multiangle and hyperspectral measurements. By evaluating the retrieved RPV parameters, we find that the RPV model provides a good representation of the BRDF in the LA megacity area. The fitted RPV parameters and their dependence on wavelength provides quantification of BRDF and potentially contributes towards reducing uncertainties in retrievals of GHGs and aerosols in megacity from space.

Preliminary Results of a U.S. Deep South Modeling Experiment Using NASA SPoRT Initialization Datasets for Operational National Weather Service Local Model Runs

NASA Technical Reports Server (NTRS)

Wood, Lance; Medlin, Jeffrey M.; Case, Jon

2012-01-01

A joint collaborative modeling effort among the NWS offices in Mobile, AL, and Houston, TX, and NASA Short-term Prediction Research and Transition (SPoRT) Center began during the 2011-2012 cold season, and continued into the 2012 warm season. The focus was on two frequent U.S. Deep South forecast challenges: the initiation of deep convection during the warm season; and heavy precipitation during the cold season. We wanted to examine the impact of certain NASA produced products on the Weather Research and Forecasting Environmental Modeling System in improving the model representation of mesoscale boundaries such as the local sea-, bay- and land-breezes (which often leads to warm season convective initiation); and improving the model representation of slow moving, or quasi-stationary frontal boundaries (which focus cold season storm cell training and heavy precipitation). The NASA products were: the 4-km Land Information System, a 1-km sea surface temperature analysis, and a 4-km greenness vegetation fraction analysis. Similar domains were established over the southeast Texas and Alabama coastlines, each with an outer grid with a 9 km spacing and an inner nest with a 3 km grid spacing. The model was run at each NWS office once per day out to 24 hours from 0600 UTC, using the NCEP Global Forecast System for initial and boundary conditions. Control runs without the NASA products were made at the NASA SPoRT Center. The NCAR Model Evaluation Tools verification package was used to evaluate both the positive and negative impacts of the NASA products on the model forecasts. Select case studies will be presented to highlight the influence of the products.

Hierarchical Organization of Auditory and Motor Representations in Speech Perception: Evidence from Searchlight Similarity Analysis

PubMed Central

Evans, Samuel; Davis, Matthew H.

2015-01-01

How humans extract the identity of speech sounds from highly variable acoustic signals remains unclear. Here, we use searchlight representational similarity analysis (RSA) to localize and characterize neural representations of syllables at different levels of the hierarchically organized temporo-frontal pathways for speech perception. We asked participants to listen to spoken syllables that differed considerably in their surface acoustic form by changing speaker and degrading surface acoustics using noise-vocoding and sine wave synthesis while we recorded neural responses with functional magnetic resonance imaging. We found evidence for a graded hierarchy of abstraction across the brain. At the peak of the hierarchy, neural representations in somatomotor cortex encoded syllable identity but not surface acoustic form, at the base of the hierarchy, primary auditory cortex showed the reverse. In contrast, bilateral temporal cortex exhibited an intermediate response, encoding both syllable identity and the surface acoustic form of speech. Regions of somatomotor cortex associated with encoding syllable identity in perception were also engaged when producing the same syllables in a separate session. These findings are consistent with a hierarchical account of how variable acoustic signals are transformed into abstract representations of the identity of speech sounds. PMID:26157026

Towards an improved and more flexible representation of water stress in coupled photosynthesis-stomatal conductance models; implications for simulated land surface fluxes and variables at various spatiotemporal scales

NASA Astrophysics Data System (ADS)

Egea, G.; Verhoef, A.; Vidale, P. L.; Black, E.; Van den Hoof, C.

2012-04-01

Coupled photosynthesis-stomatal conductance (A-gs) models are commonly used in ecosystem models to represent the exchange rate of CO2 and H2O between vegetation and the atmosphere. The ways these models account for water stress differ greatly among modelling schemes. This study provides insight into the impact of contrasting model configurations of water stress on the simulated leaf-level values of net photosynthesis (A), stomatal conductance (gs), the functional relationship among them and their ratio, the intrinsic water use efficiency (A/gs), as soil dries. A simple, yet versatile, normalized soil moisture dependent function was used to account for the effects of water stress on gs, on mesophyll conductance (gm ) and on the biochemical capacity (Egea et al., 2011). Model output was compared to leaf-level values obtained from the literature. The sensitivity analyses emphasized the necessity to combine both stomatal and non-stomatal limitations of A in coupled A-gs models to accurately capture the observed functional relationships A vs. gs and A/gs vs. gs in response to drought. Accounting for water stress in coupled A-gs models by imposing either stomatal or biochemical limitations of A, as commonly practiced in most ecosystem models, failed to reproduce the observed functional relationship between key leaf gas exchange attributes. A quantitative limitation analysis revealed that the general pattern of C3 photosynthetic response to water stress can be represented in coupled A-gs models by imposing the highest limitation strength to mesophyll conductance, then to stomatal conductance and finally to the biochemical capacity. This more realistic representation of soil water stress on the simulated leaf-level values of A and gs was embedded in the JULES (Joint UK Land Environment Simulator; Best et al., 2011), model and tested for a number of vegetation types, for which driving and flux verification data were available. These simulations provide an insight into the effect that the revised parameterization will have on GCM simulations of climate variability and change. Best, M. J. et al. (2011). The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes. Geosci. Model Dev., 4, 677-699. Egea, G., Verhoef, A., Vidale, P.L. (2011) Towards an improved and more flexible representation of water stress in coupled photosynthesis-stomatal conductance models. Agricultural and Forest Meteorology, 151 (10), 1370-1384.

One-dimensional representation of Earth to show SRTM coverage

NASA Image and Video Library

2000-02-04

JSC2000E01555 (January 2000) --- A one-dimensional representation of Earth indicates only a portion of the total anticipated coverage area for the Shuttle Radar Topography Mission (SRTM). The primary objective of SRTM is to acquire a high-resolution topographic map of the Earth's land mass (between 60 degrees north and 56 degrees south latitude) and to test new technologies for deployment of large rigid structures and measurement of their distortions to extremely high precision.

New Versions of MISR Aerosol and Land Surface Products Available

Atmospheric Science Data Center

2018-02-14

New Versions of MISR Aerosol and Land Surface Products Available Monday, February 12, ... the release of new versions of the MISR Level 2 (L2) Aerosol Product, the MISR L2 Land Surface Product, and the Level 3 (L3) Component Global Aerosol and Land Surface Products.   The new MISR L2 Aerosol Product ...

Improving the Representation of Mediterranean Heavy Precipitating Events over Land in a Regional Climate System Model.

NASA Astrophysics Data System (ADS)

Mazoyer, M.; Roehrig, R.; Nuissier, O.; Duffourg, F.; Somot, S.

2017-12-01

Most regional climate models (RCSMs) face difficulties in representing a reasonable pre-cipitation probability density function in the Mediterranean area and especially over land.Small amounts of rain are too frequent, preventing any realistic representation of droughts orheat waves, while the intensity of heavy precipitating events is underestimated and not welllocated by most state-of-the-art RCSMs using parameterized convection (resolution from10 to 50 km). Convective parameterization is a key point for the representation of suchevents and recently, the new physics implemented in the CNRM-RCSM has been shown toremarkably improve it, even at a 50-km scale.The present study seeks to further analyse the representation of heavy precipitating eventsby this new version of CNRM-RCSM using a process oriented approach. We focus on oneparticular event in the south-east of France, over the Cévennes. Two hindcast experimentswith the CNRM-RCSM (12 and 50 km) are performed and compared with a simulationbased on the convection-permitting model Meso-NH, which makes use of a very similarsetup as CNRM-RCSM hindcasts. The role of small-scale features of the regional topogra-phy and its interaction with the impinging large-scale flow in triggering the convective eventare investigated. This study provides guidance in the ongoing implementation and use of aspecific parameterization dedicated to account for subgrid-scale orography in the triggeringand closure conditions of the CNRM-RCSM convection scheme.

Estimating Indirect Emissions from Land Use Change Due to Biofuels (Invited)

NASA Astrophysics Data System (ADS)

Reilly, J. M.

2010-12-01

Interest in biofuels as an alternative fuel has led to the realization that they may not be a viable low greenhouse gas alternative, even if process emissions are low, because expansions of land area in biomass crops may lead to forest destruction and hence carbon emissions.(1,2)If the concern was only direct land use effects—changes in carbon stocks on land directly used for biomass—direct measurement would be an option. However, agricultural economists recognize that if biofuels are produced from crops grown on existing cropland the crops previously grown there will likely be replaced by production elsewhere. Given international markets in agricultural products a diversion of land or part of the corn crop in the US for biofuels would result in higher market prices for corn and other crops, and thus spur land conversion almost anywhere around the world. There have now been a number of estimates of the potential land use emissions, and those estimates vary widely and are sensitive to key parameters of both the economic models used in the analysis and the representation of biophysical processes.(3,4,5)Among the important parameters are those that describe the willingness to convert unmanaged land, the ability to intensify production on existing land, the productivity of new land coming to production compared to existing cropland, demand elasticities for agricultural products, and the representation of carbon and nitrogen cycles and storage.(6,7) 1. J. Fargione, J. et al., Science 319, 1235 (2008). 2. T. Searchinger, T et al., Science 319, 1238 (2008) 3. J.M. Melillo, Science, 326: 1397-1399 (2009) 4. M. Wise et al., Science 324, 1183 (2009). 5. W. E. Tyner, et al., Land Use Changes and Consequent CO2 Emissions due to US Corn Ethanol Production: A Comprehensive Analysis, Department of Agricultural Economics, Purdue University (July 2010). 6. T. W. Hertel, The Global Supply and Demand for Agricultural Land in 2050: A Perfect Storm in the Making? AAEA Presidential Address , Purdue University 7. Melillo, et al., op cit

Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

2010-01-01

Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

Global 30m 2000-2014 Surface Water Dynamics Map Derived from All Landsat 5, 7, and 8

NASA Astrophysics Data System (ADS)

Hudson, A.; Hansen, M.

2015-12-01

Water is critical for human life, agriculture, and ecosystems. A better understanding of where it is and how it is changing will enable better management of this valuable resource and guide protection of sensitive ecological areas. Global water maps have typically been representations of surface water at one given time. However, there is both seasonal and interannual variability: rivers meander, lakes disappear, floods arise. To address this ephemeral nature of water, in this study University of Maryland has developed a method that analyzes every Landsat 5, 7, and 8 scene from 1999-2015 to produce global seasonal maps (Winter, Spring, Summer, Fall) of surface water dynamics from 2000-2014. Each Landsat scene is automatically classified into land, water, cloud, haze, shadow, and snow via a decision tree algorithm. The land and water observations are aggregated per pixel into percent occurrence of water in a 3 year moving window for each meteorological season. These annual water percentages form a curve for each season that is discretized into a continuous 3 band RGB map. Frequency of water observation and type of surface water change (loss, gain, peak, or dip) is clearly seen through brightness and hue respectively. Additional data layers include: the year the change began, peak year, minimum year, and the year the change process ended. Currently these maps have been created for 18 1°x1° test tiles scattered around the world, and a portion of the September-November map over Bangladesh is shown below. The entire Landsat archive from 1999-2015 will be processed through a partnership with Google Earth Engine to complete the global product in the coming months. In areas where there is sufficient satellite data density (e.g. the United States), this project could be expanded to 1984-2015. This study provides both scientific researchers and the public an understandable, temporally rich, and globally consistent map showing surface water changes over time.

A potential energy surface for the process H2 + H2O yielding H + H + H2O - Ab initio calculations and analytical representation

NASA Technical Reports Server (NTRS)

Schwenke, David W.; Walch, Stephen P.; Taylor, Peter R.

1991-01-01

Extensive ab initio calculations on the ground state potential energy surface of H2 + H2O were performed using a large contracted Gaussian basis set and a high level of correlation treatment. An analytical representation of the potential energy surface was then obtained which reproduces the calculated energies with an overall root-mean-square error of only 0.64 mEh. The analytic representation explicitly includes all nine internal degrees of freedom and is also well behaved as the H2 dissociates; it thus can be used to study collision-induced dissociation or recombination of H2. The strategy used to minimize the number of energy calculations is discussed, as well as other advantages of the present method for determining the analytical representation.

Present-day irrigation mitigates heat extremes

DOE PAGES

Thiery, Wim; Davin, Edouard L.; Lawrence, David M.; ...

2017-02-16

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impactmore » on temperature extremes, with a particularly strong cooling during the hottest day of the year (-0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. In conclusion, our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections.« less

Effects of rainfall patterns and land cover on the subsurface flow generation of sloping Ferralsols in southern China

PubMed Central

Yang, Jie; Tang, Chongjun; Chen, Lihua; Liu, Yaojun; Wang, Lingyun

2017-01-01

Rainfall patterns and land cover are two important factors that affect the runoff generation process. To determine the surface and subsurface flows associated with different rainfall patterns on sloping Ferralsols under different land cover types, observational data related to surface and subsurface flows from 5 m × 15 m plots were collected from 2010 to 2012. The experiment was conducted to assess three land cover types (grass, litter cover and bare land) in the Jiangxi Provincial Soil and Water Conservation Ecological Park. During the study period, 114 natural rainfall events produced subsurface flow and were divided into four groups using k-means clustering according to rainfall duration, rainfall depth and maximum 30-min rainfall intensity. The results showed that the total runoff and surface flow values were highest for bare land under all four rainfall patterns and lowest for the covered plots. However, covered plots generated higher subsurface flow values than bare land. Moreover, the surface and subsurface flows associated with the three land cover types differed significantly under different rainfall patterns. Rainfall patterns with low intensities and long durations created more subsurface flow in the grass and litter cover types, whereas rainfall patterns with high intensities and short durations resulted in greater surface flow over bare land. Rainfall pattern I had the highest surface and subsurface flow values for the grass cover and litter cover types. The highest surface flow value and lowest subsurface flow value for bare land occurred under rainfall pattern IV. Rainfall pattern II generated the highest subsurface flow value for bare land. Therefore, grass or litter cover are able to convert more surface flow into subsurface flow under different rainfall patterns. The rainfall patterns studied had greater effects on subsurface flow than on total runoff and surface flow for covered surfaces, as well as a greater effect on surface flows associated with bare land. PMID:28792507

Comparison of Numerical Approaches to a Steady-State Landscape Equation

NASA Astrophysics Data System (ADS)

Bachman, S.; Peckham, S.

2008-12-01

A mathematical model of an idealized fluvial landscape has been developed, in which a land surface will evolve to preserve dendritic channel networks as the surface is lowered. The physical basis for this model stems from the equations for conservation of mass for water and sediment. These equations relate the divergence of the 2D vector fields showing the unit-width discharge of water and sediment to the excess rainrate and tectonic uplift on the land surface. The 2D flow direction is taken to be opposite to the water- surface gradient vector. These notions are combined with a generalized Manning-type flow resistance formula and a generalized sediment transport law to give a closed mathematical system that can, in principle, be solved for all variables of interest: discharge of water and sediment, land surface height, vertically- averaged flow velocity, water depth, and shear stress. The hydraulic geometry equations (Leopold et. al, 1964, 1995) are used to incorporate width, depth, velocity, and slope of river channels as powers of the mean-annual river discharge. Combined, they give the unit- width discharge of the stream as a power, γ, of the water surface slope. The simplified steady-state model takes into account three components among those listed above: conservation of mass for water, flow opposite the gradient, and a slope-discharge exponent γ = -1 to reflect mature drainage networks. The mathematical representation of this model appears as a second-order hyperbolic partial differential equation (PDE) where the diffusivity is inversely proportional to the square of the local surface slope. The highly nonlinear nature of this PDE has made it very difficult to solve both analytically and numerically. We present simplistic analytic solutions to this equation which are used to test the validity of the numerical algorithms. We also present three such numerical approaches which have been used in solving the differential equation. The first is based on a nonlinear diffusion filtering technique (Welk et. al, 2007) that has been applied successfully in the context of image processing. The second uses a Ritz finite element approach to the Euler-Lagrange formulation of the PDE in which an eighth degree polynomial is solved whose coefficients are locally dependent on slope and elevation. Lastly, we show a variant to the diffusion filtering approach in which a single-stage Runge-Kutta method is used to iterate a time-derivative to steady- state. The relative merits and drawbacks of these approaches are discussed, as well as stability and consistency requirements.

Assimilation of Leaf Area Index and Soil Wetness Index into the ISBA-A-gs land surface model over France

NASA Astrophysics Data System (ADS)

Barbu, A. L.; Calvet, J.-C.; Lafont, S.

2012-04-01

The development of a Land Data Assimilation System (LDAS) dedicated to carbon and water cycles is considered as a key aspect for monitoring activities of terrestrial carbon fluxes. It allows the assimilation of biophysical products in order to reduce the bias between the model simulations and the observations and have a positive impact on carbon and water fluxes. This work shows the benefits of data assimilation of Earth observations for the monitoring of vegetation status and carbon fluxes, in the framework of the GEOLAND2 project, co-funded by the European Commission within the GMES initiative in FP7. In this study, the SURFEX modelling platform developed at Meteo-France is used for describing the continental vegetation state, surface fluxes and soil moisture. It consists of the land surface model ISBA-A-gs that simulates photosynthesis and plant growth. The vegetation biomass and Leaf Area Index (LAI) evolve dynamically in response to weather and climate conditions. The ECOCLIMAP database provides detailed information about the land cover at a resolution of 1 km. Over the France domain, the most present ecosystem types are grasslands (32%), C3 crop lands (24%), deciduous forest (20%), bare soil (11%), and C4 crop lands (8%).The model also includes a representation of the soil moisture stress with two different types of drought responses for herbaceous vegetation and forests. A version of the Extended Kalman Filter (EKF) scheme is developed for the joint assimilation of satellite-derived surface soil moisture from ASCAT-25 km product, namely Soil Wetness Index (SWI-01) developed by TU-Wien, and remote sensing LAI product provided by GEOLAND2. The GEOLAND2 LAI product is derived from CYCLOPES V3.1 and MODIS collection 5 data. It is more consistent with an effective LAI for low LAI and close to the actual LAI for high values. The assimilation experiment was conducted across France at a spatial resolution of 8 km. The study period ranges from July 2007 to December 2010. In the model simulation, the start of the growing season tends to occur later than in the observations. Similarly, the senescence phase is delayed. The assimilation is able to reduce this bias. The lack of detailed knowledge of the farming practices and other shortcomings of the model are compensated by the assimilation of the remotely sensed LAI. The analyzed seasonal LAI cycle across large cropland regions (north-eastern France) is closer to the observations. A coherent impact of LAI and soil moisture updates on the carbon fluxes is noticed. Increased LAI values in the growing season due to data assimilation corrections trigger an increased photosynthetic activity. Similarly, lower LAI values corresponding to the senescence phase cause a decrease in the carbon dioxide uptake when compared to the original model simulations.

Application of FTLOADDS to Simulate Flow, Salinity, and Surface-Water Stage in the Southern Everglades, Florida

USGS Publications Warehouse

Wang, John D.; Swain, Eric D.; Wolfert, Melinda A.; Langevin, Christian D.; James, Dawn E.; Telis, Pamela A.

2007-01-01

The Comprehensive Everglades Restoration Plan requires numerical modeling to achieve a sufficient understanding of coastal freshwater flows, nutrient sources, and the evaluation of management alternatives to restore the ecosystem of southern Florida. Numerical models include a regional water-management model to represent restoration changes to the hydrology of southern Florida and a hydrodynamic model to represent the southern and western offshore waters. The coastal interface between these two systems, however, has complex surface-water/ground-water and freshwater/saltwater interactions and requires a specialized modeling effort. The Flow and Transport in a Linked Overland/Aquifer Density Dependent System (FTLOADDS) code was developed to represent connected surface- and ground-water systems with variable-density flow. The first use of FTLOADDS is the Southern Inland and Coastal Systems (SICS) application to the southeastern part of the Everglades/Florida Bay coastal region. The need to (1) expand the domain of the numerical modeling into most of Everglades National Park and the western coastal area, and (2) better represent the effect of water-delivery control structures, led to the application of the FTLOADDS code to the Tides and Inflows in the Mangroves of the Everglades (TIME) domain. This application allows the model to address a broader range of hydrologic issues and incorporate new code modifications. The surface-water hydrology is of primary interest to water managers, and is the main focus of this study. The coupling to ground water, however, was necessary to accurately represent leakage exchange between the surface water and ground water, which transfers substantial volumes of water and salt. Initial calibration and analysis of the TIME application produced simulated results that compare well statistically with field-measured values. A comparison of TIME simulation results to previous SICS results shows improved capabilities, particularly in the representation of coastal flows. This improvement most likely is due to a more stable numerical representation of the coastal creek outlets. Sensitivity analyses were performed by varying frictional resistance, leakage, barriers to flow, and topography. Changing frictional resistance values in inland areas was shown to improve water-level representation locally, but to have a negligible effect on area-wide values. These changes have only local effects and are not physically based (as are the unchanged values), and thus have limited validity. Sensitivity tests indicate that the overall accuracy of the simulation is diminished if leakage between surface water and ground water is not simulated. The inclusion of a major road as a complete barrier to surface-water flow influenced the local distribution and timing of flow; however, the changes in total flow and individual creekflows were negligible. The model land-surface altitude was lowered by 0.1 meter to determine the sensitivity to topographic variation. This topographic sensitivity test produced mixed results in matching field data. Overall, the representation of stage did not improve definitively. A final calibration utilized the results of the sensitivity analysis to refine the TIME application. To accomplish this calibration, the friction coefficient was reduced at the northern boundary inflow and increased in the southwestern corner of the model, the evapotranspiration function was varied, additional data were used for the ground-water head boundary along the southeast, and the frictional resistance of the primary coastal creek outlet was increased. The calibration improved the match between measured and simulated total flows to Florida Bay and coastal salinities. Agreement also was improved at most of the water-level sites throughout the model domain.

Role of the Soil Thermal Inertia in the short term variability of the surface temperature and consequences for the soil-moisture temperature feedback

NASA Astrophysics Data System (ADS)

Cheruy, Frederique; Dufresne, Jean-Louis; Ait Mesbah, Sonia; Grandpeix, Jean-Yves; Wang, Fuxing

2017-04-01

A simple model based on the surface energy budget at equilibrium is developed to compute the sensitivity of the climatological mean daily temperature and diurnal amplitude to the soil thermal inertia. It gives a conceptual framework to quantity the role of the atmospheric and land surface processes in the surface temperature variability and relies on the diurnal amplitude of the net surface radiation, the sensitivity of the turbulent fluxes to the surface temperature and the thermal inertia. The performances of the model are first evaluated with 3D numerical simulations performed with the atmospheric (LMDZ) and land surface (ORCHIDEE) modules of the Institut Pierre Simon Laplace (IPSL) climate model. A nudging approach is adopted, it prevents from using time-consuming long-term simulations required to account for the natural variability of the climate and allow to draw conclusion based on short-term (several years) simulations. In the moist regions the diurnal amplitude and the mean surface temperature are controlled by the latent heat flux. In the dry areas, the relevant role of the stability of the boundary layer and of the soil thermal inertia is demonstrated. In these regions, the sensitivity of the surface temperature to the thermal inertia is high, due to the high contribution of the thermal flux to the energy budget. At high latitudes, when the sensitivity of turbulent fluxes is dominated by the day-time sensitivity of the sensible heat flux to the surface temperature and when this later is comparable to the thermal inertia term of the sensitivity equation, the surface temperature is also partially controlled by the thermal inertia which can rely on the snow properties; In the regions where the latent heat flux exhibits a high day-to-day variability, such as transition regions, the thermal inertia has also significant impact on the surface temperature variability . In these not too wet (energy limited) and not too dry (moisture-limited) soil moisture (SM) ''hot spots'', it is generally admitted that the variability of the surface temperature is explained by the soil moisture trough its control on the evaporation. This work suggests that the impact of the soil moisture on the temperature through its impact on the thermal inertia can be as important as its direct impact on the evaporation. Contrarily to the evaporation related soil-moisture temperature negative feedback, the thermal inertia soil-moisture related feedback newly identified by this work is a positive feedback which limits the cooling when the soil moisture increases. These results suggest that uncertainties in the representation of the soil and snow thermal properties can be responsible of significant biases in numerical simulations and emphasize the need to carefully document and evaluate these quantities in the Land Surface Modules implemented in the climate models.

3-D World Modeling For An Autonomous Robot

NASA Astrophysics Data System (ADS)

Goldstein, M.; Pin, F. G.; Weisbin, C. R.

1987-01-01

This paper presents a methodology for a concise representation of the 3-D world model for a mobile robot, using range data. The process starts with the segmentation of the scene into "objects" that are given a unique label, based on principles of range continuity. Then the external surface of each object is partitioned into homogeneous surface patches. Contours of surface patches in 3-D space are identified by estimating the normal and curvature associated with each pixel. The resulting surface patches are then classified as planar, convex or concave. Since the world model uses a volumetric representation for the 3-D environment, planar surfaces are represented by thin volumetric polyhedra. Spherical and cylindrical surfaces are extracted and represented by appropriate volumetric primitives. All other surfaces are represented using the boolean union of spherical volumes (as described in a separate paper by the same authors). The result is a general, concise representation of the external 3-D world, which allows for efficient and robust 3-D object recognition.

The Development in modeling Tibetan Plateau Land/Climate Interaction

NASA Astrophysics Data System (ADS)

Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

2015-04-01

Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP. The offline SSiB4/TRIFFID is integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2008 with 1 degree horizontal resolution. The simulated vegetation conditions and surface hydrology are compared well with observational data with some bias, and shows strong decadal and interannual variabilities with a linear trend associated with the global warming. The TP region is covered by both discontinuous and sporadic permafrost with irregular snow layers above. A frozen soil model is developed to take the coupling effect of mass and heat transport into consideration and includes a detailed description of mass balances of volumetric liquid water, ice, as well as vapor content. It also considers contributions' of heat conduction to the energy balance. The model has been extensively tested using a number of TP station data, which included soil temperature and soil water measurements. The results suggest that it is important to include the frozen sol process to adequately simulate the surface energy balance during the freezing and thawing periods and surface temperature variability, including its diurnal variation. Issues in simulating permafrost process will also be addressed. To better understand the glacier variations under climate change scenarios, an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers and multilayer scheme for seasonal snow over glacier, soil and forest are developed within a distributed biosphere hydrological modeling framework (WEB-DHM-S model). Discharge simulations using this model show good agreement with observations for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan for three hydrologic years (2002-2004). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt) and suggests that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region.

Impact of land cover change on the environmental hydrology characteristics in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Saadatkhah, Nader; Mansor, Shattri; Khuzaimah, Zailani; Asmat, Arnis; Adnan, Noraizam; Adam, Siti Noradzah

2016-09-01

Changing the land cover/ land use has serious environmental impacts affecting the ecosystem in Malaysia. The impact of land cover changes on the environmental functions such as surface water, loss water, and soil moisture is considered in this paper on the Kelantan river basin. The study area at the east coast of the peninsular Malaysia has suffered significant land cover changes in the recent years. The current research tried to assess the impact of land cover changes in the study area focused on the surface water, loss water, and soil moisture from different land use classes and the potential impact of land cover changes on the ecosystem of Kelantan river basin. To simulate the impact of land cover changes on the environmental hydrology characteristics, a deterministic regional modeling were employed in this study based on five approaches, i.e. (1) Land cover classification based on Landsat images; (2) assessment of land cover changes during last three decades; (3) Calculation the rate of water Loss/ Infiltration; (4) Assessment of hydrological and mechanical effects of the land cover changes on the surface water; and (5) evaluation the impact of land cover changes on the ecosystem of the study area. Assessment of land cover impact on the environmental hydrology was computed with the improved transient rainfall infiltration and grid based regional model (Improved-TRIGRS) based on the transient infiltration, and subsequently changes in the surface water, due to precipitation events. The results showed the direct increased in surface water from development area, agricultural area, and grassland regions compared with surface water from other land covered areas in the study area. The urban areas or lower planting density areas tend to increase for surface water during the monsoon seasons, whereas the inter flow from forested and secondary jungle areas contributes to the normal surface water.

North-western Mediterranean sea-breeze circulation in a regional climate system model

NASA Astrophysics Data System (ADS)

Drobinski, Philippe; Bastin, Sophie; Arsouze, Thomas; Béranger, Karine; Flaounas, Emmanouil; Stéfanon, Marc

2017-04-01

In the Mediterranean basin, moisture transport can occur over large distance from remote regions by the synoptic circulation or more locally by sea breezes, driven by land-sea thermal contrast. Sea breezes play an important role in inland transport of moisture especially between late spring and early fall. In order to explicitly represent the two-way interactions at the atmosphere-ocean interface in the Mediterranean region and quantify the role of air-sea feedbacks on regional meteorology and climate, simulations at 20 km resolution performed with WRF regional climate model (RCM) and MORCE atmosphere-ocean regional climate model (AORCM) coupling WRF and NEMO-MED12 in the frame of HyMeX/MED-CORDEX are compared. One result of this study is that these simulations reproduce remarkably well the intensity, direction and inland penetration of the sea breeze and even the existence of the shallow sea breeze despite the overestimate of temperature over land in both simulations. The coupled simulation provides a more realistic representation of the evolution of the SST field at fine scale than the atmosphere-only one. Temperature and moisture anomalies are created in direct response to the SST anomaly and are advected by the sea breeze over land. However, the SST anomalies are not of sufficient magnitude to affect the large-scale sea-breeze circulation. The temperature anomalies are quickly damped by strong surface heating over land, whereas the water vapor mixing ratio anomalies are transported further inland. The inland limit of significance is imposed by the vertical dilution in a deeper continental boundary-layer.

Translation of Land Surface Model Accuracy and Uncertainty into Coupled Land-Atmosphere Prediction

NASA Technical Reports Server (NTRS)

Santanello, Joseph A.; Kumar, Sujay; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Zhou, Shuija

2012-01-01

Land-atmosphere (L-A) Interactions playa critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (US-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF Simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Reverse engineering of aircraft wing data using a partial differential equation surface model

NASA Astrophysics Data System (ADS)

Huband, Jacalyn Mann

Reverse engineering is a multi-step process used in industry to determine a production representation of an existing physical object. This representation is in the form of mathematical equations that are compatible with computer-aided design and computer-aided manufacturing (CAD/CAM) equipment. The four basic steps to the reverse engineering process are data acquisition, data separation, surface or curve fitting, and CAD/CAM production. The surface fitting step determines the design representation of the object, and thus is critical to the success or failure of the reverse engineering process. Although surface fitting methods described in the literature are used to model a variety of surfaces, they are not suitable for reversing aircraft wings. In this dissertation, we develop and demonstrate a new strategy for reversing a mathematical representation of an aircraft wing. The basis of our strategy is to take an aircraft design model and determine if an inverse model can be derived. A candidate design model for this research is the partial differential equation (PDE) surface model, proposed by Bloor and Wilson and used in the Rapid Airplane Parameter Input Design (RAPID) tool at the NASA-LaRC Geolab. There are several basic mathematical problems involved in reversing the PDE surface model: (i) deriving a computational approximation of the surface function; (ii) determining a radial parametrization of the wing; (iii) choosing mathematical models or classes of functions for representation of the boundary functions; (iv) fitting the boundary data points by the chosen boundary functions; and (v) simultaneously solving for the axial parameterization and the derivative boundary functions. The study of the techniques to solve the above mathematical problems has culminated in a reverse PDE surface model and two reverse PDE surface algorithms. One reverse PDE surface algorithm recovers engineering design parameters for the RAPID tool from aircraft wing data and the other generates a PDE surface model with spline boundary functions from an arbitrary set of grid points. Our numerical tests show that the reverse PDE surface model and the reverse PDE surface algorithms can be used for the reverse engineering of aircraft wing data.

PiTS-1: Carbon Partitioning in Loblolly Pine after 13C Labeling and Shade Treatments

DOE Data Explorer

Warren, J. M.; Iversen, C. M.; Garten, Jr., C. T.; Norby, R. J.; Childs, J.; Brice, D.; Evans, R. M.; Gu, L.; Thornton, P.; Weston, D. J.

2013-01-01

The PiTS task was established with the objective of improving the C partitioning routines in existing ecosystem models by exploring mechanistic model representations of partitioning tested against field observations. We used short-term field manipulations of C flow, through 13CO2 labeling, canopy shading and stem girdling, to dramatically alter C partitioning, and resultant data are being used to test model representation of C partitioning processes in the Community Land Model (CLM4 or CLM4.5).

Land Surface Data Assimilation

NASA Astrophysics Data System (ADS)

Houser, P. R.

2012-12-01

Information about land surface water, energy and carbon conditions is of critical importance to real-world applications such as agricultural production, water resource management, flood prediction, water supply, weather and climate forecasting, and environmental preservation. While ground-based observational networks are improving, the only practical way to observe these land surface states on continental to global scales is via satellites. Remote sensing can make spatially comprehensive measurements of various components of the terrestrial system, but it cannot provide information on the entire system (e.g. evaporation), and the observations represent only an instant in time. Land surface process models may be used to predict temporal and spatial terrestrial dynamics, but these predictions are often poor, due to model initialization, parameter and forcing, and physics errors. Therefore, an attractive prospect is to combine the strengths of land surface models and observations (and minimize the weaknesses) to provide a superior terrestrial state estimate. This is the goal of land surface data assimilation. Data Assimilation combines observations into a dynamical model, using the model's equations to provide time continuity and coupling between the estimated fields. Land surface data assimilation aims to utilize both our land surface process knowledge, as embodied in a land surface model, and information that can be gained from observations. Both model predictions and observations are imperfect and we wish to use both synergistically to obtain a more accurate result. Moreover, both contain different kinds of information, that when used together, provide an accuracy level that cannot be obtained individually. Model biases can be mitigated using a complementary calibration and parameterization process. Limited point measurements are often used to calibrate the model(s) and validate the assimilation results. This presentation will provide a brief background on land surface observation, modeling and data assimilation, followed by a discussion of various hydrologic data assimilation challenges, and finally conclude with several land surface data assimilation case studies.

Estimating morning changes in land surface temperature from MODIS day/night land surface temperature: Applications for surface energy balance modeling

USDA-ARS?s Scientific Manuscript database

Observations of land surface temperature (LST) are crucial for the monitoring of surface energy fluxes from satellite. Methods that require high temporal resolution LST observations (e.g., from geostationary orbit) can be difficult to apply globally because several geostationary sensors are required...

A COUPLED LAND-SURFACE AND DRY DEPOSITION MODEL AND COMPARISON TO FIELD MEASUREMENTS OF SURFACE HEAT, MOISTURE, AND OZONE FLUXES

EPA Science Inventory

We have developed a coupled land-surface and dry deposition model for realistic treatment of surface fluxes of heat, moisture, and chemical dry deposition within a comprehensive air quality modeling system. A new land-surface model (LSM) with explicit treatment of soil moisture...

USSR Report, Space. No. 22

DTIC Science & Technology

1983-06-06

ASTRONOMICHESKIY ZHURNAL, Jul 82) . 35 Analysis of Panoramas of ’Venera-13,’ ’Venera-14’ Landing Sites (K. P. Florenskiy, et al.; PIS’MA V...et al.; PIS’MA V ASTRONOMICHESKIY ZHURNAL, Jul 82) 38 Panoramas of ’Venera-13,’ ’Venera-14’ Landing Sites (Preliminary Analysis) (K. P...GaTapeH HayHHaa annapaiyp» Diagrammatic representation of Key: 1. Outer thermal insulation 2. Local heater 3. Descent module 4. Orbital

Climate and the equilibrium state of land surface hydrology parameterizations

NASA Technical Reports Server (NTRS)

Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

For given climatic rates of precipitation and potential evaporation, the land surface hydrology parameterizations of atmospheric general circulation models will maintain soil-water storage conditions that balance the moisture input and output. The surface relative soil saturation for such climatic conditions serves as a measure of the land surface parameterization state under a given forcing. The equilibrium value of this variable for alternate parameterizations of land surface hydrology are determined as a function of climate and the sensitivity of the surface to shifts and changes in climatic forcing are estimated.

Dynamic root distributions in ecohydrological modeling: A case study at Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Sivandran, Gajan; Bras, Rafael L.

2013-06-01

Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. In particular, the rooting strategies employed by vegetation can be critical to their survival. However, land surface models currently prescribe rooting profiles as a function of only the plant functional type of interest with no consideration for the soil texture or rainfall regime of the region being modeled. Additionally, these models do not incorporate the ability of vegetation to dynamically alter their rooting strategies in response to transient changes in environmental forcings or competition from other plant species and therefore tend to underestimate the resilience of these ecosystems. To address the simplicity of the current representation of roots in land surface models, a new dynamic rooting scheme was incorporated into the framework of the distributed ecohydrological model tRIBS+VEGGIE. The new scheme optimizes the allocation of carbon to the root zone to reduce the perceived stress of the vegetation, so that root profiles evolve based upon local climate and soil conditions. The ability of the new scheme to capture the complex dynamics of natural systems was evaluated by comparisons to hourly timescale energy flux, soil moisture, and vegetation growth observations from the Walnut Gulch Experimental Watershed, Arizona. Robust agreement was found between the model and observations, providing confidence that the improved model is able to capture the multidirectional interactions between climate, soil, and vegetation at this site.

Simulating and evaluating best management practices for integrated landscape management scenarios in biofuel feedstock production: Evaluating Best Management Practices for Biofuel Feedstock Production

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ha, Miae; Wu, May

Sound crop and land management strategies can maintain land productivity and improve the environmental sustainability of agricultural crop and feedstock production. This study evaluates the improvement of water sustainability through an integrated landscaping management strategy, where landscaping design, land management operations, crop systems, and agricultural best management practices (BMPs) play equal roles. The strategy was applied to the watershed of the South Fork Iowa River in Iowa, with a focus on implementing riparian buffers and converting low productivity land to provide cellulosic biomass while benefiting soil and water quality. The Soil and Water Assessment Tool (SWAT) was employed to simulatemore » the impact of integrated landscape design on nutrients, suspended sediments, and flow on the watershed and subbasin scales. First, the study evaluated the representation of buffer strip as a vegetative barrier and as a riparian buffer using trapping efficiency and area ratio methods in SWAT. For the riparian buffer, the area ratio method tends to be more conservative, especially in nitrate loadings, while the trapping efficiency method generates more optimistic results. The differences between the two methods increase with buffer width. The two methods may not be comparable for the field-scale vegetative barrier simulation because of limitations in model spatial resolution. Landscape scenarios were developed to quantify water quality under (1) current land use, (2) partial land conversion to switchgrass, and (3) riparian buffer implementation. Results show that when low productivity land (15.2% of total watershed land area) is converted to grow switchgrass, suspended sediment, total nitrogen, total phosphorus, and nitrate loadings are reduced by 69.3%, 55.5%, 46.1%, and 13.4%, respectively, in the watershed surface streams. The reduction was less extensive when riparian buffer strips (30 m or 50 m) were applied to the stream network at 1.4% of total land area in the watershed. At the subbasin level, the degree of nutrient and suspended sediment reduction varies extensively, ranging from a few percent up to 55%. Results indicate that effective landscape design on current agricultural land can potentially bring marked improvements in water quality and soil erosion control while producing food and fuel feedstock in the South Fork Iowa River watershed. The concept can be integrated with other watershed management programs to improve sustainability of land, water, and the ecosystem.« less

Multi-temporal analysis of land surface temperature in highly urbanized districts

NASA Astrophysics Data System (ADS)

Kaya, S.; Celik, B.; Sertel, E.; Bayram, B.; Seker, D. Z.

2017-12-01

Istanbul is one of the largest cities around the world with population over 15 million and it has 39 districts. Due to high immigration rate after the 1980s, parallel to the urbanization rapid population increase has occurred in some of these districts. Thus, a significant increase in land surface temperature were monitored and this subject became one of the most popular subject of different researches. Natural landscapes transformed into residential areas with impervious surfaces that causes rise in land surface temperatures which is one of the component of urban heat islands. This study focuses on determining the land use/land cover changes and land surface temperature in highly urbanized districts for last 32 years and examining the relationship between these two parameters using multi-temporal optical and thermal remotely sensed data. In this study, Landsat5 Thematic Mapper and Landsat8 OLI/TIR imagery with acquisition dates June 1984 and June 2016 were used. In order to assess the land use/cover change between 1984 and 2016, Vegetation Impervious Surface-soil (V-I-S) model is used. Each end-member spectra are extracted from ASTER spectral library. Additionally, V-I-S model, NDVI, NDBI and NDBaI indices have been derived for further investigation of land cover changes. The results of the study, presented that in the last 32 years, the amount of impervious surfaces substantially increased along with land surface temperatures.

Change detection in Arctic satellite imagery using clustering of sparse approximations (CoSA) over learned feature dictionaries

NASA Astrophysics Data System (ADS)

Moody, Daniela I.; Wilson, Cathy J.; Rowland, Joel C.; Altmann, Garrett L.

2015-06-01

Advanced pattern recognition and computer vision algorithms are of great interest for landscape characterization, change detection, and change monitoring in satellite imagery, in support of global climate change science and modeling. We present results from an ongoing effort to extend neuroscience-inspired models for feature extraction to the environmental sciences, and we demonstrate our work using Worldview-2 multispectral satellite imagery. We use a Hebbian learning rule to derive multispectral, multiresolution dictionaries directly from regional satellite normalized band difference index data. These feature dictionaries are used to build sparse scene representations, from which we automatically generate land cover labels via our CoSA algorithm: Clustering of Sparse Approximations. These data adaptive feature dictionaries use joint spectral and spatial textural characteristics to help separate geologic, vegetative, and hydrologic features. Land cover labels are estimated in example Worldview-2 satellite images of Barrow, Alaska, taken at two different times, and are used to detect and discuss seasonal surface changes. Our results suggest that an approach that learns from both spectral and spatial features is promising for practical pattern recognition problems in high resolution satellite imagery.

Neural dynamics of 3-D surface perception: figure-ground separation and lightness perception.

PubMed

Kelly, F; Grossberg, S

2000-11-01

This article develops the FACADE theory of three-dimensional (3-D) vision to simulate data concerning how two-dimensional pictures give rise to 3-D percepts of occluded and occluding surfaces. The theory suggests how geometrical and contrastive properties of an image can either cooperate or compete when forming the boundary and surface representations that subserve conscious visual percepts. Spatially long-range cooperation and short-range competition work together to separate boundaries of occluding figures from their occluded neighbors, thereby providing sensitivity to T-junctions without the need to assume that T-junction "detectors" exist. Both boundary and surface representations of occluded objects may be amodally completed, whereas the surface representations of unoccluded objects become visible through modal processes. Computer simulations include Bregman-Kanizsa figure-ground separation, Kanizsa stratification, and various lightness percepts, including the Münker-White, Benary cross, and checkerboard percepts.

A unified account of gloss and lightness perception in terms of gamut relativity.

PubMed

Vladusich, Tony

2013-08-01

A recently introduced computational theory of visual surface representation, termed gamut relativity, overturns the classical assumption that brightness, lightness, and transparency constitute perceptual dimensions corresponding to the physical dimensions of luminance, diffuse reflectance, and transmittance, respectively. Here I extend the theory to show how surface gloss and lightness can be understood in a unified manner in terms of the vector computation of "layered representations" of surface and illumination properties, rather than as perceptual dimensions corresponding to diffuse and specular reflectance, respectively. The theory simulates the effects of image histogram skewness on surface gloss/lightness and lightness constancy as a function of specular highlight intensity. More generally, gamut relativity clarifies, unifies, and generalizes a wide body of previous theoretical and experimental work aimed at understanding how the visual system parses the retinal image into layered representations of surface and illumination properties.

Land Surface Precipitation and Hydrology in MERRA-2

NASA Technical Reports Server (NTRS)

Reichle, R.; Koster, R.; Draper, C.; Liu, Q.; Girotto, M.; Mahanama, S.; De Lannoy, G.; Partyka, G.

2017-01-01

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at 50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface. This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cyclingMERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourlyTRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA. A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim Land and higher than that of MERRA (significantly for surface soil moisture). Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRA-Land and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim Land. Seasonal anomaly R values against naturalized stream flow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim Land, somewhat lower for MERRA-Land, and lower still for MERRA.

Evaluation of an improved intermediate complexity snow scheme in the ORCHIDEE land surface model

NASA Astrophysics Data System (ADS)

Wang, Tao; Ottlé, Catherine; Boone, Aaron; Ciais, Philippe; Brun, Eric; Morin, Samuel; Krinner, Gerhard; Piao, Shilong; Peng, Shushi

2013-06-01

Snow plays an important role in land surface models (LSM) for climate and model applied over Fran studies, but its current treatment as a single layer of constant density and thermal conductivity in ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) induces significant deficiencies. The intermediate complexity snow scheme ISBA-ES (Interaction between Soil, Biosphere and Atmosphere-Explicit Snow) that includes key snow processes has been adapted and implemented into ORCHIDEE, referred to here as ORCHIDEE-ES. In this study, the adapted scheme is evaluated against the observations from the alpine site Col de Porte (CDP) with a continuous 18 year data set and from sites distributed in northern Eurasia. At CDP, the comparisons of snow depth, snow water equivalent, surface temperature, snow albedo, and snowmelt runoff reveal that the improved scheme in ORCHIDEE is capable of simulating the internal snow processes better than the original one. Preliminary sensitivity tests indicate that snow albedo parameterization is the main cause for the large difference in snow-related variables but not for soil temperature simulated by the two models. The ability of the ORCHIDEE-ES to better simulate snow thermal conductivity mainly results in differences in soil temperatures. These are confirmed by performing sensitivity analysis of ORCHIDEE-ES parameters using the Morris method. These features can enable us to more realistically investigate interactions between snow and soil thermal regimes (and related soil carbon decomposition). When the two models are compared over sites located in northern Eurasia from 1979 to 1993, snow-related variables and 20 cm soil temperature are better reproduced by ORCHIDEE-ES than ORCHIDEE, revealing a more accurate representation of spatio-temporal variability.

weather@home 2: validation of an improved global-regional climate modelling system

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

2017-05-01

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

Representation, Modeling and Recognition of Outdoor Scenes

DTIC Science & Technology

1994-04-01

B. C. Vemuri and R . Malladi . Deformable models: Canonical parameters for surface representation and multiple view integration. In Conference on...or a high disparity gradient. If both L- R and R -L disparity images are made available, then mirror images of this pattern may be sought in the two...et at., 1991, Terzopoulos and Vasilescu, 1991, Vemuri and Malladi , 1991], parameterized surfaces [Stokely and Wu, 1992, Lowe, 1991], local surfaces

Thalamocortical dynamics of the McCollough effect: boundary-surface alignment through perceptual learning.

PubMed

Grossberg, Stephen; Hwang, Seungwoo; Mingolla, Ennio

2002-05-01

This article further develops the FACADE neural model of 3-D vision and figure-ground perception to quantitatively explain properties of the McCollough effect (ME). The model proposes that many ME data result from visual system mechanisms whose primary function is to adaptively align, through learning, boundary and surface representations that are positionally shifted due to the process of binocular fusion. For example, binocular boundary representations are shifted by binocular fusion relative to monocular surface representations, yet the boundaries must become positionally aligned with the surfaces to control binocular surface capture and filling-in. The model also includes perceptual reset mechanisms that use habituative transmitters in opponent processing circuits. Thus the model shows how ME data may arise from a combination of mechanisms that have a clear functional role in biological vision. Simulation results with a single set of parameters quantitatively fit data from 13 experiments that probe the nature of achromatic/chromatic and monocular/binocular interactions during induction of the ME. The model proposes how perceptual learning, opponent processing, and habituation at both monocular and binocular surface representations are involved, including early thalamocortical sites. In particular, it explains the anomalous ME utilizing these multiple processing sites. Alternative models of the ME are also summarized and compared with the present model.

Hierarchical Organization of Auditory and Motor Representations in Speech Perception: Evidence from Searchlight Similarity Analysis.

PubMed

Evans, Samuel; Davis, Matthew H

2015-12-01

How humans extract the identity of speech sounds from highly variable acoustic signals remains unclear. Here, we use searchlight representational similarity analysis (RSA) to localize and characterize neural representations of syllables at different levels of the hierarchically organized temporo-frontal pathways for speech perception. We asked participants to listen to spoken syllables that differed considerably in their surface acoustic form by changing speaker and degrading surface acoustics using noise-vocoding and sine wave synthesis while we recorded neural responses with functional magnetic resonance imaging. We found evidence for a graded hierarchy of abstraction across the brain. At the peak of the hierarchy, neural representations in somatomotor cortex encoded syllable identity but not surface acoustic form, at the base of the hierarchy, primary auditory cortex showed the reverse. In contrast, bilateral temporal cortex exhibited an intermediate response, encoding both syllable identity and the surface acoustic form of speech. Regions of somatomotor cortex associated with encoding syllable identity in perception were also engaged when producing the same syllables in a separate session. These findings are consistent with a hierarchical account of how variable acoustic signals are transformed into abstract representations of the identity of speech sounds. © The Author 2015. Published by Oxford University Press.

Fast protein tertiary structure retrieval based on global surface shape similarity.

PubMed

Sael, Lee; Li, Bin; La, David; Fang, Yi; Ramani, Karthik; Rustamov, Raif; Kihara, Daisuke

2008-09-01

Characterization and identification of similar tertiary structure of proteins provides rich information for investigating function and evolution. The importance of structure similarity searches is increasing as structure databases continue to expand, partly due to the structural genomics projects. A crucial drawback of conventional protein structure comparison methods, which compare structures by their main-chain orientation or the spatial arrangement of secondary structure, is that a database search is too slow to be done in real-time. Here we introduce a global surface shape representation by three-dimensional (3D) Zernike descriptors, which represent a protein structure compactly as a series expansion of 3D functions. With this simplified representation, the search speed against a few thousand structures takes less than a minute. To investigate the agreement between surface representation defined by 3D Zernike descriptor and conventional main-chain based representation, a benchmark was performed against a protein classification generated by the combinatorial extension algorithm. Despite the different representation, 3D Zernike descriptor retrieved proteins of the same conformation defined by combinatorial extension in 89.6% of the cases within the top five closest structures. The real-time protein structure search by 3D Zernike descriptor will open up new possibility of large-scale global and local protein surface shape comparison. 2008 Wiley-Liss, Inc.

Incorporating JULES into NASA's Land Information System (LIS) and Investigations of Land-Atmosphere Coupling

NASA Technical Reports Server (NTRS)

Santanello, Joseph

2011-01-01

NASA's Land Information System (LIS; lis.gsfc.nasa.gov) is a flexible land surface modeling and data assimilation framework developed over the past decade with the goal of integrating satellite- and ground-based observational data products and advanced land surface modeling techniques to produce optimal fields of land surface states and fluxes. LIS features a high performance and flexible design, and operates on an ensemble of land surface models for extension over user-specified regional or global domains. The extensible interfaces of LIS allow the incorporation of new domains, land surface models (LSMs), land surface parameters, meteorological inputs, data assimilation and optimization algorithms. In addition, LIS has also been demonstrated for parameter estimation and uncertainty estimation, and has been coupled to the Weather Research and Forecasting (WRF) mesoscale model. A visiting fellowship is currently underway to implement JULES into LIS and to undertake some fundamental science on the feedbacks between the land surface and the atmosphere. An overview of the LIS system, features, and sample results will be presented in an effort to engage the community in the potential advantages of LIS-JULES for a range of applications. Ongoing efforts to develop a framework for diagnosing land-atmosphere coupling will also be presented using the suite of LSM and PBL schemes available in LIS and WRF along with observations from the U. S .. Southern Great Plains. This methodology provides a potential pathway to study factors controlling local land-atmosphere coupling (LoCo) using the LIS-WRF system, which will serve as a testbed for future experiments to evaluate coupling diagnostics within the community.

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Yang, Runhua; Houser, Paul R.

1998-01-01

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model.

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE PAGES

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai; ...

2016-07-14

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Estimating surface fluxes over middle and upper streams of the Heihe River Basin with ASTER imagery

NASA Astrophysics Data System (ADS)

Ma, W.; Ma, Y.; Hu, Z.; Su, Z.; Wang, J.; Ishikawa, H.

2011-05-01

Land surface heat fluxes are essential measures of the strengths of land-atmosphere interactions involving energy, heat and water. Correct parameterization of these fluxes in climate models is critical. Despite their importance, state-of-the-art observation techniques cannot provide representative areal averages of these fluxes comparable to the model grid. Alternative methods of estimation are thus required. These alternative approaches use (satellite) observables of the land surface conditions. In this study, the Surface Energy Balance System (SEBS) algorithm was evaluated in a cold and arid environment, using land surface parameters derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. Field observations and estimates from SEBS were compared in terms of net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λE) over a heterogeneous land surface. As a case study, this methodology was applied to the experimental area of the Watershed Allied Telemetry Experimental Research (WATER) project, located on the mid-to-upstream sections of the Heihe River in northwest China. ASTER data acquired between 3 May and 4 June 2008, under clear-sky conditions were used to determine the surface fluxes. Ground-based measurements of land surface heat fluxes were compared with values derived from the ASTER data. The results show that the derived surface variables and the land surface heat fluxes furnished by SEBS in different months over the study area are in good agreement with the observed land surface status under the limited cases (some cases looks poor results). So SEBS can be used to estimate turbulent heat fluxes with acceptable accuracy in areas where there is partial vegetation cover in exceptive conditions. It is very important to perform calculations using ground-based observational data for parameterization in SEBS in the future. Nevertheless, the remote-sensing results can provide improved explanations of land surface fluxes over varying land coverage at greater spatial scales.

More than a headcount: towards strategic stakeholder representation in catchment management in South Africa and Zimbabwe

NASA Astrophysics Data System (ADS)

Manzungu, Emmanuel

In 1998 both South Africa and Zimbabwe promulgated new water laws to ensure that ownership and user-ship patterns of water resources match the new socio-political order. Integrated water resource management, incorporating among other things decentralized and democratized water management institutions and the principles of stakeholder participation, was regarded as the cornerstone of the reforms. This article examines how stakeholder representation, particularly of the formerly disadvantaged people, has been handled. It is observed that there has been too much effort dedicated to ensure a mere headcount of the stakeholders at the water table rather than on strategic representation. Strategic representation emphasizes stakeholder identity instead of consensus. Selective alliance building is important as is establishing genuine local level platforms with enough political space outside the state-tailored formal straight jackets. It is equally important to address developmental aspects of establishing catchment-wide bodies and structural problems such as access to land and financial resources. Without addressing these issues stakeholder representation will remain hamstrung in good intentions.

A review of multimodel superensemble forecasting for weather, seasonal climate, and hurricanes

NASA Astrophysics Data System (ADS)

Krishnamurti, T. N.; Kumar, V.; Simon, A.; Bhardwaj, A.; Ghosh, T.; Ross, R.

2016-06-01

This review provides a summary of work in the area of ensemble forecasts for weather, climate, oceans, and hurricanes. This includes a combination of multiple forecast model results that does not dwell on the ensemble mean but uses a unique collective bias reduction procedure. A theoretical framework for this procedure is provided, utilizing a suite of models that is constructed from the well-known Lorenz low-order nonlinear system. A tutorial that includes a walk-through table and illustrates the inner workings of the multimodel superensemble's principle is provided. Systematic errors in a single deterministic model arise from a host of features that range from the model's initial state (data assimilation), resolution, representation of physics, dynamics, and ocean processes, local aspects of orography, water bodies, and details of the land surface. Models, in their diversity of representation of such features, end up leaving unique signatures of systematic errors. The multimodel superensemble utilizes as many as 10 million weights to take into account the bias errors arising from these diverse features of multimodels. The design of a single deterministic forecast models that utilizes multiple features from the use of the large volume of weights is provided here. This has led to a better understanding of the error growths and the collective bias reductions for several of the physical parameterizations within diverse models, such as cumulus convection, planetary boundary layer physics, and radiative transfer. A number of examples for weather, seasonal climate, hurricanes and sub surface oceanic forecast skills of member models, the ensemble mean, and the superensemble are provided.

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations

NASA Technical Reports Server (NTRS)

Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Harrison, Ken; Zhou, Shujia

2012-01-01

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Object view in spatial system dynamics: a grassland farming example

PubMed Central

Neuwirth, Christian; Hofer, Barbara; Schaumberger, Andreas

2016-01-01

Abstract Spatial system dynamics (SSD) models are typically implemented by linking stock variables to raster grids while the use of object representations of human artefacts such as buildings or ownership has been limited. This limitation is addressed by this article, which demonstrates the use of object representations in SSD. The objects are parcels of land that are attributed to grassland farms. The model simulates structural change in agriculture, i.e., change in the size of farms. The aim of the model is to reveal relations between structural change, farmland fragmentation and variable farmland quality. Results show that fragmented farms tend to become consolidated by structural change, whereas consolidated initial conditions result in a significant increase of fragmentation. Consolidation is reinforced by a dynamic land market and high transportation costs. The example demonstrates the capabilities of the object-based approach for integrating object geometries (parcel shapes) and relations between objects (distances between parcels) dynamically in SSD. PMID:28190972

Advanced Land Surface Processes in the Coupled WRF/CMAQ with MODIS Input

EPA Science Inventory

Land surface modeling (LSM) is important in WRF/CMAQ for simulating the exchange of heat, moisture, momentum, trace atmospheric chemicals, and windblown dust between the land surface and the atmosphere.? Vegetation and soil treatments are crucial in LSM for surface energy budgets...

Short-Term Retrospective Land Data Assimilation Schemes

NASA Technical Reports Server (NTRS)

Houser, P. R.; Cosgrove, B. A.; Entin, J. K.; Lettenmaier, D.; ODonnell, G.; Mitchell, K.; Marshall, C.; Lohmann, D.; Schaake, J. C.; Duan, Q.;

Expansion of oil palm and other cash crops causes an increase of the land surface temperature in the Jambi province in Indonesia

NASA Astrophysics Data System (ADS)

Sabajo, Clifton R.; le Maire, Guerric; June, Tania; Meijide, Ana; Roupsard, Olivier; Knohl, Alexander

2017-10-01

Indonesia is currently one of the regions with the highest transformation rate of land surface worldwide related to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many ecological functions. Despite the large historic land transformation in Indonesia toward oil palm and other cash crops and governmental plans for future expansion, this is the first study so far to quantify the impacts of land transformation on the LST in Indonesia. We analyze LST from the thermal band of a Landsat image and produce a high-resolution surface temperature map (30 m) for the lowlands of the Jambi province in Sumatra (Indonesia), a region which suffered large land transformation towards oil palm and other cash crops over the past decades. The comparison of LST, albedo, normalized differenced vegetation index (NDVI) and evapotranspiration (ET) between seven different land cover types (forest, urban areas, clear-cut land, young and mature oil palm plantations, acacia and rubber plantations) shows that forests have lower surface temperatures than the other land cover types, indicating a local warming effect after forest conversion. LST differences were up to 10.1 ± 2.6 °C (mean ± SD) between forest and clear-cut land. The differences in surface temperatures are explained by an evaporative cooling effect, which offsets the albedo warming effect. Our analysis of the LST trend of the past 16 years based on MODIS data shows that the average daytime surface temperature in the Jambi province increased by 1.05 °C, which followed the trend of observed land cover changes and exceeded the effects of climate warming. This study provides evidence that the expansion of oil palm plantations and other cash crops leads to changes in biophysical variables, warming the land surface and thus enhancing the increase of the air temperature because of climate change.

K-SPAN: A lexical database of Korean surface phonetic forms and phonological neighborhood density statistics.

PubMed

Holliday, Jeffrey J; Turnbull, Rory; Eychenne, Julien

2017-10-01

This article presents K-SPAN (Korean Surface Phonetics and Neighborhoods), a database of surface phonetic forms and several measures of phonological neighborhood density for 63,836 Korean words. Currently publicly available Korean corpora are limited by the fact that they only provide orthographic representations in Hangeul, which is problematic since phonetic forms in Korean cannot be reliably predicted from orthographic forms. We describe the method used to derive the surface phonetic forms from a publicly available orthographic corpus of Korean, and report on several statistics calculated using this database; namely, segment unigram frequencies, which are compared to previously reported results, along with segment-based and syllable-based neighborhood density statistics for three types of representation: an "orthographic" form, which is a quasi-phonological representation, a "conservative" form, which maintains all known contrasts, and a "modern" form, which represents the pronunciation of contemporary Seoul Korean. These representations are rendered in an ASCII-encoded scheme, which allows users to query the corpus without having to read Korean orthography, and permits the calculation of a wide range of phonological measures.

Comparison of two perturbation methods to estimate the land surface modeling uncertainty

NASA Astrophysics Data System (ADS)

Su, H.; Houser, P.; Tian, Y.; Kumar, S.; Geiger, J.; Belvedere, D.

2007-12-01

In land surface modeling, it is almost impossible to simulate the land surface processes without any error because the earth system is highly complex and the physics of the land processes has not yet been understood sufficiently. In most cases, people want to know not only the model output but also the uncertainty in the modeling, to estimate how reliable the modeling is. Ensemble perturbation is an effective way to estimate the uncertainty in land surface modeling, since land surface models are highly nonlinear which makes the analytical approach not applicable in this estimation. The ideal perturbation noise is zero mean Gaussian distribution, however, this requirement can't be satisfied if the perturbed variables in land surface model have physical boundaries because part of the perturbation noises has to be removed to feed the land surface models properly. Two different perturbation methods are employed in our study to investigate their impact on quantifying land surface modeling uncertainty base on the Land Information System (LIS) framework developed by NASA/GSFC land team. One perturbation method is the built-in algorithm named "STATIC" in LIS version 5; the other is a new perturbation algorithm which was recently developed to minimize the overall bias in the perturbation by incorporating additional information from the whole time series for the perturbed variable. The statistical properties of the perturbation noise generated by the two different algorithms are investigated thoroughly by using a large ensemble size on a NASA supercomputer and then the corresponding uncertainty estimates based on the two perturbation methods are compared. Their further impacts on data assimilation are also discussed. Finally, an optimal perturbation method is suggested.

Land surface phenology of Northeast China during 2000-2015: temporal changes and relationships with climate changes.

PubMed

Zhang, Yue; Li, Lin; Wang, Hongbin; Zhang, Yao; Wang, Naijia; Chen, Junpeng

2017-10-01

As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

Numerical evaluation of surface modifications at landing site due to spacecraft (soft) landing on the moon

NASA Astrophysics Data System (ADS)

Mishra, Sanjeev Kumar; Prasad, K. Durga

2018-07-01

Understanding surface modifications at landing site during spacecraft landing on planetary surfaces is important for planetary missions from scientific as well as engineering perspectives. An attempt has been made in this work to numerically investigate the disturbance caused to the lunar surface during soft landing. The variability of eject velocity of dust, eject mass flux rate, ejecta amount etc. has been studied. The effect of lander hovering time and hovering altitude on the extent of disturbance is also evaluated. The study thus carried out will help us in understanding the surface modifications during landing thereby making it easier to plan a descent trajectory that minimizes the extent of disturbance. The information about the extent of damage will also be helpful in interpreting the data obtained from experiments carried on the lunar surface in vicinity of the lander.

Land-use Scene Classification in High-Resolution Remote Sensing Images by Multiscale Deeply Described Correlatons

NASA Astrophysics Data System (ADS)

Qi, K.; Qingfeng, G.

2017-12-01

With the popular use of High-Resolution Satellite (HRS) images, more and more research efforts have been placed on land-use scene classification. However, it makes the task difficult with HRS images for the complex background and multiple land-cover classes or objects. This article presents a multiscale deeply described correlaton model for land-use scene classification. Specifically, the convolutional neural network is introduced to learn and characterize the local features at different scales. Then, learnt multiscale deep features are explored to generate visual words. The spatial arrangement of visual words is achieved through the introduction of adaptive vector quantized correlograms at different scales. Experiments on two publicly available land-use scene datasets demonstrate that the proposed model is compact and yet discriminative for efficient representation of land-use scene images, and achieves competitive classification results with the state-of-art methods.

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Di Vittorio, Alan V.; Kyle, Page; Collins, William D.

Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less

What are the effects of Agro-Ecological Zones and land use region boundaries on land resource projection using the Global Change Assessment Model?

DOE PAGES

Di Vittorio, Alan V.; Kyle, Page; Collins, William D.

2016-09-03

Understanding potential impacts of climate change is complicated by spatially mismatched land representations between gridded datasets and models, and land use models with larger regions defined by geopolitical and/or biophysical criteria. Here in this study, we quantify the sensitivity of Global Change Assessment Model (GCAM) outputs to the delineation of Agro-Ecological Zones (AEZs), which are normally based on historical (1961–1990) climate. We reconstruct GCAM's land regions using projected (2071–2100) climate, and find large differences in estimated future land use that correspond with differences in agricultural commodity prices and production volumes. Importantly, historically delineated AEZs experience spatially heterogeneous climate impacts overmore » time, and do not necessarily provide more homogenous initial land productivity than projected AEZs. Finally, we conclude that non-climatic criteria for land use region delineation are likely preferable for modeling land use change in the context of climate change, and that uncertainty associated with land delineation needs to be quantified.« less

Environmental assessment of spatial plan policies through land use scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geneletti, Davide, E-mail: davide.geneletti@ing.unitn.it

2012-01-15

This paper presents a method based on scenario analysis to compare the environmental effects of different spatial plan policies in a range of possible futures. The study aimed at contributing to overcome two limitations encountered in Strategic Environmental Assessment (SEA) for spatial planning: poor exploration of how the future might unfold, and poor consideration of alternative plan policies. Scenarios were developed through what-if functions and spatial modeling in a Geographical Information System (GIS), and consisted in maps that represent future land uses under different assumptions on key driving forces. The use of land use scenarios provided a representation of howmore » the different policies will look like on the ground. This allowed gaining a better understanding of the policies' implications on the environment, which could be measured through a set of indicators. The research undertook a case-study approach by developing and assessing land use scenarios for the future growth of Caia, a strategically-located and fast-developing town in rural Mozambique. The effects of alternative spatial plan policies were assessed against a set of environmental performance indicators, including deforestation, loss of agricultural land, encroachment of flood-prone areas and wetlands and access to water sources. In this way, critical environmental effects related to the implementation of each policy were identified and discussed, suggesting possible strategies to address them. - Graphical abstract: Display Omitted Research Highlights: Black-Right-Pointing-Pointer The method contributes to two critical issues in SEA: exploration of the future and consideration of alternatives. Black-Right-Pointing-Pointer Future scenarios are used to test the environmental performance of different spatial plan policies in uncertainty conditions. Black-Right-Pointing-Pointer Spatially-explicit land use scenarios provide a representation of how different policies will look like on the ground.« less

A Continental United States High Resolution NLCD Land Cover – MODIS Albedo Database to Examine Albedo and Land Cover Change Relationships

EPA Science Inventory

Surface albedo influences climate by affecting the amount of solar radiation that is reflected at the Earth’s surface, and surface albedo is, in turn, affected by land cover. General Circulation Models typically use modeled or prescribed albedo to assess the influence of land co...

Convective Cloud and Rainfall Processes Over the Maritime Continent: Simulation and Analysis of the Diurnal Cycle

NASA Astrophysics Data System (ADS)

Gianotti, Rebecca L.

The Maritime Continent experiences strong moist convection, which produces significant rainfall and drives large fluxes of heat and moisture to the upper troposphere. Despite the importance of these processes to global circulations, current predictions of climate change over this region are still highly uncertain, largely due to inadequate representation of the diurnally-varying processes related to convection. In this work, a coupled numerical model of the land-atmosphere system (RegCM3-IBIS) is used to investigate how more physically-realistic representations of these processes can be incorporated into large-scale climate models. In particular, this work improves simulations of convective-radiative feedbacks and the role of cumulus clouds in mediating the diurnal cycle of rainfall. Three key contributions are made to the development of RegCM3-IBIS. Two pieces of work relate directly to the formation and dissipation of convective clouds: a new representation of convective cloud cover, and a new parameterization of convective rainfall production. These formulations only contain parameters that can be directly quantified from observational data, are independent of model user choices such as domain size or resolution, and explicitly account for subgrid variability in cloud water content and nonlinearities in rainfall production. The third key piece of work introduces a new method for representation of cloud formation within the boundary layer. A comprehensive evaluation of the improved model was undertaken using a range of satellite-derived and ground-based datasets, including a new dataset from Singapore's Changi airport that documents diurnal variation of the local boundary layer height. The performance of RegCM3-IBIS with the new formulations is greatly improved across all evaluation metrics, including cloud cover, cloud liquid water, radiative fluxes and rainfall, indicating consistent improvement in physical realism throughout the simulation. This work demonstrates that: (1) moist convection strongly influences the near surface environment by mediating the incoming solar radiation and net radiation at the surface; (2) dissipation of convective cloud via rainfall plays an equally important role in the convectiveradiative feedback as the formation of that cloud; and (3) over parts of the Maritime Continent, rainfall is a product of diurnally-varying convective processes that operate at small spatial scales, on the order of 1 km. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Research priorities in land use and land-cover change for the Earth system and integrated assessment modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hibbard, Kathleen A.; Janetos, Anthony C.; Van Vuuren, Detlef

2010-11-15

This special issue has highlighted recent and innovative methods and results that integrate observations and AQ3 modelling analyses of regional to global aspect of biophysical and biogeochemical interactions of land-cover change with the climate system. Both the Earth System and the Integrated Assessment modeling communities recognize the importance of an accurate representation of land use and land-cover change to understand and quantify the interactions and feedbacks with the climate and socio-economic systems, respectively. To date, cooperation between these communities has been limited. Based on common interests, this work discusses research priorities in representing land use and land-cover change for improvedmore » collaboration across modelling, observing and measurement communities. Major research topics in land use and land-cover change are those that help us better understand (1) the interaction of land use and land cover with the climate system (e.g. carbon cycle feedbacks), (2) the provision of goods and ecosystem services by terrestrial (natural and anthropogenic) land-cover types (e.g. food production), (3) land use and management decisions and (4) opportunities and limitations for managing climate change (for both mitigation and adaptation strategies).« less

Landing Characteristics of a Lenticular-Shaped Reentry Vehicle

NASA Technical Reports Server (NTRS)

Blanchard, Ulysse J.

1961-01-01

An experimental investigation was made of the landing characteristics of a 1/9-scale dynamic model of a lenticular-shaped reentry vehicle having extendible tail panels for control after reentry and for landing control (flare-out). The landing tests were made by catapulting a free model onto a hard-surface runway and onto water. A "belly-landing" technique in which the vehicle was caused to skid and rock on its curved undersurface (heat shield), converting sinking speed into angular energy, was investigated on a hard-surface runway. Landings were made in calm water and in waves both with and without auxiliary landing devices. Landing motions and acceleration data were obtained over a range of landing attitudes and initial sinking speeds during hard-surface landings and for several wave conditions during water landings. A few vertical landings (parachute letdown) were made in calm water. The hard-surface landing characteristics were good. Maximum landing accelerations on a hard surface were 5g and 18 radians per sq second over a range of landing conditions. Horizontal landings on water resulted in large violent rebounds and some diving in waves. Extreme attitude changes during rebound at initial impact made the attitude of subsequent impact random. Maximum accelerations for water landings were approximately 21g and 145 radians per sq second in waves 7 feet high. Various auxiliary water-landing devices produced no practical improvement in behavior. Reduction of horizontal speed and positive control of impact attitude did improve performance in calm water. During vertical landings in calm water maximum accelerations of 15g and 110 radians per sq second were measured for a contact attitude of -45 deg and a vertical velocity of 70 feet per second.

Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Local control on precipitation in a fully coupled climate-hydrology model.

PubMed

Larsen, Morten A D; Christensen, Jens H; Drews, Martin; Butts, Michael B; Refsgaard, Jens C

2016-03-10

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies.

An object-mediated updating account of insensitivity to transsaccadic change

PubMed Central

Tas, A. Caglar; Moore, Cathleen M.; Hollingworth, Andrew

2012-01-01

Recent evidence has suggested that relatively precise information about the location and visual form of a saccade target object is retained across a saccade. However, this information appears to be available for report only when the target is removed briefly, so that the display is blank when the eyes land. We hypothesized that the availability of precise target information is dependent on whether a post-saccade object is mapped to the same object representation established for the presaccade target. If so, then the post-saccade features of the target overwrite the presaccade features, a process of object mediated updating in which visual masking is governed by object continuity. In two experiments, participants' sensitivity to the spatial displacement of a saccade target was improved when that object changed surface feature properties across the saccade, consistent with the prediction of the object-mediating updating account. Transsaccadic perception appears to depend on a mechanism of object-based masking that is observed across multiple domains of vision. In addition, the results demonstrate that surface-feature continuity contributes to visual stability across saccades. PMID:23092946

Local control on precipitation in a fully coupled climate-hydrology model

PubMed Central

Larsen, Morten A. D.; Christensen, Jens H.; Drews, Martin; Butts, Michael B.; Refsgaard, Jens C.

2016-01-01

The ability to simulate regional precipitation realistically by climate models is essential to understand and adapt to climate change. Due to the complexity of associated processes, particularly at unresolved temporal and spatial scales this continues to be a major challenge. As a result, climate simulations of precipitation often exhibit substantial biases that affect the reliability of future projections. Here we demonstrate how a regional climate model (RCM) coupled to a distributed hydrological catchment model that fully integrates water and energy fluxes between the subsurface, land surface, plant cover and the atmosphere, enables a realistic representation of local precipitation. Substantial improvements in simulated precipitation dynamics on seasonal and longer time scales is seen for a simulation period of six years and can be attributed to a more complete treatment of hydrological sub-surface processes including groundwater and moisture feedback. A high degree of local influence on the atmosphere suggests that coupled climate-hydrology models have a potential for improving climate projections and the results further indicate a diminished need for bias correction in climate-hydrology impact studies. PMID:26960564

Modeling snowmelt infiltration in seasonally frozen ground

NASA Astrophysics Data System (ADS)

Budhathoki, S.; Ireson, A. M.

2017-12-01

In cold regions, freezing and thawing of the soil govern soil hydraulic properties that shape the surface and subsurface hydrological processes. The partitioning of snowmelt into infiltration and runoff has also important implications for integrated water resource management and flood risk. However, there is an inadequate representation of the snowmelt infiltration into frozen soils in most land-surface and hydrological models, creating the need for improved models and methods. Here we apply, the Frozen Soil Infiltration Model, FroSIn, which is a novel algorithm for infiltration in frozen soils that can be implemented in physically based models of coupled flow and heat transport. In this study, we apply the model in a simple configuration to reproduce observations from field sites in the Canadian prairies, specifically St Denis and Brightwater Creek in Saskatchewan, Canada. We demonstrate the limitations of conventional approaches to simulate infiltration, which systematically over-predict runoff and under predict infiltration. The findings show that FroSIn enables models to predict more reasonable infiltration volumes in frozen soils, and also represent how infiltration-runoff partitioning is impacted by antecedent soil moisture.

A Four-parameter Budyko Equation for Mean Annual Water Balance

NASA Astrophysics Data System (ADS)

Tang, Y.; Wang, D.

2016-12-01

In this study, a four-parameter Budyko equation for long-term water balance at watershed scale is derived based on the proportionality relationships of the two-stage partitioning of precipitation. The four-parameter Budyko equation provides a practical solution to balance model simplicity and representation of dominated hydrologic processes. Under the four-parameter Budyko framework, the key hydrologic processes related to the lower bound of Budyko curve are determined, that is, the lower bound is corresponding to the situation when surface runoff and initial evaporation not competing with base flow generation are zero. The derived model is applied to 166 MOPEX watersheds in United States, and the dominant controlling factors on each parameter are determined. Then, four statistical models are proposed to predict the four model parameters based on the dominant controlling factors, e.g., saturated hydraulic conductivity, fraction of sand, time period between two storms, watershed slope, and Normalized Difference Vegetation Index. This study shows a potential application of the four-parameter Budyko equation to constrain land-surface parameterizations in ungauged watersheds or general circulation models.

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

NASA Technical Reports Server (NTRS)

Shaw, Michael; Kumar, Sujay V.; Peters-Lidard, Christa D.; Cetola, Jeffrey

2012-01-01

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours. AFWA recognizes the importance of operational benchmarking and uncertainty characterization for land surface modeling and is developing standard methods, software, and metrics to verify and/or validate LIS output products. To facilitate this and other needs for land analysis activities at AFWA, the Model Evaluation Toolkit (MET) -- a joint product of the National Center for Atmospheric Research Developmental Testbed Center (NCAR DTC), AFWA, and the user community -- and the Land surface Verification Toolkit (LVT), developed at the Goddard Space Flight Center (GSFC), have been adapted to operational benchmarking needs of AFWA's land characterization activities.

Generation of High Resolution Land Surface Parameters in the Community Land Model

NASA Astrophysics Data System (ADS)

Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.

2010-12-01

The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.

Assessment of Mars Exploration Rover Landing Site Predictions

NASA Astrophysics Data System (ADS)

Golombek, M. P.

2005-05-01

Comprehensive analyses of remote sensing data during the 3-year effort to select the Mars Exploration Rover landing sites at Gusev crater and Meridiani Planum correctly predicted the safe and trafficable surfaces explored by the two rovers. Gusev crater was predicted to be a relatively low relief surface that was comparably dusty, but less rocky than the Viking landing sites. Available data for Meridiani Planum indicated a very flat plain composed of basaltic sand to granules and hematite that would look completely unlike any of the existing landing sites with a dark, low albedo surface, little dust and very few rocks. Orbital thermal inertia measurements of 315 J m-2 s-0.5 K-1 at Gusev suggested surfaces dominated by duricrust to cemented soil-like materials or cohesionless sand or granules, which is consistent with observed soil characteristics and measured thermal inertias from the surface. THEMIS thermal inertias along the traverse at Gusev vary from 285 at the landing site to 330 around Bonneville rim and show systematic variations that can be related to the observed increase in rock abundance (5-30%). Meridiani has an orbital bulk inertia of ~200, similar to measured surface inertias that correspond to observed surfaces dominated by 0.2 mm sand size particles. Rock abundance derived from orbital thermal differencing techniques suggested that Meridiani Planum would have very low rock abundance, consistent with the rock free plain traversed by Opportunity. Spirit landed in an 8% orbital rock abundance pixel, consistent with the measured 7% of the surface covered by rocks >0.04 m diameter at the landing site, which is representative of the plains away from craters. The orbital albedo of the Spirit traverse varies from 0.19 to 0.30, consistent with surface measurements in and out of dust devil tracks. Opportunity is the first landing in a low albedo portion of Mars as seen from orbit, which is consistent with the dark, dust-free surface and measured albedos. The close correspondence between surface characteristics inferred from orbital remote sensing data and that found at the landing sites argues that future efforts to select safe landing sites will be successful. Linking the five landing sites to their remote sensing signatures suggests that they span most of the important, likely safe surfaces available for landing on Mars.

[A review on research of land surface water and heat fluxes].

PubMed

Sun, Rui; Liu, Changming

2003-03-01

Many field experiments were done, and soil-vegetation-atmosphere transfer(SVAT) models were stablished to estimate land surface heat fluxes. In this paper, the processes of experimental research on land surface water and heat fluxes are reviewed, and three kinds of SVAT model(single layer model, two layer model and multi-layer model) are analyzed. Remote sensing data are widely used to estimate land surface heat fluxes. Based on remote sensing and energy balance equation, different models such as simplified model, single layer model, extra resistance model, crop water stress index model and two source resistance model are developed to estimate land surface heat fluxes and evapotranspiration. These models are also analyzed in this paper.

Does surface roughness dominate biophysical forcing of land use and land cover change in the eastern United States?

NASA Astrophysics Data System (ADS)

Burakowski, E. A.; Tawfik, A. B.; Ouimette, A.; Lepine, L. C.; Ollinger, S. V.; Bonan, G. B.; Zarzycki, C. M.; Novick, K. A.

2016-12-01

Changes in land use, land cover, or both promote changes in surface temperature that can amplify or dampen long-term trends driven by natural and anthropogenic climate change by modifying the surface energy budget, primarily through differences in albedo, evapotranspiration, and aerodynamic roughness. Recent advances in variable resolution global models provide the tools necessary to investigate local and global impacts of land use and land cover change by embedding a high-resolution grid over areas of interest in a seamless and computationally efficient manner. Here, we used two eddy covariance tower clusters in the Eastern US (University of New Hampshire UNH and Duke Forest) to validate simulation of surface energy fluxes and properties by the uncoupled Community Land Model (PTCLM4.5) and coupled land-atmosphere Variable-Resolution Community Earth System Model (VR-CESM1.3). Surface energy fluxes and properties are generally well captured by the models for grassland sites, however forested sites tend to underestimate latent heat and overestimate sensible heat flux. Surface roughness emerged as the dominant biophysical forcing factor affecting surface temperature in the eastern United States, generally leading to warmer nighttime temperatures and cooler daytime temperatures. However, the sign and magnitude of the roughness effect on surface temperature was highly sensitive to the calculation of aerodynamic resistance to heat transfer.

Relationship Between Landcover Pattern and Surface Net Radiation in AN Coastal City

NASA Astrophysics Data System (ADS)

Zhao, X.; Liu, L.; Liu, X.; Zhao, Y.

2016-06-01

Taking Xiamen city as the study area this research first retrieved surface net radiation using meteorological data and Landsat 5 TM images of the four seasons in the year 2009. Meanwhile the 65 different landscape metrics of each analysis unit were acquired using landscape analysis method. Then the most effective landscape metrics affecting surface net radiation were determined by correlation analysis, partial correlation analysis, stepwise regression method, etc. At both class and landscape levels, this paper comprehensively analyzed the temporal and spatial variations of the surface net radiation as well as the effects of land cover pattern on it in Xiamen from a multi-seasonal perspective. The results showed that the spatial composition of land cover pattern shows significant influence on surface net radiation while the spatial allocation of land cover pattern does not. The proportions of bare land and forest land are effective and important factors which affect the changes of surface net radiation all the year round. Moreover, the proportion of forest land is more capable for explaining surface net radiation than the proportion of bare land. So the proportion of forest land is the most important and continuously effective factor which affects and explains the cross-seasonal differences of surface net radiation. This study is helpful in exploring the formation and evolution mechanism of urban heat island. It also gave theoretical hints and realistic guidance for urban planning and sustainable development.

In Situ SIMS and IR Spectroscopy of Well-defined Surfaces Prepared by Soft Landing of Mass-selected Ions

PubMed Central

Johnson, Grant E.; Gunaratne, K. Don Dasitha; Laskin, Julia

2014-01-01

Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+ (bpy = bipyridine), onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivity of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces. PMID:24961913

In Situ SIMS and IR Spectroscopy of Well-Defined Surfaces Prepared by Soft Landing of Mass-Selected Ions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Grant E.; Gunaratne, Kalupathirannehelage Don D.; Laskin, Julia

2014-06-16

Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+, onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivitymore » of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces.« less