Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balance

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-01-01

Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p < 0.01) in the Everglades of Florida over the years 1996-2001. The modeled monthly soil moisture for Illinois of the US agrees well (R2 = 0.79, p < 0.01) with the observed over the years 1984-2001. The modeled monthly stream flow for most 12 major rivers in the US is consistent R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficients >0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.

Meter-scale slopes of candidate MER landing sites from point photoclinometry

USGS Publications Warehouse

Beyer, R.A.; McEwen, A.S.; Kirk, R.L.

2003-01-01

Photoclinometry was used to analyze the small-scale roughness of areas that fall within the proposed Mars Exploration Rover (MER) 2003 landing ellipses. The landing ellipses presented in this study were those in Athabasca Valles, Elysium Planitia, Eos Chasma, Gusev Crater, Isidis Planitia, Melas Chasma, and Meridiani Planum. We were able to constrain surface slopes on length scales comparable to the image resolution (1.5 to 12 m/pixel). The MER 2003 mission has various engineering constraints that each candidate landing ellipse must satisfy. These constraints indicate that the statistical slope values at 5 m baselines are an important criterion. We used our technique to constrain maximum surface slopes across large swaths of each image, and built up slope statistics for the images in each landing ellipse. We are confident that all MER 2003 landing site ellipses in this study, with the exception of the Melas Chasma ellipse, are within the small-scale roughness constraints. Our results have provided input into the landing hazard assessment process. In addition to evaluating the safety of the landing sites, our mapping of small-scale roughnesses can also be used to better define and map morphologic units. The morphology of a surface is characterized by the slope distribution and magnitude of slopes. In looking at how slopes are distributed, we can better define landforms and determine the boundaries of morphologic units. Copyright 2003 by the American Geophysical Union.

Surface heterogeneity impacts on boundary layer dynamics via energy balance partitioning

USDA-ARS?s Scientific Manuscript database

The role of land-atmosphere interactions under heterogeneous surface conditions is investigated in order to identify mechanisms responsible for altering surface heat and moisture fluxes. Twelve coupled land surface – large eddy simulation scenarios with four different length scales of surface variab...

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.

Spatio-temporal patterns in land use and management affecting surface runoff response of agricultural catchments - a review

NASA Astrophysics Data System (ADS)

Fiener, P.; Auerswald, K.; van Oost, K.

2009-04-01

In many landscapes, land use creates a complex pattern in addition to the patterns resulting from soil, topography and rain. Despite the static layout of fields, a spatio-temporally highly variable situation regarding the surface runoff and erosion processes results from the asynchronous seasonal variation associated with different land uses. While the behaviour of individual land-uses and their seasonal variation is analyzed in many studies, the spatio-temporal interaction related to this pattern is rarely studied despite its crucial influence on hydrological and geomorphic response of catchments. The difficulty in studying such interactions mainly results from the fact that it is impossible to set up a replicated experiment on the landscape scale. The purpose of this review is to present the advances made thus far in quantifying the effects of patchiness of land use and management on surface runoff response in agricultural catchments. We will focus on the effects of spatio-temporal patterns in land use patches on hydraulic connectivity between patches and within catchments. This will include the temporal patterns in land management affecting infiltration, surface roughness and hence runoff concentration within single fields or land use patches insofar as these effects must be known to evaluate the combined effect of patch behaviour in space and time on catchment connectivity and surface runoff. Surface runoff effects of patchiness and connectivity between patches or within a catchment, can either be addressed by modelling studies or by comprehensive catchment field measurements, e.g. paired-watershed experiments or landscape scale studies on different scales. This limits our review to studies at the scale of small catchments < 10 km², where the time constant of the network (i.e. travel time through it) is smaller than the infiltration phase. Despite this limitation, these small catchments are important as they constitute 2/3 of the total surface of large water drainage networks.

The scaling of urban surface water abundance and impairment with city size

NASA Astrophysics Data System (ADS)

Steele, M. K.

2018-03-01

Urbanization alters surface water compared to nonurban landscapes, yet little is known regarding how basic aquatic ecosystem characteristics, such as the abundance and impairment of surface water, differ with population size or regional context. This study examined the abundance, scaling, and impairment of surface water by quantifying the stream length, water body area, and impaired stream length for 3520 cities in the United States with populations from 2500 to 18 million. Stream length, water body area, and impaired stream length were quantified using the National Hydrography Dataset and the EPA's 303(d) list. These metrics were scaled with population and city area using single and piecewise power-law models and related to biophysical factors (precipitation, topography) and land cover. Results show that abundance of stream length and water body area in cities actually increases with city area; however, the per person abundance decreases with population size. Relative to population, impaired stream length did not increase until city populations were > 25,000 people, then scaled linearly with population. Some variation in abundance and impairment was explained by biophysical context and land cover. Development intensity correlated with stream density and impairment; however, those relationships depended on the orientation of the land covers. When high intensity development occupied the local elevation highs (+ 15 m) and undeveloped land the elevation lows, the percentage of impaired streams was less than the opposite land cover orientation (- 15 m) or very flat land. These results show that surface water abundance and impairment across contiguous US cities are influenced by city size and by biophysical setting interacting with land cover intensity.

An Investigation of Land-Atmosphere Coupling from Local to Regional Scales

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Van Vleck, E.; Rahn, D. A.

2017-12-01

The exchanges of mass and energy between the surface and atmosphere have been shown to depend upon both local and regional climatic influences. However, the degree of control exerted by the land surface on the coupling metrics is not well understood. In particular, we lack an understanding of the relationship between the local microclimate of a site and the regional forces responsible for land-atmosphere coupling. To address this, we investigate a series of metrics calculated from eddy covariance data and ceilometer data, land surface modeling and remotely sensed observations in the central United States to diagnose these interactions and predict the change from one coupling regime (e.g. wet/dry coupling) to another state. The stability of the coupling is quantified using a Lyapunov exponent based methodology. Through the use of a wavelet information theoretic approach, we isolate the roles local energy partitioning, as well as the temperature and moisture gradients on controlling and changing the coupling regime. Taking a multi-scale observational approach, we first examine the relationship at the tower scale. Using land surface models, we quantify to what extent current models are capable of properly diagnosing the dynamics of the coupling regime. In particular, we focus on the role of the surface moisture and vegetation to initiate and maintain precipitation feedbacks. We extend this analysis to the regional scale by utilizing reanalysis and remotely sensed observations. Thus, we are able to quantify the changes in observed coupling patterns with linkages to local interactions to address the question of the local control that the surface exerts over the maintenance of land-atmosphere coupling.

The hydrological cycle at European Fluxnet sites: modeling seasonal water and energy budgets at local scale.

NASA Astrophysics Data System (ADS)

Stockli, R.; Vidale, P. L.

2003-04-01

The importance of correctly including land surface processes in climate models has been increasingly recognized in the past years. Even on seasonal to interannual time scales land surface - atmosphere feedbacks can play a substantial role in determining the state of the near-surface climate. The availability of soil moisture for both runoff and evapotranspiration is dependent on biophysical processes occuring in plants and in the soil acting on a wide time-scale from minutes to years. Fluxnet site measurements in various climatic zones are used to drive three generations of LSM's (land surface models) in order to assess the level of complexity needed to represent vegetation processes at the local scale. The three models were the Bucket model (Manabe 1969), BATS 1E (Dickinson 1984) and SiB 2 (Sellers et al. 1996). Evapotranspiration and runoff processes simulated by these models range from simple one-layer soils and no-vegetation parameterizations to complex multilayer soils, including realistic photosynthesis-stomatal conductance models. The latter is driven by satellite remote sensing land surface parameters inheriting the spatiotemporal evolution of vegetation phenology. In addition a simulation with SiB 2 not only including vertical water fluxes but also lateral soil moisture transfers by downslope flow is conducted for a pre-alpine catchment in Switzerland. Preliminary results are presented and show that - depending on the climatic environment and on the season - a realistic representation of evapotranspiration processes including seasonally and interannually-varying state of vegetation is significantly improving the representation of observed latent and sensible heat fluxes on the local scale. Moreover, the interannual evolution of soil moisture availability and runoff is strongly dependent on the chosen model complexity. Biophysical land surface parameters from satellite allow to represent the seasonal changes in vegetation activity, which has great impact on the yearly budget of transpiration fluxes. For some sites, however, the hydrological cycle is simulated reasonably well even with simple land surface representations.

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.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.; Li, J.; Du, Y.; Wen, J.; Zhong, B.; Wang, K.

2011-12-01

As the remote sensing data accumulating, it is a challenge and significant issue how to generate high accurate and consistent land surface parameter product from the multi source remote observation and the radiation transfer modeling and inversion methodology are the theoretical bases. In this paper, recent research advances and unresolved issues are presented. At first, after a general overview, recent research advances on multi-scale remote sensing radiation transfer modeling are presented, including leaf spectrum model, vegetation canopy BRDF models, directional thermal infrared emission models, rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed, taking the land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is suggested and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China are introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

[An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

PubMed

Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

2009-10-01

Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

The implementation and validation of improved land-surface hydrology in an atmospheric general circulation model

NASA Technical Reports Server (NTRS)

Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.

1993-01-01

New land-surface hydrologic parameterizations are implemented into the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: 1) runoff and evapotranspiration functions that include the effects of subgrid-scale spatial variability and use physically based equations of hydrologic flux at the soil surface and 2) a realistic soil moisture diffusion scheme for the movement of water and root sink in the soil column. A one-dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three-dimensional GCM. Results of the final simulation with the GISS GCM and the new land-surface hydrology indicate that the runoff rate, especially in the tropics, is significantly improved. As a result, the remaining components of the heat and moisture balance show similar improvements when compared to observations. The validation of model results is carried from the large global (ocean and land-surface) scale to the zonal, continental, and finally the regional river basin scales.

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.

Magnitude and variability of land evaporation and its components at the global scale

USDA-ARS?s Scientific Manuscript database

A physics-based methodology is applied to estimate global land-surface evaporation from multi-satellite observations. GLEAM (Global Land-surface Evaporation: the Amsterdam Methodology) combines a wide range of remotely sensed observations within a Priestley and Taylor-based framework. Daily actual e...

Modifying a dynamic global vegetation model for simulating large spatial scale land surface water balances

NASA Astrophysics Data System (ADS)

Tang, G.; Bartlein, P. J.

2012-08-01

Satellite-based data, such as vegetation type and fractional vegetation cover, are widely used in hydrologic models to prescribe the vegetation state in a study region. Dynamic global vegetation models (DGVM) simulate land surface hydrology. Incorporation of satellite-based data into a DGVM may enhance a model's ability to simulate land surface hydrology by reducing the task of model parameterization and providing distributed information on land characteristics. The objectives of this study are to (i) modify a DGVM for simulating land surface water balances; (ii) evaluate the modified model in simulating actual evapotranspiration (ET), soil moisture, and surface runoff at regional or watershed scales; and (iii) gain insight into the ability of both the original and modified model to simulate large spatial scale land surface hydrology. To achieve these objectives, we introduce the "LPJ-hydrology" (LH) model which incorporates satellite-based data into the Lund-Potsdam-Jena (LPJ) DGVM. To evaluate the model we ran LH using historical (1981-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells for the conterminous US and for the entire world using coarser climate and land cover data. We evaluated the simulated ET, soil moisture, and surface runoff using a set of observed or simulated data at different spatial scales. Our results demonstrate that spatial patterns of LH-simulated annual ET and surface runoff are in accordance with previously published data for the US; LH-modeled monthly stream flow for 12 major rivers in the US was consistent with observed values respectively during the years 1981-2006 (R2 > 0.46, p < 0.01; Nash-Sutcliffe Coefficient > 0.52). The modeled mean annual discharges for 10 major rivers worldwide also agreed well (differences < 15%) with observed values for these rivers. Compared to a degree-day method for snowmelt computation, the addition of the solar radiation effect on snowmelt enabled LH to better simulate monthly stream flow in winter and early spring for rivers located at mid-to-high latitudes. In addition, LH-modeled monthly soil moisture for the state of Illinois (US) agreed well (R2 = 0.79, p < 0.01) with observed data for the years 1984-2001. Overall, this study justifies both the feasibility of incorporating satellite-based land covers into a DGVM and the reliability of LH to simulate land-surface water balances. To better estimate surface/river runoff at mid-to-high latitudes, we recommended that LPJ-DGVM considers the effects of solar radiation on snowmelt.

Scaling water and energy fluxes in climate systems - Three land-atmospheric modeling experiments

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Lakshmi, Venkataraman

1993-01-01

Three numerical experiments that investigate the scaling of land-surface processes - either of the inputs or parameters - are reported, and the aggregated processes are compared to the spatially variable case. The first is the aggregation of the hydrologic response in a catchment due to rainfall during a storm event and due to evaporative demands during interstorm periods. The second is the spatial and temporal aggregation of latent heat fluxes, as calculated from SiB. The third is the aggregation of remotely sensed land vegetation and latent and sensible heat fluxes using TM data from the FIFE experiment of 1987 in Kansas. In all three experiments it was found that the surface fluxes and land characteristics can be scaled, and that macroscale models based on effective parameters are sufficient to account for the small-scale heterogeneities investigated.

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.

Coupled land surface/hydrologic/atmospheric models

NASA Technical Reports Server (NTRS)

Pielke, Roger; Steyaert, Lou; Arritt, Ray; Lahtakia, Mercedes; Smith, Chris; Ziegler, Conrad; Soong, Su Tzai; Avissar, Roni; Wetzel, Peter; Sellers, Piers

1993-01-01

The topics covered include the following: prototype land cover characteristics data base for the conterminous United States; surface evapotranspiration effects on cumulus convection and implications for mesoscale models; the use of complex treatment of surface hydrology and thermodynamics within a mesoscale model and some related issues; initialization of soil-water content for regional-scale atmospheric prediction models; impact of surface properties on dryline and MCS evolution; a numerical simulation of heavy precipitation over the complex topography of California; representing mesoscale fluxes induced by landscape discontinuities in global climate models; emphasizing the role of subgrid-scale heterogeneity in surface-air interaction; and problems with modeling and measuring biosphere-atmosphere exchanges of energy, water, and carbon on large scales.

Texture Modification of the Shuttle Landing Facility Runway at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Daugherty, Robert H.; Yager, Thomas J.

1997-01-01

This paper describes the test procedures and the criteria used in selecting an effective runway-surface-texture modification at the Kennedy Space Center (KSC) Shuttle Landing Facility (SLF) to reduce Orbiter tire wear. The new runway surface may ultimately result in an increase of allowable crosswinds for launch and landing operations. The modification allows launch and landing operations in 20-knot crosswinds, if desired. This 5-knot increase over the previous 15-knot limit drastically increases landing safety and the ability to make on-time launches to support missions in which Space Station rendezvous are planned. The paper presents the results of an initial (1988) texture modification to reduce tire spin-up wear and then describes a series of tests that use an instrumented ground-test vehicle to compare tire friction and wear characteristics, at small scale, of proposed texture modifications placed into the SLF runway surface itself. Based on these tests, three candidate surfaces were chosen to be tested at full-scale by using a highly modified and instrumented transport aircraft capable of duplicating full Orbiter landing profiles. The full-scale Orbiter tire testing revealed that tire wear could be reduced approximately by half with either of two candidates. The texture-modification technique using a Humble Equipment Company Skidabrader(trademark) shotpeening machine proved to be highly effective, and the entire SLF runway surface was modified in September 1994. The extensive testing and evaluation effort that preceded the selection of this particular surface-texture-modification technique is described herein.

Landing Characteristics of the Apollo Spacecraft with Deployed Heat Shield Impact Attenuation Systems

NASA Technical Reports Server (NTRS)

Stubbs, Sandy M.

1965-01-01

An experimental investigation was made to determine the landing characteristics of a 1/4-scale dynamic model of the Apollo spacecraft command module using two different active (heat shield deployed prior to landing) landing systems for impact attenuation. One landing system (configuration 1) consisted of six hydraulic struts and eight crushable honeycomb struts. The other landing system (configuration 2), consisted of four hydraulic struts and six strain straps. Tests made on water and the hard clay-gravel composite landing surfaces simulated parachute letdown (vertical) velocities of 23 ft/sec (7.0 m/s) (full scale). Landings made on the sand landing surface simulated vertical velocities of 30 ft/sec (9.1 m/s). Horizontal velocities of from 0 to 50 ft/sec (15 m/s) were simulated. Landing attitudes ranged from -30'degrees to 20 degrees, and the roll attitudes were O degrees, 90 degrees, and 180 degrees. For configuration 1, maximum normal accelerations at the vehicle center of gravity for landings on water, sand, and the hard clay-gravel composite surface were 9g, 20g, and 18g, respectively. The maximum normal center-of-gravity acceleration for configuration 2 which was landed only on the hard clay-gravel landing surface was approximately 19g. Accelerations for configuration 2 were generally equal to or lower than accelerations for configuration 1 and normal.

Research Advances on Radiation Transfer Modeling and Inversion for Multi-Scale Land Surface Remote Sensing

NASA Astrophysics Data System (ADS)

Liu, Q.

2011-09-01

At first, research advances on radiation transfer modeling on multi-scale remote sensing data are presented: after a general overview of remote sensing radiation transfer modeling, several recent research advances are presented, including leaf spectrum model (dPROS-PECT), vegetation canopy BRDF models, directional thermal infrared emission models(TRGM, SLEC), rugged mountains area radiation models, and kernel driven models etc. Then, new methodologies on land surface parameters inversion based on multi-source remote sensing data are proposed. The land surface Albedo, leaf area index, temperature/emissivity, and surface net radiation etc. are taken as examples. A new synthetic land surface parameter quantitative remote sensing product generation system is designed and the software system prototype will be demonstrated. At last, multi-scale field experiment campaigns, such as the field campaigns in Gansu and Beijing, China will be introduced briefly. The ground based, tower based, and airborne multi-angular measurement system have been built to measure the directional reflectance, emission and scattering characteristics from visible, near infrared, thermal infrared and microwave bands for model validation and calibration. The remote sensing pixel scale "true value" measurement strategy have been designed to gain the ground "true value" of LST, ALBEDO, LAI, soil moisture and ET etc. at 1-km2 for remote sensing product validation.

High resolution land surface response of inland moving Indian monsoon depressions over Bay of Bengal

NASA Astrophysics Data System (ADS)

Rajesh, P. V.; Pattnaik, S.

2016-05-01

During Indian summer monsoon (ISM) season, nearly about half of the monsoonal rainfall is brought inland by the low pressure systems called as Monsoon Depressions (MDs). These systems bear large amount of rainfall and frequently give copious amount of rainfall over land regions, therefore accurate forecast of these synoptic scale systems at short time scale can help in disaster management, flood relief, food safety. The goal of this study is to investigate, whether an accurate moisture-rainfall feedback from land surface can improve the prediction of inland moving MDs. High Resolution Land Data Assimilation System (HRLDAS) is used to generate improved land state .i.e. soil moisture and soil temperature profiles by means of NOAH-MP land-surface model. Validation of the model simulated basic atmospheric parameters at surface layer and troposphere reveals that the incursion of high resolution land state yields least Root Mean Squared Error (RMSE) with a higher correlation coefficient and facilitates accurate depiction of MDs. Rainfall verification shows that HRLDAS simulations are spatially and quantitatively in more agreement with the observations and the improved surface characteristics could result in the realistic reproduction of the storm spatial structure, movement as well as intensity. These results signify the necessity of investigating more into the land surface-rainfall feedbacks through modifications in moisture flux convergence within the storm.

DISAGGREGATION OF GOES LAND SURFACE TEMPERATURES USING SURFACE EMISSIVITY

USDA-ARS?s Scientific Manuscript database

Accurate temporal and spatial estimation of land surface temperatures (LST) is important for modeling the hydrological cycle at field to global scales because LSTs can improve estimates of soil moisture and evapotranspiration. Using remote sensing satellites, accurate LSTs could be routine, but unfo...

City landscape changes effects on land surface temperature in Bucharest metropolitan area

NASA Astrophysics Data System (ADS)

Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.; Dida, Adrian I.

2017-10-01

This study investigated the influences of city land cover changes and extreme climate events on land surface temperature in relationship with several biophysical variables in Bucharest metropolitan area of Romania through satellite and in-situ monitoring data. Remote sensing data from IKONOS, Landsat TM/ETM+ and time series MODIS Terra/Aqua and NOAA AVHRR sensors have been used to assess urban land cover- temperature interactions over 2000 - 2016 period. Time series Thermal InfraRed (TIR) satellite remote sensing data in synergy with meteorological data (air temperatureAT, precipitations, wind, solar radiation, etc.) were applied mainly for analyzing land surface temperature (LST) pattern and its relationship with surface landscape characteristics, assessing urban heat island (UHI), and relating urban land cover temperatures (LST). The land surface temperature, a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Results show that in the metropolitan area ratio of impervious surface in Bucharest increased significantly during investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, LST and AT possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at metropolitan scale respectively. The NDVI was significantly correlated with precipitation. The spatial average air temperatures in urban test areas rise with the expansion of the urban size.

Estimation of effective aerodynamic roughness with altimeter measurements

NASA Technical Reports Server (NTRS)

Menenti, M.; Ritchie, J. C.

1992-01-01

A new method is presented for estimating the aerodynamic roughness length of heterogeneous land surfaces and complex landscapes using elevation measurements performed with an airborne laser altimeter and the Seasat radar altimeter. Land surface structure is characterized at increasing length scales by considering three basic landscape elements: (1) partial to complete canopies of herbaceous vegetation; (2) sparse obstacles (e.g., shrubs and trees); and (3) local relief. Measured parameters of land surface geometry are combined to obtain an effective aerodynamic roughness length which parameterizes the total atmosphere-land surface stress.

The potential for agricultural land use change to reduce flood risk in a large watershed

USDA-ARS?s Scientific Manuscript database

Effects of agricultural land management practices on surface runoff are evident at local scales, but evidence for watershed-scale impacts is limited. In this study, we used the Soil and Water Assessment Tool model to assess changes in downstream flood risks under different land uses for the large, ...

Development and Implementation of the DTOPLATS-MP land surface model over the Continental US at 30 meters

NASA Astrophysics Data System (ADS)

Chaney, N.; Wood, E. F.

2014-12-01

The increasing accessibility of high-resolution land data (< 100 m) and high performance computing allows improved parameterizations of subgrid hydrologic processes in macroscale land surface models. Continental scale fully distributed modeling at these spatial scales is possible; however, its practicality for operational use is still unknown due to uncertainties in input data, model parameters, and storage requirements. To address these concerns, we propose a modeling framework that provides the spatial detail of a fully distributed model yet maintains the benefits of a semi-distributed model. In this presentation we will introduce DTOPLATS-MP, a coupling between the NOAH-MP land surface model and the Dynamic TOPMODEL hydrologic model. This new model captures a catchment's spatial heterogeneity by clustering high-resolution land datasets (soil, topography, and land cover) into hundreds of hydrologic similar units (HSUs). A prior DEM analysis defines the connections between each HSU. At each time step, the 1D land surface model updates each HSU; the HSUs then interact laterally via the subsurface and surface. When compared to the fully distributed form of the model, this framework allows a significant decrease in computation and storage while providing most of the same information and enabling parameter transferability. As a proof of concept, we will show how this new modeling framework can be run over CONUS at a 30-meter spatial resolution. For each catchment in the WBD HUC-12 dataset, the model is run between 2002 and 2012 using available high-resolution continental scale land and meteorological datasets over CONUS (dSSURGO, NLCD, NED, and NCEP Stage IV). For each catchment, the model is run with 1000 model parameter sets obtained from a Latin hypercube sample. This exercise will illustrate the feasibility of running the model operationally at continental scales while accounting for model parameter uncertainty.

Grand challenges in understanding the interplay of climate and land changes

USDA-ARS?s Scientific Manuscript database

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. After reviewing the status and major knowledge gap...

Broad Perspectives on Mars Landing Site Selection: Geological Factors from Centimeter to Kilometer Scales

NASA Technical Reports Server (NTRS)

Jakosky, B. M.; Golombek, M. P.

2001-01-01

Selection of a landing site for the '03 and later Mars surface missions represents a balance between potential science results and landing site safety. Although safety has to be the prime consideration, it is the melding together of spacecraft hazard analysis with science analysis that provides the key to understanding the nature of the surface for determining both its safety for landing and its scientific potential. Our goal here is to discuss the geological factors that go into a determination of site safety, at scales from centimeters up to kilometers, and to understand the implications for the resulting scientific return that can be expected.

High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis

2016-04-01

The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs (from a 4 km resolution simulation) for the recent past and the decennial projections. Evidently, these simulations lead to a first analysis of the impact of climate change on carbon stocks (e.g., biomass, soil carbon) and fluxes (e.g., gross and net primary productivities (GPP and NPP) and net ecosystem production (NEP)). The surface scheme is based on two land use/land cover databases, ECOPLAN for the Flemish region and, for the Walloon region, the COS-Wallonia database and the Belgian agricultural statistics for agricultural land. Land use and land cover are fixed through time (reference year: 2007) in these simulations, but a first attempt of coupling between CARAIB and CRAFTY will be made to establish dynamic land use change scenarios for the next decades. A simulation with variable land use would allow an analysis of land use change impacts not only on crop yields and the land carbon budget, but also on climate relevant parameters, such as surface albedo, roughness length and evapotranspiration towards a coupling with the RCM.

Regional Mapping of Coupled Fluxes of Carbon and Water Using Multi-Sensor Fusion Techniques

NASA Astrophysics Data System (ADS)

Schull, M. A.; Anderson, M. C.; Semmens, K. A.; Yang, Y.; Gao, F.; Hain, C.; Houborg, R.

2014-12-01

In an ever-changing climate there is an increasing need to measure the fluxes of water, energy and carbon for decision makers to implement policies that will help mitigate the effects of climate change. In an effort to improve drought monitoring, water resource management and agriculture assessment capabilities, a multi-scale and multi-sensor framework for routine mapping of land-surface fluxes of water and energy at field to regional scales has been established. The framework uses the ALEXI (Atmosphere Land Exchange Inverse)/DisALEXI (Disaggregated ALEXI) suite of land-surface models forced by remotely sensed data from Landsat, MODIS (MODerate resolution Imaging Spectroradiometer), and GOES (Geostationary Operational Environmental Satellite). Land-surface temperature (LST) can be an effective substitute for in-situ surface moisture observations and a valuable metric for constraining land-surface fluxes at sub-field scales. The adopted multi-scale thermal-based land surface modeling framework facilitates regional to local downscaling of water and energy fluxes by using a combination of shortwave reflective and thermal infrared (TIR) imagery from GOES (4-10 km; hourly), MODIS (1 km; daily), and Landsat (30-100 m; bi-weekly). In this research the ALEXI/DisALEXI modeling suite is modified to incorporate carbon fluxes using a stomatal resistance module, which replaces the Priestley-Taylor latent heat approximation. In the module, canopy level nominal light-use-efficiency (βn) is the parameter that modulates the flux of water and carbon in and out of the canopy. Leaf chlorophyll (Chl) is a key parameter for quantifying variability in photosynthetic efficiency to facilitate the spatial distribution of coupled carbon and water retrievals. Spatial distribution of Chl are retrieved from Landsat (30 m) using a surface reflectance dataset as input to the REGularized canopy reFLECtance (REGFLEC) tool. The modified ALEXI/DisALEXI suite is applied to regions of rain fed and irrigated soybean and maize agricultural landscapes within the continental U.S. and flux estimates are compared with flux tower observations.

Fractal topography and subsurface water flows from fluvial bedforms to the continental shield

USGS Publications Warehouse

Worman, A.; Packman, A.I.; Marklund, L.; Harvey, J.W.; Stone, S.H.

2007-01-01

Surface-subsurface flow interactions are critical to a wide range of geochemical and ecological processes and to the fate of contaminants in freshwater environments. Fractal scaling relationships have been found in distributions of both land surface topography and solute efflux from watersheds, but the linkage between those observations has not been realized. We show that the fractal nature of the land surface in fluvial and glacial systems produces fractal distributions of recharge, discharge, and associated subsurface flow patterns. Interfacial flux tends to be dominated by small-scale features while the flux through deeper subsurface flow paths tends to be controlled by larger-scale features. This scaling behavior holds at all scales, from small fluvial bedforms (tens of centimeters) to the continental landscape (hundreds of kilometers). The fractal nature of surface-subsurface water fluxes yields a single scale-independent distribution of subsurface water residence times for both near-surface fluvial systems and deeper hydrogeological flows. Copyright 2007 by the American Geophysical Union.

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.

Land Surface Verification Toolkit (LVT) - A Generalized Framework for Land Surface Model Evaluation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Peters-Lidard, Christa D.; Santanello, Joseph; Harrison, Ken; Liu, Yuqiong; Shaw, Michael

2011-01-01

Model evaluation and verification are key in improving the usage and applicability of simulation models for real-world applications. In this article, the development and capabilities of a formal system for land surface model evaluation called the Land surface Verification Toolkit (LVT) is described. LVT is designed to provide an integrated environment for systematic land model evaluation and facilitates a range of verification approaches and analysis capabilities. LVT operates across multiple temporal and spatial scales and employs a large suite of in-situ, remotely sensed and other model and reanalysis datasets in their native formats. In addition to the traditional accuracy-based measures, LVT also includes uncertainty and ensemble diagnostics, information theory measures, spatial similarity metrics and scale decomposition techniques that provide novel ways for performing diagnostic model evaluations. Though LVT was originally designed to support the land surface modeling and data assimilation framework known as the Land Information System (LIS), it also supports hydrological data products from other, non-LIS environments. In addition, the analysis of diagnostics from various computational subsystems of LIS including data assimilation, optimization and uncertainty estimation are supported within LVT. Together, LIS and LVT provide a robust end-to-end environment for enabling the concepts of model data fusion for hydrological applications. The evolving capabilities of LVT framework are expected to facilitate rapid model evaluation efforts and aid the definition and refinement of formal evaluation procedures for the land surface modeling community.

Assessing the long-term effects of land use changes on runoff patterns and food production in a large lake watershed with policy implications.

PubMed

Sun, Zhandong; Lotz, Tom; Chang, Ni-Bin

2017-12-15

Effects of land use development on runoff patterns are salient at a hydrological response unit scale. However, quantitative analysis at the watershed scale is still a challenge due to the complex spatial heterogeneity of the upstream and downstream hydrological relationships and the inherent structure of drainage systems. This study aims to use the well-calibrated Soil and Water Assessment Tool (SWAT) to assess the response of hydrological processes under different land use scenarios in a large lake watershed (Lake Dongting) in the middle Yangtze River basin in China. Based on possible land use changes, scale-dependent land use scenarios were developed and parameters embedded in SWAT were calibrated and validated for hydrological systems analysis. This approach leads to the simulation of the land use change impacts on the hydrological cycle. Results indicated that evapotranspiration, surface runoff, groundwater flow, and water yield were affected by the land use change scenarios in different magnitudes. Overall, changes of land use and land cover have significant impacts on runoff patterns at the watershed scale in terms of both the total water yield (i.e., groundwater flow, surface runoff, and interflow, minus transmission losses) and the spatial distribution of runoff. The changes in runoff distribution were resulted in opposite impacts within the two land use scenarios including forest and agriculture. Water yield has a decrease of 1.8 percent in the forest-prone landscape scenario and an increase of 4.2 percent in the agriculture-rich scenario during the simulated period. Surface runoff was the most affected component in the hydrological cycle. Whereas surface runoff as part of water yield has a decrease of 8.2 percent in the forest- prone landscape scenario, there is an increase of 8.6 percent in the agriculture-rich landscape scenario. Different runoff patterns associated with each land use scenario imply the potential effect on flood or drought mitigation policy. Based on the results, key areas were identified to show that hydrological extreme mitigation and flood control can be coordinated by some land use regulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

The effects of landscape cover on surface soils in a low density residential neighborhood in Baltimore, Maryland

Treesearch

Ian D. Yesilonis; R. V. Pouyat; J. Russell-Anelli; E. Powell

2016-01-01

Previous studies at the scale of a city have shown that surface soil nutrients, pH, and soil organic matter (SOM) can vary by land cover, land use, and management. This study was conducted in Baltimore County, Maryland, to quantify the differences in characteristics of soil in a residential neighborhood and adjacent forest patch sampling at a fine scale. The first...

Modeling Environmental Controls on Tree Water Use at Different Temporal scales

NASA Astrophysics Data System (ADS)

Guan, H.; Wang, H.; Simmons, C. T.

2014-12-01

Vegetation covers 70% of land surface, significantly influencing water and carbon exchange between land surface and the atmosphere. Vegetation transpiration (Et) contributes 80% of the global terrestrial evapotranspiration, making an adequate illustration of how important vegetation is to any hydrological or climatological applications. Transpiration can be estimated through upscaling from sap flow measurements on selected trees. Alternatively, transpiration (or tree water use for forests) can be correlated with environmental variables or estimated in land surface simulations in which a canopy conductance (gc) model is often used. Transpiration and canopy conductance are constrained by supply and demand control factors. Some previous studies estimated Et and gc considering the stresses from both the supply (soil water condition) and demand (e.g. temperature, vapor pressure deficit, solar radiation) factors, while some only considered the demand controls. In this study, we examined the performance of two types of models at daily and half-hourly scales for transpiration and canopy conductance modelling based on a native species in South Australia. The results show that the significance of soil water condition for Et and gc modelling varies with time scales. The model parameter values also vary across time scales. This result calls for attention in choosing models and parameter values for soil-plant-atmosphere continuum and land surface modeling.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

PubMed

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing

PubMed Central

Holl, Felix; Savory, David J.; Andrade-Pacheco, Ricardo; Gething, Peter W.; Bennett, Adam; Sturrock, Hugh J. W.

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth’s land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources. PMID:28953943

Characterizing Impacts of Land Grabbing on Terrestrial Vegetation and Ecohydrologic change in Mozambique through Multiple-sensor Remote Sensing and Models

NASA Astrophysics Data System (ADS)

Flores, A. N.; Lakshmi, V.; Al-Barakat, R.; Maksimowicz, M.

2017-12-01

Land grabbing, the acquisition of large areas of land by external entities, results from interactions of complex global economic, social, and political processes. These transactions are controversial because they can result in large-scale disruptions to historical land uses, including increased intensity of agricultural practices and significant conversions in land cover. These large-scale disruptions have the potential to impact surface water and energy balance because vegetation controls the partitioning of incoming energy into latent and sensible heat fluxes and precipitation into runoff and infiltration. Because large-scale land acquisitions can impact local ecosystem services, it is important to document changes in terrestrial vegetation associated with these acquisitions to support the assessment of associated impacts on regional surface water and energy balance, spatiotemporal scales of those changes, and interactions and feedbacks with other processes, particularly in the atmosphere. We use remote sensing data from multiple satellite platforms to diagnose and characterize changes in terrestrial vegetation and ecohydrology in Mozambique during periods that bracket periods associated with significant. The Advanced very High Resolution Radiometer (AVHRR) sensor provides long-term continuous data that can document historical seasonal cycles of vegetation greenness. These data are augmented with analyses from Landsat multispectral data, which provides significantly higher spatial resolution. Here we quantify spatiotemporal changes in vegetation are associated with periods of significant land acquisitions in Mozambique. This analysis complements a suite of land-atmosphere modeling experiments designed to deduce potential changes in land surface water and energy budgets associated with these acquisitions. This work advance understanding of how telecouplings between global economic and political forcings and regional hydrology and climate.

Radar characteristics of Viking 1 landing sites

USGS Publications Warehouse

Tyler, G.L.; Campbell, D.B.; Downs, G.S.; Green, R.R.; Moore, H.J.

1976-01-01

Radar observations of Mars at centimeter wavelengths in May, June, and July 1976 provided estimates of surface roughness and reflectivity in three potential landing areas for Viking 1. Surface roughness is characterized by the distribution of surface landing slopes or tilts on lateral scales of the order of 1 to 10 meters; measurements of surface reflectivity are indicators of bulk surface density in the uppermost few centimeters. By these measures, the Viking 1 landing site at 47.5??W, 22.4??N is rougher than the martian average, although it may be near the martian average for elevations accessible to Viking, and is estimated to be near the Mars average in reflectivity. The AINW site at the center of Chryse Planitia, 43.5??W, 23.4??N, may be an area of anomalous radar characteristics, indicative of extreme, small-scale roughness, very low surface density, or a combination of these two characteristics. Low signal-to-noise ratio observations of the original Chryse site at 34??W, 19.5??N indicate that that area is at least twice as rough as the Mars average.

Green Infrastructure and Watershed-Scale Hydrology in a Mixed Land Cover System

NASA Astrophysics Data System (ADS)

Hoghooghi, N.; Golden, H. E.; Bledsoe, B. P.

2017-12-01

Urbanization results in replacement of pervious areas (e.g., vegetation, topsoil) with impervious surfaces such as roads, roofs, and parking lots, which cause reductions in interception, evapotranspiration, and infiltration, and increases in surface runoff (overland flow) and pollutant loads and concentrations. Research on the effectiveness of different Green Infrastructure (GI), or Low Impact Development (LID), practices to reduce these negative impacts on stream flow and water quality has been mostly focused at the local scale (e.g., plots, small catchments). However, limited research has considered the broader-scale effects of LID, such as how LID practices influence water quantity, nutrient removal, and aquatic ecosystems at watershed scales, particularly in mixed land cover and land use systems. We use the Visualizing Ecosystem Land Management Assessments (VELMA) model to evaluate the effects of different LID practices on daily and long-term watershed-scale hydrology, including infiltration surface runoff. We focus on Shayler Crossing (SHC) watershed, a mixed land cover (61% urban, 24% agriculture, 15% forest) subwatershed of the East Fork Little Miami River watershed, Ohio, United States, with a drainage area of 0.94 km2. The model was calibrated to daily stream flow at the outlet of SHC watershed from 2009 to 2010 and was applied to evaluate diverse distributions (at 25% to 100% implementation levels) and types (e.g., pervious pavement and rain gardens) of LID across the watershed. Results show reduced surface water runoff and higher rates of infiltration concomitant with increasing LID implementation levels; however, this response varies between different LID practices. The highest magnitude response in streamflow at the watershed outlet is evident when a combination of LID practices is applied. The combined scenarios elucidate that the diverse watershed-scale hydrological responses of LID practices depend primarily on the type and extent of the implemented practices. Our work provides a key advancement toward improving current understanding of the effectiveness and efficiencies of LID approaches in mixed land cover watersheds.

Biophysical Impacts of Tropical Land Transformation from Forest to Oil Palm and Rubber Plantations in Indonesia

NASA Astrophysics Data System (ADS)

Knohl, Alexander; Meijide, Ana; Fan, Yuanchao; Gunawan, Dodo; Hölscher, Dirk; June, Tania; Niu, Furong; Panferov, Oleg; Ringeler, Andre; Röll, Alexander; Sabajo, Clifton; Tiralla, Nina

2016-04-01

Indonesia currently experiences rapid and large-scale land-use changes resulting in forest loss and the expansion of cash crop plantations such as oil palm and rubber. Such land transformations are associated with changes in surface properties that affect biophysical processes influencing the atmosphere. Yet, the overall effect of such land transformations on the atmosphere at local and regional scale remains unclear. In our study, we combine measurements of microclimate, transpiration via sap-flux, surface energy fluxes via eddy covariance, surface temperature via remote sensing, land surface (CLM) and regional climate modeling (WRF) for Jambi Province in Indonesia. Our microclimatic measurements showed that air temperature within the canopy was on average 0.7-0.8°C higher in monoculture plantations (oil palm and rubber) compared to forest. Remote sensing analysis using MODIS and Landsat revealed a higher canopy surface temperature for oil palm plantations (+1.5°C) compared to forest, but only little differences for rubber plantations. Transpiration (T) and evapotranspiration (ET) as well as the contribution of T to ET of oil palm showed a strong age-dependent increase. The sensible to latent heat flux ratio decreased with age. Overall, rubber plantations showed the lowest transpirations rates (320 mm year-1), oil palm intermediate rates (414 mm year-1), and forest the highest rates (558 mm year-1) indicating substantial differences in water use. Despite the differences in water use and the higher within-canopy and surface temperatures of the plantations compared to the forest, there was only a minor effect of land transformation on the atmosphere at the regional scale (<0.2 °C), irrespectively of the large spatial extend of the transformation. In conclusion, our study shows a strong local scale biophysical impact affecting the conditions at the stand level, which is however mitigated in the atmosphere at the regional level.

Biophysical Impacts of Tropical Land Transformation from Forest to Oil Palm and Rubber Plantations in Indonesia

NASA Astrophysics Data System (ADS)

Knohl, A.; Meijide, A.; Fan, Y.; Hölscher, D.; June, T.; Niu, F.; Panferov, O.; Ringeler, A.; Röll, A.; Sabajo, C.; Tiralla, N.

2015-12-01

Indonesia currently experiences rapid and large-scale land-use changes resulting in forest loss and the expansion of cash crop plantations such as oil palm and rubber. Such land transformations are associated with changes in surface properties that affect biophysical processes influencing the atmosphere. Yet, the overall effect of such land transformations on the atmosphere at local and regional scale remains unclear. In our study, we combine measurements of microclimate, transpiration via sap-flux, surface energy fluxes via eddy covariance, surface temperature via remote sensing, land surface (CLM) and regional climate modeling (WRF) for Jambi Province in Indonesia. Our microclimatic measurements showed that air temperature within the canopy was on average 0.7-0.8°C higher in monoculture plantations (oil palm and rubber) compared to forest. Remote sensing analysis using MODIS and Landsat revealed a higher canopy surface temperature for oil palm plantations (+1.5°C) compared to forest, but only little differences for rubber plantations. Transpiration (T) and evapotranspiration (ET) as well as the contribution of T to ET of oil palm showed a strong age-dependent increase. The sensible to latent heat flux ratio decreased with age. Overall, rubber plantations showed the lowest transpirations rates (320 mm year-1), oil palm intermediate rates (414 mm year-1), and forest the highest rates (558 mm year-1) indicating substantial differences in water use. Despite the differences in water use and the higher within-canopy and surface temperatures of the plantations compared to the forest, there was only a minor effect of land transformation on the atmosphere at the regional scale (<0.2 °C), irrespectively of the large spatial extend of the transformation. In conclusion, our study shows a strong local scale biophysical impact affecting the conditions at the stand level, which is however mitigated in the atmosphere at the regional level.

Bridging the Gap Between the iLEAPS and GEWEX Land-Surface Modeling Communities

NASA Technical Reports Server (NTRS)

Bonan, Gordon; Santanello, Joseph A., Jr.

2013-01-01

Models of Earth's weather and climate require fluxes of momentum, energy, and moisture across the land-atmosphere interface to solve the equations of atmospheric physics and dynamics. Just as atmospheric models can, and do, differ between weather and climate applications, mostly related to issues of scale, resolved or parameterised physics,and computational requirements, so too can the land models that provide the required surface fluxes differ between weather and climate models. Here, however, the issue is less one of scale-dependent parameterisations.Computational demands can influence other minor land model differences, especially with respect to initialisation, data assimilation, and forecast skill. However, the distinction among land models (and their development and application) is largely driven by the different science and research needs of the weather and climate communities.

Utility of a Two-source Energy Balance Approach for Daily Mapping of Landsat-scale Fluxes Over Irrigated Agriculture in a Desert Environment

NASA Astrophysics Data System (ADS)

Houborg, R.; McCabe, M. F.; Rosas Aguilar, J.; Anderson, M. C.; Hain, C.

2014-12-01

The Middle East and North Africa (MENA) region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. Enhanced satellite-based monitoring systems are needed for aiding local water resource and agricultural management activities in these data poor arid environments. A multi-sensor and multi-scale land-surface flux monitoring capacity is being implemented over parts of MENA in order to provide meaningful decision support at relevant spatiotemporal scales. The integrated modeling system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (Landsat and MODIS; MODerate resolution Imaging Spectroradiometer) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of land surface fluxes down to sub-field scale (i.e. 30 m). Within this modeling system, thermal infrared satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and error-prone soil surface characterizations. In this study, the integrated ALEXI-DisALEXI-STARFM framework is applied over an irrigated agricultural region in Saudi Arabia, and the daily estimates of Landsat scale water, energy and carbon fluxes are evaluated against available flux tower observations and other independent in-situ and satellite-based records. The study addresses the challenges associated with time-continuous sub-field scale mapping of land-surface fluxes in a harsh desert environment, and looks into the optimization of model descriptions and parameterizations and meteorological forcing and vegetation inputs for application over these regions.

Surface Mining and Reclamation Effects on Flood Response of Watersheds in the Central Appalachian Plateau Region

NASA Technical Reports Server (NTRS)

Ferrari, J. R.; Lookingbill, T. R.; McCormick, B.; Townsend, P. A.; Eshleman, K. N.

2009-01-01

Surface mining of coal and subsequent reclamation represent the dominant land use change in the central Appalachian Plateau (CAP) region of the United States. Hydrologic impacts of surface mining have been studied at the plot scale, but effects at broader scales have not been explored adequately. Broad-scale classification of reclaimed sites is difficult because standing vegetation makes them nearly indistinguishable from alternate land uses. We used a land cover data set that accurately maps surface mines for a 187-km2 watershed within the CAP. These land cover data, as well as plot-level data from within the watershed, are used with HSPF (Hydrologic Simulation Program-Fortran) to estimate changes in flood response as a function of increased mining. Results show that the rate at which flood magnitude increases due to increased mining is linear, with greater rates observed for less frequent return intervals. These findings indicate that mine reclamation leaves the landscape in a condition more similar to urban areas rather than does simple deforestation, and call into question the effectiveness of reclamation in terms of returning mined areas to the hydrological state that existed before mining.

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.

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.

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.;

Upscaling Empirically Based Conceptualisations to Model Tropical Dominant Hydrological Processes for Historical Land Use Change

NASA Astrophysics Data System (ADS)

Toohey, R.; Boll, J.; Brooks, E.; Jones, J.

2009-12-01

Surface runoff and percolation to ground water are two hydrological processes of concern to the Atlantic slope of Costa Rica because of their impacts on flooding and drinking water contamination. As per legislation, the Costa Rican Government funds land use management from the farm to the regional scale to improve or conserve hydrological ecosystem services. In this study, we examined how land use (e.g., forest, coffee, sugar cane, and pasture) affects hydrological response at the point, plot (1 m2), and the field scale (1-6ha) to empirically conceptualize the dominant hydrological processes in each land use. Using our field data, we upscaled these conceptual processes into a physically-based distributed hydrological model at the field, watershed (130 km2), and regional (1500 km2) scales. At the point and plot scales, the presence of macropores and large roots promoted greater vertical percolation and subsurface connectivity in the forest and coffee field sites. The lack of macropores and large roots, plus the addition of management artifacts (e.g., surface compaction and a plough layer), altered the dominant hydrological processes by increasing lateral flow and surface runoff in the pasture and sugar cane field sites. Macropores and topography were major influences on runoff generation at the field scale. Also at the field scale, antecedent moisture conditions suggest a threshold behavior as a temporal control on surface runoff generation. However, in this tropical climate with very intense rainstorms, annual surface runoff was less than 10% of annual precipitation at the field scale. Significant differences in soil and hydrological characteristics observed at the point and plot scales appear to have less significance when upscaled to the field scale. At the point and plot scales, percolation acted as the dominant hydrological process in this tropical environment. However, at the field scale for sugar cane and pasture sites, saturation-excess runoff increased as irrigation intensity and duration (e.g., quantity) increased. Upscaling our conceptual models to the watershed and regional scales, historical data (1970-2004) was used to investigate whether dominant hydrological processes changed over time due to land use change. Preliminary investigations reveal much higher runoff coefficients (<30%) at the larger watershed scales. The increase in importance of runoff at the larger geographic scales suggests an emerging process and process non-linearity between the smaller and larger scales. Upscaling is an important and useful concept when investigating catchment response using the tools of field work and/or physically distributed hydrological modeling.

Applications of Land Surface Temperature from Microwave Observations

USDA-ARS?s Scientific Manuscript database

Land surface temperature (LST) is a key input for physically-based retrieval algorithms of hydrological states and fluxes. Yet, it remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observation...

Mission to Earth: LANDSAT Views the World. [Color imagery of the earth's surface

NASA Technical Reports Server (NTRS)

Short, N. M.; Lowman, P. D., Jr.; Freden, S. C.; Finch, W. A., Jr.

1976-01-01

The LANDSAT program and system is described. The entire global land surface of Earth is visualized in 400 color plates at a scale and resolution that specify natural land cultural features in man's familiar environments. A glossary is included.

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

NASA Technical Reports Server (NTRS)

Shen, Suhung; Kempler, Steven J.; Gerasimov, Irina V.

2013-01-01

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

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.

Using microwave observations to estimate land surface temperature during cloudy conditions

USDA-ARS?s Scientific Manuscript database

Land surface temperature (LST), a key ingredient for physically-based retrieval algorithms of hydrological states and fluxes, remains a poorly constrained parameter for global scale studies. The main two observational methods to remotely measure T are based on thermal infrared (TIR) observations and...

A thermal-based remote sensing modeling system for estimating daily evapotranspiration from field to global scales

USDA-ARS?s Scientific Manuscript database

Thermal-infrared (TIR) remote sensing of land surface temperature (LST) provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition as well as providing useful information for constraining prognostic land surface models. This presentation d...

Utilization of data and modeling at multiple scales to compare varying formulations of the soil resistance term affecting evaporative flux from the soil surface.

NASA Astrophysics Data System (ADS)

Smits, K. M.; Forsythe, L.; Riley, W. J.; Bisht, G.

2016-12-01

Land Surface Models (LSMs) are used to predict heat, energy, and momentum fluxesoccurring at the land surface and the resulting effects in the soil and atmosphere at various scales.Evaporation from bare soil is an integral component of the water balance that is very difficult toaccurately predict since it is complexly affected by the coupled effects of atmospheric conditions andsoil properties. Inaccurate or simplifying assumptions can have drastic effects on regional and globalLSM predictions and cause available LSMs to predict conflicting values for the soil moistureconditions and surface fluxes (e.g. evapotranspiration, infiltration, run off). The goal of this work isto see how heterogeneities in soil properties can be properly represented with a soil resistance termthat accounts for physically based parameters of the soil system at the land-atmosphere interface.Utilizing a comprehensive, experimental dataset generated from a soil with known, heterogeneousproperties under highly controlled atmospheric conditions, we are able to compare the effectivenessof various parameterizations in two different models. The first being a multiphase, non-equilibrium,and non-isothermal model that minimizes the dependence on fitting parameters. The effects ofcertain mechanisms are better understood at this fine scale and incorporated into the land surfacecomponent of the Accelerated Climate Modeling for Energy project (ALM), which is focused oncapturing the interactions between the surface and the atmosphere at larger scales. The formulationsof the resistance parameter, soil water retention curve (SWRC), and diffusivity through partiallysaturated porous media are of particular interest. The fine scale model was used in conjunction withthe experimental data to test formulations before implementing them into the ACME Land Model(ALM). Effects of these alterations were compared to the existing mechanisms in ALM and thentested against lab and field scale data sets. Initial findings suggest the Tang and Riley (2013a) soilresistance more accurately reproduces results lab and field results on multiple scales whereheterogeneity is present. Further understanding of soil resistance will lead to more robust landsurface models which decrease the reliance on such empirical relationships.

Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

NASA Astrophysics Data System (ADS)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

Asian Monsoons: Variability, Predictability, and Sensitivity to External Forcing

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

1999-01-01

In this study, we have addressed the interannual variations of Asian monsoons including both broad-scale and regional monsoon components. Particular attention is devoted to the identities of the South China Sea monsoon and Indian monsoon. We use CPC Merged Analysis of Precipitation and NCEP reanalyses to define regional monsoon indices and to depict the various monsoons. Parallel modeling studies have also been carried out to assess the potential predictability of the broad-scale and regional monsoons. Each monsoon is characterized by its unique features. While the South Asian monsoon represents a classical monsoon in which anomalous circulation is governed by Rossby-wave dynamics, the Southeast Asian monsoon symbolizes a "hybrid" monsoon that features multi-cellular meridional circulation over eastern Asia. The broad-scale Asian monsoon links to the basin-wide atmospheric circulation over the Indian-Pacific oceans. Both Sea Surface Temperatures (SST) and land surface processes are important for determining the variations of all monsoons. For the broad-scale monsoon, SST anomalies are more important than land surface processes. However, for regional monsoons, land surface processes may become equally important. Both observation and model shows that the broad-scale monsoon is potentially more predictable than regional monsoons, and that the Southeast Asian monsoon may possess higher predictability than the South Asian monsoon.

Simulating fluxes from heterogeneous land surfaces: Explicit subgrid method employing the biosphere-atmosphere transfer scheme (BATS)

NASA Technical Reports Server (NTRS)

Seth, Anji; Giorgi, Filippo; Dickinson, Robert E.

1994-01-01

A vectorized version of the biosphere-atmosphere transfer scheme (VBATS) is used to study moisture, energy, and momentum fluxes from heterogeneous land surfaces st the scale of an atmospheric model (AM) grid cells. To incorporate subgrid scale inhomogeneity, VBATS includes two important features: (1) characterization of the land surface (vegetation and soil parameters) at N subgrid points within an AM grid cell and (2) explicit distribution of climate forcing (precipitation, clouds, etc.) over the subgrid. In this study, VBATS is used in stand-alone mode to simulate a single AM grid cell and to evaluate the effects of subgrid scale vegetation and climate specification on the surface fluxes and hydrology. It is found that the partitioning of energy can be affected by up to 30%, runoff by 50%, and surface stress in excess of 60%. Distributing climate forcing over the AM grid cell increases the Bowen ratio, as a result of enhanced sensible heat flux and reduced latent heat flux. The combined effect of heterogeneous vegetation and distribution of climate is found to be dependent on the dominat vegetation class in the AM grid cell. Development of this method is part of a larger program to explore the importance of subgrid scale processes in regional and global climate simulations.

MODIS Vegetative Cover Conversion and Vegetation Continuous Fields

NASA Astrophysics Data System (ADS)

Carroll, Mark; Townshend, John; Hansen, Matthew; DiMiceli, Charlene; Sohlberg, Robert; Wurster, Karl

Land cover change occurs at various spatial and temporal scales. For example, large-scale mechanical removal of forests for agro-industrial activities contrasts with the small-scale clearing of subsistence farmers. Such dynamics vary in spatial extent and rate of land conversion. Such changes are attributable to both natural and anthropogenic factors. For example, lightning- or human-ignited fires burn millions of acres of land surface each year. Further, land cover conversion requires ­contrasting with the land cover modification. In the first instance, the dynamic represents extensive categorical change between two land cover types. Land cover modification mechanisms such as selective logging and woody encroachment depict changes within a given land cover type rather than a conversion from one land cover type to another. This chapter describes the production of two standard MODIS land products used to document changes in global land cover. The Vegetative Cover Conversion (VCC) product is designed primarily to serve as a global alarm for areas where land cover change occurs rapidly (Zhan et al. 2000). The Vegetation Continuous Fields (VCF) product is designed to continuously ­represent ground cover as a proportion of basic vegetation traits. Terra's launch in December 1999 afforded a new opportunity to observe the entire Earth every 1.2 days at 250-m spatial resolution. The MODIS instrument's appropriate spatial and ­temporal resolutions provide the opportunity to substantially improve the characterization of the land surface and changes occurring thereupon (Townshend et al. 1991).

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, B.; Wang, J.; Ishikawa, H.

2009-06-01

Surface fluxes are important boundary conditions for climatological modeling and the Asian monsoon system. Recent availability of high-resolution, multi-band imagery from the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) sensor has enabled us to estimate surface fluxes to bridge the gap between local scale flux measurements using micrometeorological instruments and regional scale land-atmosphere exchanges of water and heat fluxes that are fundamental for the understanding of the water cycle in the Asian monsoon system. A Surface Energy Balance System (SEBS) method based on ASTER data and field observations has been proposed and tested for deriving net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λ E) over heterogeneous land surface in this paper. As a case study, the methodology was applied to the experimental area of the WATER (Watershed Allied Telemetry Experimental Research), located at the mid-to-upstream sections of the Heihe River, northwest China. The ASTER data of 3 May and 4 June in 2008 was used in this paper for the case of mid-to-upstream sections of the Heihe River Basin. To validate the proposed methodology, the ground-measured land surface heat fluxes (net radiation flux (Rn), soil heat flux (G0), sensible heat flux (H) and latent heat flux (λ E)) were compared to the ASTER derived values. The results show that the derived surface variables and land surface heat fluxes in different months over the study area are in good accordance with the land surface status. It is therefore concluded that the proposed methodology is successful for the retrieval of land surface heat fluxes using the ASTER data and filed observation over the study area.

Land surface phenological responses to land use and climate variation in a changing Central Asia

NASA Astrophysics Data System (ADS)

Kariyeva, Jahan

During the last few decades Central Asia has experienced widespread changes in land cover and land use following the socio-economic and institutional transformations of the region catalyzed by the USSR collapse in 1991. The decade-long drought events and steadily increasing temperature regimes in the region came on top of these institutional transformations, affecting the long term and landscape scale vegetation responses. This research is based on the need to better understand the potential ecological and policy implications of climate variation and land use practices in the contexts of landscape-scale changes dynamics and variability patterns of land surface phenology responses in Central Asia. The land surface phenology responses -- the spatio-temporal dynamics of terrestrial vegetation derived from the remotely sensed data -- provide measurements linked to the timing of vegetation growth cycles (e.g., start of growing season) and total vegetation productivity over the growing season, which are used as a proxy for the assessment of effects of variations in environmental settings. Local and regional scale assessment of the before and after the USSR collapse vegetation response patterns in the natural and agricultural systems of the Central Asian drylands was conducted to characterize newly emerging links (since 1991) between coupled human and natural systems, e.g., socio-economic and policy drivers of altered land and water use and distribution patterns. Spatio-temporal patterns of bioclimatic responses were examined to determine how phenology is associated with temperature and precipitation in different land use types, including rainfed and irrigated agricultural types. Phenological models were developed to examine relationship between environmental drivers and effect of their altitudinal and latitudinal gradients on the broad-scale vegetation response patterns in non-cropland ecosystems of the desert, steppe, and mountainous regional landscapes of Central Asia. The study results demonstrated that the satellite derived measurements of temporal cycles of vegetation greenness and productivity data was a valuable bioclimatic integrator of climatic and land use variation in Central Asia. The synthesis of broad-scale phenological changes in Central Asia showed that linkages of natural and human systems vary across space and time comprising complex and tightly integrated patterns and processes that are not evident when studied separately.

Land Capability Potential Index (LCPI) for the Lower Missouri River Valley

USGS Publications Warehouse

Jacobson, Robert B.; Chojnacki, Kimberly A.; Reuter, Joanna M.

2007-01-01

The Land Capability Potential Index (LCPI) was developed to serve as a relatively coarse-scale index to delineate broad land capability classes in the valley of the Lower Missouri River. The index integrates fundamental factors that determine suitability of land for various uses, and may provide a useful mechanism to guide land-management decisions. The LCPI was constructed from integration of hydrology, hydraulics, land-surface elevations, and soil permeability (or saturated hydraulic conductivity) datasets for an area of the Lower Missouri River, river miles 423–670. The LCPI estimates relative wetness based on intersecting water-surface elevations, interpolated from measurements or calculated from hydraulic models, with a high-resolution land-surface elevation dataset. The potential for wet areas to retain or drain water is assessed using soil-drainage classes that are estimated from saturated hydraulic conductivity of surface soils. Terrain mapping that delineates areas with convex, concave, and flat parts of the landscape provides another means to assess tendency of landscape patches to retain surface water.

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.

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.

A two stream radiative transfer model for scaling solar induced fluorescence from leaf to canopy

NASA Astrophysics Data System (ADS)

Quaife, T. L.

2017-12-01

Solar induced fluorescence (SIF) is becoming widely used as a proxy for gross primary productivity (GPP), in particular with the advent of its measurement by Earth Observation satellites such as OCO and GOSAT. A major attraction of SIF is that it is independent of the assumptions embedded in light use efficiency based GPP products derived from satellite missions such as MODIS. The assumptions in such products are likely not compatible with any given land surface model and hence comparing the two is problematic. On the other hand to compare land surface model predictions of GPP to satellite based SIF data requires either (a) translation of SIF into estimates of GPP, or (b) direct predictions of SIF from the land surface model itself. The former typically relies on empirical relationships, whereas the latter can make direct use of our physiological understanding of the link between photosynthesis and fluorescence at the leaf scale and is therefore preferable. Here I derive a two stream model for fluorescence that is capable of translating between leaf scale models of SIF and the canopy leaving radiance taking into account all levels of photon scattering. Other such models have been developed previously but the model described here is physically consistent with the Sellers' two stream radiative transfer scheme which is widely used in modern land surface models. Consequently any model that already employs the Sellers's scheme can use the new model without requiring modification. This includes, for example, JULES, the land surface model of the new UK Earth System Model (UKESM) and CLM, the US Community Land Model (part of the NCAR Earth System Model). The new canopy SIF model is extremely computationally efficient and can be applied to vertically inhomogeneous canopies.

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.

Multi-Annual Data Products on Turbulent Heat Fluxes at the Local and Continental Scale Using AATSR and FY-2 Data

NASA Astrophysics Data System (ADS)

Menenti, M.; Ghafarian, H.; Tang, B.; Faivre, R.; Colin, J.; Jia, L.; Roupios, L.

2013-01-01

This paper summarizes the results of studies carried in the framework of the Dragon 2 Program - Project 5322 Key Eco-Hydrological Parameters Retrieval and Land Data Assimilation System Development in a Typical Inland River Basin of Chinas Arid Region. The investigations were focused on monitoring the fluxes of energy and water at the land-atmosphere interface across a range of spatial scales, using multi-spectral radiometric data collected by space-borne imaging radiometers. At the local scale a new approach to parameterize heat and vapour fluxes was developed and applied using Computational Fluid Dynamics to describe state and dynamics of the boundary layer over the heterogeneous and 3D structured land surface. An airborne scanning LIDAR was used to capture in detail surface geometry. Over the large area of the Qinghai-Tibet Plateau a land-atmospheric model was used to characterize the atmospheric Planetary Boundary Layer. The effect of land surface heterogeneity and structure on the exchange of heat and water was captured using the bi-angular observations of brightness temperature provided by the AATSR imaging radiometer. The heat and water flux densities were calculated hourly with Feng-Yun C, D and E VISSR data over the Qinghai-Tibet Plateau and the headwaters of main rivers around it.

Weak Hydrological Sensitivity to Temperature Change over Land, Independent of Climate Forcing

NASA Technical Reports Server (NTRS)

Samset, B. H.; Myhre, G.; Forster, P. M.; Hodnebrog, O.; Andrews, T.; Boucher, O.; Faluvegi, G.; Flaeschner, D.; Kasoar, M.; Kharin, V.;

Estimation of Land Surface Temperature for the Quantitative Analysis of Land Cover of Lower Areas of Sindh to Assess the Impacts of Climate Variability

NASA Astrophysics Data System (ADS)

Qaisar, Maha

2016-07-01

Due to the present land use practices and climate variability, drastic shifts in regional climate and land covers are easily seen and their future reduction and gain are too well predicted. Therefore, there is an increasing need for data on land-cover changes at narrow and broad spatial scales. In this study, a remote sensing-based technique for land-cover-change analysis is applied to the lower Sindh areas for the last decade. Landsat satellite products were analyzed on an alternate yearly basis, from 1990 to 2016. Then Land-cover-change magnitudes were measured and mapped for alternate years. Land Surface Temperature (LST) is one of the critical elements in the natural phenomena of surface energy and water balance at local and global extent. However, LST was computed by using Landsat thermal bands via brightness temperature and a vegetation index. Normalized difference vegetation index (NDVI) was interpreted and maps were achieved. LST reflected NDVI patterns with complexity of vegetation patterns. Along with this, Object Based Image Analysis (OBIA) was done for classifying 5 major classes of water, vegetation, urban, marshy lands and barren lands with significant map layouts. Pakistan Meteorological Department provided the climate data in which rainfall, temperature and air temperature are included. Once the LST and OBIA are performed, overlay analysis was done to correlate the results of LST with OBIA and LST with meteorological data to ascertain the changes in land covers due to increasing centigrade of LST. However, satellite derived LST was also correlated with climate data for environmental analysis and to estimate Land Surface Temperature for assessing the inverse impacts of climate variability. This study's results demonstrate the land-cover changes in Lower Areas of Sindh including the Indus Delta mostly involve variations in land-cover conditions due to inter-annual climatic variability and temporary shifts in seasonality. However it is too concluded that transitory alteration of the biophysical characteristics of the surface driven by variations in rainfall is the prevailing progression. Moreover, future work will focus on finer-scale analysis and validations of patterns of changes due to rapid urbanization and population explosion in poverty stricken areas of Sindh which are posing an adverse impact on the land utilization and in turn increasing the land surface temperature and ultimately more stress on the low lying areas of Sindh i.e. Indus Delta will be losing its productivity and capacity to bear biodiversity whether the fauna or flora. Hence, this regional scale problem will become a global concern. Therefore, it is needed to stop the menace in its starting phase to mitigate the problem and to bring minds on this horrendous situation.

Analysis of Surface Heterogeneity Effects with Mesoscale Terrestrial Modeling Platforms

NASA Astrophysics Data System (ADS)

Simmer, C.

2015-12-01

An improved understanding of the full variability in the weather and climate system is crucial for reducing the uncertainty in weather forecasting and climate prediction, and to aid policy makers to develop adaptation and mitigation strategies. A yet unknown part of uncertainty in the predictions from the numerical models is caused by the negligence of non-resolved land surface heterogeneity and the sub-surface dynamics and their potential impact on the state of the atmosphere. At the same time, mesoscale numerical models using finer horizontal grid resolution [O(1)km] can suffer from inconsistencies and neglected scale-dependencies in ABL parameterizations and non-resolved effects of integrated surface-subsurface lateral flow at this scale. Our present knowledge suggests large-eddy-simulation (LES) as an eventual solution to overcome the inadequacy of the physical parameterizations in the atmosphere in this transition scale, yet we are constrained by the computational resources, memory management, big-data, when using LES for regional domains. For the present, there is a need for scale-aware parameterizations not only in the atmosphere but also in the land surface and subsurface model components. In this study, we use the recently developed Terrestrial Systems Modeling Platform (TerrSysMP) as a numerical tool to analyze the uncertainty in the simulation of surface exchange fluxes and boundary layer circulations at grid resolutions of the order of 1km, and explore the sensitivity of the atmospheric boundary layer evolution and convective rainfall processes on land surface heterogeneity.

Impacts of surface gold mining on land use systems in Western Ghana.

PubMed

Schueler, Vivian; Kuemmerle, Tobias; Schröder, Hilmar

2011-07-01

Land use conflicts are becoming increasingly apparent from local to global scales. Surface gold mining is an extreme source of such a conflict, but mining impacts on local livelihoods often remain unclear. Our goal here was to assess land cover change due to gold surface mining in Western Ghana, one of the world's leading gold mining regions, and to study how these changes affected land use systems. We used Landsat satellite images from 1986-2002 to map land cover change and field interviews with farmers to understand the livelihood implications of mining-related land cover change. Our results showed that surface mining resulted in deforestation (58%), a substantial loss of farmland (45%) within mining concessions, and widespread spill-over effects as relocated farmers expand farmland into forests. This points to rapidly eroding livelihood foundations, suggesting that the environmental and social costs of Ghana's gold boom may be much higher than previously thought.

Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

Generating multi-scale albedo look-up maps using MODIS BRDF/Albedo products and landsat imagery

USDA-ARS?s Scientific Manuscript database

Surface albedo determines radiative forcing and is a key parameter for driving Earth’s climate. Better characterization of surface albedo for individual land cover types can reduce the uncertainty in estimating changes to Earth’s radiation balance due to land cover change. This paper presents a mult...

Spatial scaling of net primary productivity using subpixel landcover information

NASA Astrophysics Data System (ADS)

Chen, X. F.; Chen, Jing M.; Ju, Wei M.; Ren, L. L.

2008-10-01

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. These biases result from overlooking subpixel variability of land surface characteristics. Vegetation heterogeneity is an important factor introducing biases in regional ecological modeling, especially when the modeling is made on large grids. This study suggests a simple algorithm that uses subpixel information on the spatial variability of land cover type to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. The algorithm operates in such a way that NPP obtained from calculations made at coarse spatial resolutions are multiplied by simple functions that attempt to reproduce the effects of subpixel variability of land cover type on NPP. Its application to a carbon-hydrology coupled model(BEPS-TerrainLab model) estimates made at a 1-km resolution over a watershed (named Baohe River Basin) located in the southwestern part of Qinling Mountains, Shaanxi Province, China, improved estimates of average NPP as well as its spatial variability.

Remote sensing of land surface phenology

USGS Publications Warehouse

Meier, G.A.; Brown, Jesslyn F.

2014-01-01

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

Functional Connectivity of Precipitation Networks in the Brazilian Rainforest-Savanna Transition Zone

NASA Astrophysics Data System (ADS)

Adera, S.; Larsen, L.; Levy, M. C.; Thompson, S. E.

2016-12-01

In the Brazilian rainforest-savanna transition zone, vegetation change has the potential to significantly affect precipitation patterns. Deforestation, in particular, can affect precipitation patterns by increasing land surface albedo, increasing aerosol loading to the atmosphere, changing land surface roughness, and reducing transpiration. Understanding land surface-precipitation couplings in this region is important not only for sustaining Amazon and Cerrado ecosystems, but also for cattle ranching and agriculture, hydropower generation, and drinking water management. Simulations suggest complex, scale-dependent interactions between precipitation and land cover. For example, the size and distribution of deforested patches has been found to affect precipitation patterns. We take an empirical approach to ask: (1) what are the dominant spatial and temporal length scales of precipitation coupling in the Brazilian rainforest-savanna transition zone? (2) How do these length scales change over time? (3) How does the connectivity of precipitation change over time? The answers to these questions will help address fundamental questions about the impacts of deforestation on precipitation. We use rain gauge data from 1100 rain gauges intermittently covering the period 1980 - 2013, a period of intensive land cover change in the region. The dominant spatial and temporal length scales of precipitation coupling are resolved using transfer entropy, a metric from information theory. Connectivity of the emergent network of couplings is quantified using network statistics. Analyses using transfer entropy and network statistics reveal the spatial and temporal interdependencies of rainfall events occurring in different parts of the study domain.

Land use, water and Mediterranean landscapes: modelling long-term dynamics of complex socio-ecological systems.

PubMed

Barton, C Michael; Ullah, Isaac I; Bergin, Sean

2010-11-28

The evolution of Mediterranean landscapes during the Holocene has been increasingly governed by the complex interactions of water and human land use. Different land-use practices change the amount of water flowing across the surface and infiltrating the soil, and change water's ability to move surface sediments. Conversely, water amplifies the impacts of human land use and extends the ecological footprint of human activities far beyond the borders of towns and fields. Advances in computational modelling offer new tools to study the complex feedbacks between land use, land cover, topography and surface water. The Mediterranean Landscape Dynamics project (MedLand) is building a modelling laboratory where experiments can be carried out on the long-term impacts of agropastoral land use, and whose results can be tested against the archaeological record. These computational experiments are providing new insights into the socio-ecological consequences of human decisions at varying temporal and spatial scales.

Accuracy assessment of land surface temperature retrievals from Landsat 7 ETM + in the Dry Valleys of Antarctica using iButton temperature loggers and weather station data.

PubMed

Brabyn, Lars; Zawar-Reza, Peyman; Stichbury, Glen; Cary, Craig; Storey, Bryan; Laughlin, Daniel C; Katurji, Marwan

2014-04-01

The McMurdo Dry Valleys of Antarctica are the largest snow/ice-free regions on this vast continent, comprising 1% of the land mass. Due to harsh environmental conditions, the valleys are bereft of any vegetation. Land surface temperature is a key determinate of microclimate and a driver for sensible and latent heat fluxes of the surface. The Dry Valleys have been the focus of ecological studies as they arguably provide the simplest trophic structure suitable for modelling. In this paper, we employ a validation method for land surface temperatures obtained from Landsat 7 ETM + imagery and compared with in situ land surface temperature data collected from four transects totalling 45 iButtons. A single meteorological station was used to obtain a better understanding of daily and seasonal cycles in land surface temperatures. Results show a good agreement between the iButton and the Landsat 7 ETM + product for clear sky cases. We conclude that Landsat 7 ETM + derived land surface temperatures can be used at broad spatial scales for ecological and meteorological research.

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Service (KMS)

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

SPoRT/SERVIR/RCMRD/KMS Collaboration: Builds off strengths of each organization. SPoRT: Transition of satellite, modeling and verification capabilities; SERVIR-Africa/RCMRD: International capacity-building expertise; KMS: Operational organization with regional weather forecasting expertise in East Africa. Hypothesis: Improved land-surface initialization over Eastern Africa can lead to better temperature, moisture, and ultimately precipitation forecasts in NWP models. KMS currently initializes Weather Research and Forecasting (WRF) model with NCEP/Global Forecast System (GFS) model 0.5-deg initial / boundary condition data. LIS will provide much higher-resolution land-surface data at a scale more representative to regional WRF configuration. Future implementation of real-time NESDIS/VIIRS vegetation fraction to further improve land surface representativeness.

Canopies to Continents: What spatial scales are needed to represent landcover distributions in earth system models?

NASA Astrophysics Data System (ADS)

Guenther, A. B.; Duhl, T.

2011-12-01

Increasing computational resources have enabled a steady improvement in the spatial resolution used for earth system models. Land surface models and landcover distributions have kept ahead by providing higher spatial resolution than typically used in these models. Satellite observations have played a major role in providing high resolution landcover distributions over large regions or the entire earth surface but ground observations are needed to calibrate these data and provide accurate inputs for models. As our ability to resolve individual landscape components improves, it is important to consider what scale is sufficient for providing inputs to earth system models. The required spatial scale is dependent on the processes being represented and the scientific questions being addressed. This presentation will describe the development a contiguous U.S. landcover database using high resolution imagery (1 to 1000 meters) and surface observations of species composition and other landcover characteristics. The database includes plant functional types and species composition and is suitable for driving land surface models (CLM and MEGAN) that predict land surface exchange of carbon, water, energy and biogenic reactive gases (e.g., isoprene, sesquiterpenes, and NO). We investigate the sensitivity of model results to landcover distributions with spatial scales ranging over six orders of magnitude (1 meter to 1000000 meters). The implications for predictions of regional climate and air quality will be discussed along with recommendations for regional and global earth system modeling.

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.

Observed increase in local cooling effect of deforestation at higher latitudes.

PubMed

Lee, Xuhui; Goulden, Michael L; Hollinger, David Y; Barr, Alan; Black, T Andrew; Bohrer, Gil; Bracho, Rosvel; Drake, Bert; Goldstein, Allen; Gu, Lianhong; Katul, Gabriel; Kolb, Thomas; Law, Beverly E; Margolis, Hank; Meyers, Tilden; Monson, Russell; Munger, William; Oren, Ram; Paw U, Kyaw Tha; Richardson, Andrew D; Schmid, Hans Peter; Staebler, Ralf; Wofsy, Steven; Zhao, Lei

2011-11-16

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo-sea ice feedback. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models. © 2011 Macmillan Publishers Limited. All rights reserved

Remote-sensing application for facilitating land resource assessment and monitoring for utility-scale solar energy development

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

Hamada, Yuki; Grippo, Mark A.

2015-01-01

A monitoring plan that incorporates regional datasets and integrates cost-effective data collection methods is necessary to sustain the long-term environmental monitoring of utility-scale solar energy development in expansive, environmentally sensitive desert environments. Using very high spatial resolution (VHSR; 15 cm) multispectral imagery collected in November 2012 and January 2014, an image processing routine was developed to characterize ephemeral streams, vegetation, and land surface in the southwestern United States where increased utility-scale solar development is anticipated. In addition to knowledge about desert landscapes, the methodology integrates existing spectral indices and transformation (e.g., visible atmospherically resistant index and principal components); a newlymore » developed index, erosion resistance index (ERI); and digital terrain and surface models, all of which were derived from a common VHSR image. The methodology identified fine-scale ephemeral streams with greater detail than the National Hydrography Dataset and accurately estimated vegetation distribution and fractional cover of various surface types. The ERI classified surface types that have a range of erosive potentials. The remote-sensing methodology could ultimately reduce uncertainty and monitoring costs for all stakeholders by providing a cost-effective monitoring approach that accurately characterizes the land resources at potential development sites.« less

Effect of spatial organisation behaviour on upscaling the overland flow formation in an arable land

NASA Astrophysics Data System (ADS)

Silasari, Rasmiaditya; Blöschl, Günter

2014-05-01

Overland flow during rainfall events on arable land is important to investigate as it affects the land erosion process and water quality in the river. The formation of overland flow may happen through different ways (i.e. Hortonian overland flow, saturation excess overland flow) which is influenced by the surface and subsurface soil characteristics (i.e. land cover, soil infiltration rate). As the soil characteristics vary throughout the entire catchment, it will form distinct spatial patterns with organised or random behaviour. During the upscaling of hydrological processes from plot to catchment scale, this behaviour will become substantial since organised patterns will result in higher spatial connectivity and thus higher conductivity. However, very few of the existing studies explicitly address this effect of spatial organisations of the patterns in upscaling the hydrological processes to the catchment scale. This study will assess the upscaling of overland flow formation with concerns of spatial organisation behaviour of the patterns by application of direct field observations under natural conditions using video camera and soil moisture sensors and investigation of the underlying processes using a physical-based hydrology model. The study area is a Hydrological Open Air Laboratory (HOAL) located at Petzenkirchen, Lower Austria. It is a 64 ha catchment with land use consisting of arable land (87%), forest (6%), pasture (5%) and paved surfaces (2%). A video camera is installed 7m above the ground on a weather station mast in the middle of the arable land to monitor the overland flow patterns during rainfall events in a 2m x 6m plot scale. Soil moisture sensors with continuous measurement at different depth (5, 10, 20 and 50cm) are installed at points where the field is monitored by the camera. The patterns of overland flow formation and subsurface flow state at the plot scale will be generated using a coupled surface-subsurface flow physical-based hydrology model. The observation data will be assimilated into the model to verify the corresponding processes between surface and subsurface flow during the rainfall events. The patterns of conductivity then will be analyzed at catchment scale using the spatial stochastic analysis based on the classification of soil characteristics of the entire catchment. These patterns of conductivity then will be applied in the model at catchment scale to see how the organisational behaviour can affect the spatial connectivity of the hydrological processes and the results of the catchment response. A detailed modelling of the underlying processes in the physical-based model will allow us to see the direct effect of the spatial connectivity to the occurring surface and subsurface flow. This will improve the analysis of the effect of spatial organisations of the patterns in upscaling the hydrological processes from plot to catchment scale.

Spatial Correlations of Anomaly Time Series of AIRS Version-6 Land Surface Skin Temperatures with the Nino-4 Index

NASA Technical Reports Server (NTRS)

Susskind, Joel; Lee, Jae N.; Iredell, Lena

2013-01-01

The AIRS Science Team Version-6 data set is a valuable resource for meteorological studies. Quality Controlled earth's surface skin temperatures are produced on a 45 km x 45 km spatial scale under most cloud cover conditions. The same retrieval algorithm is used for all surface types under all conditions. This study used eleven years of AIRS monthly mean surface skin temperature and cloud cover products to show that land surface skin temperatures have decreased significantly in some areas and increased significantly in other areas over the period September 2002 through August 2013. These changes occurred primarily at 1:30 PM but not at 1:30 AM. Cooling land areas contained corresponding increases in cloud cover over this time period, with the reverse being true for warming land areas. The cloud cover anomaly patterns for a given month are affected significantly by El Nino/La Nina activity, and anomalies in cloud cover are a driving force behind anomalies in land surface skin temperature.

Validation of Satellite Retrieved Land Surface Variables

NASA Technical Reports Server (NTRS)

Lakshmi, Venkataraman; Susskind, Joel

1999-01-01

The effective use of satellite observations of the land surface is limited by the lack of high spatial resolution ground data sets for validation of satellite products. Recent large scale field experiments include FIFE, HAPEX-Sahel and BOREAS which provide us with data sets that have large spatial coverage and long time coverage. It is the objective of this paper to characterize the difference between the satellite estimates and the ground observations. This study and others along similar lines will help us in utilization of satellite retrieved data in large scale modeling studies.

Estimating and validating surface energy fluxes at field scale over a heterogeneous land surfaces based on two-source energy balance model (TSEB)

USDA-ARS?s Scientific Manuscript database

Accurate estimation of surface energy fluxes at field scale over large areas has the potential to improve agricultural water management in arid and semiarid watersheds. Remote sensing may be the only viable approach for mapping fluxes over heterogeneous landscapes. The Two-Source Energy Balance mode...

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.

Challenges of model transferability to data-scarce regions (Invited)

NASA Astrophysics Data System (ADS)

Samaniego, L. E.

2013-12-01

Developing the ability to globally predict the movement of water on the land surface at spatial scales from 1 to 5 km constitute one of grand challenges in land surface modelling. Copying with this grand challenge implies that land surface models (LSM) should be able to make reliable predictions across locations and/or scales other than those used for parameter estimation. In addition to that, data scarcity and quality impose further difficulties in attaining reliable predictions of water and energy fluxes at the scales of interest. Current computational limitations impose also seriously limitations to exhaustively investigate the parameter space of LSM over large domains (e.g. greater than half a million square kilometers). Addressing these challenges require holistic approaches that integrate the best techniques available for parameter estimation, field measurements and remotely sensed data at their native resolutions. An attempt to systematically address these issues is the multiscale parameterisation technique (MPR) that links high resolution land surface characteristics with effective model parameters. This technique requires a number of pedo-transfer functions and a much fewer global parameters (i.e. coefficients) to be inferred by calibration in gauged basins. The key advantage of this technique is the quasi-scale independence of the global parameters which enables to estimate global parameters at coarser spatial resolutions and then to transfer them to (ungauged) areas and scales of interest. In this study we show the ability of this technique to reproduce the observed water fluxes and states over a wide range of climate and land surface conditions ranging from humid to semiarid and from sparse to dense forested regions. Results of transferability of global model parameters in space (from humid to semi-arid basins) and across scales (from coarser to finer) clearly indicate the robustness of this technique. Simulations with coarse data sets (e.g. EOBS forcing 25x25 km2, FAO soil map 1:5000000) using parameters obtained with high resolution information (REGNIE forcing 1x1 km2, BUEK soil map 1:1000000) in different climatic regions indicate the potential of MPR for prediction in data-scarce regions. In this presentation, we will also discuss how the transferability of global model parameters across scales and locations helps to identify deficiencies in model structure and regionalization functions.

Experimental study of the impact of large-scale wind farms on land-atmosphere exchanges

NASA Astrophysics Data System (ADS)

Zhang, wei; Markfort, Corey; Porté-Agel, Fernando

2013-04-01

Wind energy is one of the fastest growing sources of renewable energy world-wide, and it is expected that many more large-scale wind farms will be built and cover a significant portion of land and ocean surfaces. By extracting kinetic energy from the atmospheric boundary layer and converting it to electricity, wind farms may affect the transport of momentum, heat, moisture and trace gases (e.g. CO2) between the atmosphere and the land surface locally and globally. Understanding wind farm-atmosphere interactions and subsequent environmental impacts are complicated by the effects of turbine array configuration, wind farm size, land-surface characteristics and atmospheric thermal stability. In particular, surface scalar flux is influenced by wind farms and needs to be appropriately parameterized in meso-scale and/or high-resolution numerical models. Wind-tunnel experiments of model wind farms with perfectly aligned and staggered configurations, having the same turbine distribution density, were conducted in a neutral turbulent boundary layer with a surface heat source. Turbulent flow and fluxes over and through the wind farm were measured using a custom x-wire/cold-wire anemometer; and surface scalar flux was measured with an array of surface-mounted heat flux sensors within the quasi-developed flow regime. Although the overall surface heat flux change produced by the wind farms was found to be small, with a net reduction of 4% for the staggered wind farm and nearly zero for the aligned wind farm, the highly heterogeneous spatial distribution of the surface heat flux, dependent on wind farm layout, is significant. The difference between the minimum and maximum surface heat fluxes could be up to 12% and 7% in aligned and staggered wind farms, respectively. This finding is important for planning intensive agriculture practices and optimizing agricultural land use with regard to wind energy project development. The well-controlled wind-tunnel experiments presented here also provide a first comprehensive dataset on turbulent flow and scalar transport in wind farms, which can be further used to develop and validate new parameterizations for surface scalar fluxes in numerical models.

Spatial and Temporal Patterns of Dissolved Nitrogen and Phosphorus in Surface Waters of a Multi-Land Use Basin

EPA Science Inventory

Research on relationships between dissolved nutrients and land use at the watershed scale is a high priority for protecting surface water quality. We measured dissolved nitrogen (DN) and ortho-phosphorus (P) along 130 km of the Calapooia River (Oregon, USA) and 44 of its sub-bas...

Heat waves measured with MODIS land surface temperature data predict changes in avian community structure

Treesearch

Thomas P. Albright; Anna M. Pidgeon; Chadwick D. Rittenhouse; Murray K. Clayton; Curtis H. Flather; Patrick D. Culbert; Volker C. Radeloff

2011-01-01

Heat waves are expected to become more frequent and severe as climate changes, with unknown consequences for biodiversity. We sought to identify ecologically-relevant broad-scale indicators of heat waves based on MODIS land surface temperature (LST) and interpolated air temperature data and assess their associations with avian community structure. Specifically, we...

Bridging the Global Precipitation and Soil Moisture Active Passive Missions: Variability of Microwave Surface Emissivity from In situ and Remote Sensing Perspectives

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P.; Hong, Y.; Turk, J.

2016-12-01

The overland precipitation retrievals from satellite passive microwave (PMW) sensors such as the Global Precipitation Mission (GPM) microwave imager (GMI) are impacted by the land surface emissivity. The estimation of PMW emissivity faces challenges because it is highly variable under the influence of surface properties such as soil moisture, surface roughness and vegetation. This study proposes an improved quantitative understanding of the relationship between the emissivity and surface parameters. Surface parameter information is obtained through (i) in-situ measurements from the International Soil Moisture Network and (ii) satellite measurements from the Soil Moisture Active and Passive mission (SMAP) which provides global scale soil moisture estimates. The variation of emissivity is quantified with soil moisture, surface temperature and vegetation at various frequencies/polarization and over different types of land surfaces to sheds light into the processes governing the emission of the land. This analysis is used to estimate the emissivity under rainy conditions. The framework built with in-situ measurements serves as a benchmark for satellite-based analyses, which paves a way toward global scale emissivity estimates using SMAP.

Simulation and Analysis of Topographic Effect on Land Surface Albedo over Mountainous Areas

NASA Astrophysics Data System (ADS)

Hao, D.; Wen, J.; Xiao, Q.

2017-12-01

Land surface albedo is one of the significant geophysical variables affecting the Earth's climate and controlling the surface radiation budget. Topography leads to the formation of shadows and the redistribution of incident radiation, which complicates the modeling and estimation of the land surface albedo. Some studies show that neglecting the topography effect may lead to significant bias in estimating the land surface albedo for the sloping terrain. However, for the composite sloping terrain, the topographic effects on the albedo remain unclear. Accurately estimating the sub-topographic effect on the land surface albedo over the composite sloping terrain presents a challenge for remote sensing modeling and applications. In our study, we focus on the development of a simplified estimation method for land surface albedo including black-sky albedo (BSA) and white-sky albedo (WSA) of the composite sloping terrain at a kilometer scale based on the fine scale DEM (30m) and quantitatively investigate and understand the topographic effects on the albedo. The albedo is affected by various factors such as solar zenith angle (SZA), solar azimuth angle (SAA), shadows, terrain occlusion, and slope and aspect distribution of the micro-slopes. When SZA is 30°, the absolute and relative deviations between the BSA of flat terrain and that of rugged terrain reaches 0.12 and 50%, respectively. When the mean slope of the terrain is 30.63° and SZA=30°, the absolute deviation of BSA caused by SAA can reach 0.04. The maximal relative and relative deviation between the WSA of flat terrain and that of rugged terrain reaches 0.08 and 50%. These results demonstrate that the topographic effect has to be taken into account in the albedo estimation.

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.

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.

Runoff production in a small agricultural catchment in Lao PDR : influence of slope, land-use and observation scale.

NASA Astrophysics Data System (ADS)

Patin, J.; Ribolzi, O.; Mugler, C.; Valentin, C.; Mouche, E.

2009-04-01

We study the surface and sub-surface hydrology of a small agricultural catchment (60ha) located in the Luang Prabang province of Lao PDR. This catchment is representative of the rural mountainous south east Asia. It exhibits steep slopes (up to 100% and more) under a monsoon climate. After years of traditional slash and burn cultures, it is now under high land pressures due to population resettling and environment preservation policies. This evolution leads to rapid land-use changes such as shifting cultivation reduction or growing of teak forest instead of classical crops. This catchment is a benchmark site of the Managing Soil Erosion Consortium since 1998. The international consortium aims to understand the effects of agricultural changes on the catchment hydrology and soil erosion in south east Asia. The Huay Pano catchment is subdivided into small sub-catchments that are gauged and monitored. Differ- ent agricultural practices where tested along the years. At a smaller scale, plot of 1m2 are instrumented to follow runoff and detachment of soil under natural rainfall along the monsoon season. Our modeling work aims to develop a distributed hydrological model integrating experimental data at the different scales. One of the objective is to understand the impact of land-use, soil properties (slope, crust, etc) and rainfall (dry and wet seasons) on surface and subsurface flows. We present here modeling results of the runoff plot experiments (1m2 scale) performed from 2002 to 2007. The plots distribution among the catchment and over the years gives a good representativity of the different runoff responses. The role of crust, slope and land-use on runoff is examined. Finally we discuss how this plot scale will be integrated in a sub-catchment model, with a particular attention on the observed paradox: how to explain that runoff coefficients at the catchment scale are much slower than at the plot scale ?

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

NASA Astrophysics Data System (ADS)

Dong, Jingnuo; Ochsner, Tyson E.

2018-03-01

Soil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (˜1-100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic-ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12-32 km, 13-20 km, and 14-45 km, respectively. Soil moisture was more strongly correlated with sand content (r = -0.536 to -0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

Assessing Northern Hemisphere Land-Atmosphere Hotspots Using Dynamical Adjustment

NASA Astrophysics Data System (ADS)

Merrifield, Anna; Lehner, Flavio; Deser, Clara; Xie, Shang-Ping

2017-04-01

Understanding the influence of soil moisture on surface air temperature (SAT) is made more challenging by large-scale, internal atmospheric variability present in the midlatitude summer atmosphere. In this study, dynamical adjustment is used to characterize and remove summer SAT variability associated with large-scale circulation patterns in the Community Earth System Model large ensemble (CESM-LE). The adjustment is performed over North America and Europe with two different circulation indicators: sea level pressure (SLP) and 500mb height (Z500). The removal of dynamical "noise" leaves residual SAT variability in the central U.S. and Mediterranean regions identified as hotspots of land-atmosphere interaction (e.g. Koster et al. 2004, Seneviratne et al. 2006). The residual SAT variability "signal" is not clearly related to modes of sea surface temperature (SST) variability, but is related to local soil moisture, evaporative fraction, and radiation availability. These local relationships suggest that residual SAT variability is representative of the aggregate land surface signal. SLP dynamical adjustment removes ˜15% more variability in the central U.S. hotspot region than Z500 dynamical adjustment. Similar amounts of variability are removed by SLP and Z500 in the Mediterranean region. Differences in SLP and Z500 signal magnitude in the central U.S. are likely due to the modification of SLP by local land surface conditions, while the proximity of European hotspots to the Mediterranean sea mitigates the land surface influence. Variations in the Z500 field more closely resemble large-scale midlatitude circulation patterns and therefore Z500 may be a more suitable circulation indicator for summer dynamical adjustment. Changes in the residual SAT variability signal under increased greenhouse gas forcing will also be explored.

Drought and Heat Waves: The Role of SST and Land Surface Feedbacks

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2011-01-01

Drought occurs on a wide range of time scales, and within a variety of different types of regional climates. At the shortest time scales it is often associated with heat waves that last only several weeks to a few months but nevertheless can have profound detrimental impacts on society (e.g., heat-related impacts on human health, desiccation of croplands, increased fire hazard), while at the longest time scales it can extend over decades and can lead to long term structural changes in many aspects of society (e.g., agriculture, water resources, wetlands, tourism, population shifts). There is now considerable evidence that sea surface temperatures (SSTs) play a leading role in the development of drought world-wide, especially at seasonal and longer time scales, though land-atmosphere feedbacks can also play an important role. At shorter (subseasonal) time scales, SSTs are less important, but land feedbacks can play a critical role in maintaining and amplifying the atmospheric conditions associated with heat waves and short-term droughts. This talk reviews our current understanding of the physical mechanisms that drive precipitation and temperature variations on subseasonal to centennial time scales. This includes an assessment of predictability, prediction skill, and user needs at all time scales.

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).

A Lagrangian stochastic model to demonstrate multi-scale interactions between convection and land surface heterogeneity in the atmospheric boundary layer

NASA Astrophysics Data System (ADS)

Parsakhoo, Zahra; Shao, Yaping

2017-04-01

Near-surface turbulent mixing has considerable effect on surface fluxes, cloud formation and convection in the atmospheric boundary layer (ABL). Its quantifications is however a modeling and computational challenge since the small eddies are not fully resolved in Eulerian models directly. We have developed a Lagrangian stochastic model to demonstrate multi-scale interactions between convection and land surface heterogeneity in the atmospheric boundary layer based on the Ito Stochastic Differential Equation (SDE) for air parcels (particles). Due to the complexity of the mixing in the ABL, we find that linear Ito SDE cannot represent convections properly. Three strategies have been tested to solve the problem: 1) to make the deterministic term in the Ito equation non-linear; 2) to change the random term in the Ito equation fractional, and 3) to modify the Ito equation by including Levy flights. We focus on the third strategy and interpret mixing as interaction between at least two stochastic processes with different Lagrangian time scales. The model is in progress to include the collisions among the particles with different characteristic and to apply the 3D model for real cases. One application of the model is emphasized: some land surface patterns are generated and then coupled with the Large Eddy Simulation (LES).

Scaling up from field to region for wind erosion prediction using a field-scale wind erosion model and GIS

USGS Publications Warehouse

Zobeck, T.M.; Parker, N.C.; Haskell, S.; Guoding, K.

2000-01-01

Factors that affect wind erosion such as surface vegetative and other cover, soil properties and surface roughness usually change spatially and temporally at the field-scale to produce important field-scale variations in wind erosion. Accurate estimation of wind erosion when scaling up from fields to regions, while maintaining meaningful field-scale process details, remains a challenge. The objectives of this study were to evaluate the feasibility of using a field-scale wind erosion model with a geographic information system (GIS) to scale up to regional levels and to quantify the differences in wind erosion estimates produced by different scales of soil mapping used as a data layer in the model. A GIS was used in combination with the revised wind erosion equation (RWEQ), a field-scale wind erosion model, to estimate wind erosion for two 50 km2 areas. Landsat Thematic Mapper satellite imagery from 1993 with 30 m resolution was used as a base map. The GIS database layers included land use, soils, and other features such as roads. The major land use was agricultural fields. Data on 1993 crop management for selected fields of each crop type were collected from local government agency offices and used to 'train' the computer to classify land areas by crop and type of irrigation (agroecosystem) using commercially available software. The land area of the agricultural land uses was overestimated by 6.5% in one region (Lubbock County, TX, USA) and underestimated by about 21% in an adjacent region (Terry County, TX, USA). The total estimated wind erosion potential for Terry County was about four times that estimated for adjacent Lubbock County. The difference in potential erosion among the counties was attributed to regional differences in surface soil texture. In a comparison of different soil map scales in Terry County, the generalised soil map had over 20% more of the land area and over 15% greater erosion potential in loamy sand soils than did the detailed soil map. As a result, the wind erosion potential determined using the generalised soil map Was about 26% greater than the erosion potential estimated by using the detailed soil map in Terry County. This study demonstrates the feasibility of scaling up from fields to regions to estimate wind erosion potential by coupling a field-scale wind erosion model with GIS and identifies possible sources of error with this approach.

Soil Moisture Processes in the Near Surface Unsaturated Zone: Experimental Investigations in Multi-scale Test Systems

NASA Astrophysics Data System (ADS)

Illangasekare, T. H.; Sakaki, T.; Smits, K. M.; Limsuwat, A.; Terrés-Nícoli, J. M.

2008-12-01

Understanding the dynamics of soil moisture distribution near the ground surface is of interest in various applications involving land-atmospheric interaction, evaporation from soils, CO2 leakage from carbon sequestration, vapor intrusion into buildings, and land mine detection. Natural soil heterogeneity in combination with water and energy fluxes at the soil surface creates complex spatial and temporal distributions of soil moisture. Even though considerable knowledge exists on how soil moisture conditions change in response to flux and energy boundary conditions, emerging problems involving land atmospheric interactions require the quantification of soil moisture variability both at high spatial and temporal resolutions. The issue of up-scaling becomes critical in all applications, as in general, field measurements are taken at sparsely distributed spatial locations that require assimilation with measurements taken using remote sensing technologies. It is our contention that the knowledge that will contribute to both improving our understanding of the fundamental processes and practical problem solution cannot be obtained easily in the field due to a number of constraints. One of these basic constraints is the inability to make measurements at very fine spatial scales at high temporal resolutions in naturally heterogeneous field systems. Also, as the natural boundary conditions at the land/atmospheric interface are not controllable in the field, even in pilot scale studies, the developed theories and tools cannot be validated for the diversity of conditions that could be expected in the field. Intermediate scale testing using soil tanks packed to represent different heterogeneous test configurations provides an attractive and cost effective alternative to investigate a class of problems involving the shallow unsaturated zone. In this presentation, we will discuss the advantages and limitations of studies conducted in both two and three dimensional intermediate scale test systems together with instrumentation and measuring techniques. The features and capabilities of a new coupled porous media/climate wind tunnel test system that allows for the study of near surface unsaturated soil moisture conditions under climate boundary conditions will also be presented with the goal of exploring opportunities to use such a facility to study some of the multi-scale problems in the near surface unsaturated zone.

Hydrogeological controls of groundwater - land surface interactions

NASA Astrophysics Data System (ADS)

Bresciani, Etienne; Batelaan, Okke; Goderniaux, Pascal

2017-04-01

Interaction of groundwater with the land surface impacts a wide range of climatic, hydrologic, ecologic and geomorphologic processes. Many site-specific studies have successfully focused on measuring and modelling groundwater-surface water interaction, but upscaling or estimation at catchment or regional scale appears to be challenging. The factors controlling the interaction at regional scale are still poorly understood. In this contribution, a new 2-D (cross-sectional) analytical groundwater flow solution is used to derive a dimensionless criterion that expresses the conditions under which the groundwater outcrops at the land surface (Bresciani et al., 2016). The criterion gives insights into the functional relationships between geology, topography, climate and the locations of groundwater discharge along river systems. This sheds light on the debate about the topographic control of groundwater flow and groundwater-surface water interaction, as effectively the topography only influences the interaction when the groundwater table reaches the land surface. The criterion provides a practical tool to predict locations of groundwater discharge if a limited number of geomorphological and hydrogeological parameters (recharge, hydraulic conductivity and depth to impervious base) are known, and conversely it can provide regional estimates of the ratio of recharge over hydraulic conductivity if locations of groundwater discharge are known. A case study with known groundwater discharge locations located in South-West Brittany, France shows the feasibility of regional estimates of the ratio of recharge over hydraulic conductivity. Bresciani, E., Goderniaux, P. and Batelaan, O., 2016, Hydrogeological controls of water table-land surface interactions. Geophysical Research Letters 43(18): 9653-9661. http://dx.doi.org/10.1002/2016GL070618

A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

2011-01-01

Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

Impacts of land cover changes on climate trends in Jiangxi province China.

PubMed

Wang, Qi; Riemann, Dirk; Vogt, Steffen; Glaser, Rüdiger

2014-07-01

Land-use/land-cover (LULC) change is an important climatic force, and is also affected by climate change. In the present study, we aimed to assess the regional scale impact of LULC on climate change using Jiangxi Province, China, as a case study. To obtain reliable climate trends, we applied the standard normal homogeneity test (SNHT) to surface air temperature and precipitation data for the period 1951-1999. We also compared the temperature trends computed from Global Historical Climatology Network (GHCN) datasets and from our analysis. To examine the regional impacts of land surface types on surface air temperature and precipitation change integrating regional topography, we used the observation minus reanalysis (OMR) method. Precipitation series were found to be homogeneous. Comparison of GHCN and our analysis on adjusted temperatures indicated that the resulting climate trends varied slightly from dataset to dataset. OMR trends associated with surface vegetation types revealed a strong surface warming response to land barrenness and weak warming response to land greenness. A total of 81.1% of the surface warming over vegetation index areas (0-0.2) was attributed to surface vegetation type change and regional topography. The contribution of surface vegetation type change decreases as land cover greenness increases. The OMR precipitation trend has a weak dependence on surface vegetation type change. We suggest that LULC integrating regional topography should be considered as a force in regional climate modeling.

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Zaitchik, Benjamin F.; Rodell, Matt

2008-01-01

The NASA Gravity Recovery and Climate Experiment (GRACE) system of satellites provides observations of large-scale, monthly terrestrial water storage (TWS) changes. In. this presentation we describe a land data assimilation system that ingests GRACE observations and show that the assimilation improves estimates of water storage and fluxes, as evaluated against independent measurements. The ensemble-based land data assimilation system uses a Kalman smoother approach along with the NASA Catchment Land Surface Model (CLSM). We assimilated GRACE-derived TWS anomalies for each of the four major sub-basins of the Mississippi into the Catchment Land Surface Model (CLSM). Compared with the open-loop (no assimilation) CLSM simulation, assimilation estimates of groundwater variability exhibited enhanced skill with respect to measured groundwater. Assimilation also significantly increased the correlation between simulated TWS and gauged river flow for all four sub-basins and for the Mississippi River basin itself. In addition, model performance was evaluated for watersheds smaller than the scale of GRACE observations, in the majority of cases, GRACE assimilation led to increased correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications. We will also describe how the output from the GRACE land data assimilation system is now being prepared for use in the North American Drought Monitor.

Extratropical Respones to Amazon Deforestation

NASA Astrophysics Data System (ADS)

Badger, A.; Dirmeyer, P.

2014-12-01

Land-use change (LUC) is known to impact local climate conditions through modifications of land-atmosphere interactions. Large-scale LUC, such as Amazon deforestation, could have a significant effect on the local and regional climates. The question remains as to what the global impact of large-scale LUC could be, as previous modeling studies have shown non-local responses due to Amazon deforestation. A common shortcoming in many previous modeling studies is the use of prescribed ocean conditions, which can act as a boundary condition to dampen the global response with respect to changes in the mean and variability. Using fully coupled modeling simulations with the Community Earth System Model version 1.2.0, the Amazon rainforest has been replaced with a distribution of representative tropical crops. Through the modifications of local land-atmosphere interactions, a significant change in the region, both at the surface and throughout the atmosphere, can be quantified. Accompanying these local changes are significant changes to the atmospheric circulation across all scales, thus modifying regional climates in other locales. Notable impacts include significant changes in precipitation, surface fluxes, basin-wide sea surface temperatures and ENSO behavior.

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.

Influence of Idealized Heterogeneity on Wet and Dry Planetary Boundary Layers Coupled to the Land Surface. 1; Instantaneous Fields and Statistics

NASA Technical Reports Server (NTRS)

Houser, Paul (Technical Monitor); Patton, Edward G.; Sullivan, Peter P.; Moeng, Chin-Hoh

2003-01-01

This is the first in a two-part series of manuscripts describing numerical experiments on the influence of 2-30 km striplike heterogeneity on wet and dry boundary layers coupled to the land surface. The strip-like heterogeneity is shown to dramatically alter the structure of the free-convective boundary layer by inducing significant organized circulations that modify turbulent statistics. The coupling with the land-surface modifies the circulations compared to previous studies using fixed surface forcing. Total boundary layer turbulence kinetic energy increases significantly for surface heterogeneity at scales between Lambda/z(sub i) = 4 and 9, however entrainment rates for all cases are largely unaffected by the strip-like heterogeneity.

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.

Assimilation of Satellite-Derived Precipitation into the Regional Atmospheric Model System (RAMS): Its Impacts on the Weather and Hydrology in the Southwest United States

NASA Astrophysics Data System (ADS)

Yi, H.; Gao, X.; Sorooshian, S.

2002-05-01

As one aspect of the study of interactions between the atmosphere, vegetation, soil, and hydrology, there has been on going efforts to assimilate soil moisture data using coupled and uncoupled land surface-atmosphere hydrology models. The assimilation of soil moisture is expected to have influence due to its vital function in regulating runoff, partitioning latent and sensible heat, and through determining groundwater recharge. Soil moisture can provides long-term memory or persistence of the surface boundary condition, influencing large-scale atmospheric circulation over subsequent intervals. Now that the application of satellite remote sensing has become obvious to provide input parameters associated with land surface processes to the numerical models, this study utilizes remotely sensed precipitation data, PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) to assimilate soil moisture and other soil surface characteristics. Compared to the other earlier modeling experiments of seasonal or interannual temporal scale in continental or global spatial scale, this study investigates short term predictability in regional scale with the southwest United States as a study area, which has unique metrological and geographical features that provide special difficulties for mesoscale modeling. Research objectives are to assimilate the PERSIANN precipitation data into the mesoscale model for model initialization, examine the influence and memory of model precipitation errors on the land surface and atmospheric processes, and thereby study the short term predictability of meteorology and hydrology in the Southwest United States.

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.

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

Mapping Impervious Surfaces Globally at 30m Resolution Using Global Land Survey Data

NASA Technical Reports Server (NTRS)

DeColstoun, Eric Brown; Huang, Chengquan; Tan, Bin; Smith, Sarah Elizabeth; Phillips, Jacqueline; Wang, Panshi; Ling, Pui-Yu; Zhan, James; Li, Sike; Taylor, Michael P.;

Mapping Impervious Surfaces Globally at 30m Resolution Using Landsat Global Land Survey Data

NASA Astrophysics Data System (ADS)

Brown de Colstoun, E.; Huang, C.; Wolfe, R. E.; Tan, B.; Tilton, J.; Smith, S.; Phillips, J.; Wang, P.; Ling, P.; Zhan, J.; Xu, X.; Taylor, M. P.

2013-12-01

Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (~2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified archive of the National Geospatial Intelligence Agency (NGA). For each continental area several million training pixels are derived by analysts using image segmentation algorithms and tools and then aggregated to the 30m resolution of Landsat. Here we will discuss the production/testing of this massive data set for Europe, North and South America and Africa, including assessments of the 2010 surface reflectance data. This type of analysis is only possible because of the availability of long term 30m data sets from GLS and shows much promise for integration of Landsat 8 data in the future.

Global Modeling, Field Campaigns, Upscaling and Ray Desjardins

NASA Technical Reports Server (NTRS)

Sellers, P. J.; Hall, F. G.

2012-01-01

In the early 1980's, it became apparent that land surface radiation and energy budgets were unrealistically represented in Global Circulation models (GCM's), Shortly thereafter, it became clear that the land carbon budget was also poorly represented in Earth System Models (ESM's), A number of scientific communities, including GCM/ESM modelers, micrometeorologists, satellite data specialists and plant physiologists, came together to design field experiments that could be used to develop and validate the contemporary prototype land surface models. These experiments were designed to measure land surface fluxes of radiation, heat, water vapor and CO2 using a network of flux towers and other plot-scale techniques, coincident with satellite measurements of related state variables, The interdisciplinary teams involved in these experiments quickly became aware of the scale gap between plot-scale measurements (approx 10 - 100m), satellite measurements (100m - 10 km), and GCM grid areas (l0 - 200km). At the time, there was no established flux measurement capability to bridge these scale gaps. Then, a Canadian science learn led by Ray Desjardins started to actively participate in the design and execution of the experiments, with airborne eddy correlation providing the radically innovative bridge across the scale gaps, In a succession of brilliantly executed field campaigns followed up by convincing scientific analyses, they demonstrated that airborne eddy correlation allied with satellite data was the most powerful upscaling tool available to the community, The rest is history: the realism and credibility of weather and climate models has been enormously improved enormously over the last 25 years with immense benefits to the public and policymakers.

Global observation-based diagnosis of soil moisture control on land surface flux partition

NASA Astrophysics Data System (ADS)

Gallego-Elvira, Belen; Taylor, Christopher M.; Harris, Phil P.; Ghent, Darren; Veal, Karen L.; Folwell, Sonja S.

2016-04-01

Soil moisture plays a central role in the partition of available energy at the land surface between sensible and latent heat flux to the atmosphere. As soils dry out, evapotranspiration becomes water-limited ("stressed"), and both land surface temperature (LST) and sensible heat flux rise as a result. This change in surface behaviour during dry spells directly affects critical processes in both the land and the atmosphere. Soil water deficits are often a precursor in heat waves, and they control where feedbacks on precipitation become significant. State-of-the-art global climate model (GCM) simulations for the Coupled Model Intercomparison Project Phase 5 (CMIP5) disagree on where and how strongly the surface energy budget is limited by soil moisture. Evaluation of GCM simulations at global scale is still a major challenge owing to the scarcity and uncertainty of observational datasets of land surface fluxes and soil moisture at the appropriate scale. Earth observation offers the potential to test how well GCM land schemes simulate hydrological controls on surface fluxes. In particular, satellite observations of LST provide indirect information about the surface energy partition at 1km resolution globally. Here, we present a potentially powerful methodology to evaluate soil moisture stress on surface fluxes within GCMs. Our diagnostic, Relative Warming Rate (RWR), is a measure of how rapidly the land warms relative to the overlying atmosphere during dry spells lasting at least 10 days. Under clear skies, this is a proxy for the change in sensible heat flux as soil dries out. We derived RWR from MODIS Terra and Aqua LST observations, meteorological re-analyses and satellite rainfall datasets. Globally we found that on average, the land warmed up during dry spells for 97% of the observed surface between 60S and 60N. For 73% of the area, the land warmed faster than the atmosphere (positive RWR), indicating water stressed conditions and increases in sensible heat flux. Higher RWRs were observed for shorter vegetation and bare soil compared to tall, deep-rooted vegetation due to differences in both aerodynamic and hydrological properties. The variation of RWR with antecedent rainfall provides information on which evaporation regime a particular region lies in climatologically. Different drying stages for a given antecedent rainfall can thus be observed depending on land cover type. For instance, our results suggest that forests in a continental climate remain unstressed during a 10 day dry spell provided the previous month saw at least 95 mm of rain. Conversely, RWR values indicate that under similar conditions regions of grass/crop cover are water-stressed.

Validating Large Scale Networks Using Temporary Local Scale Networks

USDA-ARS?s Scientific Manuscript database

The USDA NRCS Soil Climate Analysis Network and NOAA Climate Reference Networks are nationwide meteorological and land surface data networks with soil moisture measurements in the top layers of soil. There is considerable interest in scaling these point measurements to larger scales for validating ...

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

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.

A Simple Downscaling Algorithm for Remotely Sensed Land Surface Temperature

NASA Astrophysics Data System (ADS)

Sandholt, I.; Nielsen, C.; Stisen, S.

2009-05-01

The method is illustrated using a combination of MODIS NDVI data with a spatial resolution of 250m and 3 Km Meteosat Second Generation SEVIRI LST data. Geostationary Earth Observation data carry a large potential for assessment of surface state variables. Not the least the European Meteosat Second Generation platform with its SEVIRI sensor is well suited for studies of the dynamics of land surfaces due to its high temporal frequency (15 minutes) and its red, Near Infrared (NIR) channels that provides vegetation indices, and its two split window channels in the thermal infrared for assessment of Land Surface Temperature (LST). For some applications the spatial resolution in geostationary data is too coarse. Due to the low statial resolution of 4.8 km at nadir for the SEVIRI sensor, a means of providing sub pixel information is sought for. By combining and properly scaling two types of satellite images, namely data from the MODIS sensor onboard the polar orbiting platforms TERRA and AQUA and the coarse resolution MSG-SEVIRI, we exploit the best from two worlds. The vegetation index/surface temperature space has been used in a vast number of studies for assessment of air temperature, soil moisture, dryness indices, evapotranspiration and for studies of land use change. In this paper, we present an improved method to derive a finer resolution Land Surface Temperature (LST). A new, deterministic scaling method has been applied, and is compared to existing deterministic downscaling methods based on LST and NDVI. We also compare our results from in situ measurements of LST from the Dahra test site in West Africa.

Observed increase in local cooling effect of deforestation at higher latitudes

Treesearch

Xuhui Lee; Michael L. Goulden; David Y. Hollinger; Alan Barr; T. Andrew Black; Gil Bohrer; Rosvel Bracho; Bert Drake; Allen Goldstein; Lianhong Gu; Gabriel Katul; Thomas Kolb; Beverly E. Law; Hank Margolis; Tilden Meyers; Russell Monson; William Munger; Ram Oren; Kyaw Tha Paw U; Andrew D. Richardson; Hans Peter Schmid; Ralf Staebler; Steven Wofsy; Lei Zhao

2011-01-01

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo–sea ice feedback. This feedback is crucial in the model predictions; without it...

Aircraft Observations of Soil Hydrological Influence on the Atmosphere in Northern India

NASA Astrophysics Data System (ADS)

Taylor, Christopher M.; Barton, Emma J.; Belusic, Danijel; Böing, Steven J.; Hunt, Kieran M. R.; Mitra, Ashis K.; Parker, Douglas J.; Turner, Andrew G.

2017-04-01

India is considered to be a region of the world where the influence of land surface fluxes of sensible and latent heat play an important role in regional weather and climate. Indian rainfall simulations in GCMs are known to be particularly sensitive to soil moisture. However, in a monsoon region where seasonal convective rainfall dominates, it is a big challenge for GCMs to capture, on the one hand, a realistic depiction of surface fluxes during wetting up and drying down at seasonal and sub-seasonal scales, and on the other, the sensitivity of convective rainfall and regional circulations to space-time fluctuations in land surface fluxes. On top of this, most GCMs and operational atmospheric forecast models don't explicitly consider irrigation. In the Indo-Gangetic plains of the Indian sub-continent, irrigated agriculture has become the dominant land use. Irrigation suppresses temporal flux variability for much of the year, and at the same time enhances spatial heterogeneity. One of the key objectives of the Anglo-Indian Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) collaborative project is to better understand the coupling between the land surface and the Indian summer monsoon, and build this understanding into improved prediction of rainfall on multiple time and space scales. During June and July 2016, a series of research flights was performed across the sub-continent using the NERC/Met Office BAe146 aircraft. Here we will present results for a case study from a flight on 30th June which sampled the Planetary Boundary Layer (PBL) on a 700 km low level transect, from the semi-arid region of Rajasthan eastwards into the extensively irrigated state of Uttar Pradesh. As well as crossing different land uses, the flight also sampled mesoscale regions with contrasting recent rainfall conditions. Here we will show how variations in surface hydrology, driven by both irrigation and rainfall, influence the temperature, humidity and winds in the PBL. These unique observations will provide a powerful tool for understanding the dominant land-atmosphere coupling mechanisms operating on a range of multiple length scales, and which help to shape the Indian monsoon.

Regional Climate Implications of Large-scale Cultivation of Biofuel Crops

NASA Astrophysics Data System (ADS)

Rowe, C. M.; Oglesby, R. J.; Hays, C. J.; van Etten, A. R.

2008-12-01

Conversion from corn-based ethanol to cellulosic ethanol has the potential to dramatically alter the production of biofuels in the United States and could result in large-scale changes in the agricultural landscape of vast areas of the country. Regions currently dominated by corn production could see widespread planting of switchgrass and other fast-growing, water-efficient sources of cellulose biomass. An often overlooked side effect of these land-cover changes could be a significant alteration of the energy fluxes between the land surface and the atmosphere with profound local, regional, and continental impacts on the climate system. Changes in the surface energy balance result primarily from differences in the seasonality of transpiration from corn versus switchgrass and could be enhanced as a result of a reduced need for irrigation of switchgrass in areas where corn can be produced only under irrigation. Preliminary modeling results using a simple "bucket" land surface model coupled to the WRF mesoscale model have demonstrated increases in summertime average daily maximum temperature of up to 4° C, smaller increases of up to 2° C in nighttime minimum temperatures and reductions in precipitation by up to 25% when corn was changed to switchgrass over the central United States. Improved parameterization of biofuel crops in more sophisticated land surface models will allow us to refine these preliminary estimates and assess the impacts of large-scale conversion to cellulosic biofuel crops, relative to greenhouse gas induced regional climate change.

Grand challenges in understanding the interplay of climate and land changes

USGS Publications Warehouse

Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; Ford, James D.; Fox, Andrew; Gallo, Kevin; Hatfield, Jerry L.; Henebry, Geoffrey M.; Huntington, Thomas G.; Liu, Zhihua; Loveland, Thomas R.; Norby, Richard J.; Sohl, Terry L.; Steiner, Allison L.; Yuan, Wenping; Zhang, Zhao; Zhao, Shuqing

2017-01-01

Half of 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 affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.

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.

Modeling large-scale human alteration of land surface hydrology and climate

NASA Astrophysics Data System (ADS)

Pokhrel, Yadu N.; Felfelani, Farshid; Shin, Sanghoon; Yamada, Tomohito J.; Satoh, Yusuke

2017-12-01

Rapidly expanding human activities have profoundly affected various biophysical and biogeochemical processes of the Earth system over a broad range of scales, and freshwater systems are now amongst the most extensively altered ecosystems. In this study, we examine the human-induced changes in land surface water and energy balances and the associated climate impacts using a coupled hydrological-climate model framework which also simulates the impacts of human activities on the water cycle. We present three sets of analyses using the results from two model versions—one with and the other without considering human activities; both versions are run in offline and coupled mode resulting in a series of four experiments in total. First, we examine climate and human-induced changes in regional water balance focusing on the widely debated issue of the desiccation of the Aral Sea in central Asia. Then, we discuss the changes in surface temperature as a result of changes in land surface energy balance due to irrigation over global and regional scales. Finally, we examine the global and regional climate impacts of increased atmospheric water vapor content due to irrigation. Results indicate that the direct anthropogenic alteration of river flow in the Aral Sea basin resulted in the loss of 510 km3 of water during the latter half of the twentieth century which explains about half of the total loss of water from the sea. Results of irrigation-induced changes in surface energy balance suggest a significant surface cooling of up to 3.3 K over 1° grids in highly irrigated areas but a negligible change in land surface temperature when averaged over sufficiently large global regions. Results from the coupled model indicate a substantial change in 2 m air temperature and outgoing longwave radiation due to irrigation, highlighting the non-local (regional and global) implications of irrigation. These results provide important insights on the direct human alteration of land surface water and energy balances, highlighting the need to incorporate human activities such as irrigation into the framework of global climate models and Earth system models for better prediction of future changes under increasing human influence and continuing global climate change.

Exploring Remote Sensing Products Online with Giovanni for Studying Urbanization

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory G.; Gerasimov, Irina; Kempler, Steve

2012-01-01

Recently, a Large amount of MODIS land products at multi-spatial resolutions have been integrated into the online system, Giovanni, to support studies on land cover and land use changes focused on Northern Eurasia and Monsoon Asia regions. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC) providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data. The customized Giovanni Web portals (Giovanni-NEESPI and Giovanni-MAIRS) are created to integrate land, atmospheric, cryospheric, and social products, that enable researchers to do quick exploration and basic analyses of land surface changes and their relationships to climate at global and regional scales. This presentation documents MODIS land surface products in Giovanni system. As examples, images and statistical analysis results on land surface and local climate changes associated with urbanization over Yangtze River Delta region, China, using data in Giovanni are shown.

The Effects of Fine-scale Soil Moisture and Canopy Heterogeneities on Energy and Soil Water Fluxes in a Temperate Mixed Deciduous Forest

NASA Astrophysics Data System (ADS)

He, L.; Ivanov, V. Y.; Bohrer, G.; Maurer, K.; Vogel, C. S.; Moghaddam, M.

2011-12-01

Vegetation is heterogeneous at different scales, influencing spatially variable energy and water exchanges between land-surface and atmosphere. Current land surface parameterizations of large-scale models consider spatial variability at a scale of a few kilometers and treat vegetation cover as aggregated patches with uniform properties. However, the coupling mechanisms between fine-scale soil moisture, vegetation, and energy fluxes such as evapotranspiration are strongly nonlinear; the aggregation of surface variations may produce biased energy fluxes. This study aims to improve the understanding of the scale impact in atmosphere-biosphere-hydrosphere interactions, which affects predictive capabilities of land surface models. The study uses a high-resolution, physically-based ecohydrological model tRIBS + VEGGIE as a data integration tool to upscale the heterogeneity of canopy distribution resolved at a few meters to the watershed scale. The study was carried out for a spatially heterogeneous, temperate mixed forest environment of Northern Michigan located near the University of Michigan Biological Station (UMBS). Energy and soil water dynamics were simulated at the tree-canopy resolution in the horizontal plane for a small domain (~2 sq. km) located within a footprint of the AmeriFlux tower. A variety of observational data were used to constrain and confirm the model, including a 3-m profile continuous soil moisture dataset and energy flux data (measured at the AmeriFlux tower footprint). A scenario with a spatially uniform canopy, corresponding to the commonly used 'big-leaf' scheme in land surface parameterizations was used to infer the effects of coarse-scale averaging. To gain insights on how heterogeneous canopy and soil moisture interact and contribute to the domain-averaged transpiration, several scenarios of tree-scale leaf area and soil moisture spatial variability were designed. Specifically, for the same mean states, the scenarios of variability of canopy biomass account for the spatial distribution of photosynthesis (and thus the stomatal resistance), the aerodynamic and leaf boundary layer resistances as well as the differential radiation forcing due to tall tree exposure and lateral shading of short trees. The numerical experiments show that by transpiring spatially varying amounts of water, heterogeneous canopies adjust the spatial soil water state to the scaled inverse of the canopy biomass regardless of the initial moisture state. Such a spatial distribution can be further wiped out because of the differential water stress. The aggregation of canopy-scale atmosphere-biosphere-hydrosphere interactions demonstrates non-linear relationship between soil moisture and evapotranspiration, influencing domain-averaged energy fluxes.

Regional Scale/Regional Climate Model Development and Its Applications at Goddard

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lau, W.; Qian, J.; Jia, Y.; Wetzel, P.; Chou, M.-D.; Wang, Y.; Lynn, B.

2000-01-01

A Regional Land-Atmosphere Climate Simulation System (RELACS) is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model (Penn State/NCAR MM5) with improved physical processes and in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water/energy cycles in the Indo-China/South China Sea (SCS)/China, N. America and S. America region.

Evaluating Water Budget Closure Across Spatial Scales: An Observational Approach through Texas Water Observatory

NASA Astrophysics Data System (ADS)

Gaur, N.; Jaimes, A.; Vaughan, S.; Morgan, C.; Moore, G. W.; Miller, G. R.; Everett, M. E.; Lawing, M.; Mohanty, B.

2017-12-01

Applications varying from improving water conservation practices at the field scale to predicting global hydrology under a changing climate depend upon our ability to achieve water budget closure. 1) Prevalent heterogeneity in soils, geology and land-cover, 2) uncertainties in observations and 3) space-time scales of our control volume and available data are the main factors affecting the percentage of water budget closure that we can achieve. The Texas Water Observatory presents a unique opportunity to observe the major components of the water cycle (namely precipitation, evapotranspiration, root zone soil moisture, streamflow and groundwater) in varying eco-hydrological regions representative of the lower Brazos River basin at multiple scales. The soils in these regions comprise of heavy clays that swell and shrink to create complex preferential pathways in the sub-surface, thus, making the hydrology in this region difficult to quantify. This work evaluates the water budget of the region by varying the control volume in terms of 3 temporal (weekly, monthly and seasonal) and 3 different spatial scales. The spatial scales are 1) Point scale - that is typical for process understanding of water dynamics, 2) Eddy Covariance footprint scale - that is typical of most eco-hydrological applications at the field scale and, 3) Satellite footprint scale- that is typically used in regional and global hydrological analysis. We employed a simple water balance model to evaluate the water budget at all scales. The point scale water budget was assessed using direct observations from hydro-geo-thematically located observation locations within different eddy covariance footprints. At the eddy covariance footprint scale, the sub-surface of each eddy covariance footprint was intensively characterized using electromagnetic induction (EM 38) and the resultant data was used to calculate the inter-point variability to upscale the sub-surface storage while the satellite scale water budget was evaluated using SMAP satellite observations supplemented with reanalysis products. At the point scale, we found differences in sub-surface storage in the same land-cover depending on the landscape position of the observation point while land-cover significantly affected water budget at the larger scales.

Asian Monsoons: Variability, Predictability, and Sensitivity to External Forcing

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.

1999-01-01

In this study, we have addressed the interannual variations of Asian monsoons including both broad-scale and regional monsoon components. Particular attention is devoted to the identities of the South China Sea monsoon and Indian monsoon. We use CPC Merged Analysis of Precipitation and NCEP reanalyses to define regional monsoon indices and to depict the various monsoons. Parallel modeling studies have also been carried out to assess the role of boundary forcing and the potential predictability of the monsoons. Each monsoon is characterized by its unique features. While the South Asian monsoon represents a classical monsoon in which anomalous circulation is governed by Rossby-wave dynamics, the Southeast Asian monsoon symbolizes a "hybrid" monsoon that features multi-cellular meridional circulation over eastern Asia. The broad-scale Asian monsoon links to the basin-wide atmospheric circulation over the Indian-Pacific oceans. Both SST and land surface processes are important for determining the variations of all monsoons. For the broad-scale monsoon, SST anomalies are more important than land surface processes. For regional monsoons, however, land surface processes may become equally important. Both observation and model shows that the broad-scale monsoon is potentially more predictable than regional monsoons, and that the Southeast Asian monsoon may possess higher predictability than the South Asian monsoon.

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.

To make a land use inventory and its change with time and development. To investigate how this area in the semi-arid climate is developing, and the ecological impact with the construction of several government projects in Central Mexico

NASA Technical Reports Server (NTRS)

Acoustadelcampo, C. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Comparison between ERTS-1 image scale 1:1,000,000 and CETENAL's charts scale 1:50,000 in irrigated land surface determination in one selected spot gave the following results: Surface on CETENAL's charts 129,900 Has. and arbitrarily we gave 100 percent to this value. Surface on image 122,400 Has., 94.5 percent of the first value. It is necessary to use all four bands to have optimum results on the interpretation. The Principal investigator made use of photointerpretation techniques only, mostly monoscopically.

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.

Quantifying the impact of land use change on hydrological responses in the Upper Ganga Basin, India

NASA Astrophysics Data System (ADS)

Tsarouchi, Georgia-Marina; Mijic, Ana; Moulds, Simon; Chawla, Ila; Mujumdar, Pradeep; Buytaert, Wouter

2013-04-01

Quantifying how changes in land use affect the hydrological response at the river basin scale is a challenge in hydrological science and especially in the tropics where many regions are considered data sparse. Earlier work by the authors developed and used high-resolution, reconstructed land cover maps for northern India, based on satellite imagery and historic land-use maps for the years 1984, 1998 and 2010. Large-scale land use changes and their effects on landscape patterns can impact water supply in a watershed by altering hydrological processes such as evaporation, infiltration, surface runoff, groundwater discharge and stream flow. Three land use scenarios were tested to explore the sensitivity of the catchment's response to land use changes: (a) historic land use of 1984 with integrated evolution to 2010; (b) land use of 2010 remaining stable; and (c) hypothetical future projection of land use for 2030. The future scenario was produced with Markov chain analysis and generation of transition probability matrices, indicating transition potentials from one land use class to another. The study used socio-economic (population density), geographic (distances to roads and rivers, and location of protected areas) and biophysical drivers (suitability of soil for agricultural production, slope, aspect, and elevation). The distributed version of the land surface model JULES was integrated at a resolution of 0.01° for the years 1984 to 2030. Based on a sensitivity analysis, the most sensitive parameters were identified. Then, the model was calibrated against measured daily stream flow data. The impact of land use changes was investigated by calculating annual variations in hydrological components, differences in annual stream flow and surface runoff during the simulation period. The land use changes correspond to significant differences on the long-term hydrologic fluxes for each scenario. Once analysed from a future water resources perspective, the results will be beneficial in constructing decision support tools for regional land-use planning and management.

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.

Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

NASA Astrophysics Data System (ADS)

Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

2017-06-01

Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

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

Flood quantiles scaling with upper soil hydraulic properties for different land uses at catchment scale

NASA Astrophysics Data System (ADS)

Peña, Luis E.; Barrios, Miguel; Francés, Félix

2016-10-01

Changes in land use within a catchment are among the causes of non-stationarity in the flood regime, as they modify the upper soil physical structure and its runoff production capacity. This paper analyzes the relation between the variation of the upper soil hydraulic properties due to changes in land use and its effect on the magnitude of peak flows: (1) incorporating fractal scaling properties to relate the effect of the static storage capacity (the sum of capillary water storage capacity in the root zone, canopy interception and surface puddles) and the upper soil vertical saturated hydraulic conductivity on the flood regime; (2) describing the effect of the spatial organization of the upper soil hydraulic properties at catchment scale; (3) examining the scale properties in the parameters of the Generalized Extreme Value (GEV) probability distribution function, in relation to the upper soil hydraulic properties. This study considered the historical changes of land use in the Combeima River catchment in South America, between 1991 and 2007, using distributed hydrological modeling of daily discharges to describe the hydrological response. Through simulation of land cover scenarios, it was demonstrated that it is possible to quantify the magnitude of peak flows in scenarios of land cover changes through its Wide-Sense Simple Scaling with the upper soil hydraulic properties.

Quantitative Estimation of Land Surface Characteristic Parameters and Actual Evapotranspiration in the Nagqu River Basin over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zhong, L.; Ma, Y.; Ma, W.; Zou, M.; Hu, Y.

2016-12-01

Actual evapotranspiration (ETa) is an important component of the water cycle in the Tibetan Plateau. It is controlled by many hydrological and meteorological factors. Therefore, it is of great significance to estimate ETa accurately and continuously. It is also drawing much attention of scientific community to understand land surface parameters and land-atmosphere water exchange processes in small watershed-scale areas. Based on in-situ meteorological data in the Nagqu river basin and surrounding regions, the main meteorological factors affecting the evaporation process were quantitatively analyzed and the point-scale ETa estimation models in the study area were successfully built. On the other hand, multi-source satellite data (such as SPOT, MODIS, FY-2C) were used to derive the surface characteristics in the river basin. A time series processing technique was applied to remove cloud cover and reconstruct data series. Then improved land surface albedo, improved downward shortwave radiation flux and reconstructed normalized difference vegetation index (NDVI) were coupled into the topographical enhanced surface energy balance system to estimate ETa. The model-estimated results were compared with those ETa values determined by combinatory method. The results indicated that the model-estimated ETa agreed well with in-situ measurements with correlation coefficient, mean bias error and root mean square error of 0.836, 0.087 and 0.140 mm/h respectively.

CONTRIBUTION OF NUTRIENTS AND E.COLI TO SURFACE WATER CONDITION IN THE OZARKS: PART II USING LANDSCAPE ECOLOGY AND PARTIAL LEAST SQUARES PREDICTIONS TO MAP WATERSHEDS THAT ARE VULNERABLE TO NON-POINT SOURCE POLLUTION

EPA Science Inventory

The results of this project provide watershed managers with the first broad-scale predictions that can be used to explain how land cover type, land cover configuration, environmental change, and human activities may affect the chemical and biological characteristics of surface wa...

The potential for land use change to reduce flood risk in mid-sized catchments in the Myjava region of Slovakia

NASA Astrophysics Data System (ADS)

Rončák, Peter; Lisovszki, Evelin; Szolgay, Ján; Hlavčová, Kamila; Kohnová, Silvia; Csoma, Rózsa; Poórová, Jana

2017-06-01

The effects of land use management practices on surface runoff are evident on a local scale, but evidence of their impact on the scale of a watershed is limited. This study focuses on an analysis of the impact of land use changes on the flood regime in the Myjava River basin, which is located in Western Slovakia. The Myjava River basin has an area of 641.32 km2 and is typified by the formation of fast runoff processes, intensive soil erosion, and muddy floods. The main factors responsible for these problems with flooding and soil erosion are the basin's location, geology, pedology, agricultural land use, and cropping practices. The GIS-based, spatially distributed WetSpa rainfall-runoff model was used to simulate mean daily discharges in the outlet of the basin as well as the individual components of the water balance. The model was calibrated based on the period between 1997 and 2012 with outstanding results (an NS coefficient of 0.702). Various components of runoff (e.g., surface, interflow and groundwater) and several elements of the hydrological balance (evapotranspiration and soil moisture) were simulated under various land use scenarios. Six land use scenarios (`crop', `grass', `forest', `slope', `elevation' and `optimal') were developed. The first three scenarios exhibited the ability of the WetSpa model to simulate runoff under changed land use conditions and enabled a better adjustment of the land use parameters of the model. Three other "more realistic" land use scenarios, which were based on the distribution of land use classes (arable land, grass and forest) regarding permissible slopes in the catchment, confirmed the possibility of reducing surface runoff and maximum discharges with applicable changes in land use and land management. These scenarios represent practical, realistic and realizable land use management solutions and they could be economically implemented to mitigate soil erosion processes and enhance the flood protection measures in the Myjava River basin.

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.

Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

NASA Technical Reports Server (NTRS)

Beaudoing, Hiroko Kato; Rodell, Matthew; Ozdogan, Mutlu

2010-01-01

Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

Vegetation controls on the biophysical surface properties at global scale

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Cescatti, Alessandro

2016-04-01

Leaf area index (LAI) plays an important role in determining resistances to heat, moisture and momentum exchanges between the land surface and atmosphere. Exploring how variations in LAI may induce changes in the surface energy balance is a key to understanding vegetation-climate interactions and for predicting biophysical climate impacts associated to changes in land cover. To this end, we analyzed remote sensing-observed dynamics in LAI, surface energy fluxes and climate drivers at global scale. We investigated the link between interannual variability of LAI and the components of the surface energy budget under diverse climate gradients. Results show that a 25% increase in annual LAI may induce up to 2% increase in available surface energy, as consequence of higher short wave absorption due to reduced albedos, up to 20% increase and 10% decrease in latent and sensible heat, respectively, leading to a decrease of the Bowen ratio in densely vegetated canopies. Opposite patterns are found for a reduction in LAI of similar magnitude. Such changes are strongly modulated by concurrent year-to-year variations and climatological means of air temperature, precipitation and snow cover as well as by land cover-specific physiological processes. Boreal and semi-arid regions appear to be mostly exposed to large changes in biophysical surface processes induced by interannual fluctuations in LAI. The combination of the emergent patters translates into variations in the long-wave outgoing radiation that reflect the surface warming/cooling associated to LAI changes. These findings provide a deeper understanding of the vegetation control on biophysical surface properties and define a set of observational-based diagnostics of LAI-dependent land surface-atmosphere interactions.

Viking High-Resolution Topography and Mars '01 Site Selection: Application to the White Rock Area

NASA Astrophysics Data System (ADS)

Tanaka, K. L.; Kirk, Randolph L.; Mackinnon, D. J.; Howington-Kraus, E.

1999-06-01

Definition of the local topography of the Mars '01 Lander site is crucial for assessment of lander safety and rover trafficability. According to Golombek et al., steep surface slopes may (1) cause retro-rockets to be fired too early or late for a safe landing, (2) the landing site slope needs to be < 1deg to ensure lander stability, and (3) a nearly level site is better for power generation of both the lander and the rover and for rover trafficability. Presently available datasets are largely inadequate to determine surface slope at scales pertinent to landing-site issues. Ideally, a topographic model of the entire landing site at meter-scale resolution would permit the best assessment of the pertinent topographic issues. MOLA data, while providing highly accurate vertical measurements, are inadequate to address slopes along paths of less than several hundred meters, because of along-track data spacings of hundreds of meters and horizontal errors in positioning of 500 to 2000 m. The capability to produce stereotopography from MOC image pairs is not yet in hand, nor can we necessarily expect a suitable number of stereo image pairs to be acquired. However, for a limited number of sites, high-resolution Viking stereo imaging is available at tens of meters horizontal resolution, capable of covering landing-ellipse sized areas. Although we would not necessarily suggest that the chosen Mars '01 Lander site should be located where good Viking stereotopography is available, an assessment of typical surface slopes at these scales for a range of surface types may be quite valuable in landing-site selection. Thus this study has a two-fold application: (1) to support the proposal of White Rock as a candidate Mars '01 Lander site, and (2) to evaluate how Viking high resolution stereotopography may be of value in the overall Mars '01 Lander site selection process.

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

NASA Astrophysics Data System (ADS)

Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru

2017-08-01

The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be extended to the water balance study of the whole Heihe River basin.

Estimation of Regional Net CO2 Exchange over the Southern Great Plains

NASA Astrophysics Data System (ADS)

Biraud, S. C.; Riley, W. J.; Fischer, M. L.; Torn, M. S.; Cooley, H. S.

2004-12-01

Estimating spatially distributed ecosystem CO2 exchange is an important component of the North American Carbon Program. We describe here a methodology to estimate Net Ecosystem Exchange (NEE) over the Southern Great Plains, using: (1) data from the Department Of Energy's Atmospheric Radiation Measurement (ARM) sites in Oklahoma and Kansas; (2) meteorological forcing data from the Mesonet facilities; (3) soil and vegetation types from 1 km resolution USGS databases; (4) vegetation status (e.g., LAI) from 1 km satellite measurements of surface reflectance (MODIS); (5) a tested land-surface model; and (6) a coupled land-surface and meteorological model (MM5/ISOLSM). This framework allows us to simulate regional surface fluxes in addition to ABL and free troposphere concentrations of CO2 at a continental scale with fine-scale nested grids centered on the ARM central facility. We use the offline land-surface and coupled models to estimate regional NEE, and compare predictions to measurements from the 9 Extended Facility sites with eddy correlation measurements. Site level comparisons to portable ECOR measurements in several crop types are also presented. Our approach also allows us to extend bottom-up estimates to periods and areas where meteorological forcing data are unavailable.

Disentangling Climate and Land-use Impacts on Grassland Carbon and Water Fluxes

NASA Astrophysics Data System (ADS)

Brunsell, N. A.; Nippert, J. B.

2014-12-01

Regional climate and land cover interact in a complex, non-linear manner to alter the local cycling of mass and energy. It is often difficult to isolate the role of either mechanism on the resultant fluxes. Here, we attempt to isolate these mechanisms through the use of network of 4 Ameriflux eddy covariance towers installed over different land cover and land use classes along a pronounced rainfall gradient. The land cover types include: annually burned C4 grassland, a 4 year burn site experiencing woody encroachment, an abandoned agricultural field and a new perennial agricultural site. We investigated the impact of rainfall variability, drought, and heat waves on the water and carbon budgets using data analysis, remote sensing, and modeling approaches. In addition, we have established a network of mini-meteorological stations at the annually and 4-year burn sites to assess micro-scale variability within the footprints of the towers as a function of topographic position, soil depth and soil water availability. Through the use of a wavelet multiscale decomposition and information theory metrics, we have isolated the role of environmental factors (temperature, humidity, soil moisture, etc.) on the fluxes across the different sites. By applying a similar analysis to model output, we can assess the ability of land-surface models to recreate the observed sensitity. Results indicate the utility of a network of measurement systems used in conjunction with land surface modeling and time series analysis to assess differential impacts to similar regional scale climate forcings. Implications for the role of land cover class in regional and global scale modeling systems will also be discussed.

Dynamic Model Investigation of Water Pressures and Accelerations Encountered During Landings of the Apollo Spacecraft

NASA Technical Reports Server (NTRS)

Stubbs, Sandy M.

1967-01-01

An experimental investigation was made to determine impact water pressures, accelerations, and landing dynamics of a 1/4-scale dynamic model of the command module of the Apollo spacecraft. A scaled-stiffness aft heat shield was used on the model to simulate the structural deflections of the full-scale heat shield. Tests were made on water to obtain impact pressure data at a simulated parachute letdown (vertical) velocity component of approximately 30 ft/sec (9.1 m/sec) full scale. Additional tests were made on water, sand, and hard clay-gravel landing surfaces at simulated vertical velocity components of 23 ft/sec (7.0 m/sec) full scale. Horizontal velocity components investigated ranged from 0 to 50 ft/sec (15 m/sec) full scale and the pitch attitudes ranged from -40 degrees to 29 degrees. Roll attitudes were O degrees, 90 degrees, and 180 degrees, and the yaw attitude was 0 degrees.

Classifying land cover from an object-oriented approach - applied to LANDSAT 8 at the regional scale of the Lake Tana Basin (Ethiopia)

NASA Astrophysics Data System (ADS)

Lemma, Hanibal; Frankl, Amaury; Poesen, Jean; Adgo, Enyew; Nyssen, Jan

2017-04-01

Object-oriented image classification has been gaining prominence in the field of remote sensing and provides a valid alternative to the 'traditional' pixel based methods. Recent studies have proven the superiority of the object-based approach. So far, object-oriented land cover classifications have been applied either at limited spatial coverages (ranging 2 to 1091 km2) or by using very high resolution (0.5-16 m) imageries. The main aim of this study is to drive land cover information for large area from Landsat 8 OLI surface reflectance using the Estimation of Scale Parameter (ESP) tool and the object oriented software eCognition. The available land cover map of Lake Tana Basin (Ethiopia) is about 20 years old with a courser spatial scale (1:250,000) and has limited use for environmental modelling and monitoring studies. Up-to-date and basin wide land cover maps are essential to overcome haphazard natural resources management, land degradation and reduced agricultural production. Indeed, object-oriented approach involves image segmentation prior to classification, i.e. adjacent similar pixels are aggregated into segments as long as the heterogeneity in the spectral and spatial domains is minimized. For each segmented object, different attributes (spectral, textural and shape) were calculated and used for in subsequent classification analysis. Moreover, the commonly used error matrix is employed to determine the quality of the land cover map. As a result, the multiresolution segmentation (with parameters of scale=30, shape=0.3 and Compactness=0.7) produces highly homogeneous image objects as it is observed in different sample locations in google earth. Out of the 15,089 km2 area of the basin, cultivated land is dominant (69%) followed by water bodies (21%), grassland (4.8%), forest (3.7%) and shrubs (1.1%). Wetlands, artificial surfaces and bare land cover only about 1% of the basin. The overall classification accuracy is 80% with a Kappa coefficient of 0.75. With regard to individual classes, the classification show higher Producer's and User's accuracy (above 84%) for cultivated land, water bodies and forest, but lower (less than 70%) for shrubs, bare land and grassland. Key words: accuracy assessment, eCognition, Estimation of Scale Parameter, land cover, Landsat 8, remote sensing

Global Impacts of Long-Term Land Cover Changes Within China's Densely Populated Rural Regions

NASA Astrophysics Data System (ADS)

Ellis, E. C.

2006-12-01

Long-term changes in land cover are usually investigated in terms of large-scale change processes such as urban expansion, deforestation and land conversion to agriculture. Yet China's densely populated agricultural regions, which cover more than 2 million square kilometers of Monsoon Asia, have been transformed profoundly over the past fifty years by fine-scale changes in land cover caused by unprecedented changes in population, technology and social conditions. Using a regional sampling and upscaling design coupled with high-resolution landscape change measurements at five field sites, we investigated long-term changes in land cover and ecological processes, circa 1945 to 2002, within and across China's densely populated agricultural regions. As expected, the construction of buildings and roads increased impervious surface area over time, but the total net increase was surprising, being similar in magnitude to the total current extent of China's cities. Agricultural land area declined over the same period, while tree cover increased, by about 10%, driven by tree planting and regrowth around new buildings, the introduction of perennial agriculture, improved forestry, and declines in annual crop cultivation. Though changes in impervious surface areas were closely related to changes in population density, long-term changes in agricultural land and tree cover were unrelated to populated density and required explanation by more complex models with strong regional and biophysical components. Moreover, most of these changes occurred primarily at fine spatial scales (< 30 m), under the threshold for conventional global and regional land cover change measurements. Given that these changes in built structures and vegetation cover have the potential to contribute substantially to regional and global changes in biogeochemistry, hydrology, and land-atmosphere interactions, future investigations of these changes and their impacts across Monsoon Asia would benefit from models that incorporate fine-scale landscape structure and its changes over time.

Potential climatic impacts and reliability of very large-scale wind farms

NASA Astrophysics Data System (ADS)

Wang, C.; Prinn, R. G.

2010-02-01

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled substantial interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1 °C over land installations. In contrast, surface cooling exceeding 1 °C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

Potential climatic impacts and reliability of very large-scale wind farms

NASA Astrophysics Data System (ADS)

Wang, C.; Prinn, R. G.

2009-09-01

Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled legitimate interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a three-dimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using wind turbines to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1°C over land installations. In contrast, surface cooling exceeding 1°C is computed over ocean installations, but the validity of simulating the impacts of wind turbines by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate wind turbines. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.

Weak hydrological sensitivity to temperature change over land, independent of climate forcing

NASA Astrophysics Data System (ADS)

Samset, Bjorn H.

2017-04-01

As the global surface temperature changes, so will patterns and rates of precipitation. Theoretically, these changes can be understood in terms of changes to the energy balance of the atmosphere, caused by introducing drivers of climate change such as greenhouse gases, aerosols and altered insolation. Climate models, however, disagree strongly in their prediction of precipitation changes, both for historical and future emission pathways, and per degree of surface warming in idealized experiments. The latter value, often termed the apparent hydrological sensitivity, has also been found to differ substantially between climate drivers. Here, we present the global and regional hydrological sensitivity (HS) to surface temperature changes, for perturbations to CO2, CH4, sulfate and black carbon concentrations, and solar irradiance. Based on results from 10 climate models participating in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), we show how modeled global mean precipitation increases by 2-3 % per kelvin of global mean surface warming, independent of driver, when the effects of rapid adjustments are removed. Previously reported differences in response between drivers are therefore mainly ascribable to rapid atmospheric adjustment processes. All models show a sharp contrast in behavior over land and over ocean, with a strong surface temperature driven (slow) ocean HS of 3-5 %/K, while the slow land HS is only 0-2 %/K. Separating the response into convective and large-scale cloud processes, we find larger inter-model differences, in particular over land regions. Large-scale precipitation changes are most relevant at high latitudes, while the equatorial HS is dominated by convective precipitation changes. Black carbon stands out as the driver with the largest inter-model slow HS variability, and also the strongest contrast between a weak land and strong sea response. Convective precipitation in the Arctic and large scale precipitation around the Equator are found to be topics where further model investigations and observational constraints may provide rapid improvements to modelling of the precipitation response to future, CO2 dominated climate change.

Simulating the biogeochemical and biogeophysical impacts of transient land cover change and wood harvest in the Community Climate System Model (CCSM4) from 1850 to 2100

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

Lawrence, Peter J.; Feddema, Johannes J.; Bonan, Gordon B.

To assess the climate impacts of historical and projected land cover change and land use in the Community Climate System Model (CCSM4) we have developed new time series of transient Community Land Model (CLM4) Plant Functional Type (PFT) parameters and wood harvest parameters. The new parameters capture the dynamics of the Coupled Model Inter-comparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005, and for the four Representative Concentration Pathways (RCP) periods from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 with the parametersmore » found the model produced an historical cumulative land use flux of 148.4 PgC from 1850 to 2005, which was in good agreement with other global estimates of around 156 PgC for the same period. The biogeophysical impacts of only applying the transient land cover change parameters in CCSM4 were cooling of the near surface atmospheric over land by -0.1OC, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was overwhelmed at global scales by decreases in snow albedo from black carbon deposition and from high latitude warming. At regional scales however the land cover change forcing persisted resulting in reduced warming, with the biggest impacts in eastern North America. The future CCSM4 RCP simulations showed that the CLM4 transient PFT and wood harvest parameters could be used to represent a wide range of human land cover change and land use scenarios. Furthermore, these simulations ranged from the RCP 4.5 reforestation scenario that was able to draw down 82.6 PgC from the atmosphere, to the RCP 8.5 wide scale deforestation scenario that released 171.6 PgC to the atmosphere.« less

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

NASA Technical Reports Server (NTRS)

Jin, Menglin; King, Michael D.

2005-01-01

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

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.

Evaluating 20th Century precipitation characteristics between multi-scale atmospheric models with different land-atmosphere coupling

NASA Astrophysics Data System (ADS)

Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.

2016-12-01

Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.

Applying Geospatial Techniques to Investigate Boundary Layer Land-Atmosphere Interactions Involved in Tornadogensis

NASA Astrophysics Data System (ADS)

Weigel, A. M.; Griffin, R.; Knupp, K. R.; Molthan, A.; Coleman, T.

2017-12-01

Northern Alabama is among the most tornado-prone regions in the United States. This region has a higher degree of spatial variability in both terrain and land cover than the more frequently studied North American Great Plains region due to its proximity to the southern Appalachian Mountains and Cumberland Plateau. More research is needed to understand North Alabama's high tornado frequency and how land surface heterogeneity influences tornadogenesis in the boundary layer. Several modeling and simulation studies stretching back to the 1970's have found that variations in the land surface induce tornadic-like flow near the surface, illustrating a need for further investigation. This presentation introduces research investigating the hypothesis that horizontal gradients in land surface roughness, normal to the direction of flow in the boundary layer, induce vertically oriented vorticity at the surface that can potentially aid in tornadogenesis. A novel approach was implemented to test this hypothesis using a GIS-based quadrant pattern analysis method. This method was developed to quantify spatial relationships and patterns between horizontal variations in land surface roughness and locations of tornadogenesis. Land surface roughness was modeled using the Noah land surface model parameterization scheme which, was applied to MODIS 500 m and Landsat 30 m data in order to compare the relationship between tornadogenesis locations and roughness gradients at different spatial scales. This analysis found a statistical relationship between areas of higher roughness located normal to flow surrounding tornadogenesis locations that supports the tested hypothesis. In this presentation, the innovative use of satellite remote sensing data and GIS technologies to address interactions between the land and atmosphere will be highlighted.

Urban watershed modeling in Seattle, Washington using VELMA – a spatially explicit ecohydrological watershed model

EPA Science Inventory

Urban watersheds are notoriously difficult to model due to their complex, small-scale combinations of landscape and land use characteristics including impervious surfaces that ultimately affect the hydrologic system. We utilized EPA’s Visualizing Ecosystem Land Management A...

Multiple Scale Remote Sensing for Monitoring Rangelands

USDA-ARS?s Scientific Manuscript database

Based on a land-cover classification from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS), rangelands cover 48% of the Earth’s land surface, not including Antarctica. Nearly all analyses imply the most economical means of monitoring large areas of rangelands worldwide is with remote se...

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.

Surface Properties and Characteristics of Mars Landing Sites from Remote Sensing Data and Ground Truth

NASA Astrophysics Data System (ADS)

Golombek, M. P.; Haldemann, A. F.; Simpson, R. A.; Furgason, R. L.; Putzig, N. E.; Huertas, A.; Arvidson, R. E.; Heet, T.; Bell, J. F.; Mellon, M. T.; McEwen, A. S.

2008-12-01

Surface characteristics at the six sites where spacecraft have successfully landed on Mars can be related favorably to their signatures in remotely sensed data from orbit and from the Earth. Comparisons of the rock abundance, types and coverage of soils (and their physical properties), thermal inertia, albedo, and topographic slope all agree with orbital remote sensing estimates and show that the materials at the landing sites can be used as ground truth for the materials that make up most of the equatorial and mid- to moderately high-latitude regions of Mars. The six landing sites sample two of the three dominant global thermal inertia and albedo units that cover ~80% of the surface of Mars. The Viking, Spirit, Mars Pathfinder, and Phoenix landing sites are representative of the moderate to high thermal inertia and intermediate to high albedo unit that is dominated by crusty, cloddy, blocky or frozen soils (duricrust that may be layered) with various abundances of rocks and bright dust. The Opportunity landing site is representative of the moderate to high thermal inertia and low albedo surface unit that is relatively dust free and composed of dark eolian sand and/or increased abundance of rocks. Rock abundance derived from orbital thermal differencing techniques in the equatorial regions agrees with that determined from rock counts at the surface and varies from ~3-20% at the landing sites. The size-frequency distributions of rocks >1.5 m diameter fully resolvable in HiRISE images of the landing sites follow exponential models developed from lander measurements of smaller rocks and are continuous with these rock distributions indicating both are part of the same population. Interpretation of radar data confirms the presence of load bearing, relatively dense surfaces controlled by the soil type at the landing sites, regional rock populations from diffuse scattering similar to those observed directly at the sites, and root-mean-squared slopes that compare favorably with 100 m scale topographic slopes extrapolated from altimetry profiles and meter scale slopes from high-resolution stereo images. The third global unit has very low thermal inertia and very high albedo, indicating it is dominated by deposits of bright red atmospheric dust that may be neither load bearing nor trafficable. The landers have thus sampled the majority of likely safe and trafficable surfaces that cover most of Mars and show that remote sensing data can be used to infer the surface characteristics, slopes, and surface materials present at other locations.

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.

Simulating land-atmosphere feedbacks and response to widespread forest disturbance: The role of lower boundary configuration and dynamic water table in meteorological modeling

NASA Astrophysics Data System (ADS)

Forrester, M.; Maxwell, R. M.; Bearup, L. A.; Gochis, D.

2017-12-01

Numerical meteorological models are frequently used to diagnose land-atmosphere interactions and predict large-scale response to extreme or hazardous events, including widespread land disturbance or perturbations to near-surface moisture. However, few atmospheric modeling platforms consider the impact that dynamic groundwater storage, specifically 3D subsurface flow, has on land-atmosphere interactions. In this study, we use the Weather Research and Forecasting (WRF) mesoscale meteorological model to identify ecohydrologic and land-atmosphere feedbacks to disturbance by the mountain pine beetle (MPB) over the Colorado Headwaters region. Disturbance simulations are applied to WRF with various lower boundary configurations: Including default Noah land surface model soil moisture representation; a version of WRF coupled to ParFlow (PF), an integrated groundwater-surface water model that resolves variably saturated flow in the subsurface; and WRF coupled to PF in a static water table version, simulating only vertical and no lateral subsurface flow. Our results agree with previous literature showing MPB-induced reductions in canopy transpiration in all lower boundary scenarios, as well as energy repartitioning, higher water tables, and higher planetary boundary layer over infested regions. Simulations show that expanding from local to watershed scale results in significant damping of MPB signal as unforested and unimpacted regions are added; and, while deforestation appears to have secondary feedbacks to planetary boundary layer and convection, these slight perturbations to cumulative summer precipitation are insignificant in the context of ensemble methodologies. Notably, the results suggest that groundwater representation in atmospheric modeling affects the response intensity of a land disturbance event. In the WRF-PF case, energy and atmospheric processes are more sensitive to disturbance in regions with higher water tables. Also, when dynamic subsurface hydrology is removed, WRF simulates a greater response to MPB at the land-atmosphere interface, including greater changes to daytime skin temperature, Bowen ratio and near-surface humidity. These findings highlight lower boundary representations in computational meteorology and numerical land-atmosphere modeling.

Verification of land-atmosphere coupling in forecast models, reanalyses and land surface models using flux site observations.

PubMed

Dirmeyer, Paul A; Chen, Liang; Wu, Jiexia; Shin, Chul-Su; Huang, Bohua; Cash, Benjamin A; Bosilovich, Michael G; Mahanama, Sarith; Koster, Randal D; Santanello, Joseph A; Ek, Michael B; Balsamo, Gianpaolo; Dutra, Emanuel; Lawrence, D M

2018-02-01

We confront four model systems in three configurations (LSM, LSM+GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly under-represent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land-atmosphere coupling), and may over-represent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally under-represent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Our analysis illuminates targets for coupled land-atmosphere model development, as well as the value of long-term globally-distributed observational monitoring.

Land Cover and Topography Affect the Land Transformation Caused by Wind Facilities

PubMed Central

Diffendorfer, Jay E.; Compton, Roger W.

2014-01-01

Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here. PMID:24558449

Land cover and topography affect the land transformation caused by wind facilities

USGS Publications Warehouse

Diffendorfer, Jay E.; Compton, Roger W.

2014-01-01

Land transformation (ha of surface disturbance/MW) associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only), sites (strings with roads connecting them, buried cables and other infrastructure), and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure). An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.

Relationships between landscape pattern and land surface temperature and their applications to the study of West Nile Virus: As case studies in cities of Indianapolis and Chicago, United States

NASA Astrophysics Data System (ADS)

Liu, Hua

A new synthesis of remote sensing and landscape ecology approaches was developed to establish relationships between the landscape patterns and land surface temperatures (LST) in the city of Indianapolis, Indiana, United States. Land use and land cover (LULC) and LST images were derived from Terra Satellite's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns and land surface temperature zones. Detailed landscape pattern analyses at the landscape and class scales were conducted using landscape metrics in the City of Indianapolis. The effects of spatial resolution on the identification of the relationship were examined in the same city. The best level of equalization between the LULC and LST maps was determined based on minimum distance analysis in landscape metrics space. The analyses of relationships between the landscape patterns and land surface temperatures, and scaling effects were applied to the spread of West Nile Virus (WNV) in the City of Chicago, Illinois. Results show that urban, forest, and grassland were the main landscape components in Indianapolis. They possessed relatively higher fractal dimensions but lower spatial aggregation levels in April 5, 2004, June 16, 2001, and October 3, 2000, but not in February 6, 2006. Obvious seasonal differences existed with the most distinct landscape pattern detected on February 6, 2006. Urban was the dominant LULC type in high-temperature zones, while water and vegetation mainly fell in low-temperature zones. For each individual date, the metrics of LST zones apparently corresponded to the metrics of LULC types. In the study of scaling-up effect analysis, Patch Percentage, Patch Density, and Landscape Shape index were found to be able to effectively quantify the spatial changes of LULC types and temperature zones at different scales without contradiction. Urban, forest, and grassland in each season were more easily affected by the process in Patch Density and Landscape Shape index. Ninety meters was believed to be the optimal spatial resolution to examine relationships between landscape patterns and LSTs in the City of Indianapolis. In the study of the spread of West Nile Virus in the City of Chicago, WNV was found to have been spread throughout all of Cook County since 2001. Landscape factors, like landscape aggregation index and areas of urban, grass, and water showed a strong correlation with the number of WNV infections. Socioeconomic conditions, like population above 65 years old also showed a strong relationship with the spread of WNV in Cook County. Thermal conditions of water had a lower but still significant correlation to the spread of WNV. This research offers an opportunity to explore the mechanism of interaction between urban landscape patterns and land surface temperatures at different spatial scales, and show the effects of landscape pattern and land surface temperature on the spread of West Nile Virus. This study can be useful for urban planning and environmental management practices in the studied areas. It also contributes to public health management and protection.

Modeling evapotranspiration over China's landmass from 1979-2012 using three surface models

NASA Astrophysics Data System (ADS)

Sun, Shaobo; Chen, Baozhang; Zhang, Huifang; Lin, Xiaofeng

2017-04-01

Land surface models (LSMs) are useful tools to estimate land evapotranspiration at a grid scale and for a long-term applications. Here, the Community Land Model 4.0 (CLM4.0), Dynamic Land Model (DLM) and Variable Infiltration Capacity (VIC) model were driven with observation-based forcing data sets, and a multiple LSM ensemble-averaged evapotranspiration (ET) product (LSMs-ET) was developed and its spatial-temporal variations were analyzed for the China landmass over the period 1979-2012. Evaluations against measurements from nine flux towers at site scale and surface water budget based ET at regional scale showed that the LSMs-ET had good performance in most areas of China's landmass. The inter-comparisons between the ET estimates and the independent ET products from remote sensing and upscaling methods suggested that there were a fairly consistent patterns between each data sets. The LSMs-ET produced a mean annual ET of 351.24±10.7 mm yr-1 over 1979-2012, and its spatial-temporal variation analyses showed that (i) there was an overall significant ET increasing trend, with a value of 0.72 mm yr-1 (p < 0.01); (ii) 36.01% of Chinese land had significant increasing trends, ranging from 1 to 9 mm yr-1, while only 6.41% of the area showed significant decreasing trends, ranging from -6.28 to -0.08 mm yr-1. Analyses of ET variations in each climate region clearly showed that the Tibetan Plateau areas were the main contributors to the overall increasing ET trends of China.

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).

Non-radiative processes dominate land surface signals in the climate system

NASA Astrophysics Data System (ADS)

Bright, R. M.; Davin, E.; O'Halloran, T. L.; Pongratz, J.; Zhao, K.; Cescatti, A.

2016-12-01

Perturbations to the surface energy budget linked to land cover/land management changes (LCMC) are rarely included in land-climate assessments although they have long been recognized as important drivers of local climate change. At local scales, climate forcings from LCMC depend strongly on changes to surface energy redistribution by various non-radiative mechanisms, dampening or even outweighing the local radiative effect of an albedo change. The extent to which these mechanisms are locally relevant for different types of LCMC across the world remains largely unquantified. Here, we combine extensive records of remote sensing and in-situ observations to quantify local forcings for nine common real-world LCMC perturbations, identifying their underlying physical mechanisms and analyzing their spatial patterns at the global scale. We find that throughout the densely populated regions, non-radiative forcings dominate the local surface temperature response in 8 of 9 LCMC scenarios. Further, the observed local response to re-/afforestation is an annual cooling in all regions south of the upper conterminous United States, Western Europe, and Indo-China. Given that the global response to re-/afforestation in these regions is likely a cooling, projects here can be seen as attractive mitigation measures. Our results - gridded to a 1° x 1° resolution - can be directly used to evaluate climate models or compute indicators providing a more comprehensive picture of the trade-offs between local and global climate forcings linked to land sector projects and policies.

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE)

PubMed Central

Tian, Xin; Li, Zengyuan; Chen, Erxue; Liu, Qinhuo; Yan, Guangjian; Wang, Jindi; Niu, Zheng; Zhao, Shaojie; Li, Xin; Pang, Yong; Su, Zhongbo; van der Tol, Christiaan; Liu, Qingwang; Wu, Chaoyang; Xiao, Qing; Yang, Le; Mu, Xihan; Bo, Yanchen; Qu, Yonghua; Zhou, Hongmin; Gao, Shuai; Chai, Linna; Huang, Huaguo; Fan, Wenjie; Li, Shihua; Bai, Junhua; Jiang, Lingmei; Zhou, Ji

2015-01-01

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) comprises a network of remote sensing experiments designed to enhance the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Two types of experimental campaigns were established under the framework of COMPLICATE. The first was designed for continuous and elaborate experiments. The experimental strategy helps enhance our understanding of the radiative and scattering mechanisms of soil and vegetation and modeling of remotely sensed information for complex land surfaces. To validate the methodologies and models for dynamic analyses of remote sensing for complex land surfaces, the second campaign consisted of simultaneous satellite-borne, airborne, and ground-based experiments. During field campaigns, several continuous and intensive observations were obtained. Measurements were undertaken to answer key scientific issues, as follows: 1) Determine the characteristics of spatial heterogeneity and the radiative and scattering mechanisms of remote sensing on complex land surfaces. 2) Determine the mechanisms of spatial and temporal scale extensions for remote sensing on complex land surfaces. 3) Determine synergist inversion mechanisms for soil and vegetation parameters using multi-mode remote sensing on complex land surfaces. Here, we introduce the background, the objectives, the experimental designs, the observations and measurements, and the overall advances of COMPLICATE. As a result of the implementation of COMLICATE and for the next several years, we expect to contribute to quantitative remote sensing science and Earth observation techniques. PMID:26332035

Internal variability of fine-scale components of meteorological fields in extended-range limited-area model simulations with atmospheric and surface nudging

NASA Astrophysics Data System (ADS)

Separovic, Leo; Husain, Syed Zahid; Yu, Wei

2015-09-01

Internal variability (IV) in dynamical downscaling with limited-area models (LAMs) represents a source of error inherent to the downscaled fields, which originates from the sensitive dependence of the models to arbitrarily small modifications. If IV is large it may impose the need for probabilistic verification of the downscaled information. Atmospheric spectral nudging (ASN) can reduce IV in LAMs as it constrains the large-scale components of LAM fields in the interior of the computational domain and thus prevents any considerable penetration of sensitively dependent deviations into the range of large scales. Using initial condition ensembles, the present study quantifies the impact of ASN on IV in LAM simulations in the range of fine scales that are not controlled by spectral nudging. Four simulation configurations that all include strong ASN but differ in the nudging settings are considered. In the fifth configuration, grid nudging of land surface variables toward high-resolution surface analyses is applied. The results show that the IV at scales larger than 300 km can be suppressed by selecting an appropriate ASN setup. At scales between 300 and 30 km, however, in all configurations, the hourly near-surface temperature, humidity, and winds are only partly reproducible. Nudging the land surface variables is found to have the potential to significantly reduce IV, particularly for fine-scale temperature and humidity. On the other hand, hourly precipitation accumulations at these scales are generally irreproducible in all configurations, and probabilistic approach to downscaling is therefore recommended.

Spatio-Temporal Evolution and Scaling Properties of Human Settlements (Invited)

NASA Astrophysics Data System (ADS)

Small, C.; Milesi, C.; Elvidge, C.; Baugh, K.; Henebry, G. M.; Nghiem, S. V.

2013-12-01

Growth and evolution of cities and smaller settlements is usually studied in the context of population and other socioeconomic variables. While this is logical in the sense that settlements are groups of humans engaged in socioeconomic processes, our means of collecting information about spatio-temporal distributions of population and socioeconomic variables often lack the spatial and temporal resolution to represent the processes at scales which they are known to occur. Furthermore, metrics and definitions often vary with country and through time. However, remote sensing provides globally consistent, synoptic observations of several proxies for human settlement at spatial and temporal resolutions sufficient to represent the evolution of settlements over the past 40 years. We use several independent but complementary proxies for anthropogenic land cover to quantify spatio-temporal (ST) evolution and scaling properties of human settlements globally. In this study we begin by comparing land cover and night lights in 8 diverse settings - each spanning gradients of population density and degree of land surface modification. Stable anthropogenic night light is derived from multi-temporal composites of emitted luminance measured by the VIIRS and DMSP-OLS sensors. Land cover is represented as mixtures of sub-pixel fractions of rock, soil and impervious Substrates, Vegetation and Dark surfaces (shadow, water and absorptive materials) estimated from Landsat imagery with > 94% accuracy. Multi-season stability and variability of land cover fractions effectively distinguishes between spectrally similar land covers that corrupt thematic classifications based on single images. We find that temporal stability of impervious substrates combined with persistent shadow cast between buildings results in temporally stable aggregate reflectance across seasons at the 30 m scale of a Landsat pixel. Comparison of night light brightness with land cover composition, stability and variability yields several consistent relationships that persist across a variety of settlement types and physical environments. We use the multiple threshold method of Small et al (2011) to represent a continuum of settlement density by segmenting both night light brightness and multi-season land cover characteristics. Rank-size distributions of spatially contiguous segments quantify scaling and connectivity of land cover. Spatial and temporal evolution of rank-size distributions is consistent with power laws as suggested by Zipf's Law for city size based on population. However, unlike Zipf's Law, the observed distributions persist to global scales in which the larger agglomerations are much larger than individual cities. The scaling relations observed extend from the scale of cities and smaller settlements up to vast spatial networks of interconnected settlements.

Geographic Analysis and Monitoring Program

USGS Publications Warehouse

Campbell, Jon C.

2007-01-01

The surface of the Earth is changing rapidly, at local, regional, national, and global scales, with significant repercussions for people, the economy, and the environment. Some changes have natural causes, such as wildland fires or hurricanes, while other changes on the land, such as resource extraction, agricultural practices, and urban growth, are human-induced processes. There are other types of changes that are a combination of natural and human-induced factors; landslides and floods, for example, are fundamentally natural processes that are often intensified or accelerated by human land use practices. Whatever their cause, land-surface changes can have profound environmental and economic impacts.

Data needs and data bases for climate studies

NASA Technical Reports Server (NTRS)

Matthews, Elaine

1986-01-01

Two complementary global digital data bases of vegetation and land use, compiled at 1 deg resolution from published sources for use in climate studies, are discussed. The data bases were implemented, in several individually tailored formulations, in a series of climate related applications including: land-surface prescriptions in three-dimensional general circulation models, global biogeochemical cycles (CO2, methane), critical-area mapping for satellite monitoring of land-cover change, and large-scale remote sensing of surface reflectance. The climate applications are discussed with reference to data needs, and data availability from traditional and remote sensing sources.

Computer-implemented land use classification with pattern recognition software and ERTS digital data. [Mississippi coastal plains

NASA Technical Reports Server (NTRS)

Joyce, A. T.

1974-01-01

Significant progress has been made in the classification of surface conditions (land uses) with computer-implemented techniques based on the use of ERTS digital data and pattern recognition software. The supervised technique presently used at the NASA Earth Resources Laboratory is based on maximum likelihood ratioing with a digital table look-up approach to classification. After classification, colors are assigned to the various surface conditions (land uses) classified, and the color-coded classification is film recorded on either positive or negative 9 1/2 in. film at the scale desired. Prints of the film strips are then mosaicked and photographed to produce a land use map in the format desired. Computer extraction of statistical information is performed to show the extent of each surface condition (land use) within any given land unit that can be identified in the image. Evaluations of the product indicate that classification accuracy is well within the limits for use by land resource managers and administrators. Classifications performed with digital data acquired during different seasons indicate that the combination of two or more classifications offer even better accuracy.

Integrated modelling of anthropogenic land-use and land-cover change on the global scale

NASA Astrophysics Data System (ADS)

Schaldach, R.; Koch, J.; Alcamo, J.

2009-04-01

In many cases land-use activities go hand in hand with substantial modifications of the physical and biological cover of the Earth's surface, resulting in direct effects on energy and matter fluxes between terrestrial ecosystems and the atmosphere. For instance, the conversion of forest to cropland is changing climate relevant surface parameters (e.g. albedo) as well as evapotranspiration processes and carbon flows. In turn, human land-use decisions are also influenced by environmental processes. Changing temperature and precipitation patterns for example are important determinants for location and intensity of agriculture. Due to these close linkages, processes of land-use and related land-cover change should be considered as important components in the construction of Earth System models. A major challenge in modelling land-use change on the global scale is the integration of socio-economic aspects and human decision making with environmental processes. One of the few global approaches that integrates functional components to represent both anthropogenic and environmental aspects of land-use change, is the LandSHIFT model. It simulates the spatial and temporal dynamics of the human land-use activities settlement, cultivation of food crops and grazing management, which compete for the available land resources. The rational of the model is to regionalize the demands for area intensive commodities (e.g. crop production) and services (e.g. space for housing) from the country-level to a global grid with the spatial resolution of 5 arc-minutes. The modelled land-use decisions within the agricultural sector are influenced by changing climate and the resulting effects on biomass productivity. Currently, this causal chain is modelled by integrating results from the process-based vegetation model LPJmL model for changing crop yields and net primary productivity of grazing land. Model output of LandSHIFT is a time series of grid maps with land-use/land-cover information that can serve as basis for further impact analysis. An exemplary simulation study with LandSHIFT is presented, based on scenario assumptions from the UNEP Global Environmental Outlook 4. Time horizon of the analysis is the year 2050. Changes of future food production on country level are computed by the agro-economy model IMPACT as a function of demography, economic development and global trade pattern. Together with scenario assumptions on climatic change and population growth, this data serves as model input to compute the changing land-use und land-cover. The continental and global scale model results are then analysed with respect to changes in the spatial pattern of natural vegetation as well as the resulting effects on evapotranspiration processes and land surface parameters. Furthermore, possible linkages of LandSHIFT to the different components of Earth System models (e.g. climate and natural vegetation) are discussed.

Effects of leaf area index on the coupling between water table, land surface energy fluxes, and planetary boundary layer at the regional scale

NASA Astrophysics Data System (ADS)

Lu, Y.; Rihani, J.; Langensiepen, M.; Simmer, C.

2013-12-01

Vegetation plays an important role in the exchange of moisture and energy at the land surface. Previous studies indicate that vegetation increases the complexity of the feedbacks between the atmosphere and subsurface through processes such as interception, root water uptake, leaf surface evaporation, and transpiration. Vegetation cover can affect not only the interaction between water table depth and energy fluxes, but also the development of the planetary boundary layer. Leaf Area Index (LAI) is shown to be a major factor influencing these interactions. In this work, we investigate the sensitivity of water table, surface energy fluxes, and atmospheric boundary layer interactions to LAI as a model input. We particularly focus on the role LAI plays on the location and extent of transition zones of strongest coupling and how this role changes over seasonal timescales for a real catchment. The Terrestrial System Modelling Platform (TerrSysMP), developed within the Transregional Collaborative Research Centre 32 (TR32), is used in this study. TerrSysMP consists of the variably saturated groundwater model ParFlow, the land surface model Community Land Model (CLM), and the regional climate and weather forecast model COSMO (COnsortium for Small-scale Modeling). The sensitivity analysis is performed over a range of LAI values for different vegetation types as extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset for the Rur catchment in Germany. In the first part of this work, effects of vegetation structure on land surface energy fluxes and their connection to water table dynamics are studied using the stand-alone CLM and the coupled subsurface-surface components of TerrSysMP (ParFlow-CLM), respectively. The interconnection between LAI and transition zones of strongest coupling are investigated and analyzed through a subsequent set of subsurface-surface-atmosphere coupled simulations implementing the full TerrSysMP model system.

Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

2010-01-01

Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of variance suggesting that the algorithm is reliable and robust, except in the tropics where some systematic differences are observed. Finally, comparisons with ground data suggest that the algorithm is performing well, but that end of season metrics associated with vegetation senescence and dormancy have higher uncertainties than start of season metrics.

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.

Spatial-Temporal Variations of Water Quality and Its Relationship to Land Use and Land Cover in Beijing, China

PubMed Central

Chen, Xiang; Zhou, Weiqi; Pickett, Steward T. A.; Li, Weifeng; Han, Lijian

2016-01-01

Rapid urbanization with intense land use and land cover (LULC) change and explosive population growth has a great impact on water quality. The relationship between LULC characteristics and water quality provides important information for non-point sources (NPS) pollution management. In this study, we first quantified the spatial-temporal patterns of five water quality variables in four watersheds with different levels of urbanization in Beijing, China. We then examined the effects of LULC on water quality across different scales, using Pearson correlation analysis, redundancy analysis, and multiple regressions. The results showed that water quality was improved over the sampled years but with no significant difference (p > 0.05). However, water quality was significantly different among nonurban and both exurban and urban sites (p < 0.05). Forest land was positively correlated with water quality and affected water quality significantly (p < 0.05) within a 200 m buffer zone. Impervious surfaces, water, and crop land were negatively correlated with water quality. Crop land and impervious surfaces, however, affected water quality significantly (p < 0.05) for buffer sizes greater than 800 m. Grass land had different effects on water quality with the scales. The results provide important insights into the relationship between LULC and water quality, and thus for controlling NPS pollution in urban areas. PMID:27128934

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

Diagnosing scaling behavior of groundwater with a fully-integrated, high resolution hydrologic model simulated over the continental US (Invited)

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.; Kollet, S. J.

2013-12-01

Groundwater is an important component of the hydrologic cycle yet its importance is often overlooked. Aquifers are a critical water resource, particularly in irrigation, but also participates in moderating the land-energy balance over the so-called critical zone of 2-10m in water table depth. Yet,the scaling behavior of groundwater is not well known. Here, we present the results of a fully-integrated hydrologic model run over a 6.3M km2 domain that covers much of North America focused on the continental United States. This model encompasses both the Mississippi and Colorado River watersheds in their entirety at 1km resolution and is constructed using the fully-integrated groundwater-vadose zone-surface water-land surface model, ParFlow. Results from this work are compared to observations (both of surface water flow and groundwater depths) and approaches are presented for observing of these integrated systems. Furthermore, results are used to understand the scaling behavior of groundwater over the continent at high resolution. Implications for understanding dominant hydrological processes at large scales will be discussed.

A framework for global diurnally-resolved observations of Land Surface Temperature

NASA Astrophysics Data System (ADS)

Ghent, Darren; Remedios, John

2014-05-01

Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Being a key boundary condition in land surface models, which determine the surface to atmosphere fluxes of heat, water and carbon; thus influencing cloud cover, precipitation and atmospheric chemistry predictions within Global models, the requirement for global diurnal observations of LST is well founded. Earth Observation satellites offer an opportunity to obtain global coverage of LST, with the appropriate exploitation of data from multiple instruments providing a capacity to resolve the diurnal cycle on a global scale. Here we present a framework for the production of global, diurnally resolved, data sets for LST which is a key request from users of LST data. We will show how the sampling of both geostationary and low earth orbit data sets could conceptually be employed to build combined, multi-sensor, pole-to-pole data sets. Although global averages already exist for individual instruments and merging of geostationary based LST is already being addressed operationally (Freitas, et al., 2013), there are still a number of important challenges to overcome. In this presentation, we will consider three of the issues still open in LST remote sensing: 1) the consistency amongst retrievals; 2) the clear-sky bias and its quantification; and 3) merging methods and the propagation of uncertainties. For example, the combined use of both geostationary earth orbit (GEO) and low earth orbit (LEO) data, and both infra-red and microwave data are relatively unexplored but are necessary to make the most progress. Hence this study will suggest what is state-of-the-art and how considerable advances can be made, accounting also for recent improvements in techniques and data quality. The GlobTemperature initiative under the Data User Element of ESA's 4th Earth Observation Envelope Programme (2013-2017), which aims to support the wider uptake of global-scale satellite LST by the research and operational user communities, will be a particularly important element in the development and subsequent provision of global diurnal LST. References Freitas, S.C., Trigo, I.F., Macedo, J., Barroso, C., Silva, R., & Perdigao, R., 2013, Land surface temperature from multiple geostationary satellites, International Journal of Remote Sensing, 34, 3051-3068.

Surface-material maps of Viking landing sites on Mars

NASA Technical Reports Server (NTRS)

Moore, H. J.; Keller, J. M.

1991-01-01

Researchers mapped the surface materials at the Viking landing sites on Mars to gain a better understanding of the materials and rock populations at the sites and to provide information for future exploration. The maps extent to about 9 m in front of each lander and are about 15 m wide - an area comparable to the area of a pixel in high resolution Viking Orbiter images. The maps are divided into the near and far fields. Data for the near fields are from 1/10 scale maps, umpublished maps, and lander images. Data for the far fields are from 1/20 scale contour maps, contoured lander camera mosaics, and lander images. Rocks are located on these maps using stereometric measurements and the contour maps. Frequency size distribution of rocks and the responses of soil-like materials to erosion by engine exhausts during landings are discussed.

Multi-scale landscape factors influencing stream water quality in the state of Oregon.

PubMed

Nash, Maliha S; Heggem, Daniel T; Ebert, Donald; Wade, Timothy G; Hall, Robert K

2009-09-01

Enterococci bacteria are used to indicate the presence of human and/or animal fecal materials in surface water. In addition to human influences on the quality of surface water, a cattle grazing is a widespread and persistent ecological stressor in the Western United States. Cattle may affect surface water quality directly by depositing nutrients and bacteria, and indirectly by damaging stream banks or removing vegetation cover, which may lead to increased sediment loads. This study used the State of Oregon surface water data to determine the likelihood of animal pathogen presence using enterococci and analyzed the spatial distribution and relationship of biotic (enterococci) and abiotic (nitrogen and phosphorous) surface water constituents to landscape metrics and others (e.g. human use, percent riparian cover, natural covers, grazing, etc.). We used a grazing potential index (GPI) based on proximity to water, land ownership and forage availability. Mean and variability of GPI, forage availability, stream density and length, and landscape metrics were related to enterococci and many forms of nitrogen and phosphorous in standard and logistic regression models. The GPI did not have a significant role in the models, but forage related variables had significant contribution. Urban land use within stream reach was the main driving factor when exceeding the threshold (> or =35 cfu/100 ml), agriculture was the driving force in elevating enterococci in sites where enterococci concentration was <35 cfu/100 ml. Landscape metrics related to amount of agriculture, wetlands and urban all contributed to increasing nutrients in surface water but at different scales. The probability of having sites with concentrations of enterococci above the threshold was much lower in areas of natural land cover and much higher in areas with higher urban land use within 60 m of stream. A 1% increase in natural land cover was associated with a 12% decrease in the predicted odds of having a site exceeding the threshold. Opposite to natural land cover, a one unit change in each of manmade barren and urban land use led to an increase of the likelihood of exceeding the threshold by 73%, and 11%, respectively. Change in urban land use had a higher influence on the likelihood of a site exceeding the threshold than that of natural land cover.

A Multi-scale Approach to Urban Thermal Analysis

NASA Technical Reports Server (NTRS)

Gluch, Renne; Quattrochi, Dale A.

2005-01-01

An environmental consequence of urbanization is the urban heat island effect, a situation where urban areas are warmer than surrounding rural areas. The urban heat island phenomenon results from the replacement of natural landscapes with impervious surfaces such as concrete and asphalt and is linked to adverse economic and environmental impacts. In order to better understand the urban microclimate, a greater understanding of the urban thermal pattern (UTP), including an analysis of the thermal properties of individual land covers, is needed. This study examines the UTP by means of thermal land cover response for the Salt Lake City, Utah, study area at two scales: 1) the community level, and 2) the regional or valleywide level. Airborne ATLAS (Advanced Thermal Land Applications Sensor) data, a high spatial resolution (10-meter) dataset appropriate for an environment containing a concentration of diverse land covers, are used for both land cover and thermal analysis at the community level. The ATLAS data consist of 15 channels covering the visible, near-IR, mid-IR and thermal-IR wavelengths. At the regional level Landsat TM data are used for land cover analysis while the ATLAS channel 13 data are used for the thermal analysis. Results show that a heat island is evident at both the community and the valleywide level where there is an abundance of impervious surfaces. ATLAS data perform well in community level studies in terms of land cover and thermal exchanges, but other, more coarse-resolution data sets are more appropriate for large-area thermal studies. Thermal response per land cover is consistent at both levels, which suggests potential for urban climate modeling at multiple scales.

An increase in aerosol burden due to the land-sea warming contrast

NASA Astrophysics Data System (ADS)

Hassan, T.; Allen, R.; Randles, C. A.

2017-12-01

Climate models simulate an increase in most aerosol species in response to warming, particularly over the tropics and Northern Hemisphere midlatitudes. This increase in aerosol burden is related to a decrease in wet removal, primarily due to reduced large-scale precipitation. Here, we show that the increase in aerosol burden, and the decrease in large-scale precipitation, is related to a robust climate change phenomenon—the land/sea warming contrast. Idealized simulations with two state of the art climate models, the National Center for Atmospheric Research Community Atmosphere Model version 5 (NCAR CAM5) and the Geophysical Fluid Dynamics Laboratory Atmospheric Model 3 (GFDL AM3), show that muting the land-sea warming contrast negates the increase in aerosol burden under warming. This is related to smaller decreases in near-surface relative humidity over land, and in turn, smaller decreases in large-scale precipitation over land—especially in the NH midlatitudes. Furthermore, additional idealized simulations with an enhanced land/sea warming contrast lead to the opposite result—larger decreases in relative humidity over land, larger decreases in large-scale precipitation, and larger increases in aerosol burden. Our results, which relate the increase in aerosol burden to the robust climate projection of enhanced land warming, adds confidence that a warmer world will be associated with a larger aerosol burden.

Land surface and climate parameters and malaria features in Vietnam

NASA Astrophysics Data System (ADS)

Liou, Y. A.; Anh, N. K.

2017-12-01

Land surface parameters may affect local microclimate, which in turn alters the development of mosquito habitats and transmission risks (soil-vegetation-atmosphere-vector borne diseases). Forest malaria is a chromic issue in Southeast Asian countries, in particular, such as Vietnam (in 1991, approximate 2 million cases and 4,646 deaths were reported (https://sites.path.org)). Vietnam has lowlands, sub-tropical high humidity, and dense forests, resulting in wide-scale distribution and high biting rate of mosquitos in Vietnam, becoming a challenging and out of control scenario, especially in Vietnamese Central Highland region. It is known that Vietnam's economy mainly relies on agriculture and malaria is commonly associated with poverty. There is a strong demand to investigate the relationship between land surface parameters (land cover, soil moisture, land surface temperature, etc.) and climatic variables (precipitation, humidity, evapotranspiration, etc.) in association with malaria distribution. GIS and remote sensing have been proven their powerful potentials in supporting environmental and health studies. The objective of this study aims to analyze physical attributes of land surface and climate parameters and their links with malaria features. The outcomes are expected to illustrate how remotely sensed data has been utilized in geohealth applications, surveillance, and health risk mapping. In addition, a platform with promising possibilities of allowing disease early-warning systems with citizen participation will be proposed.

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.

The influence of land-use change and landscape dynamics on the climate system: relevance to climate-change policy beyond the radiative effect of greenhouse gases.

PubMed

Pielke, Roger A; Marland, Gregg; Betts, Richard A; Chase, Thomas N; Eastman, Joseph L; Niles, John O; Niyogi, Dev Dutta S; Running, Steven W

2002-08-15

Our paper documents that land-use change impacts regional and global climate through the surface-energy budget, as well as through the carbon cycle. The surface-energy budget effects may be more important than the carbon-cycle effects. However, land-use impacts on climate cannot be adequately quantified with the usual metric of 'global warming potential'. A new metric is needed to quantify the human disturbance of the Earth's surface-energy budget. This 'regional climate change potential' could offer a new metric for developing a more inclusive climate protocol. This concept would also implicitly provide a mechanism to monitor potential local-scale environmental changes that could influence biodiversity.

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

Using Landsat Thematic Mapper (TM) sensor to detect change in land surface temperature in relation to land use change in Yazd, Iran

NASA Astrophysics Data System (ADS)

Zareie, Sajad; Khosravi, Hassan; Nasiri, Abouzar; Dastorani, Mostafa

2016-11-01

Land surface temperature (LST) is one of the key parameters in the physics of land surface processes from local to global scales, and it is one of the indicators of environmental quality. Evaluation of the surface temperature distribution and its relation to existing land use types are very important to the investigation of the urban microclimate. In arid and semi-arid regions, understanding the role of land use changes in the formation of urban heat islands is necessary for urban planning to control or reduce surface temperature. The internal factors and environmental conditions of Yazd city have important roles in the formation of special thermal conditions in Iran. In this paper, we used the temperature-emissivity separation (TES) algorithm for LST retrieving from the TIRS (Thermal Infrared Sensor) data of the Landsat Thematic Mapper (TM). The root mean square error (RMSE) and coefficient of determination (R2) were used for validation of retrieved LST values. The RMSE of 0.9 and 0.87 °C and R2 of 0.98 and 0.99 were obtained for the 1998 and 2009 images, respectively. Land use types for the city of Yazd were identified and relationships between land use types, land surface temperature and normalized difference vegetation index (NDVI) were analyzed. The Kappa coefficient and overall accuracy were calculated for accuracy assessment of land use classification. The Kappa coefficient values are 0.96 and 0.95 and the overall accuracy values are 0.97 and 0.95 for the 1998 and 2009 classified images, respectively. The results showed an increase of 1.45 °C in the average surface temperature. The results of this study showed that optical and thermal remote sensing methodologies can be used to research urban environmental parameters. Finally, it was found that special thermal conditions in Yazd were formed by land use changes. Increasing the area of asphalt roads, residential, commercial and industrial land use types and decreasing the area of the parks, green spaces and fallow lands in Yazd caused a rise in surface temperature during the 11-year period.

Monitoring land at regional and national scales and the role of remote sensing

NASA Astrophysics Data System (ADS)

Dymond, John R.; Bégue, Agnes; Loseen, Danny

There is a need world wide for monitoring land and its ecosystems to ensure their sustainable use. Despite the laudable intentions of Agenda 21 at the Rio Earth Summit, 1992, in which many countries agreed to monitor and report on the status of their land, systematic monitoring of land has yet to begin. The problem is truly difficult, as the earth's surface is vast and the funds available for monitoring are relatively small. This paper describes several methods for cost-effective monitoring of large land areas, including: strategic monitoring; statistical sampling; risk-based approaches; integration of land and water monitoring; and remote sensing. The role of remote sensing is given special attention, as it is the only method that can monitor land exhaustively and directly, at regional and national scales. It is concluded that strategic monitoring, whereby progress towards environmental goals is assessed, is a vital element in land monitoring as it provides a means for evaluating the utility of monitoring designs.

Scale Dependence of Land Atmosphere Interactions in Wet and Dry Regions as Simulated with NU-WRF over the Southwestern and Southeast US

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Wu, Di; Lau, K.- M.; Tao, Wei-Kuo

2016-01-01

Large-scale forcing and land-atmosphere interactions on precipitation are investigated with NASA-Unified WRF (NU-WRF) simulations during fast transitions of ENSO phases from spring to early summer of 2010 and 2011. The model is found to capture major precipitation episodes in the 3-month simulations without resorting to nudging. However, the mean intensity of the simulated precipitation is underestimated by 46% and 57% compared with the observations in dry and wet regions in the southwestern and south-central United States, respectively. Sensitivity studies show that large-scale atmospheric forcing plays a major role in producing regional precipitation. A methodology to account for moisture contributions to individual precipitation events, as well as total precipitation, is presented under the same moisture budget framework. The analysis shows that the relative contributions of local evaporation and large-scale moisture convergence depend on the dry/wet regions and are a function of temporal and spatial scales. While the ratio of local and large-scale moisture contributions vary with domain size and weather system, evaporation provides a major moisture source in the dry region and during light rain events, which leads to greater sensitivity to soil moisture in the dry region and during light rain events. The feedback of land surface processes to large-scale forcing is well simulated, as indicated by changes in atmospheric circulation and moisture convergence. Overall, the results reveal an asymmetrical response of precipitation events to soil moisture, with higher sensitivity under dry than wet conditions. Drier soil moisture tends to suppress further existing below-normal precipitation conditions via a positive soil moisture-land surface flux feedback that could worsen drought conditions in the southwestern United States.

Numerical simulations of island-scale airflow over Maui and the Maui vortex under summer trade wind conditions

Treesearch

DaNa L. Carlis; Yi-Leng Chen; Vernon R. Morris

2010-01-01

The fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) coupled with the Noah land surface model (LSM) is employed to simulate island-scale airflow and circulations over Maui County, Hawaii, under summer trade wind conditions, during July–August 2005. The model forecasts are validated by surface observations with good agreement.

Improving wind energy forecasts using an Ensemble Kalman Filter data assimilation technique in a fully coupled hydrologic and atmospheric model

NASA Astrophysics Data System (ADS)

Williams, J. L.; Maxwell, R. M.; Delle Monache, L.

2012-12-01

Wind power is rapidly gaining prominence as a major source of renewable energy. Harnessing this promising energy source is challenging because of the chaotic nature of wind and its propensity to change speed and direction over short time scales. Accurate forecasting tools are critical to support the integration of wind energy into power grids and to maximize its impact on renewable energy portfolios. Numerous studies have shown that soil moisture distribution and land surface vegetative processes profoundly influence atmospheric boundary layer development and weather processes on local and regional scales. Using the PF.WRF model, a fully-coupled hydrologic and atmospheric model employing the ParFlow hydrologic model with the Weather Research and Forecasting model coupled via mass and energy fluxes across the land surface, we have explored the connections between the land surface and the atmosphere in terms of land surface energy flux partitioning and coupled variable fields including hydraulic conductivity, soil moisture and wind speed, and demonstrated that reductions in uncertainty in these coupled fields propagate through the hydrologic and atmospheric system. We have adapted the Data Assimilation Research Testbed (DART), an implementation of the robust Ensemble Kalman Filter data assimilation algorithm, to expand our capability to nudge forecasts produced with the PF.WRF model using observational data. Using a semi-idealized simulation domain, we examine the effects of assimilating observations of variables such as wind speed and temperature collected in the atmosphere, and land surface and subsurface observations such as soil moisture on the quality of forecast outputs. The sensitivities we find in this study will enable further studies to optimize observation collection to maximize the utility of the PF.WRF-DART forecasting system.

Case analyses and numerical simulation of soil thermal impacts on land surface energy budget based on an off-line land surface model

NASA Astrophysics Data System (ADS)

Guo, W. D.; Sun, S. F.; Qian, Y. F.

2002-05-01

The statistical relationship between soil thermal anomaly and short-term climate change is presented based on a typical case study. Furthermore, possible physical mechanisms behind the relationship are revealed through using an off-line land surface model with a reasonable soil thermal forcing at the bottom of the soil layer. In the first experiment, the given heat flux is 5 W m(-2) at the bottom of the soil layer (in depth of 6.3 m) for 3 months, while only a positive ground temperature anomaly of 0.06degreesC can be found compared to the control run. The anomaly, however, could reach 0.65degreesC if the soil thermal conductivity was one order of magnitude larger. It could be even as large as 0.81degreesC assuming the heat flux at bottom is 10 W m(-2). Meanwhile, an increase of about 10 W m(-2) was detected both for heat flux in soil and sensible heat on land surface, which is not neglectable to the short-term climate change. The results show that considerable response in land surface energy budget could be expected when the soil thermal forcing reaches a certain spatial-temporal scale. Therefore, land surface models should not ignore the upward heat flux from the bottom of the soil layer, Moreover, integration for a longer period of time and coupled land-atmosphere model are also necessary for the better understanding of this issues.

Anticipating land surface change

PubMed Central

Streeter, Richard; Dugmore, Andrew J.

2013-01-01

The interplay of human actions and natural processes over varied spatial and temporal scales can result in abrupt transitions between contrasting land surface states. Understanding these transitions is a key goal of sustainability science because they can represent abrupt losses of natural capital. This paper recognizes flickering between alternate land surface states in advance of threshold change and critical slowing down in advance of both threshold changes and noncritical transformation. The early warning signals we observe are rises in autocorrelation, variance, and skewness within millimeter-resolution thickness measurements of tephra layers deposited in A.D. 2010 and A.D. 2011. These signals reflect changing patterns of surface vegetation, which are known to provide early warning signals of critical transformations. They were observed toward migrating soil erosion fronts, cryoturbation limits, and expanding deflation zones, thus providing potential early warning signals of land surface change. The record of the spatial patterning of vegetation contained in contemporary tephra layers shows how proximity to land surface change could be assessed in the widespread regions affected by shallow layers of volcanic fallout (those that can be subsumed within the existing vegetation cover). This insight shows how we could use tephra layers in the stratigraphic record to identify “near misses,” close encounters with thresholds that did not lead to tipping points, and thus provide additional tools for archaeology, sustainability science, and contemporary land management. PMID:23530230

Landsat Data Continuity Mission - Launch Fever

NASA Technical Reports Server (NTRS)

Irons, James R.; Loveland, Thomas R.; Markham, Brian L.; Masek, Jeffrey G.; Cook, Bruce; Dwyer, John L.

2012-01-01

The year 2013 will be an exciting period for those that study the Earth land surface from space, particularly those that observe and characterize land cover, land use, and the change of cover and use over time. Two new satellite observatories will be launched next year that will enhance capabilities for observing the global land surface. The United States plans to launch the Landsat Data Continuity Mission (LDCM) in January. That event will be followed later in the year by the European Space Agency (ESA) launch of the first Sentinel 2 satellite. Considered together, the two satellites will increase the frequency of opportunities for viewing the land surface at a scale where human impact and influence can be differentiated from natural change. Data from the two satellites will provide images for similar spectral bands and for comparable spatial resolutions with rigorous attention to calibration that will facilitate cross comparisons. This presentation will provide an overview of the LDCM satellite system and report its readiness for the January launch.

Increasing bioenergy production on arable land: Does the regional and local climate respond? Germany as a case study

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Gutjahr, Oliver; Busch, Gerald; Thiele, Jan C.

2014-03-01

The extent and magnitude of land cover change effect on local and regional future climate during the vegetation period due to different forms of bioenergy plants are quantified for extreme temperatures and energy fluxes. Furthermore, we vary the spatial extent of plant allocation on arable land and simulate alternative availability of transpiration water to mimic both rainfed agriculture and irrigation. We perform climate simulations down to 1 km scale for 1970-1975 C20 and 2070-2075 A1B over Germany with Consortium for Small-Scale Modeling in Climate Mode. Here an impact analysis indicates a strong local influence due to land cover changes. The regional effect is decreased by two thirds of the magnitude of the local-scale impact. The changes are largest locally for irrigated poplar with decreasing maximum temperatures by 1°C in summer months and increasing specific humidity by 0.15 g kg-1. The increased evapotranspiration may result in more precipitation. The increase of surface radiative fluxes Rnet due to changes in latent and sensible heat is estimated by 5 W m-2locally. Moreover, increases in the surface latent heat flux cause strong local evaporative cooling in the summer months, whereas the associated regional cooling effect is pronounced by increases in cloud cover. The changes on a regional scale are marginal and not significant. Increasing bioenergy production on arable land may result in local temperature changes but not in substantial regional climate change in Germany. We show the effect of agricultural practices during climate transitions in spring and fall.

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

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

Tesfa, Teklu K.; Ruby Leung, L.; Huang, Maoyi

2014-03-27

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., abilities to perform consistently across a range of spatial resolutions) in simulating runoff generation. Simulations produced by the grid- and subbasin-based configurations of the Community Land Model (CLM) are compared at four spatial resolutions (0.125o, 0.25o, 0.5o and 1o) over the topographically diverse region of the U.S. Pacific Northwest. Using the 0.125o resolution simulation as the “reference”, statistical skill metrics are calculated and compared across simulations at 0.25o, 0.5o and 1o spatial resolutions of each modelingmore » approach at basin and topographic region levels. Results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach for runoff generation. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o compared to 0.125o are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages of the subbasin-based approach are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning, which is related to air temperature and surface elevation. Scalability of a topographic parameter used in the runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes, with implications to surface heat fluxes in coupled land-atmosphere modeling.« less

Green Infrastructure and Watershed-Scale Hydrology in Mixed Land Cover System

EPA Science Inventory

Urbanization results in replacement of pervious areas (e.g., vegetation, topsoil) with impervious surfaces such as roads, roofs, and parking lots, which cause reductions in interception, evapotranspiration, and infiltration, and increases in surface runoff (overland flow) and pol...

Hydrologic and land-cover features of the Caloosahatchee River Basin, Lake Okeechobee to Franklin Lock, Florida

USGS Publications Warehouse

LaRose, Henry R.; McPherson, Benjamin F.

1980-01-01

The freshwater part of the Caloosahatchee River basin, Fla., from Franklin Lock to Lake Okeechobee, is shown at a scale of 1 inch equals 1 mile on an aerial photomosaic, dated January 1979. The basin is divided into 16 subbasins, and the land cover and land use in each subbasin are given. The basin is predominantly rangeland and agricultural land. Surface-water flow in the basin is largely controlled. Some selected data on water quality are given. (USGS)

Moving towards Hyper-Resolution Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Rouf, T.; Maggioni, V.; Houser, P.; Mei, Y.

2017-12-01

Developing a predictive capability for terrestrial hydrology across landscapes, with water, energy and nutrients as the drivers of these dynamic systems, faces the challenge of scaling meter-scale process understanding to practical modeling scales. Hyper-resolution land surface modeling can provide a framework for addressing science questions that we are not able to answer with coarse modeling scales. In this study, we develop a hyper-resolution forcing dataset from coarser resolution products using a physically based downscaling approach. These downscaling techniques rely on correlations with landscape variables, such as topography, roughness, and land cover. A proof-of-concept has been implemented over the Oklahoma domain, where high-resolution observations are available for validation purposes. Hourly NLDAS (North America Land Data Assimilation System) forcing data (i.e., near-surface air temperature, pressure, and humidity) have been downscaled to 500m resolution over the study area for 2015-present. Results show that correlation coefficients between the downscaled temperature dataset and ground observations are consistently higher than the ones between the NLDAS temperature data at their native resolution and ground observations. Not only correlation coefficients are higher, but also the deviation around the 1:1 line in the density scatterplots is smaller for the downscaled dataset than the original one with respect to the ground observations. Results are therefore encouraging as they demonstrate that the 500m temperature dataset has a good agreement with the ground information and can be adopted to force the land surface model for soil moisture estimation. The study has been expanded to wind speed and direction, incident longwave and shortwave radiation, pressure, and precipitation. Precipitation is well known to vary dramatically with elevation and orography. Therefore, we are pursuing a downscaling technique based on both topographical and vegetation characteristics.

Monitoring and validating spatio-temporal continuously daily evapotranspiration and its components at river basin scale

NASA Astrophysics Data System (ADS)

Song, L.; Liu, S.; Kustas, W. P.; Nieto, H.

2017-12-01

Operational estimation of spatio-temporal continuously daily evapotranspiration (ET), and the components evaporation (E) and transpiration (T), at watershed scale is very useful for developing a sustainable water resource strategy in semi-arid and arid areas. In this study, multi-year all-weather daily ET, E and T were estimated using MODIS-based (Dual Temperature Difference) DTD model under different land covers in Heihe watershed, China. The remotely sensed ET was validated using ground measurements from large aperture scintillometer systems, with a source area of several kilometers, under grassland, cropland and riparian shrub-forest. The results showed that the remotely sensed ET produced mean absolute percent deviation (MAPD) errors of about 30% during the growing season for all-weather conditions, but the model performed better under clear sky conditions. However, uncertainty in interpolated MODIS land surface temperature input data under cloudy conditions to the DTD model, and the representativeness of LAS measurements for the heterogeneous land surfaces contribute to the discrepancies between the modeled and ground measured surface heat fluxes, especially for the more humid grassland and heterogeneous shrub-forest sites.

Pairing FLUXNET sites to validate model representations of land-use/land-cover change

NASA Astrophysics Data System (ADS)

Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.

2018-01-01

Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.

Quantifying the Terrestrial Surface Energy Fluxes Using Remotely-Sensed Satellite Data

NASA Astrophysics Data System (ADS)

Siemann, Amanda Lynn

The dynamics of the energy fluxes between the land surface and the atmosphere drive local and regional climate and are paramount to understand the past, present, and future changes in climate. Although global reanalysis datasets, land surface models (LSMs), and climate models estimate these fluxes by simulating the physical processes involved, they merely simulate our current understanding of these processes. Global estimates of the terrestrial, surface energy fluxes based on observations allow us to capture the dynamics of the full climate system. Remotely-sensed satellite data is the source of observations of the land surface which provide the widest spatial coverage. Although net radiation and latent heat flux global, terrestrial, surface estimates based on remotely-sensed satellite data have progressed, comparable sensible heat data products and ground heat flux products have not progressed at this scale. Our primary objective is quantifying and understanding the terrestrial energy fluxes at the Earth's surface using remotely-sensed satellite data with consistent development among all energy budget components [through the land surface temperature (LST) and input meteorology], including validation of these products against in-situ data, uncertainty assessments, and long-term trend analysis. The turbulent fluxes are constrained by the available energy using the Bowen ratio of the un-constrained products to ensure energy budget closure. All final products are within uncertainty ranges of literature values, globally. When validated against the in-situ estimates, the sensible heat flux estimates using the CFSR air temperature and constrained with the products using the MODIS albedo produce estimates closest to the FLUXNET in-situ observations. Poor performance over South America is consistent with the largest uncertainties in the energy budget. From 1984-2007, the longwave upward flux increase due to the LST increase drives the net radiation decrease, and the decrease in the available energy balances the decrease in the sensible heat flux. These datasets are useful for benchmarking climate models and LSM output at the global annual scale and the regional scale subject to the regional uncertainties and performance. Future work should improve the input data, particularly the temperature gradient and Zilitinkevich empirical constant, to reduce uncertainties.

Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) Science Plan

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

Fast, JD; Berg, LK

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 contain uncertainties resulting in part from insufficient coincident data that couples cloud macrophysical and microphysical properties to inhomogeneities in boundary layer and aerosol properties. The Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign is designed to provide a detailed set of measurements that are needed to obtain a moremore » complete understanding of the life cycle of shallow clouds by coupling cloud macrophysical and microphysical properties to land surface properties, ecosystems, and aerosols. HI-SCALE consists of 2, 4-week intensive observational periods, one in the spring and the other in the late summer, to take advantage of different stages and distribution of “greenness” for various types of vegetation in the vicinity of the Atmospheric Radiation and Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site as well as aerosol properties that vary during the growing season. Most of the proposed instrumentation will be deployed on the ARM Aerial Facility (AAF) Gulfstream 1 (G-1) aircraft, including those that measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions, and cloud condensation nuclei concentrations. Routine ARM aerosol measurements made at the surface will be supplemented with aerosol microphysical properties measurements. The G-1 aircraft will complete transects over the SGP Central Facility at multiple altitudes within the boundary layer, within clouds, and above clouds.« less

Atmospheric sensitivity to land surface changes: comparing the impact of albedo, roughness, and evaporative resistance on near-surface air temperature using an idealized land model.

NASA Astrophysics Data System (ADS)

Lague, M. M.; Swann, A. L. S.; Bonan, G. B.

2017-12-01

Past studies have demonstrated how changes in vegetation can impact the atmosphere; however, it is often difficult to identify the exact physical pathway through which vegetation changes drive an atmospheric response. Surface properties (such as vegetation color, or height) control surface energy fluxes, which feed back on the atmosphere on both local and global scales by modifying temperatures, cloud cover, and energy gradients. Understanding how land surface properties influence energy fluxes is crucial for improving our understanding of how vegetation change - past, present, and future - impacts the atmosphere, global climate, and people. We explore the sensitivity of the atmosphere to perturbations of three land surface properties - albedo, roughness, and evaporative resistance - using an idealized land model coupled to an Earth System Model. We derive a relationship telling us how large a change in each surface property is required to drive a local 0.1 K change in 2m air temperature. Using this idealized framework, we are able to separate the influence on the atmosphere of each individual surface property. We demonstrate that the impact of each surface property on the atmosphere is spatially variable - that is, a similar change in vegetation can have different climate impacts if made in different locations. This analysis not only improves our understanding of how the land system can influence climate, but also provides us with a set of theoretical limits on the potential climate impact of arbitrary vegetation change (natural or anthropogenic).

Assessment of the water and energy budget simulation of three land surface models: CLM4.5, CoLM2014, and CoLM2005

NASA Astrophysics Data System (ADS)

Li, C.; Lu, H.; Wen, X.

2015-12-01

Land surface model (LSM), which simulates energy, water and momentum exchanges between land and atmosphere, is an important component of Earth System Models (ESM). As shown in CMIP5, different ESMs usually use different LSMs and represent various land surface status. In order to select a land surface model which could be embedded into the ESM developed in Tsinghua University, we firstly evaluate the performance of three LSMs: Community Land Model (CLM4.5) and two different versions of Common Land Model (CoLM2005 and CoLM2014). All of three models were driven by CRUNCEP data and simulation results from 1980 to 2010 were used in this study. Diagnostic data provided by NCAR, global latent and sensible heat flux map estimated by Jung, net radiation from SRB, and in situ observation collected from FluxNet were used as reference data. Two variables, surface runoff and snow depth, were used for evaluating the model performance in water budget simulation, while three variables including net radiation, sensible heat, and latent heat were used for assessing energy budget simulation. For 30 years averaged runoff, global average value of Colm2014 is 0.44mm/day and close to the diagnostic value of 0.75 mm/day, while that of Colm2005 is 0.44mm/day and that of CLM is 0.20mm/day. For snow depth simulation, three models all have overestimation in the Northern Hemisphere and underestimation in the Southern Hemisphere compare to diagnostic data. For 30 years energy budget simulation, at global scale, CoLM2005 performs best in latent heat estimation, CoLM2014 performs best in sensible heat simulation, and CoLM2005 and CoLM2014 make similar performance in net radiation estimation but is still better than CLM. At regional and local scale, comparing to the four years average of flux tower observation, RMSE of CoLM2005 is the smallest for latent heat (9.717 W/m2) , and for sensible heat simulation, RMSE of CoLM2005 (13.048 W/m2) is slightly greater than CLM(10.767 W/m2) but still better than CoLM2014(30.085 W/m2). Our analysis shows that both CoLM 2005 and CoLM 2014 are able to reproduce comparable land surface water and energy fluxes. It implies that the ESM developed in Tsinghua University may use CoLM, a LSM developed and maintained in China, as the land surface component. .

What determines transitions between energy- and moisture-limited evaporative regimes?

NASA Astrophysics Data System (ADS)

Haghighi, E.; Gianotti, D.; Akbar, R.; Salvucci, G.; Entekhabi, D.

2017-12-01

The relationship between evaporative fraction (EF) and soil moisture (SM) has traditionally been used in atmospheric and land-surface modeling communities to determine the strength of land-atmosphere coupling in the context of the dominant evaporative regime (energy- or moisture-limited). However, recent field observations reveal that EF-SM relationship is not unique and could vary substantially with surface and/or meteorological conditions. This implies that conventional EF-SM relationships (exclusive of surface and meteorological conditions) are embedded in more complex dependencies and that in fact it is a multi-dimensional function. To fill the fundamental knowledge gaps on the important role of varying surface and meteorological conditions not accounted for by the traditional evaporative regime conceptualization, we propose a generalized EF framework using a mechanistic pore-scale model for evaporation and energy partitioning over drying soil surfaces. Nonlinear interactions among the components of the surface energy balance are reflected in a critical SM that marks the onset of transition between energy- and moisture-limited evaporative regimes. The new generalized EF framework enables physically based estimates of the critical SM, and provides new insights into the origin of land surface EF partitioning linked to meteorological input data and the evolution of land surface temperature during surface drying that affect the relative efficiency of surface energy balance components. Our results offer new opportunities to advance predictive capabilities quantifying land-atmosphere coupling for a wide range of present and projected meteorological input data.

Modelling the influence of land-use changes on biophysical and biochemical interactions at regional and global scales.

PubMed

Devaraju, N; Bala, G; Nemani, R

2015-09-01

Land-use changes since the start of the industrial era account for nearly one-third of the cumulative anthropogenic CO2 emissions. In addition to the greenhouse effect of CO2 emissions, changes in land use also affect climate via changes in surface physical properties such as albedo, evapotranspiration and roughness length. Recent modelling studies suggest that these biophysical components may be comparable with biochemical effects. In regard to climate change, the effects of these two distinct processes may counterbalance one another both regionally and, possibly, globally. In this article, through hypothetical large-scale deforestation simulations using a global climate model, we contrast the implications of afforestation on ameliorating or enhancing anthropogenic contributions from previously converted (agricultural) land surfaces. Based on our review of past studies on this subject, we conclude that the sum of both biophysical and biochemical effects should be assessed when large-scale afforestation is used for countering global warming, and the net effect on global mean temperature change depends on the location of deforestation/afforestation. Further, although biochemical effects trigger global climate change, biophysical effects often cause strong local and regional climate change. The implication of the biophysical effects for adaptation and mitigation of climate change in agriculture and agroforestry sectors is discussed. © 2014 John Wiley & Sons Ltd.

The influence of the fault zone width on land surface vibrations after the high-energy tremor in the "Rydułtowy-Anna" hard coal mine

NASA Astrophysics Data System (ADS)

Pilecka, Elżbieta; Szwarkowski, Dariusz

2018-04-01

In the article, a numerical analysis of the impact of the width of the fault zone on land surface tremors on the area of the "Rydułtowy - Anna" hard coal mine was performed. The analysis covered the dynamic impact of the actual seismic wave after the high-energy tremor of 7 June 2013. Vibrations on the land surface are a measure of the mining damage risk. It is particularly the horizontal components of land vibrations that are dangerous to buildings which is reflected in the Mining Scales of Intensity (GSI) of vibrations. The run of a seismic wave in the rock mass from the hypocenter to the area's surface depends on the lithology of the area and the presence of fault zones. The rock mass network cut by faults of various widths influences the amplitude of tremor reaching the area's surface. The analysis of the impact of the width of the fault zone was done for three alternatives.

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.

Land and federal mineral ownership coverage for southern Wyoming

USGS Publications Warehouse

Biewick, L.H.; Mercier, T.J.; Saber, T.T.; Urbanowski, S.R.; Neasloney, Larry

1999-01-01

This Arc/Info coverage contains land status and Federal mineral ownership for approximately 37,800 square miles in southern Wyoming. The polygon coverage (which is also provided here as a shapefile) contains two attributes of ownership information for each polygon. One attribute indicates where the surface is State owned, privately owned, or, if Federally owned, which Federal agency manages the land surface. The other attribute indicates which minerals, if any, are owned by the Federal govenment. This coverage is based on land status and Federal mineral ownership data compiled by the U.S. Geological Survey (USGS) and the Wyoming State Bureau of Land Management (BLM) at a scale of 1:24,000. This coverage was compiled primarily to serve the USGS National Oil and Gas Resource Assessment and National Coal Resource Assessment Projects in the Northern Rocky Mountains/Great Plains Region.

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...

Systematic Mapping and Statistical Analyses of Valley Landform and Vegetation Asymmetries Across Hydroclimatic Gradients

NASA Astrophysics Data System (ADS)

Poulos, M. J.; Pierce, J. L.; McNamara, J. P.; Flores, A. N.; Benner, S. G.

2015-12-01

Terrain aspect alters the spatial distribution of insolation across topography, driving eco-pedo-hydro-geomorphic feedbacks that can alter landform evolution and result in valley asymmetries for a suite of land surface characteristics (e.g. slope length and steepness, vegetation, soil properties, and drainage development). Asymmetric valleys serve as natural laboratories for studying how landscapes respond to climate perturbation. In the semi-arid montane granodioritic terrain of the Idaho batholith, Northern Rocky Mountains, USA, prior works indicate that reduced insolation on northern (pole-facing) aspects prolongs snow pack persistence, and is associated with thicker, finer-grained soils, that retain more water, prolong the growing season, support coniferous forest rather than sagebrush steppe ecosystems, stabilize slopes at steeper angles, and produce sparser drainage networks. We hypothesize that the primary drivers of valley asymmetry development are changes in the pedon-scale water-balance that coalesce to alter catchment-scale runoff and drainage development, and ultimately cause the divide between north and south-facing land surfaces to migrate northward. We explore this conceptual framework by coupling land surface analyses with statistical modeling to assess relationships and the relative importance of land surface characteristics. Throughout the Idaho batholith, we systematically mapped and tabulated various statistical measures of landforms, land cover, and hydroclimate within discrete valley segments (n=~10,000). We developed a random forest based statistical model to predict valley slope asymmetry based upon numerous measures (n>300) of landscape asymmetries. Preliminary results suggest that drainages are tightly coupled with hillslopes throughout the region, with drainage-network slope being one of the strongest predictors of land-surface-averaged slope asymmetry. When slope-related statistics are excluded, due to possible autocorrelation, valley slope asymmetry is most strongly predicted by asymmetries of insolation and drainage density, which generally supports a water-balance based conceptual model of valley asymmetry development. Surprisingly, vegetation asymmetries had relatively low predictive importance.

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.

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.

Influence of Idealized Heterogeneity on Wet and Dry Planetary Boundary Layers Coupled to the Land Surface. 2; Phase-Averages

NASA Technical Reports Server (NTRS)

Houser, Paul (Technical Monitor); Patton, Edward G.; Sullivan, Peter P.; Moeng, Chin-Hoh

2003-01-01

We examine the influence of surface heterogeneity on boundary layers using a large-eddy simulation coupled to a land-surface model. Heterogeneity, imposed in strips varying from 2-30 km (1 less than lambda/z(sub i) less than 18), is found to dramatically alter the structure of the free convective boundary layer by inducing significant organized circulations. A conditional sampling technique, based on the scale of the surface heterogeneity (phase averaging), is used to identify and quantify the organized surface fluxes and motions in the atmospheric boundary layer. The impact of the organized motions on turbulent transport depends critically on the scale of the heterogeneity lambda, the boundary layer height zi and the initial moisture state of the boundary layer. Dynamical and scalar fields respond differently as the scale of the heterogeneity varies. Surface heterogeneity of scale 4 less than lamba/z(sub i) less than 9 induces the strongest organized flow fields (up, wp) while heterogeneity with smaller or larger lambda/z(sub i) induces little organized motion. However, the organized components of the scalar fields (virtual potential temperature and mixing ratio) grow continuously in magnitude and horizontal scale, as lambda/z(sub i) increases. For some cases, the organized motions can contribute nearly 100% of the total vertical moisture flux. Patch-induced fluxes are shown to dramatically impact point measurements that assume the time-average vertical velocity to be zero. The magnitude and sign of this impact depends on the location of the measurement within the region of heterogeneity.

Data-driven modeling of surface temperature anomaly and solar activity trends

USGS Publications Warehouse

Friedel, Michael J.

2012-01-01

A novel two-step modeling scheme is used to reconstruct and analyze surface temperature and solar activity data at global, hemispheric, and regional scales. First, the self-organizing map (SOM) technique is used to extend annual modern climate data from the century to millennial scale. The SOM component planes are used to identify and quantify strength of nonlinear relations among modern surface temperature anomalies (<150 years), tropical and extratropical teleconnections, and Palmer Drought Severity Indices (0–2000 years). Cross-validation of global sea and land surface temperature anomalies verifies that the SOM is an unbiased estimator with less uncertainty than the magnitude of anomalies. Second, the quantile modeling of SOM reconstructions reveal trends and periods in surface temperature anomaly and solar activity whose timing agrees with published studies. Temporal features in surface temperature anomalies, such as the Medieval Warm Period, Little Ice Age, and Modern Warming Period, appear at all spatial scales but whose magnitudes increase when moving from ocean to land, from global to regional scales, and from southern to northern regions. Some caveats that apply when interpreting these data are the high-frequency filtering of climate signals based on quantile model selection and increased uncertainty when paleoclimatic data are limited. Even so, all models find the rate and magnitude of Modern Warming Period anomalies to be greater than those during the Medieval Warm Period. Lastly, quantile trends among reconstructed equatorial Pacific temperature profiles support the recent assertion of two primary El Niño Southern Oscillation types. These results demonstrate the efficacy of this alternative modeling approach for reconstructing and interpreting scale-dependent climate variables.

Tower-scale performance of four observation-based evapotranspiration algorithms within the WACMOS-ET project

NASA Astrophysics Data System (ADS)

Michel, Dominik; Miralles, Diego; Jimenez, Carlos; Ershadi, Ali; McCabe, Matthew F.; Hirschi, Martin; Seneviratne, Sonia I.; Jung, Martin; Wood, Eric F.; (Bob) Su, Z.; Timmermans, Joris; Chen, Xuelong; Fisher, Joshua B.; Mu, Quiaozen; Fernandez, Diego

2015-04-01

Research on climate variations and the development of predictive capabilities largely rely on globally available reference data series of the different components of the energy and water cycles. Several efforts have recently aimed at producing large-scale and long-term reference data sets of these components, e.g. based on in situ observations and remote sensing, in order to allow for diagnostic analyses of the drivers of temporal variations in the climate system. Evapotranspiration (ET) is an essential component of the energy and water cycle, which cannot be monitored directly on a global scale by remote sensing techniques. In recent years, several global multi-year ET data sets have been derived from remote sensing-based estimates, observation-driven land surface model simulations or atmospheric reanalyses. The LandFlux-EVAL initiative presented an ensemble-evaluation of these data sets over the time periods 1989-1995 and 1989-2005 (Mueller et al. 2013). The WACMOS-ET project (http://wacmoset.estellus.eu) started in the year 2012 and constitutes an ESA contribution to the GEWEX initiative LandFlux. It focuses on advancing the development of ET estimates at global, regional and tower scales. WACMOS-ET aims at developing a Reference Input Data Set exploiting European Earth Observations assets and deriving ET estimates produced by a set of four ET algorithms covering the period 2005-2007. The algorithms used are the SEBS (Su et al., 2002), Penman-Monteith from MODIS (Mu et al., 2011), the Priestley and Taylor JPL model (Fisher et al., 2008) and GLEAM (Miralles et al., 2011). The algorithms are run with Fluxnet tower observations, reanalysis data (ERA-Interim), and satellite forcings. They are cross-compared and validated against in-situ data. In this presentation the performance of the different ET algorithms with respect to different temporal resolutions, hydrological regimes, land cover types (including grassland, cropland, shrubland, vegetation mosaic, savanna, woody savanna, needleleaf forest, deciduous forest and mixed forest) are evaluated at the tower-scale in 24 pre-selected study regions on three continents (Europe, North America, and Australia). References: Fisher, J. B., Tu, K.P., and Baldocchi, D.D. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites, Remote Sens. Environ. 112, 901-919, 2008. Jiménez, C. et al. Global intercomparison of 12 land surface heat flux estimates. J. Geophys. Res. 116, D02102, 2011. 
 Miralles, D.G. et al. Global land-surface evaporation estimated from satellite-based observations. Hydrol. Earth Syst. Sci. 15, 453-469, 2011. 
 Mu, Q., Zhao, M. & Running, S.W. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens. Environ. 115, 1781-1800, 2011. 
 Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A. J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G., McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang, Y., and Seneviratne, S. I. (2013). Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis. Hydrology and Earth System Sciences, 17, 3707-3720. Mueller, B. et al. Benchmark products for land evapotranspiration: LandFlux-EVAL multi-dataset synthesis. Hydrol. Earth Syst. Sci. 17, 3707-3720, 2013. Su, Z. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes. Hydrol. Earth Syst. Sci. 6, 85-99, 2002.

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

Simulation of Urban Heat Island Mitigation Strategies in Atlanta, GA Using High-Resolution Land Use/Land Cover Data Set to Enhance Meteorological Modeling

NASA Technical Reports Server (NTRS)

Crosson, William L.; Dembek, Scott; Estes, Maurice G., Jr.; Limaye, Ashutosh S.; Lapenta, William; Quattrochi, Dale A.; Johnson, Hoyt; Khan, Maudood

2006-01-01

The specification of land use/land cover (LULC) and associated land surface parameters in meteorological models at all scales has a major influence on modeled surface energy fluxes and boundary layer states. In urban areas, accurate representation of the land surface may be even more important than in undeveloped regions due to the large heterogeneity within the urban area. Deficiencies in the characterization of the land surface related to the spatial or temporal resolution of the data, the number of LULC classes defined, the accuracy with which they are defined, or the degree of heterogeneity of the land surface properties within each class may degrade the performance of the models. In this study, an experiment was conducted to test a new high-resolution LULC data set for meteorological simulations for the Atlanta, Georgia metropolitan area using a mesoscale meteorological model and to evaluate the effects of urban heat island (UHI) mitigation strategies on modeled meteorology for 2030. Simulation results showed that use of the new LULC data set reduced a major deficiency of the land use data used previously, specifically the poor representation of urban and suburban land use. Performance of the meteorological model improved substantially, with the overall daytime cold bias reduced by over 30%. UHI mitigation strategies were projected to offset much of a predicted urban warming between 2000 and 2030. In fact, for the urban core, the cooling due to UHI mitigation strategies was slightly greater than the warming associated with urbanization over this period. For the larger metropolitan area, cooling only partially offset the projected warming trend.

Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, X.; Ju, W.

2013-03-01

Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shaanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modeled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modeled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI), elevation and aspect have small and additive effects on improving the spatial scaling between these two resolutions.

Effects of vegetation heterogeneity and surface topography on spatial scaling of net primary productivity

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, X.; Ju, W.

2013-07-01

Due to the heterogeneous nature of the land surface, spatial scaling is an inevitable issue in the development of land models coupled with low-resolution Earth system models (ESMs) for predicting land-atmosphere interactions and carbon-climate feedbacks. In this study, a simple spatial scaling algorithm is developed to correct errors in net primary productivity (NPP) estimates made at a coarse spatial resolution based on sub-pixel information of vegetation heterogeneity and surface topography. An eco-hydrological model BEPS-TerrainLab, which considers both vegetation and topographical effects on the vertical and lateral water flows and the carbon cycle, is used to simulate NPP at 30 m and 1 km resolutions for a 5700 km2 watershed with an elevation range from 518 m to 3767 m in the Qinling Mountain, Shanxi Province, China. Assuming that the NPP simulated at 30 m resolution represents the reality and that at 1 km resolution is subject to errors due to sub-pixel heterogeneity, a spatial scaling index (SSI) is developed to correct the coarse resolution NPP values pixel by pixel. The agreement between the NPP values at these two resolutions is improved considerably from R2 = 0.782 to R2 = 0.884 after the correction. The mean bias error (MBE) in NPP modelled at the 1 km resolution is reduced from 14.8 g C m-2 yr-1 to 4.8 g C m-2 yr-1 in comparison with NPP modelled at 30 m resolution, where the mean NPP is 668 g C m-2 yr-1. The range of spatial variations of NPP at 30 m resolution is larger than that at 1 km resolution. Land cover fraction is the most important vegetation factor to be considered in NPP spatial scaling, and slope is the most important topographical factor for NPP spatial scaling especially in mountainous areas, because of its influence on the lateral water redistribution, affecting water table, soil moisture and plant growth. Other factors including leaf area index (LAI) and elevation have small and additive effects on improving the spatial scaling between these two resolutions.

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

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

Quantifying Arctic Terrestrial Environment Behaviors Using Geophysical, Point-Scale and Remote Sensing Data

NASA Astrophysics Data System (ADS)

Dafflon, B.; Hubbard, S. S.; Ulrich, C.; Peterson, J. E.; Wu, Y.; Wainwright, H. M.; Gangodagamage, C.; Kholodov, A. L.; Kneafsey, T. J.

2013-12-01

Improvement in parameterizing Arctic process-rich terrestrial models to simulate feedbacks to a changing climate requires advances in estimating the spatiotemporal variations in active layer and permafrost properties - in sufficiently high resolution yet over modeling-relevant scales. As part of the DOE Next-Generation Ecosystem Experiments (NGEE-Arctic), we are developing advanced strategies for imaging the subsurface and for investigating land and subsurface co-variability and dynamics. Our studies include acquisition and integration of various measurements, including point-based, surface-based geophysical, and remote sensing datasets These data have been collected during a series of campaigns at the NGEE Barrow, AK site along transects that traverse a range of hydrological and geomorphological conditions, including low- to high- centered polygons and drained thaw lake basins. In this study, we describe the use of galvanic-coupled electrical resistance tomography (ERT), capacitively-coupled resistivity (CCR) , permafrost cores, above-ground orthophotography, and digital elevation model (DEM) to (1) explore complementary nature and trade-offs between characterization resolution, spatial extent and accuracy of different datasets; (2) develop inversion approaches to quantify permafrost characteristics (such as ice content, ice wedge frequency, and presence of unfrozen deep layer) and (3) identify correspondences between permafrost and land surface properties (such as water inundation, topography, and vegetation). In terms of methods, we developed a 1D-based direct search approach to estimate electrical conductivity distribution while allowing exploration of multiple solutions and prior information in a flexible way. Application of the method to the Barrow datasets reveals the relative information content of each dataset for characterizing permafrost properties, which shows features variability from below one meter length scales to large trends over more than a kilometer. Further, we used Pole- and Kite-based low-altitude aerial photography with inferred DEM, as well as DEM from LiDAR dataset, to quantify land-surface properties and their co-variability with the subsurface properties. Comparison of the above- and below-ground characterization information indicate that while some permafrost characteristics correspond with changes in hydrogeomorphological expressions, others features show more complex linkages with landscape properties. Overall, our results indicate that remote sensing data, point-scale measurements and surface geophysical measurements enable the identification of regional zones having similar relations between subsurface and land surface properties. Identification of such zonation and associated permafrost-land surface properties can be used to guide investigations of carbon cycling processes and for model parameterization.

Decoding the origins of vertical land motions observed today at coasts

NASA Astrophysics Data System (ADS)

Pfeffer, J.; Spada, G.; Mémin, A.; Boy, J.-P.; Allemand, P.

2017-07-01

In recent decades, geodetic techniques have allowed detecting vertical land motions and sea-level changes of a few millimetres per year, based on measurements taken at the coast (tide gauges), on board of satellite platforms (satellite altimetry) or both (Global Navigation Satellite System). Here, contemporary vertical land motions are analysed from January 1993 to July 2013 at 849 globally distributed coastal sites. The vertical displacement of the coastal platform due to surface mass changes is modelled using elastic and viscoelastic Green's functions. Special attention is paid to the effects of glacial isostatic adjustment induced by past and present-day ice melting. Various rheological and loading parameters are explored to provide a set of scenarios that could explain the coastal observations of vertical land motions globally. In well-instrumented regions, predicted vertical land motions explain more than 80 per cent of the variance observed at scales larger than a few hundred kilometres. Residual vertical land motions show a strong local variability, especially in the vicinity of plate boundaries due to the earthquake cycle. Significant residual signals are also observed at scales of a few hundred kilometres over nine well-instrumented regions forming observation windows on unmodelled geophysical processes. This study highlights the potential of our multitechnique database to detect geodynamical processes, driven by anthropogenic influence, surface mass changes (surface loading and glacial isostatic adjustment) and tectonic activity (including the earthquake cycle, sediment and volcanic loading, as well as regional tectonic constraints). Future improvements should be aimed at densifying the instrumental network and at investigating more thoroughly the uncertainties associated with glacial isostatic adjustment models.

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.

Comparative Study of Lunar Roughness from Multi - Source Data

NASA Astrophysics Data System (ADS)

Lou, Y.; Kang, Z.

2017-07-01

The lunar terrain can show its collision and volcanic history. The lunar surface roughness can give a deep indication of the effects of lunar surface magma, sedimentation and uplift. This paper aims to get different information from the roughness through different data sources. Besides introducing the classical Root-mean-square height method and Morphological Surface Roughness (MSR) algorithm, this paper takes the area of the Jurassic mountain uplift in the Sinus Iridum and the Plato Crater area as experimental areas. And then make the comparison and contrast of the lunar roughness derived from LRO's DEM and CE-2 DOM. The experimental results show that the roughness obtained by the traditional roughness calculation method reflect the ups and downs of the topography, while the results obtained by morphological surface roughness algorithm show the smoothness of the lunar surface. So, we can first use the surface fluctuation situation derived from RMSH to select the landing area range which ensures the lands are gentle. Then the morphological results determine whether the landing area is suitable for the detector walking and observing. The results obtained at two different scales provide a more complete evaluation system for selecting the landing site of the lunar probe.

Assessment of NPP VIIRS Albedo Over Heterogeneous Crop Land in Northern China

NASA Astrophysics Data System (ADS)

Wu, Xiaodan; Wen, Jianguang; Xiao, Qing; Yu, Yunyue; You, Dongqin; Hueni, Andreas

2017-12-01

In this paper, the accuracy of Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (VIIRS) land surface albedo, which is derived from the direct estimation algorithm, was assessed using ground-based albedo observations from a wireless sensor network over a heterogeneous cropland in the Huailai station, northern China. Data from six nodes spanning 2013-2014 over vegetation, bare soil, and mixed terrain surfaces were utilized to provide ground reference at VIIRS pixel scale. The performance of VIIRS albedo was also compared with Global LAnd Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) albedos (Collection 5 and 6). The results indicate that the current granular VIIRS albedo has a high accuracy with a root-mean-square error of 0.02 for typical land covers. They are significantly correlated with ground references indicated by a correlation coefficient (R) of 0.73. The VIIRS albedo shows distinct advantages to GLASS and MODIS albedos over bare soil and mixed-cover surfaces, while it is inferior to the other two products over vegetated surfaces. Furthermore, its time continuity and the ability to capture the abrupt change of surface albedo are better than that of GLASS and MODIS albedo.

Soil Moisture Dynamics in the Shallow Subsurface Near the Land/Atmospheric Interface- Challenges and New Research Approaches (Invited)

NASA Astrophysics Data System (ADS)

Illangasekare, T. H.; Smits, K. M.; Trautz, A.; Rice, A. K.; Cihan, A.; Davarzani, H.

2013-12-01

SSoil moisture processes in the subsurface/near-land-surface, play a crucial role in the hydrologic cycle and global water budget. This zone is subject to both natural and human induced disturbances, resulting in continually changing soil structure and hydraulic, thermal, and mechanical properties. Understanding of the dynamics of soil moisture distribution in this zone is of interest in various applications in hydrology such as land-atmospheric interaction, soil evaporation and evapotranspiration, as well as emerging problems on assessing the risk of leakage of sequestrated CO2 from deep geologic formations to the shallow subsurface, and potential leakage of methane to the atmosphere in shale gas development that contributes to global warming. Shallow subsurface soil moisture is highly influenced by diurnal temperature variations, evaporation/condensation, precipitation and liquid water and water vapor flow, all of which are strongly coupled. Modeling studies, have shown that soil moisture in this zone is highly sensitive to the heat and mass flux boundary conditions at the land surface. Hence, approximation of these boundary conditions without properly incorporating complex feedback between the land and the atmospheric boundary layer are expected to result in significant errors. Even though considerable knowledge exists on how soil moisture changes in response to the flux and energy boundary conditions, emerging problems involving land atmospheric interactions require the quantification of soil moisture variability at higher spatial and temporal resolutions than what is needed in traditional applications in soil physics and vadose zone hydrology. These factors lead to many modeling challenges, primarily of which is the issue of up-scaling. It is our contention that knowledge that will contribute to both improving our understanding of the fundamental processes and practical problem solutions cannot be obtained using only field data. Basic to this limitation is the inability to make field measurements at very fine scales at high temporal resolutions. Also, as the natural boundary conditions at the land/atmospheric interface are not controllable in the field, even in pilot scale studies, the developed theories and models cannot be validated for a diversity of conditions that could be expected. As an alternative, we propose an innovative testing approach that couples a low velocity boundary layer climate wind tunnel to intermediate scale porous media tanks. Intermediate scale testing using soil tanks packed to represent different heterogeneous test configurations provides an attractive and cost effective alternative to investigate a class of problems involving the shallow unsaturated zone. In this talk, we will present examples of studies we have conducted in a hierarchy of test systems, including the intermediate scale. The advantages and limitations of testing at this scale are discussed using these examples. The features and capabilities of newly developed test systems are presented with the goal of exploring opportunities to use them to study some of the challenging multi-scale problems in the near surface unsaturated zone.

The Contribution of Reservoirs to Global Land Surface Water Storage Variations

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

Zhou, Tian; Nijssen, Bart; Gao, Huilin

Man-made reservoirs play a key role in the terrestrial water system. They alter water fluxes at the land surface and impact surface water storage through water management regulations for diverse purposes such as irrigation, municipal water supply, hydropower generation, and flood control. Although most developed countries have established sophisticated observing systems for many variables in the land surface water cycle, long-term and consistent records of reservoir storage are much more limited and not always shared. Furthermore, most land surface hydrological models do not represent the effects of water management activities. Here, the contribution of reservoirs to seasonal water storage variationsmore » is investigated using a large-scale water management model to simulate the effects of reservoir management at basin and continental scales. The model was run from 1948 to 2010 at a spatial resolution of 0.258 latitude–longitude. A total of 166 of the largest reservoirs in the world with a total capacity of about 3900 km3 (nearly 60%of the globally integrated reservoir capacity) were simulated. The global reservoir storage time series reflects the massive expansion of global reservoir capacity; over 30 000 reservoirs have been constructed during the past half century, with a mean absolute interannual storage variation of 89 km3. The results indicate that the average reservoir-induced seasonal storage variation is nearly 700 km3 or about 10%of the global reservoir storage. For some river basins, such as the Yellow River, seasonal reservoir storage variations can be as large as 72%of combined snow water equivalent and soil moisture storage.« less

Multi-Temporal Multi-Sensor Analysis of Urbanization and Environmental/Climate Impact in China for Sustainable Urban Development

NASA Astrophysics Data System (ADS)

Ban, Yifang; Gong, Peng; Gamba, Paolo; Taubenbock, Hannes; Du, Peijun

2016-08-01

The overall objective of this research is to investigate multi-temporal, multi-scale, multi-sensor satellite data for analysis of urbanization and environmental/climate impact in China to support sustainable planning. Multi- temporal multi-scale SAR and optical data have been evaluated for urban information extraction using innovative methods and algorithms, including KTH- Pavia Urban Extractor, Pavia UEXT, and an "exclusion- inclusion" framework for urban extent extraction, and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Various pixel- based and object-based change detection algorithms were also developed to extract urban changes. Several Chinese cities including Beijing, Shanghai and Guangzhou are selected as study areas. Spatio-temporal urbanization patterns and environmental impact at regional, metropolitan and city core were evaluated through ecosystem service, landscape metrics, spatial indices, and/or their combinations. The relationship between land surface temperature and land-cover classes was also analyzed.The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal SAR data with the KTH-Pavia Urban Extractor and UEXT. The fusion of SAR data at multiple scales from multiple sensors was proven to improve urban extraction. For urban land cover mapping, the results show that the fusion of multitemporal SAR and optical data could produce detailed land cover maps with improved accuracy than that of SAR or optical data alone. Pixel-based and object-based change detection algorithms developed with the project were effective to extract urban changes. Comparing the urban land cover results from mulitemporal multisensor data, the environmental impact analysis indicates major losses for food supply, noise reduction, runoff mitigation, waste treatment and global climate regulation services through landscape structural changes in terms of decreases in service area, edge contamination and fragmentation. In terms ofclimate impact, the results indicate that land surface temperature can be related to land use/land cover classes.

Lunar and Planetary Science XXXV: Mars: Surface Coatings, Mineralogy, and Surface Properties

NASA Technical Reports Server (NTRS)

2004-01-01

The session "Mars: Surface Coatings, Mineralogy, and Surface Properties" contained the following reports:High-Silica Rock Coatings: TES Surface-Type 2 and Chemical Weathering on Mars; Old Desert Varnish-like Coatings and Young Breccias at the Mars Pathfinder Landing Site; Analyses of IR-Stealthy and Coated Surface Materials: A Comparison of LIBS and Reflectance Spectra and Their Application to Mars Surface Exploration; Contrasting Interpretations of TES Spectra of the 2003 Rover:Opportunity-Landing Site: Hematite Coatings and Gray Hematite; A New Hematite Formation Mechanism for Mars; Geomorphic and Diagenetic Analogs to Hematite Regions on Mars: Examples from Jurassic Sandstones of Southern Utah, USA; The Geologic Record of Early Mars: A Layered, Cratered, and "Valley-"ed: Volume; A Simple Approach to Estimating Surface Emissivity with THEMIS; A Large Scale Topographic Correction for THEMIS Data; Thermophysical Properties of Meridiani Planum, Mars; Thermophysical and Spectral Properties of Gusev, the MER-Spirit Landing Site on Mars; Determining Water Content of Geologic Materials Using Reflectance Spectroscopy; and Global Mapping of Martian Bound Water at 6.1 Microns Based on TES Data: Seasonal Hydration.

Monitoring urban land cover change by updating the national land cover database impervious surface products

USGS Publications Warehouse

Xian, George Z.; Homer, Collin G.

2009-01-01

The U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001 is widely used as a baseline for national land cover and impervious conditions. To ensure timely and relevant data, it is important to update this base to a more recent time period. A prototype method was developed to update the land cover and impervious surface by individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season from both 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, impervious surface was estimated for areas of change by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain a variety of metropolitan areas. Results from the five study areas show that the vast majority of impervious surface changes associated with urban developments were accurately captured and updated. The approach optimizes mapping efficiency and can provide users a flexible method to generate updated impervious surface at national and regional scales.

The Face of Alaska: A Look at Land Cover and the Potential Drivers of Change

USGS Publications Warehouse

Jones, Benjamin M.

2008-01-01

The purpose of this report is to provide statewide baseline information on the status and potential drivers of land-cover change in Alaska. The information gathered for this report is based on a review and analysis of published literature and consists of prominent factors contributing to the current state of the land surface of Alaska as well as a synthesis of information about the status and trends of the factors affecting the land surface of Alaska. The land surface of Alaska is sparsely populated and the impacts from humans are far less extensive when compared to the contiguous United States. The changes in the population and the economy of Alaska have historically been driven by boom and bust cycles, primarily from mineral discoveries, logging, military expansion, and oil and gas development; however, the changes as a result of these factors have occurred in relatively small, localized areas. Many of the large-scale statewide changes taking place in the land surface however, are a result of natural or climate driven processes as opposed to direct anthropogenic activities. In recent times, reports such as this have become increasingly useful as a means of synthesizing information about the magnitude and frequency of changes imparted by natural and anthropogenic forces. Thus, it is essential to assess the current state of the land surface of Alaska and identify apparent trends in the surficial changes that are occurring in order to be prepared for the future.

Influence of Soil Heterogeneity on Mesoscale Land Surface Fluxes During Washita '92

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Jin, Hao

1998-01-01

The influence of soil heterogeneity on the partitioning of mesoscale land surface energy fluxes at diurnal time scales is investigated over a 10(exp 6) sq km domain centered on the Little Washita Basin, Oklahoma, for the period June 10 - 18, 1992. The sensitivity study is carried out using MM5/PLACE, the Penn State/NCAR MM5 model enhanced with the Parameterization for Land-Atmosphere-Cloud Exchange or PLACE. PLACE is a one-dimensional land surface model possessing detailed plant and soil water physics algorithms, multiple soil layers, and the capacity to model subgrid heterogeneity. A series of 12-hour simulations were conducted with identical atmospheric initialization and land surface characterization but with different initial soil moisture and texture. A comparison then was made of the simulated land surface energy flux fields, the partitioning of net radiation into latent and sensible heat, and the soil moisture fields. Results indicate that heterogeneity in both soil moisture and texture affects the spatial distribution and partitioning of mesoscale energy balance. Spatial averaging results in an overprediction of latent heat flux, and an underestimation of sensible heat flux. In addition to the primary focus on the partitioning of the land surface energy, the modeling effort provided an opportunity to examine the issue of initializing the soil moisture fields for coupled three-dimensional models. For the present case, the initial soil moisture and temperature were determined from off-line modeling using PLACE at each grid box, driven with a combination of observed and assimilated data fields.

Biogeophysical consequences of a tropical deforestation scenario: A GCM simulation study

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

Sud, Y.C.; Lau, W.K.M.; Walker, G.K.

1996-12-01

Two 3-year (1979-1982) integrations were carried out with a version of the GLA GCM that contains the Simple Biosphere Model (SiB) for simulating land-atmosphere interactions. The control case used the usual SiB vegetation cover (comprising 12 vegetation types), while its twin, the deforestation case, imposed a scenario in which all tropical rainforests were entirely replaced by grassland. Except for this difference, all other initial and prescribed boundary conditions were kept identical in both integrations. An intercomparison of the integrations shows that tropical: deforestation decreases evapotranspiration and increases land surface outgoing longwave radiation and sensible heat flux, thereby warming and dryingmore » the planetary boundary layer. This happens despite the reduced absorption of solar radiation due to higher surface albedo of the deforested land. Produces significant and robust local as well as global climate changes. The local effect includes significant changes (mostly reductions) in precipitation and diabatic heating, while the large-scale effect is to weaken the Hadley circulation but invigorate the southern Ferrel cell, drawing larger air mass from the indirect polar cells. Decreases the surface stress (drag force) owing to reduced surface roughness of deforested land, which in turn intensifies winds in the planetary boundary layer, thereby affecting the dynamic structure of moisture convergence. The simulated surface winds are about 70% stronger and are accompanied by significant changes in the power spectrum of the annual cycle of surface and PBL winds and precipitation. Our results broadly confirm several findings of recent tropical deforestation simulation experiments. In addition, some global-scale climatic influences of deforestation not identified in earlier studies are delineated. 57 refs., 10 figs., 3 tabs.« less

Landing Hazard Avoidance Display

NASA Technical Reports Server (NTRS)

Abernathy, Michael Franklin (Inventor); Hirsh, Robert L. (Inventor)

2016-01-01

Landing hazard avoidance displays can provide rapidly understood visual indications of where it is safe to land a vehicle and where it is unsafe to land a vehicle. Color coded maps can indicate zones in two dimensions relative to the vehicles position where it is safe to land. The map can be simply green (safe) and red (unsafe) areas with an indication of scale or can be a color coding of another map such as a surface map. The color coding can be determined in real time based on topological measurements and safety criteria to thereby adapt to dynamic, unknown, or partially known environments.

Evaluation of MuSyQ land surface albedo based on LAnd surface Parameters VAlidation System (LAPVAS)

NASA Astrophysics Data System (ADS)

Dou, B.; Wen, J.; Xinwen, L.; Zhiming, F.; Wu, S.; Zhang, Y.

2016-12-01

satellite derived Land surface albedo is an essential climate variable which controls the earth energy budget and it can be used in applications such as climate change, hydrology, and numerical weather prediction. However, the accuracy and uncertainty of surface albedo products should be evaluated with a reliable reference truth data prior to applications. A new comprehensive and systemic project of china, called the Remote Sensing Application Network (CRSAN), has been launched recent years. Two subjects of this project is developing a Multi-source data Synergized Quantitative Remote Sensin g Production System ( MuSyQ ) and a Web-based validation system named LAnd surface remote sensing Product VAlidation System (LAPVAS) , which aims to generate a quantitative remote sensing product for ecosystem and environmental monitoring and validate them with a reference validation data and a standard validation system, respectively. Land surface BRDF/albedo is one of product datasets of MuSyQ which has a pentad period with 1km spatial resolution and is derived by Multi-sensor Combined BRDF Inversion ( MCBI ) Model. In this MuSyQ albedo evaluation, a multi-validation strategy is implemented by LAPVAS, including directly and multi-scale validation with field measured albedo and cross validation with MODIS albedo product with different land cover. The results reveal that MuSyQ albedo data with a 5-day temporal resolution is in higher sensibility and accuracy during land cover change period, e.g. snowing. But results without regard to snow or changed land cover, MuSyQ albedo generally is in similar accuracy with MODIS albedo and meet the climate modeling requirement of an absolute accuracy of 0.05.

Evaluation of various LandFlux evapotranspiration algorithms using the LandFlux-EVAL synthesis benchmark products and observational data

NASA Astrophysics Data System (ADS)

Michel, Dominik; Hirschi, Martin; Jimenez, Carlos; McCabe, Mathew; Miralles, Diego; Wood, Eric; Seneviratne, Sonia

2014-05-01

Research on climate variations and the development of predictive capabilities largely rely on globally available reference data series of the different components of the energy and water cycles. Several efforts aimed at producing large-scale and long-term reference data sets of these components, e.g. based on in situ observations and remote sensing, in order to allow for diagnostic analyses of the drivers of temporal variations in the climate system. Evapotranspiration (ET) is an essential component of the energy and water cycle, which can not be monitored directly on a global scale by remote sensing techniques. In recent years, several global multi-year ET data sets have been derived from remote sensing-based estimates, observation-driven land surface model simulations or atmospheric reanalyses. The LandFlux-EVAL initiative presented an ensemble-evaluation of these data sets over the time periods 1989-1995 and 1989-2005 (Mueller et al. 2013). Currently, a multi-decadal global reference heat flux data set for ET at the land surface is being developed within the LandFlux initiative of the Global Energy and Water Cycle Experiment (GEWEX). This LandFlux v0 ET data set comprises four ET algorithms forced with a common radiation and surface meteorology. In order to estimate the agreement of this LandFlux v0 ET data with existing data sets, it is compared to the recently available LandFlux-EVAL synthesis benchmark product. Additional evaluation of the LandFlux v0 ET data set is based on a comparison to in situ observations of a weighing lysimeter from the hydrological research site Rietholzbach in Switzerland. These analyses serve as a test bed for similar evaluation procedures that are envisaged for ESA's WACMOS-ET initiative (http://wacmoset.estellus.eu). Reference: Mueller, B., Hirschi, M., Jimenez, C., Ciais, P., Dirmeyer, P. A., Dolman, A. J., Fisher, J. B., Jung, M., Ludwig, F., Maignan, F., Miralles, D. G., McCabe, M. F., Reichstein, M., Sheffield, J., Wang, K., Wood, E. F., Zhang, Y., and Seneviratne, S. I. (2013). Benchmark products for land evapotranspiration: LandFlux-EVAL multi-data set synthesis. Hydrology and Earth System Sciences, 17(10): 3707-3720.

Simulating effects of microtopography on wetland specific yield and hydroperiod

USGS Publications Warehouse

Summer, David M.; Wang, Xixi

2011-01-01

Specific yield and hydroperiod have proven to be useful parameters in hydrologic analysis of wetlands. Specific yield is a critical parameter to quantitatively relate hydrologic fluxes (e.g., rainfall, evapotranspiration, and runoff) and water level changes. Hydroperiod measures the temporal variability and frequency of land-surface inundation. Conventionally, hydrologic analyses used these concepts without considering the effects of land surface microtopography and assumed a smoothly-varying land surface. However, these microtopographic effects could result in small-scale variations in land surface inundation and water depth above or below the land surface, which in turn affect ecologic and hydrologic processes of wetlands. The objective of this chapter is to develop a physically-based approach for estimating specific yield and hydroperiod that enables the consideration of microtopographic features of wetlands, and to illustrate the approach at sites in the Florida Everglades. The results indicate that the physically-based approach can better capture the variations of specific yield with water level, in particular when the water level falls between the minimum and maximum land surface elevations. The suggested approach for hydroperiod computation predicted that the wetlands might be completely dry or completely wet much less frequently than suggested by the conventional approach neglecting microtopography. One reasonable generalization may be that the hydroperiod approaches presented in this chapter can be a more accurate prediction tool for water resources management to meet the specific hydroperiod threshold as required by a species of plant or animal of interest.

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.

Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.; Forman, Barton A.; Draper, Clara S.; Liu, Qing

2013-01-01

A land data assimilation system (LDAS) can merge satellite observations (or retrievals) of land surface hydrological conditions, including soil moisture, snow, and terrestrial water storage (TWS), into a numerical model of land surface processes. In theory, the output from such a system is superior to estimates based on the observations or the model alone, thereby enhancing our ability to understand, monitor, and predict key elements of the terrestrial water cycle. In practice, however, satellite observations do not correspond directly to the water cycle variables of interest. The present paper addresses various aspects of this seeming mismatch using examples drawn from recent research with the ensemble-based NASA GEOS-5 LDAS. These aspects include (1) the assimilation of coarse-scale observations into higher-resolution land surface models, (2) the partitioning of satellite observations (such as TWS retrievals) into their constituent water cycle components, (3) the forward modeling of microwave brightness temperatures over land for radiance-based soil moisture and snow assimilation, and (4) the selection of the most relevant types of observations for the analysis of a specific water cycle variable that is not observed (such as root zone soil moisture). The solution to these challenges involves the careful construction of an observation operator that maps from the land surface model variables of interest to the space of the assimilated observations.

Estimation of Key Parameters of the Coupled Energy and Water Model by Assimilating Land Surface Data

NASA Astrophysics Data System (ADS)

Abdolghafoorian, A.; Farhadi, L.

2017-12-01

Accurate estimation of land surface heat and moisture fluxes, as well as root zone soil moisture, is crucial in various hydrological, meteorological, and agricultural applications. Field measurements of these fluxes are costly and cannot be readily scaled to large areas relevant to weather and climate studies. Therefore, there is a need for techniques to make quantitative estimates of heat and moisture fluxes using land surface state observations that are widely available from remote sensing across a range of scale. In this work, we applies the variational data assimilation approach to estimate land surface fluxes and soil moisture profile from the implicit information contained Land Surface Temperature (LST) and Soil Moisture (SM) (hereafter the VDA model). The VDA model is focused on the estimation of three key parameters: 1- neutral bulk heat transfer coefficient (CHN), 2- evaporative fraction from soil and canopy (EF), and 3- saturated hydraulic conductivity (Ksat). CHN and EF regulate the partitioning of available energy between sensible and latent heat fluxes. Ksat is one of the main parameters used in determining infiltration, runoff, groundwater recharge, and in simulating hydrological processes. In this study, a system of coupled parsimonious energy and water model will constrain the estimation of three unknown parameters in the VDA model. The profile of SM (LST) at multiple depths is estimated using moisture diffusion (heat diffusion) equation. In this study, the uncertainties of retrieved unknown parameters and fluxes are estimated from the inverse of Hesian matrix of cost function which is computed using the Lagrangian methodology. Analysis of uncertainty provides valuable information about the accuracy of estimated parameters and their correlation and guide the formulation of a well-posed estimation problem. The results of proposed algorithm are validated with a series of experiments using a synthetic data set generated by the simultaneous heat and water (SHAW) model. In addition, the feasibility of extending this algorithm to use remote sensing observations that have low temporal resolution is examined by assimilating the limited number of land surface moisture and temperature observations.

Building hydrologic information systems to promote climate resilience in the Blue Nile/Abay higlands

USDA-ARS?s Scientific Manuscript database

Climate adaptation requires information about climate and land-surface conditions – spatially distributed, and at scales of human influence (the field scale). This article describes a project aimed at combining meteorological data, satellite remote sensing, hydrologic modeling, and downscaled clima...

Land and federal mineral ownership coverage for northwestern Colorado

USGS Publications Warehouse

Biewick, L.H.; Mercier, T.J.; Levitt, Pam; Deikman, Doug; Vlahos, Bob

1999-01-01

This Arc/Info coverage contains land status and Federal mineral ownership for approximately 26,800 square miles in northwestern Colorado. The polygon coverage (which is also provided here as a shapefile) contains two attributes of ownership information for each polygon. One attribute indicates where the surface is State owned, privately owned, or, if Federally owned, which Federal agency manages the land surface. The other attribute indicates which minerals, if any, are owned by the Federal govenment. This coverage is based on land status and Federal mineral ownership data compiled by the U.S. Geological Survey (USGS) and three Colorado State Bureau of Land Management (BLM) former district offices at a scale of 1:24,000. This coverage was compiled primarily to serve the USGS National Oil and Gas Resource Assessment Project in the Uinta-Piceance Basin Province and the USGS National Coal Resource Assessment Project in the Colorado Plateau.

Deriving a global land surface albedo product from Landsat MSS, TM, ETM+, and OLI data based on the unified direct estimation approach

USDA-ARS?s Scientific Manuscript database

Surface albedo is widely used in climate and environment applications as an important parameter for controlling the surface energy budget. There is an increasing need for fine resolution (< 100 m) albedo data for use in small scale applications and for validating coarse-resolution datasets; however,...

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

Estimation of evapotranspiration across the conterminous United States using a regression with climate and land-cover data

USGS Publications Warehouse

Sanford, Ward E.; Selnick, David L.

2013-01-01

Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water-balance method was combined with a climate and land-cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971-2000 across the U.S. to obtain long-term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land-cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land-cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land-cover data can also improve those predictions. Using the climate and land-cover data at an 800-m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land-cover data are plentiful.

Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Vrije; VandeGriend, Adriaan A.

2000-01-01

Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.

The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?

NASA Technical Reports Server (NTRS)

Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.; Or, Dani; Best, Martin J.; Johnson, Helen R.; Balsamo, Gianpaolo; Boone, Aaron; Cuntz, Matthais; Decharme, Bertrand;

An Analysis of Inter-annual Variability and Uncertainty of Continental Surface Heat Fluxes

NASA Astrophysics Data System (ADS)

Huang, S. Y.; Deng, Y.; Wang, J.

2016-12-01

The inter-annual variability and the corresponding uncertainty of land surface heat fluxes during the first decade of the 21st century are re-evaluated at continental scale based on the heat fluxes estimated by the maximum entropy production (MEP) model. The MEP model predicted heat fluxes are constrained by surface radiation fluxes, automatically satisfy surface energy balance, and are independent of temperature/moisture gradient, wind speed, and roughness lengths. The surface radiation fluxes and temperature data from Clouds and the Earth's Radiant Energy System and the surface specific humidity data from Modern-Era Retrospective analysis for Research and Applications were used to reproduce the global surface heat fluxes with land-cover data from the NASA Energy and Water cycle Study (NEWS). Our analysis shows that the annual means of continental latent heat fluxes have increasing trends associated with increasing trends in surface net radiative fluxes. The sensible heat fluxes also have increasing trends over most continents except for South America. Ground heat fluxes have little trends. The continental-scale analysis of the MEP fluxes are compared with other existing global surface fluxes data products and the implications of the results for inter-annual to decadal variability of regional surface energy budget are discussed.

Exploring the Influence of Impervious Surface Density and Shape on Urban Heat Islands in the Northeast USA Using MODIS and Landsat

NASA Technical Reports Server (NTRS)

Zhang, Ping; Imhoff, Marc L.; Bounoua, Lahouri; Wolfe, Robert E.

2011-01-01

Impervious surface area (ISA) from the National Land Cover Database (NLCD) 2001 and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature and its relationship to settlement size and shape, development intensity distribution, and land cover composition for 42 urban settlements embedded in forest biomes in the Northeastern United States. Development intensity zones, based on percent ISA, are defined for each urban area emanating outward from the urban core to nearby rural areas and are used to stratify land surface temperature. The stratification is further constrained by biome type and elevation to insure objective intercomparisons between urban zones within an urban settlement and between settlements. Stratification based on ISA allows the definition of hierarchically ordered urban zones that are consistent across urban settlements and scales. In addition to the surrounding ecological context, we find that the settlement size and shape as well as the development intensity distribution significantly influence the amplitude of summer daytime UHI. Within the Northeastern US temperate broadleaf mixed forest, UHI magnitude is positively related to the logarithm of the urban area size. Our study indicates that for similar urban area sizes, the development intensity distribution is one of the major drivers of UHI. In addition to urban area size and development intensity distribution, this analysis shows that both the shape of the urban area and the land cover composition in the surrounding rural area play an important role in modulating the UHI magnitude in different urban settlements. Our results indicate that remotely sensed urban area size and shape as well as the development intensity distribution influence UHI amplitude across regional scales.

Turbulent flow and scalar transport in a large wind farm

NASA Astrophysics Data System (ADS)

Porte-Agel, F.; Markfort, C. D.; Zhang, W.

2012-12-01

Wind energy is one of the fastest growing sources of renewable energy world-wide, and it is expected that many more large-scale wind farms will be built and cover a significant portion of land and ocean surfaces. By extracting kinetic energy from the atmospheric boundary layer and converting it to electricity, wind farms may affect the transport of momentum, heat, moisture and trace gases (e.g. CO_2) between the atmosphere and the land surface locally and globally. Understanding wind farm-atmosphere interaction is complicated by the effects of turbine array configuration, wind farm size, land-surface characteristics, and atmospheric thermal stability. A wind farm of finite length may be modeled as an added roughness or as a canopy in large-scale weather and climate models. However, it is not clear which analogy is physically more appropriate. Also, surface scalar flux is affected by wind farms and needs to be properly parameterized in meso-scale and/or high-resolution numerical models. Experiments involving model wind farms, with perfectly aligned and staggered configurations, having the same turbine distribution density, were conducted in a thermally-controlled boundary-layer wind tunnel. A neutrally stratified turbulent boundary layer was developed with a surface heat source. Measurements of the turbulent flow and fluxes over and through the wind farm were made using a custom x-wire/cold-wire anemometer; and surface scalar flux was measured with an array of surface-mounted heat flux sensors far within the quasi-developed region of the wind-farm. The turbulence statistics exhibit similar properties to those of canopy-type flows, but retain some characteristics of surface-layer flows in a limited region above the wind farms as well. The flow equilibrates faster and the overall momentum absorption is higher for the staggered compared to the aligned farm, which is consistent with canopy scaling and leads to a larger effective roughness. Although the overall surface heat flux change produced by the wind farms is found to be small, with a net reduction of 4% for the staggered wind farm and nearly zero change for the aligned wind farm, the highly heterogeneous spatial distribution of the surface heat flux, dependent on wind farm layout, is significant. This comprehensive first wind-tunnel dataset on turbulent flow and scalar transport in wind farms will be further used to develop and validate new parameterizations of surface fluxes in numerical models.

Fire modeling in the Brazilian arc of deforestation through nested coupling of atmosphere, dynamic vegetation, LUCC and fire spread models

NASA Astrophysics Data System (ADS)

Tourigny, E.; Nobre, C.; Cardoso, M. F.

2012-12-01

Deforestation of tropical forests for logging and agriculture, associated to slash-and-burn practices, is a major source of CO2 emissions, both immediate due to biomass burning and future due to the elimination of a potential CO2 sink. Feedbacks between climate change and LUCC (Land-Use and Land-Cover Change) can potentially increase the loss of tropical forests and increase the rate of CO2 emissions, through mechanisms such as land and soil degradation and the increase in wildfire occurrence and severity. However, current understanding of the processes of fires (including ignition, spread and consequences) in tropical forests and climatic feedbacks are poorly understood and need further research. As the processes of LUCC and associated fires occur at local scales, linking them to large-scale atmospheric processes requires a means of up-scaling higher resolutions processes to lower resolutions. Our approach is to couple models which operate at various spatial and temporal scales: a Global Climate Model (GCM), Dynamic Global Vegetation Model (DGVM) and local-scale LUCC and fire spread model. The climate model resolves large scale atmospheric processes and forcings, which are imposed on the surface DGVM and fed-back to climate. Higher-resolution processes such as deforestation, land use management and associated (as well as natural) fires are resolved at the local level. A dynamic tiling scheme allows to represent local-scale heterogeneity while maintaining computational efficiency of the land surface model, compared to traditional landscape models. Fire behavior is modeled at the regional scale (~500m) to represent the detailed landscape using a semi-empirical fire spread model. The relatively coarse scale (as compared to other fire spread models) is necessary due to the paucity of detailed land-cover information and fire history (particularly in the tropics and developing countries). This work presents initial results of a spatially-explicit fire spread model coupled to the IBIS DGVM model. Our area of study comprises selected regions in and near the Brazilian "arc of deforestation". For model training and evaluation, several areas have been mapped using high-resolution imagery from the Landsat TM/ETM+ sensors (Figure 1). This high resolution reference data is used for local-scale simulations and also to evaluate the accuracy of the global MCD45 burned area product, which will be used in future studies covering the entire "arc of deforestation".; Area of study along the arc of deforestation and cerrado: landsat scenes used and burned area (2010) from MCD45 product.

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.

Environmental geochemistry at the global scale

USGS Publications Warehouse

Plant, J.; Smith, D.; Smith, B.; Williams, L.

2000-01-01

Land degradation and pollution caused by population pressure and economic development pose a threat to the sustainability of the Earth's surface, especially in tropical regions where a long history of chemical weathering has made the surface environment particularly fragile. Systematic baseline geochemical data provide a means of monitoring the state of the environment and identifying problem areas. Regional surveys have already been carried out in some countries, and with increased national and international funding they can be extended to cover the rest of the land surface of the globe. Preparations have been made, under the auspices of the IUGS, for the establishment of just such an integrated global database.

A Catchment-Based Land Surface Model for GCMs and the Framework for its Evaluation

NASA Technical Reports Server (NTRS)

Ducharen, A.; Koster, R. D.; Suarez, M. J.; Kumar, P.

1998-01-01

A new GCM-scale land surface modeling strategy that explicitly accounts for subgrid soil moisture variability and its effects on evaporation and runoff is now being explored. In a break from traditional modeling strategies, the continental surface is disaggregated into a mosaic of hydrological catchments, with boundaries that are not dictated by a regular grid but by topography. Within each catchment, the variability of soil moisture is deduced from TOP-MODEL equations with a special treatment of the unsaturated zone. This paper gives an overview of this new approach and presents the general framework for its off-line evaluation over North-America.

Surficial Geologic Map of the Ashby-Lowell-Sterling-Billerica 11-Quadrangle Area in Northeast-Central Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.

2007-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of eleven 7.5-minute quadrangles (total 505 mi2) in northeast-central Massachusetts. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions. This compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock, and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), a regional map at 1:50,000 scale (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial Geologic Map of the Salem Depot-Newburyport East-Wilmington-Rockport 16-Quadrangle Area in Northeast Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet Radway; DiGiacomo-Cohen, Mary L.

2006-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 16 7.5-minute quadrangles (total 658 mi2) in northeast Massachusetts. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (grain size, sedimentary structures, mineral and rock-particle composition), constructional geomorphic features, stratigraphic relationships, and age. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions. This compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock, and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), a regional map at 1:50,000 scale (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Spatiotemporal Variations in the Difference between Satellite-observed Land Surface Temperature and Station-based Near-surface Air Temperature

NASA Astrophysics Data System (ADS)

Lian, X.

2016-12-01

There is an increasing demand to integrate land surface temperature (LST) into climate research due to its global coverage, which requires a comprehensive knowledge of its distinctive characteristics compared to near-surface air temperature ( ). Using satellite observations and in-situ station-based datasets, we conducted a global-scale assessment of the spatial, seasonal, and interannual variations in the difference between daytime maximum LST and daytime maximum ( , LST - ) during 2003-2014. Spatially, LST is generally higher than over arid and sparsely vegetated regions in the mid-low latitudes, but LST is lower than in the tropical rainforests due to strong evaporative cooling, and in the high-latitude regions due to snow-induced radiative cooling. Seasonally, is negative in tropical regions throughout the year, while it displays a pronounced seasonality in both the mid-latitudes and boreal regions. The seasonality in the mid-latitudes is a result of the asynchronous responses of LST and to the seasonal cycle of radiation and vegetation abundance, whereas in the boreal regions, seasonality is mainly caused by the change in snow cover. At an interannual scale, only a small proportion of the land surface displays a statistically significant trend (P <0.05) due to the short time span of current measurements. Our study identified substantial spatial heterogeneity and seasonality in , as well as its determinant environmental drivers, and thus provides a useful reference for monitoring near-surface temperature changes using remote sensing, particularly in remote regions.

The importance of lake-specific characteristics for water quality across the continental United States.

PubMed

Read, Emily K; Patil, Vijay P; Oliver, Samantha K; Hetherington, Amy L; Brentrup, Jennifer A; Zwart, Jacob A; Winters, Kirsten M; Corman, Jessica R; Nodine, Emily R; Woolway, R Iestyn; Dugan, Hilary A; Jaimes, Aline; Santoso, Arianto B; Hong, Grace S; Winslow, Luke A; Hanson, Paul C; Weathers, Kathleen C

2015-06-01

Lake water quality is affected by local and regional drivers, including lake physical characteristics, hydrology, landscape position, land cover, land use, geology, and climate. Here, we demonstrate the utility of hypothesis testing within the landscape limnology framework using a random forest algorithm on a national-scale, spatially explicit data set, the United States Environmental Protection Agency's 2007 National Lakes Assessment. For 1026 lakes, we tested the relative importance of water quality drivers across spatial scales, the importance of hydrologic connectivity in mediating water quality drivers, and how the importance of both spatial scale and connectivity differ across response variables for five important in-lake water quality metrics (total phosphorus, total nitrogen, dissolved organic carbon, turbidity, and conductivity). By modeling the effect of water quality predictors at different spatial scales, we found that lake-specific characteristics (e.g., depth, sediment area-to-volume ratio) were important for explaining water quality (54-60% variance explained), and that regionalization schemes were much less effective than lake specific metrics (28-39% variance explained). Basin-scale land use and land cover explained between 45-62% of variance, and forest cover and agricultural land uses were among the most important basin-scale predictors. Water quality drivers did not operate independently; in some cases, hydrologic connectivity (the presence of upstream surface water features) mediated the effect of regional-scale drivers. For example, for water quality in lakes with upstream lakes, regional classification schemes were much less effective predictors than lake-specific variables, in contrast to lakes with no upstream lakes or with no surface inflows. At the scale of the continental United States, conductivity was explained by drivers operating at larger spatial scales than for other water quality responses. The current regulatory practice of using regionalization schemes to guide water quality criteria could be improved by consideration of lake-specific characteristics, which were the most important predictors of water quality at the scale of the continental United States. The spatial extent and high quality of contextual data available for this analysis makes this work an unprecedented application of landscape limnology theory to water quality data. Further, the demonstrated importance of lake morphology over other controls on water quality is relevant to both aquatic scientists and managers.

Reply to comment by Ma and Zhang on "Rescaling the complementary relationship for land surface evaporation"

NASA Astrophysics Data System (ADS)

Crago, Richard; Qualls, Russell; Szilagyi, Jozsef; Huntington, Justin

2017-07-01

Ma and Zhang (2017) note a concern they have with our rescaled Complementary Relationship (CR) for land surface evaporation when daily average wind speeds are very low (perhaps less than 1 m/s). We discuss conditions and specific formulations that lead to this concern, but ultimately argue that under these conditions, a key assumption behind the CR itself may not be satisfied at the daily time scale. Thus, careful consideration of the reliability of the CR is needed when wind speeds are very low.

The Impact of Anthropogenic Land Cover Change on Continental River Flow

NASA Astrophysics Data System (ADS)

Sterling, S. M.; Ducharne, A.; Polcher, J.

2006-12-01

The 2003 World Water Forum highlighted a water crisis that forces over one billion people to drink contaminated water and leaves countless millions with insufficient supplies for agriculture industry. This crisis has spurred numerous recent calls for improved science and understanding of how we alter the water cycle. Here we investigate how this global water crisis is affected by human-caused land cover change. We examine the impact of the present extent of land cover change on the water cycle, in particular on evapotranspiration and streamflow, through numerical experiments with the ORCHIDEE land surface model. Using Geographic Information Systems, we characterise land cover change by assembling and modifying existing global-scale maps of land cover change. To see how the land cover change impacts river runoff streamflow, we input the maps into ORCHIDEE and run 50-year "potential vegetation" and "current land cover" simulations of the land surface and energy fluxes, forced by the 50-year NCC atmospheric forcing data set. We present global maps showing the "hotspot" areas with the largest change in ET and streamflow due to anthropogenic land cover change. The results of this project enhance scientific understanding of the nature of human impact on the global water cycle.

Empirical Scaling Laws of Rocket Exhaust Cratering

NASA Technical Reports Server (NTRS)

Donahue, Carly M.; Metzger, Philip T.; Immer, Christopher D.

2005-01-01

When launching or landing a space craft on the regolith of a terrestrial surface, special attention needs to be paid to the rocket exhaust cratering effects. If the effects are not controlled, the rocket cratering could damage the spacecraft or other surrounding hardware. The cratering effects of a rocket landing on a planet's surface are not understood well, especially for the lunar case with the plume expanding in vacuum. As a result, the blast effects cannot be estimated sufficiently using analytical theories. It is necessary to develop physics-based simulation tools in order to calculate mission-essential parameters. In this work we test out the scaling laws of the physics in regard to growth rate of the crater depth. This will provide the physical insight necessary to begin the physics-based modeling.

The influence of global sea surface temperature variability on the large-scale land surface temperature

NASA Astrophysics Data System (ADS)

Tyrrell, Nicholas L.; Dommenget, Dietmar; Frauen, Claudia; Wales, Scott; Rezny, Mike

2015-04-01

In global warming scenarios, global land surface temperatures () warm with greater amplitude than sea surface temperatures (SSTs), leading to a land/sea warming contrast even in equilibrium. Similarly, the interannual variability of is larger than the covariant interannual SST variability, leading to a land/sea contrast in natural variability. This work investigates the land/sea contrast in natural variability based on global observations, coupled general circulation model simulations and idealised atmospheric general circulation model simulations with different SST forcings. The land/sea temperature contrast in interannual variability is found to exist in observations and models to a varying extent in global, tropical and extra-tropical bands. There is agreement between models and observations in the tropics but not the extra-tropics. Causality in the land-sea relationship is explored with modelling experiments forced with prescribed SSTs, where an amplification of the imposed SST variability is seen over land. The amplification of to tropical SST anomalies is due to the enhanced upper level atmospheric warming that corresponds with tropical moist convection over oceans leading to upper level temperature variations that are larger in amplitude than the source SST anomalies. This mechanism is similar to that proposed for explaining the equilibrium global warming land/sea warming contrast. The link of the to the dominant mode of tropical and global interannual climate variability, the El Niño Southern Oscillation (ENSO), is found to be an indirect and delayed connection. ENSO SST variability affects the oceans outside the tropical Pacific, which in turn leads to a further, amplified and delayed response of.

Influence of snow cover changes on surface radiation and heat balance based on the WRF model

NASA Astrophysics Data System (ADS)

Yu, Lingxue; Liu, Tingxiang; Bu, Kun; Yang, Jiuchun; Chang, Liping; Zhang, Shuwen

2017-10-01

The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes, indicating the importance of snow cover changes in the surface-atmospheric feedback system.

Analyzing energy-water exchange dynamics in the Thar desert

NASA Astrophysics Data System (ADS)

Raja, P.; Singh, Nilendu; Srinivas, C. V.; Singhal, Mohit; Chauhan, Pankaj; Singh, Maharaj; Sinha, N. K.

2017-07-01

Regions of strong land-atmosphere coupling will be more susceptible to the hydrological impacts in the intensifying hydrological cycle. In this study, micrometeorological experiments were performed to examine the land-atmosphere coupling strength over a heat low region (Thar desert, NW India), known to influence the Indian summer monsoon (ISM). Within the vortex of Thar desert heat low, energy-water exchange and coupling behavior were studied for 4 consecutive years (2011-2014) based on sub-hourly measurements of radiative-convective flux, state parameters and sub-surface thermal profiles using lead-lag analysis between various E-W balance components. Results indicated a strong (0.11-0.35) but variable monsoon season (July-September) land-atmosphere coupling events. Coupling strength declined with time, becomes negative beyond 10-day lag. Evapotranspiration (LE) influences rainfall at the monthly time-scale (20-40 days). Highly correlated monthly rainfall and LE anomalies (r = 0.55, P < 0.001) suggested a large precipitation memory linked to the local land surface state. Sensible heating (SH) during March and April are more strongly (r = 0.6-0.7) correlated to ISM rainfall than heating during May or June (r = 0.16-0.36). Analyses show strong and weak couplings among net radiation (Rn)-vapour pressure deficit (VPD), LE-VPD and Rn-LE switching between energy-limited to water-limited conditions. Consistently, +ve and -ve residual energy [(dE) = (Rn - G) - (SH + LE)] were associated with regional wet and dry spells respectively with a lead of 10-40 days. Dew deposition (18.8-37.9 mm) was found an important component in the annual surface water balance. Strong association of variation of LE and rainfall was found during monsoon at local-scale and with regional-scale LE (MERRA 2D) but with a lag which was more prominent at local-scale than at regional-scale. Higher pre-monsoon LE at local-scale as compared to low and monotonous variation in regional-scale LE led to hypothesize that excess energy and water vapour brought through advection caused by pre-monsoon rainfall might have been recycled through rainfall to compensate for early part of monsoon rainfall at local-scale. However, long-term measurements and isotope analysis would be able to strengthen this hypothesis. This study would fill the key gaps in the global flux studies and improve understanding on local E-W exchange pathways, responses and feedbacks.

V2.2_i6 L2AS Detailed Release Description November 27, 2002

Atmospheric Science Data Center

2013-03-14

... Increase the valid range of BHR and DHR from 1.0 to 1.05. This affects the scaling factors which are used to unscale the ... for heterogeneous surfaces to give a larger residual if (rho_misr - rho_model) becomes negative. In the land surface retrieval, ...

Mapping Daily Evapotranspiration at Field to Global Scales using Geostationary and Polar Orbiting Satellite Imagery

USDA-ARS?s Scientific Manuscript database

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetati...

Role of subsurface physics in the assimilation of surface soil moisture observations

USDA-ARS?s Scientific Manuscript database

Soil moisture controls the exchange of water and energy between the land surface and the atmosphere and exhibits memory that may be useful for climate prediction at monthly time scales. Though spatially distributed observations of soil moisture are increasingly becoming available from remotely sense...

Parameter studies on the energy balance closure problem using large-eddy simulation

NASA Astrophysics Data System (ADS)

De Roo, Frederik; Banerjee, Tirtha; Mauder, Matthias

2017-04-01

The imbalance of the surface energy budget in eddy-covariance measurements is still a pending problem. A possible cause is the presence of land surface heterogeneity. Heterogeneities of the boundary layer scale or larger are most effective in influencing the boundary layer turbulence, and large-eddy simulations have shown that secondary circulations within the boundary layer can affect the surface energy budget. However, the precise influence of the surface characteristics on the energy imbalance and its partitioning is still unknown. To investigate the influence of surface variables on all the components of the flux budget under convective conditions, we set up a systematic parameter study by means of large-eddy simulation. For the study we use a virtual control volume approach, and we focus on idealized heterogeneity by considering spatially variable surface fluxes. The surface fluxes vary locally in intensity and these patches have different length scales. The main focus lies on heterogeneities of length scales of the kilometer scale and one decade smaller. For each simulation, virtual measurement towers are positioned at functionally different positions. We discriminate between the locally homogeneous towers, located within land use patches, with respect to the more heterogeneous towers, and find, among others, that the flux-divergence and the advection are strongly linearly related within each class. Furthermore, we seek correlators for the energy balance ratio and the energy residual in the simulations. Besides the expected correlation with measurable atmospheric quantities such as the friction velocity, boundary-layer depth and temperature and moisture gradients, we have also found an unexpected correlation with the temperature difference between sonic temperature and surface temperature. In additional simulations with a large number of virtual towers, we investigate higher order correlations, which can be linked to secondary circulations. In a companion presentation (EGU2017-2130) these correlations are investigated and confirmed with the help of micrometeorological measurements from the TERENO sites where the effects of landscape scale surface heterogeneities are deemed to be important.

CARETS: A prototype regional environmental information system. Volume 5: Interpretation, compilation and field verification procedures in the CARETS project

NASA Technical Reports Server (NTRS)

Alexander, R. H. (Principal Investigator); Deforth, P. W.; Fitzpatrick, K. A.; Lins, H. F., Jr.; Mcginty, H. K., III

1975-01-01

The author has identified the following significant results. Level 2 land use mapping from high altitude aircraft photography at a scale of 1:100,000 required production of a photomosaic mapping base for each of the 48, 50 x 50 km sheets, and the interpretation and coding of land use polygons on drafting film overlays. To enhance the value of the land use sheets, a series of overlays was compiled, showing cultural features, county boundaries and census tracts, surface geology, and drainage basins. In producing level 1 land use maps from LANDSAT imagery, at a scale of 1:250,000 drafting film was directly overlaid on LANDSAT color composite transparencies. Numerous areas of change were identified, but extensive areas of false changes were also noted.

Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds

PubMed Central

Yang, Yingbao; Li, Xiaolong; Pan, Xin; Zhang, Yong; Cao, Chen

2017-01-01

Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 °C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions. PMID:28368301

Wind-tunnel experiments of scalar transport in aligned and staggered wind farms

NASA Astrophysics Data System (ADS)

Zhang, W.; Markfort, C. D.; Porté-Agel, F.

2012-04-01

Wind energy is the fastest growing renewable energy worldwide, and it is expected that many more large-scale wind farms will be built and will cover a significant portion of land and ocean surfaces. By extracting kinetic energy from the atmospheric boundary layer, wind farms may affect the exchange/transport of momentum, heat and moisture between the atmosphere and land surface. To ensure the long-term sustainability of wind energy, it is important to understand the influence of large-scale wind farms on land-atmosphere interaction. Knowledge of this impact will also be useful to improve parameterizations of wind farms in numerical prediction tools, such as large-scale weather models and large-eddy simulation. Here, we present wind-tunnel measurements of the surface scalar (heat) flux from model wind farms, consisting of more than 10 rows of wind turbines, in a turbulent boundary layer with a surface heat source. Spatially distributed surface heat flux was obtained in idealized aligned and staggered wind farm layouts, having the same turbine distribution density. Measurements, using surface-mounted heat flux sensors, were taken at the 11th out of 12 rows of wind turbines, where the mean flow achieves a quasi-equilibrium state. In the aligned farm, there exist two distinct regions of increased and decreased surface heat flux on either side of turbine columns. The regions are correlated with coherent wake rotation in the turbine-array. On the upwelling side there is decreased flux, while on the downwelling side cool air moves towards the surface causing increased flux. For the staggered farm, the surface heat flux exhibits a relatively uniform distribution and an overall reduction with respect to the boundary layer flow, except in the vicinity of the turbine tower. This observation is also supported by near-surface temperature and turbulent heat flux measured using a customized x-wire/cold-wire. The overall surface heat flux, relative to that of the boundary layer flow without wind turbines, is reduced by approximately 4% in the staggered wind farm and remains nearly the same in the aligned wind farm.

Land-Atmosphere Interactions: Successes, Problems and Prospects

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Mocko, D. M.

1999-01-01

After two decades of active research, a much better understanding of the broader role of biospheric processes on the local climate has emerged. A surface-albedo increase, particularly in desert border regions of the subtropics (as well as the deforested tropical regions), leads to a net surface energy deficit, which in turn leads to a relative sinking and reduced rainfall. On the other hand, studies of the influence of altered ratios of evapotranspiration and sensible fluxes, in situations where the net solar income is unchanged, show that evapotranspiration is a more desirable flux for increased precipitation and vitality of the biosphere. Besides providing water vapor and convective available potential energy (CAPE) to the lower troposphere, evapotranspiration helps in building larger CAPE before "turning on" the moist-convection. Larger CAPE in the lower troposphere enables convection to reach into the deeper atmosphere thereby heating the upper troposphere; indeed, moist-convection is also accompanied by the evaporation of falling precipitation that cools and moistens the lower atmosphere. While convective, as opposed to stratiform, precipitation reduces the fractional cloud cover; it also allows more solar radiation to reach the surface thereby invigorating surface fluxes. These, together with moist convection and associated downdrafts help to maintain the characteristic upper temperature limit(s) of the moist-land as well as oceanic regions. Regardless of the above understanding, several important problems continue to hinder the accurate simulation of a realistic land atmosphere interaction in a numerical model (both GCM and/or Meso-scale models). Among the unsolved problems are parameterization of sub-grid scale land processes that include small-scale variability of soil moisture, snow-cover and snow-physics, the biodiversity of the biosphere, orography, local drainage characteristics under natural conditions, and surface flow over the natural terrain. A well-known non-linear response of surface fluxes to these variations makes the problem of parameterizing land-atmosphere interaction processes hard-to-address and simulate, particularly in a GCM. In our presentation, we will discuss how orographic, snow-cover, and water table interactions can be included into a Simple Biosphere Model such as SiB/SSiB. Figure I shows how, in the Russian region, spring snowmelt affects the soil moisture profile. Corresponding figure 2 shows how interaction with the water table decreases the natural evapotranspiration in the Sahel region simulation. While these simulations need better validation with data, the simulations reveal that surface processes are sensitive to these parameterizations. With these developments, we continue to advance our understanding of the interaction of land with the atmosphere aloft, but the intrinsic variability of the newer parameters, e. g., hydraulic properties of the soil, diminish the positive influences of these advances on the improved climate simulation with GCMs.

Impacts of Land Cover Changes on Climate over China

NASA Astrophysics Data System (ADS)

Chen, L.; Frauenfeld, O. W.

2014-12-01

Land cover changes can influence regional climate through modifying the surface energy balance and water fluxes, and can also affect climate at large scales via changes in atmospheric general circulation. With rapid population growth and economic development, China has experienced significant land cover changes, such as deforestation, grassland degradation, and farmland expansion. In this study, the Community Earth System Model (CESM) is used to investigate the climate impacts of anthropogenic land cover changes over China. To isolate the climatic effects of land cover change, we focus on the CAM and CLM models, with prescribed climatological sea surface temperature and sea ice cover. Two experiments were performed, one with current vegetation and the other with potential vegetation. Current vegetation conditions were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations, and potential vegetation over China was obtained from Ramankutty and Foley's global potential vegetation dataset. Impacts of land cover changes on surface air temperature and precipitation are assessed based on the difference of the two experiments. Results suggest that land cover changes have a cold-season cooling effect in a large region of China, but a warming effect in summer. These temperature changes can be reconciled with albedo forcing and evapotranspiration. Moreover, impacts on atmospheric circulation and the Asian Monsoon is also discussed.

A Physically Based Runoff Routing Model for Land Surface and Earth System Models

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

Li, Hongyi; Wigmosta, Mark S.; Wu, Huan

2013-06-13

A new physically based runoff routing model, called the Model for Scale Adaptive River Transport (MOSART), has been developed to be applicable across local, regional, and global scales. Within each spatial unit, surface runoff is first routed across hillslopes and then discharged along with subsurface runoff into a ‘‘tributary subnetwork’’ before entering the main channel. The spatial units are thus linked via routing through the main channel network, which is constructed in a scale-consistent way across different spatial resolutions. All model parameters are physically based, and only a small subset requires calibration.MOSART has been applied to the Columbia River basinmore » at 1/ 168, 1/ 88, 1/ 48, and 1/ 28 spatial resolutions and was evaluated using naturalized or observed streamflow at a number of gauge stations. MOSART is compared to two other routing models widely used with land surface models, the River Transport Model (RTM) in the Community Land Model (CLM) and the Lohmann routing model, included as a postprocessor in the Variable Infiltration Capacity (VIC) model package, yielding consistent performance at multiple resolutions. MOSART is further evaluated using the channel velocities derived from field measurements or a hydraulic model at various locations and is shown to be capable of producing the seasonal variation and magnitude of channel velocities reasonably well at different resolutions. Moreover, the impacts of spatial resolution on model simulations are systematically examined at local and regional scales. Finally, the limitations ofMOSART and future directions for improvements are discussed.« less

Downscaling Soil Moisture in the Southern Great Plains Through a Calibrated Multifractal Model for Land Surface Modeling Applications

NASA Technical Reports Server (NTRS)

Mascaro, Giuseppe; Vivoni, Enrique R.; Deidda, Roberto

2010-01-01

Accounting for small-scale spatial heterogeneity of soil moisture (theta) is required to enhance the predictive skill of land surface models. In this paper, we present the results of the development, calibration, and performance evaluation of a downscaling model based on multifractal theory using aircraft!based (800 m) theta estimates collected during the southern Great Plains experiment in 1997 (SGP97).We first demonstrate the presence of scale invariance and multifractality in theta fields of nine square domains of size 25.6 x 25.6 sq km, approximately a satellite footprint. Then, we estimate the downscaling model parameters and evaluate the model performance using a set of different calibration approaches. Results reveal that small-scale theta distributions are adequately reproduced across the entire region when coarse predictors include a dynamic component (i.e., the spatial mean soil moisture ) and a stationary contribution accounting for static features (i.e., topography, soil texture, vegetation). For wet conditions, we found similar multifractal properties of soil moisture across all domains, which we ascribe to the signature of rainfall spatial variability. For drier states, the theta fields in the northern domains are more intermittent than in southern domains, likely because of differences in the distribution of vegetation coverage. Through our analyses, we propose a regional downscaling relation for coarse, satellite-based soil moisture estimates, based on ancillary information (static and dynamic landscape features), which can be used in the study area to characterize statistical properties of small-scale theta distribution required by land surface models and data assimilation systems.

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.

Scale-dependency of the global mean surface temperature trend and its implication for the recent hiatus of global warming.

PubMed

Lin, Yong; Franzke, Christian L E

2015-08-11

Studies of the global mean surface temperature trend are typically conducted at a single (usually annual or decadal) time scale. The used scale does not necessarily correspond to the intrinsic scales of the natural temperature variability. This scale mismatch complicates the separation of externally forced temperature trends from natural temperature fluctuations. The hiatus of global warming since 1999 has been claimed to show that human activities play only a minor role in global warming. Most likely this claim is wrong due to the inadequate consideration of the scale-dependency in the global surface temperature (GST) evolution. Here we show that the variability and trend of the global mean surface temperature anomalies (GSTA) from January 1850 to December 2013, which incorporate both land and sea surface data, is scale-dependent and that the recent hiatus of global warming is mainly related to natural long-term oscillations. These results provide a possible explanation of the recent hiatus of global warming and suggest that the hiatus is only temporary.

Qualitatively Modeling solute fate and transport across scales in an agricultural catchment with diverse lithology

NASA Astrophysics Data System (ADS)

Wayman, C. R.; Russo, T. A.; Li, L.; Forsythe, B.; Hoagland, B.

2017-12-01

As part of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO) project, we have collected geochemical and hydrological data from several subcatchments and four monitoring sites on the main stem of Shaver's Creek, in Huntingon county, Pennsylvania. One subcatchment (0.43 km2) is under agricultural land use, and the monitoring locations on the larger Shaver's Creek (up to 163 km2) drain watersheds with 0 to 25% agricultural area. These two scales of investigation, coupled with advances made across the SSHCZO on multiple lithologies allow us to extrapolate from the subcatchment to the larger watershed. We use geochemical surface and groundwater data to estimate the solute and water transport regimes within the catchment, and to show how lithology and land use are major controls on ground and surface water quality. One area of investigation includes the transport of nutrients between interflow and regional groundwater, and how that connectivity may be reflected in local surface waters. Water and nutrient (Nitrogen) isotopes, will be used to better understand the relative contributions of local and regional groundwater and interflow fluxes into nearby streams. Following initial qualitative modeling, multiple hydrologic and nutrient transport models (e.g. SWAT and CYCLES/PIHM) will be evaluated from the subcatchment to large watershed scales. We will evaluate the ability to simulate the contributions of regional groundwater versus local groundwater, and also impacts of agricultural land management on surface water quality. Improving estimations of groundwater contributions to stream discharge will provide insight into how much agricultural development can impact stream quality and nutrient loading.

Mapping surface heat fluxes by assimilating GOES land surface temperature and SMAP products

NASA Astrophysics Data System (ADS)

Lu, Y.; Steele-Dunne, S. C.; Van De Giesen, N.

2017-12-01

Surface heat fluxes significantly affect the land-atmosphere interaction, but their modelling is often hindered by the lack of in-situ measurements and the high spatial heterogeneity. Here, we propose a hybrid particle assimilation strategy to estimate surface heat fluxes by assimilating GOES land surface temperature (LST) data and SMAP products into a simple dual-source surface energy balance model, in which the requirement for in-situ data is minimized. The study aims to estimate two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). CHN scales the sum of surface energy fluxes, and EF represents the partitioning between flux components. To bridge the huge resolution gap between GOES and SMAP data, SMAP data are assimilated using a particle filter to update soil moisture which constrains EF, and GOES data are assimilated with an adaptive particle batch smoother to update CHN. The methodology is applied to an area in the US Southern Great Plains with forcing data from NLDAS-2 and the GPM mission. Assessment against in-situ observations suggests that the sensible and latent heat flux estimates are greatly improved at both daytime and 30-min scale after assimilation, particularly for latent heat fluxes. Comparison against an LST-only assimilation case demonstrates that despite the coarse resolution, assimilating SMAP data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the modelling uncertainties are large. Since the methodology is independent on in-situ data, it can be easily applied to other areas.

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.

Description and validation of the Simple, Efficient, Dynamic, Global, Ecological Simulator (SEDGES v.1.0)

NASA Astrophysics Data System (ADS)

Paiewonsky, Pablo; Elison Timm, Oliver

2018-03-01

In this paper, we present a simple dynamic global vegetation model whose primary intended use is auxiliary to the land-atmosphere coupling scheme of a climate model, particularly one of intermediate complexity. The model simulates and provides important ecological-only variables but also some hydrological and surface energy variables that are typically either simulated by land surface schemes or else used as boundary data input for these schemes. The model formulations and their derivations are presented here, in detail. The model includes some realistic and useful features for its level of complexity, including a photosynthetic dependency on light, full coupling of photosynthesis and transpiration through an interactive canopy resistance, and a soil organic carbon dependence for bare-soil albedo. We evaluate the model's performance by running it as part of a simple land surface scheme that is driven by reanalysis data. The evaluation against observational data includes net primary productivity, leaf area index, surface albedo, and diagnosed variables relevant for the closure of the hydrological cycle. In this setup, we find that the model gives an adequate to good simulation of basic large-scale ecological and hydrological variables. Of the variables analyzed in this paper, gross primary productivity is particularly well simulated. The results also reveal the current limitations of the model. The most significant deficiency is the excessive simulation of evapotranspiration in mid- to high northern latitudes during their winter to spring transition. The model has a relative advantage in situations that require some combination of computational efficiency, model transparency and tractability, and the simulation of the large-scale vegetation and land surface characteristics under non-present-day conditions.

Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) Field Campaign Report

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

Fast, J. D.; Berg, L. K.; Burleyson, C.

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 contain uncertainties resulting in part from insufficient coincident data that couples cloud macrophysical and microphysical properties to inhomogeneities in land surface, boundary layer, and aerosol properties. The Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign was designed to provide a detailed set of measurements that are needed to obtainmore » a more complete understanding of the lifecycle of shallow clouds by coupling cloud macrophysical and microphysical properties to land surface properties, ecosystems, and aerosols. Some of the land-atmosphere-cloud interactions that can be studied using HI-SCALE data are shown in Figure 1. HI-SCALE consisted of two 4-week intensive operation periods (IOPs), one in the spring (April 24-May 21) and the other in the late summer (August 28-September 24) of 2016, to take advantage of different stages of the plant lifecycle, the distribution of “greenness” for various types of vegetation in the vicinity of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains (SGP) site, and aerosol properties that vary during the growing season. As expected, satellite measurements indicated that the Normalized Difference Vegetation Index (NDVI) was much “greener” in the vicinity of the SGP site during the spring IOP than the late summer IOP as a result of winter wheat maturing in the spring and being harvested in the early summer. As shown in Figure 2, temperatures were cooler than average and soil moisture was high during the spring IOP, while temperatures were warmer than average and soil moisture was low during the late summer IOP. These factors likely influence the occurrence and lifecycle of shallow clouds. Most of the instrumentation was deployed on the ARM Aerial Facility (AAF) Gulfstream 1 (G-1) aircraft, including those that measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions, and cloud condensation nuclei (CCN) concentrations. The specific instrumentation is listed in Table 1. The team of scientists participating in the G-1 flights were from Pacific Northwest National Laboratory (PNNL), Brookhaven National Laboratory (BNL), and the University of Washington. Routine ARM aerosol measurements made at the surface were supplemented with aerosol microphysical properties measurements, with support from the DOE Environmental Molecular Sciences Laboratory (EMSL) User Facility and the Atmospheric System Radiation (ASR) program. This included deploying a scanning mobility particle sizer (SMPS) to measure aerosol size distribution, a proton transfer reaction-mass spectrometer (PTR-MS) to measure volatile organic compounds, an aerosol mass spectrometer (AMS) to measure bulk aerosol composition, and the single-particle laser ablation time-of-flight mass spectrometer (SPLAT II) to measure single-particle aerosol composition at the SGP site Guest Instrumentation Facility. In this way, characterization of aerosol properties at the surface and on the G-1 were consistent. In addition, the HI-SCALE: Nanoparticle Composition and Precursors add-on campaign was conducted during the second IOP in which several state-of-the-science chemical ionization mass spectrometers were deployed to measure nanoparticle composition and precursors. Scientists participating in the surface measurements were from PNNL, BNL, University California–Irvine, Augsberg College, Colorado University, Aerodyne Inc., and Aerosol Dynamics Inc.« less

The DOE water cycle pilot study.

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

Miller, N. L.; King, A. W.; Miller, M. A.

In 1999, the U.S. Global Change Research Program (USGCRP) formed a Water Cycle Study Group (Hornberger et al. 2001) to organize research efforts in regional hydrologic variability, the extent to which this variability is caused by human activity, and the influence of ecosystems. The USGCRP Water Cycle Study Group was followed by a U.S. Department of Energy (DOE) Water Cycle Research Plan (Department of Energy 2002) that outlined an approach toward improving seasonal-to-interannual hydroclimate predictability and closing a regional water budget. The DOE Water Cycle Research Plan identified key research areas, including a comprehensive long-term observational database to support modelmore » development, and to develop a better understanding of the relationship between the components of local water budgets and large scale processes. In response to this plan, a multilaboratory DOE Water Cycle Pilot Study (WCPS) demonstration project began with a focus on studying the water budget and its variability at multiple spatial scales. Previous studies have highlighted the need for continued efforts to observationally close a local water budget, develop a numerical model closure scheme, and further quantify the scales in which predictive accuracy are optimal. A concerted effort within the National Oceanic and Atmospheric Administration (NOAA)-funded Global Energy and Water Cycle Experiment (GEWEX) Continental-scale International Project (GCIP) put forth a strategy to understand various hydrometeorological processes and phenomena with an aim toward closing the water and energy budgets of regional watersheds (Lawford 1999, 2001). The GCIP focus on such regional budgets includes the measurement of all components and reduction of the error in the budgets to near zero. To approach this goal, quantification of the uncertainties in both measurements and modeling is required. Model uncertainties within regional climate models continue to be evaluated within the Program to Intercompare Regional Climate Simulations (Takle et al. 1999), and model uncertainties within land surface models are being evaluated within the Program to Intercompare Land Surface Schemes (e.g., Henderson-Sellers 1993; Wood et al. 1998; Lohmann et al. 1998). In the context of understanding the water budget at watershed scales, the following two research questions that highlight DOE's unique water isotope analysis and high-performance modeling capabilities were posed as the foci of this pilot study: (1) Can the predictability of the regional water budget be improved using high-resolution model simulations that are constrained and validated with new hydrospheric water measurements? (2) Can water isotopic tracers be used to segregate different pathways through the water cycle and predict a change in regional climate patterns? To address these questions, numerical studies using regional atmospheric-land surface models and multiscale land surface hydrologic models were generated and, to the extent possible, the results were evaluated with observations. While the number of potential processes that may be important in the local water budget is large, several key processes were examined in detail. Most importantly, a concerted effort was made to understand water cycle processes and feedbacks at the land surface-atmosphere interface at spatial scales ranging from 30 m to hundreds of kilometers. A simple expression for the land surface water budget at the watershed scale is expressed as {Delta}S = P + G{sub in} - ET - Q - G{sub out}, where {Delta}S is the change in water storage, P is precipitation, ET is evapotranspiration, Q is streamflow, G{sub in} is groundwater entering the watershed, and G{sub out} is groundwater leaving the watershed, per unit time. The WCPS project identified data gaps and necessary model improvements that will lead to a more accurate representation of the terms in Eq. (1). Table 1 summarizes the components of this water cycle pilot study and the respective participants. The following section provides a description of the surface observation and modeling sites. This is followed by a section on model analyses, and then the summary and concluding remarks.« less

Assessment of Mars Pathfinder landing site predictions

USGS Publications Warehouse

Golombek, M.P.; Moore, H.J.; Haldemann, A.F.C.; Parker, T.J.; Schofield, J.T.

1999-01-01

Remote sensing data at scales of kilometers and an Earth analog were used to accurately predict the characteristics of the Mars Pathfinder landing site at a scale of meters. The surface surrounding the Mars Pathfinder lander in Ares Vallis appears consistent with orbital interpretations, namely, that it would be a rocky plain composed of materials deposited by catastrophic floods. The surface and observed maximum clast size appears similar to predictions based on an analogous surface of the Ephrata Fan in the Channeled Scabland of Washington state. The elevation of the site measured by relatively small footprint delay-Doppler radar is within 100 m of that determined by two-way ranging and Doppler tracking of the spacecraft. The nearly equal elevations of the Mars Pathfinder and Viking Lander 1 sites allowed a prediction of the atmospheric conditions with altitude (pressure, temperature, and winds) that were well within the entry, descent, and landing design margins. High-resolution (~38 m/pixel) Viking Orbiter 1 images showed a sparsely cratered surface with small knobs with relatively low slopes, consistent with observations of these features from the lander. Measured rock abundance is within 10% of that expected from Viking orbiter thermal observations and models. The fractional area covered by large, potentially hazardous rocks observed is similar to that estimated from model rock distributions based on data from the Viking landing sites, Earth analog sites, and total rock abundance. The bulk and fine-component thermal inertias measured from orbit are similar to those calculated from the observed rock size-frequency distribution. A simple radar echo model based on the reflectivity of the soil (estimated from its bulk density), and the measured fraction of area covered by rocks was used to approximate the quasi-specular and diffuse components of the Earth-based radar echos. Color and albedo orbiter data were used to predict the relatively dust free or unweathered surface around the Pathfinder lander compared to the Viking landing sites. Comparisons with the experiences of selecting the Viking landing sites demonstrate the enormous benefit the Viking data and its analyses and models had on the successful predictions of the Pathfinder site. The Pathfinder experience demonstrates that, in certain locations, geologic processes observed in orbiter data can be used to infer surface characteristics where those processes dominate over other processes affecting the Martian surface layer. Copyright 1999 by the American Geophysical Union.

Validation of the Land-Surface Energy Budget and Planetary Boundary Layer for Several Intensive field Experiments

NASA Technical Reports Server (NTRS)

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

1999-01-01

Land-surface processes in a data assimilation system influence the lower troposphere and must be properly represented. With the recent incorporation of the Mosaic Land-surface Model (LSM) into the GEOS Data Assimilation System (DAS), the detailed land-surface processes require strict validation. While global data sources can identify large-scale systematic biases at the monthly timescale, the diurnal cycle is difficult to validate. Moreover, global data sets rarely include variables such as evaporation, sensible heat and soil water. Intensive field experiments, on the other hand, can provide high temporal resolution energy budget and vertical profile data for sufficiently long periods, without global coverage. Here, we evaluate the GEOS DAS against several intensive field experiments. The field experiments are First ISLSCP Field Experiment (FIFE, Kansas, summer 1987), Cabauw (as used in PILPS, Netherlands, summer 1987), Atmospheric Radiation Measurement (ARM, Southern Great Plains, winter and summer 1998) and the Surface Heat Budget of the Arctic Ocean (SHEBA, Arctic ice sheet, winter and summer 1998). The sites provide complete surface energy budget data for periods of at least one year, and some periods of vertical profiles. This comparison provides a detailed validation of the Mosaic LSM within the GEOS DAS for a variety of climatologic and geographic conditions.

Spatiotemporal analysis of land use and land cover change in the Brazilian Amazon

PubMed Central

Li, Guiying; Moran, Emilio; Hetrick, Scott

2013-01-01

This paper provides a comparative analysis of land use and land cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired in the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach. A classification system composed of six classes – forest, savanna, other-vegetation (secondary succession and plantations), agro-pasture, impervious surface, and water, was designed for this study. A hierarchical-based classification method was used to classify Landsat images into thematic maps. This research shows different spatiotemporal change patterns, composition and rates among the three study areas and indicates the importance of analyzing LULC change at multiple scales. The LULC change analysis over time for entire study areas provides an overall picture of change trends, but detailed change trajectories and their spatial distributions can be better examined at a per-pixel scale. The LULC change at the polygon scale provides the information of the changes in patch sizes over time, while the LULC change at census sector scale gives new insights on how human-induced activities (e.g., urban expansion, roads, and land use history) affect LULC change patterns and rates. This research indicates the necessity to implement change detection at multiple scales for better understanding the mechanisms of LULC change patterns and rates. PMID:24127130

1km Global Terrestrial Carbon Flux: Estimations and Evaluations

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Saito, M.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.

2017-12-01

Estimating global scale of the terrestrial carbon flux change with high accuracy and high resolution is important to understand global environmental changes. Furthermore the estimations of the global spatiotemporal distribution may contribute to the political and social activities such as REDD+. In order to reveal the current state of terrestrial carbon fluxes covering all over the world and a decadal scale. The satellite-based diagnostic biosphere model is suitable for achieving this purpose owing to observing on the present global land surface condition uniformly at some time interval. In this study, we estimated the global terrestrial carbon fluxes with 1km grids by using the terrestrial biosphere model (BEAMS). And we evaluated our new carbon flux estimations on various spatial scales and showed the transition of forest carbon stocks in some regions. Because BEAMS required high resolution meteorological data and satellite data as input data, we made 1km interpolated data using a kriging method. The data used in this study were JRA-55, GPCP, GOSAT L4B atmospheric CO2 data as meteorological data, and MODIS land product as land surface satellite data. Interpolating process was performed on the meteorological data because of insufficient resolution, but not on MODIS data. We evaluated our new carbon flux estimations using the flux tower measurement (FLUXNET2015 Datasets) in a point scale. We used 166 sites data for evaluating our model results. These flux sites are classified following vegetation type (DBF, EBF, ENF, mixed forests, grass lands, croplands, shrub lands, Savannas, wetlands). In global scale, the BEAMS estimations was underestimated compared to the flux measurements in the case of carbon uptake and release. The monthly variations of NEP showed relatively high correlations in DBF and mixed forests, but the correlation coefficients of EBF, ENF, and grass lands were less than 0.5. In the meteorological factors, air temperature and solar radiation showed very high correlations, and slight variations were showed in precipitation data. LAI data that was another large driving factor of terrestrial carbon cycle was not included in FLUXNET2015 datasets and it could not be evaluated.

Mapping Urban Ecosystem Services Using High Resolution Aerial Photography

NASA Astrophysics Data System (ADS)

Pilant, A. N.; Neale, A.; Wilhelm, D.

2010-12-01

Ecosystem services (ES) are the many life-sustaining benefits we receive from nature: e.g., clean air and water, food and fiber, cultural-aesthetic-recreational benefits, pollination and flood control. The ES concept is emerging as a means of integrating complex environmental and economic information to support informed environmental decision making. The US EPA is developing a web-based National Atlas of Ecosystem Services, with a component for urban ecosystems. Currently, the only wall-to-wall, national scale land cover data suitable for this analysis is the National Land Cover Data (NLCD) at 30 m spatial resolution with 5 and 10 year updates. However, aerial photography is acquired at higher spatial resolution (0.5-3 m) and more frequently (1-5 years, typically) for most urban areas. Land cover was mapped in Raleigh, NC using freely available USDA National Agricultural Imagery Program (NAIP) with 1 m ground sample distance to test the suitability of aerial photography for urban ES analysis. Automated feature extraction techniques were used to extract five land cover classes, and an accuracy assessment was performed using standard techniques. Results will be presented that demonstrate applications to mapping ES in urban environments: greenways, corridors, fragmentation, habitat, impervious surfaces, dark and light pavement (urban heat island). Automated feature extraction results mapped over NAIP color aerial photograph. At this scale, we can look at land cover and related ecosystem services at the 2-10 m scale. Small features such as individual trees and sidewalks are visible and mappable. Classified aerial photo of Downtown Raleigh NC Red: impervious surface Dark Green: trees Light Green: grass Tan: soil

Impacts of land use/cover classification accuracy on regional climate simulations

NASA Astrophysics Data System (ADS)

Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.

2007-03-01

Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.

Land Capability Potential Index (LCPI) and geodatabase for the Lower Missouri River Valley

USGS Publications Warehouse

Chojnacki, Kimberly A.; Struckhoff, Matthew A.; Jacobson, Robert B.

2012-01-01

The Land Capacity Potential Index (LCPI) is a coarse-scale index intended to delineate broad land-capability classes in the Lower Missouri River valley bottom from the Gavins Point Dam near Yankton, South Dakota to the mouth of the Missouri River near St. Louis, Missouri (river miles 811–0). The LCPI provides a systematic index of wetness potential and soil moisture-retention potential of the valley-bottom lands by combining the interactions among water-surface elevations, land-surface elevations, and the inherent moisture-retention capability of soils. A nine-class wetness index was generated by intersecting a digital elevation model for the valley bottom with sloping water-surface elevation planes derived from eight modeled discharges. The flow-recurrence index was then intersected with eight soil-drainage classes assigned to soils units in the digital Soil Survey Geographic (SSURGO) Database (Soil Survey Staff, 2010) to create a 72-class index of potential flow-recurrence and moisture-retention capability of Missouri River valley-bottom lands. The LCPI integrates the fundamental abiotic factors that determine long-term suitability of land for various uses, particularly those relating to vegetative communities and their associated values. Therefore, the LCPI provides a mechanism allowing planners, land managers, landowners, and other stakeholders to assess land-use capability based on the physical properties of the land, in order to guide future land-management decisions. This report documents data compilation for the LCPI in a revised and expanded, 72-class version for the Lower Missouri River valley bottom, and inclusion of additional soil attributes to allow users flexibility in exploring land capabilities.

Diurnal Cycles of High Resolution Land Surface Temperatures (LSTs) Determined from UAV Platforms Across a Range of Surface Types

NASA Astrophysics Data System (ADS)

McCabe, M.; Rosas Aguilar, J.; Parkes, S. D.; Aragon, B.

2017-12-01

Observation of land surface temperature (LST) has many practical uses, from studying boundary layer dynamics and land-atmosphere coupling, to investigating surface properties such as soil moisture status, heat stress and surface heat fluxes. Typically, LST is observed via satellite based sensors such as LandSat or via point measurements using IR radiometers. These measurements provide either good spatial coverage and resolution or good temporal coverage. However, neither are able to provide the needed spatial and temporal resolution for many of the research applications described above. Technological developments in the use of Unmanned Aerial Vehicles (UAVs), together with small thermal frame cameras, has enabled a capacity to overcome this spatiotemporal constraint. Utilising UAV platforms to collect LST measurements across diurnal cycles provides an opportunity to study how meteorological and surface properties vary in both space and time. Here we describe the collection of LST data from a multi-rotor UAV across a study domain that is observed multiple times throughout the day. Flights over crops of Rhodes grass and alfalfa, along with a bare desert surface, were repeated with between 8 and 11 surveys covering the period from early morning to sunset. Analysis of the collected thermal imagery shows that the constructed LST maps illustrate a strong diurnal cycle consistent with expected trends, but with considerable spatial and temporal variability observed within and between the different domains. These results offer new insights into the dynamics of land surface behavior in both dry and wet soil conditions and at spatiotemporal scales that are unable to be replicated using traditional satellite platforms.

Genetic particle filter application to land surface temperature downscaling

NASA Astrophysics Data System (ADS)

Mechri, Rihab; Ottlé, Catherine; Pannekoucke, Olivier; Kallel, Abdelaziz

2014-03-01

Thermal infrared data are widely used for surface flux estimation giving the possibility to assess water and energy budgets through land surface temperature (LST). Many applications require both high spatial resolution (HSR) and high temporal resolution (HTR), which are not presently available from space. It is therefore necessary to develop methodologies to use the coarse spatial/high temporal resolutions LST remote-sensing products for a better monitoring of fluxes at appropriate scales. For that purpose, a data assimilation method was developed to downscale LST based on particle filtering. The basic tenet of our approach is to constrain LST dynamics simulated at both HSR and HTR, through the optimization of aggregated temperatures at the coarse observation scale. Thus, a genetic particle filter (GPF) data assimilation scheme was implemented and applied to a land surface model which simulates prior subpixel temperatures. First, the GPF downscaling scheme was tested on pseudoobservations generated in the framework of the study area landscape (Crau-Camargue, France) and climate for the year 2006. The GPF performances were evaluated against observation errors and temporal sampling. Results show that GPF outperforms prior model estimations. Finally, the GPF method was applied on Spinning Enhanced Visible and InfraRed Imager time series and evaluated against HSR data provided by an Advanced Spaceborne Thermal Emission and Reflection Radiometer image acquired on 26 July 2006. The temperatures of seven land cover classes present in the study area were estimated with root-mean-square errors less than 2.4 K which is a very promising result for downscaling LST satellite products.

Interannual Variations in Global Vegetation Phenology Derived from a Long Term AVHRR and MODIS Data Record

NASA Astrophysics Data System (ADS)

Zhang, X.; Friedl, M. A.; Yu, Y.

2013-12-01

Land surface phenology metrics are widely retrieved from satellite observations at regional and global scales, and have been shown to be valuable for monitoring terrestrial ecosystem dynamics in response to extreme climate events and predicting biological responses to future climate scenarios. While the response of spring vegetation greenup to climate warming at mid-to-high latitudes is well-documented, understanding of diverse phenological responses to climate change over entire growing cycles and at broad geographic scales is incomplete. Many studies assume that the timing of individual phenological indicators in responses to climate forcing is independent of phenological events that occur at other times during the growing season. In this paper we use a different strategy. Specifically, we hypothesize that integrating sequences of key phenological indicators across growing seasons provides a more effective way to capture long-term variation in phenology in response to climate change. To explore this hypothesis we use global land surface phenology metrics derived from the Version 3 Long Term Vegetation Index Products from Multiple Satellite Data Records data set to examine interannual variations and trends in global land surface phenology from 1982-2010. Using daily enhanced vegetation index (EVI) data at a spatial resolution of 0.05 degrees, we model the phenological trajectory for each individual pixel using piecewise logistic models. The modeled trajectories were then used to detect phenological indicators including the onset of greenness increase, the onset of greenness maximum, the onset of greenness decrease, the onset of greenness minimum, and the growing season length, among others at global scale. The quality of land surface phenology detection for individual pixels was calculated based on metrics that characterize the EVI quality and model fits in annual time series at each pixel. Phenological indicators characterized as having good quality were then used to detect interannual variation and long-term trends using linear and nonlinear trend analysis techniques.

Comparison of GCM subgrid fluxes calculated using BATS and SiB schemes with a coupled land-atmosphere high-resolution model

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

Shen, Jinmei; Arritt, R.W.

The importance of land-atmosphere interactions and biosphere in climate change studies has long been recognized, and several land-atmosphere interaction schemes have been developed. Among these, the Simple Biosphere scheme (SiB) of Sellers et al. and the Biosphere Atmosphere Transfer Scheme (BATS) of Dickinson et al. are two of the most widely known. The effects of GCM subgrid-scale inhomogeneities of surface properties in general circulation models also has received increasing attention in recent years. However, due to the complexity of land surface processes and the difficulty to prescribe the large number of parameters that determine atmospheric and soil interactions with vegetation,more » many previous studies and results seem to be contradictory. A GCM grid element typically represents an area of 10{sup 4}-10{sup 6} km{sup 2}. Within such an area, there exist variations of soil type, soil wetness, vegetation type, vegetation density and topography, as well as urban areas and water bodies. In this paper, we incorporate both BATS and SiB2 land surface process schemes into a nonhydrostatic, compressible version of AMBLE model (Atmospheric Model -- Boundary-Layer Emphasis), and compare the surface heat fluxes and mesoscale circulations calculated using the two schemes. 8 refs., 5 figs.« less

Utilization of point soil moisture measurements for field scale soil moisture averages and variances in agricultural landscapes

USDA-ARS?s Scientific Manuscript database

Soil moisture is a key variable in understanding the hydrologic processes and energy fluxes at the land surface. In spite of new technologies for in-situ soil moisture measurements and increased availability of remotely sensed soil moisture data, scaling issues between soil moisture observations and...

Finite Element Simulation of Three Full-Scale Crash Tests for Cessna 172 Aircraft

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Warren, Jerry E., Jr.

2017-01-01

The NASA Emergency Locator Transmitter Survivability and Reliability (ELT-SAR) project was initiated in 2013 to assess the crash performance standards for the next generation of emergency locator transmitter (ELT) systems. Three Cessna 172 aircraft were acquired to perform crash testing at NASA Langley Research Center's Landing and Impact Research Facility. Full-scale crash tests were conducted in the summer of 2015 and each test article was subjected to severe, but survivable, impact conditions including a flare-to-stall during emergency landing, and two controlled-flight-into-terrain scenarios. Full-scale finite element analyses were performed using a commercial explicit solver, ABAQUS. The first test simulated impacting a concrete surface represented analytically by a rigid plane. Tests 2 and 3 simulated impacting a dirt surface represented analytically by an Eulerian grid of brick elements using a Mohr-Coulomb material model. The objective of this paper is to summarize the test and analysis results for the three full-scale crash tests. Simulation models of the airframe which correlate well with the tests are needed for future studies of alternate ELT mounting configurations.

Progress on Implementing Additional Physics Schemes into ...

EPA Pesticide Factsheets

The U.S. Environmental Protection Agency (USEPA) has a team of scientists developing a next generation air quality modeling system employing the Model for Prediction Across Scales – Atmosphere (MPAS-A) as its meteorological foundation. Several preferred physics schemes and options available in the Weather Research and Forecasting (WRF) model are regularly used by the USEPA with the Community Multiscale Air Quality (CMAQ) model to conduct retrospective air quality simulations. These include the Pleim surface layer, the Pleim-Xiu (PX) land surface model with fractional land use for a 40-class National Land Cover Database (NLCD40), the Asymmetric Convective Model 2 (ACM2) planetary boundary layer scheme, the Kain-Fritsch (KF) convective parameterization with subgrid-scale cloud feedback to the radiation schemes and a scale-aware convective time scale, and analysis nudging four-dimensional data assimilation (FDDA). All of these physics modules and options have already been implemented by the USEPA into MPAS-A v4.0, tested, and evaluated (please see the presentations of R. Gilliam and R. Bullock at this workshop). Since the release of MPAS v5.1 in May 2017, work has been under way to implement these preferred physics options into the MPAS-A v5.1 code. Test simulations of a summer month are being conducted on a global variable resolution mesh with the higher resolution cells centered over the contiguous United States. Driving fields for the FDDA and soil nudging are

A calibration-free formulation of the complementary relationship of evaporation for continental-scale hydrology

NASA Astrophysics Data System (ADS)

Szilagyi, Jozsef; Crago, Richard; Qualls, Russell

2017-01-01

An important scaling consideration is introduced into the formulation of the complementary relationship (CR) of land surface evapotranspiration (ET) by specifying the maximum possible evaporation rate (Epmax) of a small water body (or wet patch) as a result of adiabatic drying from the prevailing near-neutral atmospheric conditions. In dimensionless form the CR therefore becomes yB = f(Epmax-EpEpmax-EwxB) = f(X) = 2X2 - X3, where yB = ET/Ep, xB = Ew/Ep. Ew is the wet-environment evaporation rate as given by the Priestley-Taylor equation, Ep is the evaporation rate of the same small wet surface for which Epmax is specified and estimated by the Penman equation. With the help of North American Regional Reanalysis data, the CR this way yields better continental-scale performance than earlier, calibrated versions of it and is on par with current land surface model results, the latter requiring vegetation, soil information and soil moisture bookkeeping. Validation has been performed by Parameter-Elevation Regressions on Independent Slopes Model precipitation and United States Geological Survey runoff data. A novel approach is also introduced to calculate the value of the Priestley-Taylor parameter to be used with continental-scale data, making the new formulation of the CR completely calibration free.

Evaluating soil moisture constraints on surface fluxes in land surface models globally

NASA Astrophysics Data System (ADS)

Harris, Phil; Gallego-Elvira, Belen; Taylor, Christopher; Folwell, Sonja; Ghent, Darren; Veal, Karen; Hagemann, Stefan

2016-04-01

Soil moisture availability exerts a strong control over land evaporation in many regions. However, global climate models (GCMs) disagree on when and where evaporation is limited by soil moisture. Evaluation of the relevant modelled processes has suffered from a lack of reliable, global observations of land evaporation at the GCM grid box scale. Satellite observations of land surface temperature (LST) offer spatially extensive but indirect information about the surface energy partition and, under certain conditions, about soil moisture availability on evaporation. Specifically, as soil moisture decreases during rain-free dry spells, evaporation may become limited leading to increases in LST and sensible heat flux. We use MODIS Terra and Aqua observations of LST at 1 km from 2000 to 2012 to assess changes in the surface energy partition during dry spells lasting 10 days or longer. The clear-sky LST data are aggregated to a global 0.5° grid before being composited as a function dry spell day across many events in a particular region and season. These composites are then used to calculate a Relative Warming Rate (RWR) between the land surface and near-surface air. This RWR can diagnose the typical strength of short term changes in surface heat fluxes and, by extension, changes in soil moisture limitation on evaporation. Offline land surface model (LSM) simulations offer a relatively inexpensive way to evaluate the surface processes of GCMs. They have the benefits that multiple models, and versions of models, can be compared on a common grid and using unbiased forcing. Here, we use the RWR diagnostic to assess global, offline simulations of several LSMs (e.g., JULES and JSBACH) driven by the WATCH Forcing Data-ERA Interim. Both the observed RWR and the LSMs use the same 0.5° grid, which allows the observed clear-sky sampling inherent in the underlying MODIS LST to be applied to the model outputs directly. This approach avoids some of the difficulties in analysing free-running simulations in which land and atmosphere are coupled and, as such, it provides a flexible intermediate step in the assessment of surface processes in GCMs.

Hydrologic connections between environmental and societal change at the Bonneville Salt Flats, Utah

NASA Astrophysics Data System (ADS)

Bowen, B. B.; Harman, C. J.; Kipnis, E. L.; Liu, T.; Bernau, J. A.; Horel, J.

2017-12-01

The Bonneville Salt Flats (BSF) is an ephemeral and valued salt pan in northwestern Utah where a century of land speed racing and potash mining have created a complex and intertwined social and hydrologic system. The character of BSF changes on daily, weekly, monthly, annual, and geologic time scales in response to fluctuations in water balance, solute flux, and groundwater flow which is impacted by both local meteorology and water management associated with potash mining. In addition, the texture of the salt surface is changed by land use including racing activities, which impacts water fluxes through the crust. Ongoing research is focused on characterizing physical changes in the BSF environment and attributing observed changes in the landscape to specific processes and drivers. Five years of field observations and sampling, analyses of satellite imagery dating back the 1980s, and geochemical analysis of surface brines have shown that spatiotemporal changes in surface water and fluctuations in the surface salt footprint are linked to both climate and land use. Climate data over the last 30 years are examined to identify annual patterns in surface water balance at BSF to identify annual and seasonal climate constraints on flooding, evaporation, and desiccation cycles. A new weather station installed in the Fall of 2016 in the middle of BSF allows for unprecedented analyses of halite surface dynamics. Spatiotemporally dispersed stable isotope analyses of BSF surface brine samples constrain brine sources and evolution. An understanding of the processes that change the surface composition and texture through time inform interpretation of subsurface saline deposits at BSF. The wide range of temporal and spatial scales of observation help to guide to best management practices of this iconic natural resource.

Responses of Surface Ozone Air Quality to Anthropogenic Nitrogen Deposition

NASA Astrophysics Data System (ADS)

Zhang, L.; Zhao, Y.; Tai, A. P. K.; Chen, Y.; Pan, Y.

2017-12-01

Human activities have substantially increased atmospheric deposition of reactive nitrogen to the Earth's surface, inducing unintentional effects on ecosystems with complex environmental and climate consequences. One consequence remaining unexplored is how surface air quality might respond to the enhanced nitrogen deposition through surface-atmosphere exchange. We combine a chemical transport model (GEOS-Chem) and a global land model (Community Land Model) to address this issue with a focus on ozone pollution in the Northern Hemisphere. We consider three processes that are important for surface ozone and can be perturbed by addition of atmospheric deposited nitrogen: emissions of biogenic volatile organic compounds (VOCs), ozone dry deposition, and soil nitrogen oxide (NOx) emissions. We find that present-day anthropogenic nitrogen deposition (65 Tg N a-1 to the land), through enhancing plant growth (represented as increases in vegetation leaf area index (LAI) in the model), could increase surface ozone from increased biogenic VOC emissions, but could also decrease ozone due to higher ozone dry deposition velocities. Meanwhile, deposited anthropogenic nitrogen to soil enhances soil NOx emissions. The overall effect on summer mean surface ozone concentrations show general increases over the globe (up to 1.5-2.3 ppbv over the western US and South Asia), except for some regions with high anthropogenic NOx emissions (0.5-1.0 ppbv decreases over the eastern US, Western Europe, and North China). We compare the surface ozone changes with those driven by the past 20-year climate and historical land use changes. We find that the impacts from anthropogenic nitrogen deposition can be comparable to the climate and land use driven surface ozone changes at regional scales, and partly offset the surface ozone reductions due to land use changes reported in previous studies. Our study emphasizes the complexity of biosphere-atmosphere interactions, which can have important implications for future air quality prediction.

Muiti-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Holmes, Thomas

2007-01-01

A historical climatology of continuous satellite derived global land surface soil moisture is being developed. The data set consists of surface soil moisture retrievals from observations of both historical and currently active satellite microwave sensors, including Nimbus-7 SMMR, DMSP SSM/I, TRMM TMI, and AQUA AMSR-E. The data sets span the period from November 1978 through the end of 2006. The soil moisture retrievals are made with the Land Parameter Retrieval Model, a physically-based model which was developed jointly by researchers from the above institutions. These data are significant in that they are the longest continuous data record of observational surface soil moisture at a global scale. Furthermore, while previous reports have intimated that higher frequency sensors such as on SSM/I are unable to provide meaningful information on soil moisture, our results indicate that these sensors do provide highly useful soil moisture data over significant parts of the globe, and especially in critical areas located within the Earth's many arid and semi-arid regions.

Chapman Conference on the Hydrologic Aspects of Global Climate Change, Lake Chelan, WA, June 12-14, 1990, Selected Papers

NASA Technical Reports Server (NTRS)

Lettenmaier, Dennis P. (Editor); Rind, D. (Editor)

1992-01-01

The present conference on the hydrological aspects of global climate change discusses land-surface schemes for future climate models, modeling of the land-surface boundary in climate models as a composite of independent vegetation, a land-surface hydrology parameterizaton with subgrid variability for general circulation models, and conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. Attention is given to the impact of global warming on river runoff, the influence of atmospheric moisture transport on the fresh water balance of the Atlantic drainage basin, a comparison of observations and model simulations of tropospheric water vapor, and the use of weather types to disaggregate the prediction of general circulation models. Topics addressed include the potential response of an Arctic watershed during a period of global warming and the sensitivity of groundwater recharge estimates to climate variability and change.

Integrated remote sensing for multi-temporal analysis of urban land cover-climate interactions

NASA Astrophysics Data System (ADS)

Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.

2016-08-01

Climate change is considered to be the biggest environmental threat in the future in the South- Eastern part of Europe. In frame of predicted global warming, urban climate is an important issue in scientific research. Surface energy processes have an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. This paper investigated the influences of urban growth on thermal environment in relationship with other biophysical variables in Bucharest metropolitan area of Romania. Remote sensing data from Landsat TM/ETM+ and time series MODIS Terra/Aqua sensors have been used to assess urban land cover- climate interactions over period between 2000 and 2015 years. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Based on these parameters, the urban growth, and urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

Application and Evaluation of MODIS LAI, fPAR, and Albedo Products in the WRFCMAQ System

EPA Science Inventory

Leaf area index (LAI), vegetation fraction (VF), and surface albedo are important parameters in the land surface model (LSM) for meteorology and air quality modeling systems such as WRF/CMAQ. LAI and VF control not only leaf to canopy level evapotranspiration flux scaling but al...

Relative roles of differential SST warming, uniform SST warming and land surface warming in determining the Walker circulation changes under global warming

NASA Astrophysics Data System (ADS)

Zhang, Lei; Li, Tim

2017-02-01

Most of CMIP5 models projected a weakened Walker circulation in tropical Pacific, but what causes such change is still an open question. By conducting idealized numerical simulations separating the effects of the spatially uniform sea surface temperature (SST) warming, extra land surface warming and differential SST warming, we demonstrate that the weakening of the Walker circulation is attributed to the western North Pacific (WNP) monsoon and South America land effects. The effect of the uniform SST warming is through so-called "richest-get-richer" mechanism. In response to a uniform surface warming, the WNP monsoon is enhanced by competing moisture with other large-scale convective branches. The strengthened WNP monsoon further induces surface westerlies in the equatorial western-central Pacific, weakening the Walker circulation. The increase of the greenhouse gases leads to a larger land surface warming than ocean surface. As a result, a greater thermal contrast occurs between American Continent and equatorial Pacific. The so-induced zonal pressure gradient anomaly forces low-level westerly anomalies over the equatorial eastern Pacific and weakens the Walker circulation. The differential SST warming also plays a role in driving low-level westerly anomalies over tropical Pacific. But such an effect involves a positive air-sea feedback that amplifies the weakening of both east-west SST gradient and Pacific trade winds.

Remote Sensing of the Environmental Impacts of Utility-Scale Solar Energy Plants

NASA Astrophysics Data System (ADS)

Edalat, Mohammad Masih

Solar energy has many environmental benefits compared with fossil fuels but solar farming can have environmental impacts especially during construction and development. Thus, in order to enhance environmental sustainability, it is imperative to understand the environmental impacts of utility-scale solar energy (USSE) plants. During recent decades, remote sensing techniques and geographic information systems have become standard techniques in environmental applications. In this study, the environmental impacts of USSE plants are investigated by analyzing changes to land surface characteristics using remote sensing. The surface characteristics studied include land cover, land surface temperature, and hydrological response whereas changes are mapped by comparing pre-, syn-, and post- construction conditions. In order to study the effects of USSE facilities on land cover, the changes in the land cover are measured and analyzed inside and around two USSE facilities. The principal component analysis (PCA), minimum noise fraction (MNF), and spectral mixture analysis (SMA) of remote sensing images are used to estimate the subpixel fraction of four land surface endmembers: high-albedo, low-albedo, shadow, and vegetation. The results revealed that USSE plants do not significantly impact land cover outside the plant boundary. However, land-cover radiative characteristics within the plant area are significantly affected after construction. During the construction phase, site preparation practices including shrub removal and land grading increase high-albedo and decrease low-albedo fractions. The thermal effects of USSE facilities are studied by the time series analysis of remote sensing land surface temperature (LST). A statistical trend analysis of LST, with seasonal trends removed is performed with a particular consideration of panel shadowing by analyzing sun angles for different times of year. The results revealed that the LST outside the boundary of the solar plant does not change, whereas it significantly decreases inside the plant at 10 AM after the construction. The decrease in LST mainly occurred in winters due to lower sun's altitude, which casts longer shadows on the ground. In order to study the hydrological impacts of PV plants, pre- and post-installation hydrological response over single-axis technology is compared. A theoretical reasoning is developed to explain flows under the influence of PV panels. Moreover, a distributed parametric hydrologic model is used to estimate runoff before and after the construction of PV plants. The results revealed that peak flow, peak flow time, and runoff volume alter after panel installation. After panel installation, peak flow decreases and is observed to shift in time, which depends on orientation. Likewise, runoff volume increases irrespective of panel orientation. The increase in the tilt angle of panel results in decrease in the peak flow, peak flow time, and runoff. This study provides an insight into the environmental impacts of USSE development using remote sensing. The research demonstrates that USSE plants are environmentally sustainable due to minimal impact on land cover and surface temperature in their vicinity. In addition, this research explains the role of rainfall shadowing on hydrological behavior at USSE plants.

Multisource Imaging of Seasonal Dynamics in Land Surface Phenology Using Harmonized Landsat and Sentinel-2 Data

NASA Astrophysics Data System (ADS)

Melaas, E. K.; Graesser, J.; Friedl, M. A.

2017-12-01

Land surface phenology, including the timing of phenophase transitions and the entire seasonal cycle of surface reflectance and vegetation indices, is important for a myriad of applications including monitoring the response of terrestrial ecosystems to climate variability and extreme events, and land cover mapping. While methods to monitor and map phenology from coarse spatial resolution instruments such as MODIS are now relatively mature, the spatial resolution of these instruments is inadequate where vegetation properties, land use, and land cover vary at spatial scales of tens of meters. To address this need, algorithms to map phenology at moderate spatial resolution (30 m) using data from Landsat have recently been developed. However, the 16-day repeat cycle of Landsat presents significant challenges in regions where changes are rapid or where cloud cover reduces the frequency of clear-sky views. The European Space Agency's Sentinel-2 satellites, which are designed to provide moderate spatial resolution data at 5-day revisit frequency near the equator and 3 day revisit frequency in the mid-latitudes, will alleviate this constraint in many parts of the world. Here, we use harmonized time series of data from Sentinel-2A and Landsat OLI (HLS) to quantify the timing of land surface phenology metrics across a sample of deciduous forest and grassland-dominated sites, and then compare these estimates with co-located in situ observations. The resulting phenology maps demonstrate the improved information related to landscape-scale features that can be estimated from HLS data relative to comparable metrics from coarse spatial resolution instruments. For example, our results based on HLS data reveal spatial patterns in phenological metrics related to topographic and land cover controls that are not resolved in MODIS data, and show good agreement with transition dates observed from in situ measurements. Our results also show systematic bias toward earlier timing of spring, which is caused by inadequate density of observations that will be mitigated once data from Sentinel-2B are available. Overall, our results highlight the potential for using moderate spatial resolution data from Landsat and Sentinel-2 for developing operational phenology algorithms and products in support of the science community.

Small scale noise and wind tunnel tests of upper surface blowing nozzle flap concepts. Volume 1. Aerodynamic test results

NASA Technical Reports Server (NTRS)

Renselaer, D. J.; Nishida, R. S.; Wilkin, C. A.

1975-01-01

The results and analyses of aerodynamic and acoustic studies conducted on the small scale noise and wind tunnel tests of upper surface blowing nozzle flap concepts are presented. Various types of nozzle flap concepts were tested. These are an upper surface blowing concept with a multiple slot arrangement with seven slots (seven slotted nozzle), an upper surface blowing type with a large nozzle exit at approximately mid-chord location in conjunction with a powered trailing edge flap with multiple slots (split flow or partially slotted nozzle). In addition, aerodynamic tests were continued on a similar multi-slotted nozzle flap, but with 14 slots. All three types of nozzle flap concepts tested appear to be about equal in overall aerodynamic performance but with the split flow nozzle somewhat better than the other two nozzle flaps in the landing approach mode. All nozzle flaps can be deflected to a large angle to increase drag without significant loss in lift. The nozzle flap concepts appear to be viable aerodynamic drag modulation devices for landing.

Techniques for the Retrieval of Aerosol Properties Over Land and Ocean Using Multi-angle Imaging

NASA Technical Reports Server (NTRS)

Martonchik, John V.; Diner, David J.; Kahn, Ralph; Ackerman, Thomas P.; Verstraete, Michel M.; Pinty, Bernard; Gordon, Howard R.

1997-01-01

Aerosols are believed to play a direct role in the radiation budget of Earth but their net radiative effect is not well established, particularly on regional scales. Whether aerosols heat or cool a given location depends on their composition and column amount and also on the surface albedo, information that is not routinely available, especially over land.

An integrated model for assessing both crop productivity and agricultural water resources at a large scale

NASA Astrophysics Data System (ADS)

Okada, M.; Sakurai, G.; Iizumi, T.; Yokozawa, M.

2012-12-01

Agricultural production utilizes regional resources (e.g. river water and ground water) as well as local resources (e.g. temperature, rainfall, solar energy). Future climate changes and increasing demand due to population increases and economic developments would intensively affect the availability of water resources for agricultural production. While many studies assessed the impacts of climate change on agriculture, there are few studies that dynamically account for changes in water resources and crop production. This study proposes an integrated model for assessing both crop productivity and agricultural water resources at a large scale. Also, the irrigation management to subseasonal variability in weather and crop response varies for each region and each crop. To deal with such variations, we used the Markov Chain Monte Carlo technique to quantify regional-specific parameters associated with crop growth and irrigation water estimations. We coupled a large-scale crop model (Sakurai et al. 2012), with a global water resources model, H08 (Hanasaki et al. 2008). The integrated model was consisting of five sub-models for the following processes: land surface, crop growth, river routing, reservoir operation, and anthropogenic water withdrawal. The land surface sub-model was based on a watershed hydrology model, SWAT (Neitsch et al. 2009). Surface and subsurface runoffs simulated by the land surface sub-model were input to the river routing sub-model of the H08 model. A part of regional water resources available for agriculture, simulated by the H08 model, was input as irrigation water to the land surface sub-model. The timing and amount of irrigation water was simulated at a daily step. The integrated model reproduced the observed streamflow in an individual watershed. Additionally, the model accurately reproduced the trends and interannual variations of crop yields. To demonstrate the usefulness of the integrated model, we compared two types of impact assessment of climate change on crop productivity in a watershed. The first was carried out by the large-scale crop model alone. The second was carried out by the integrated model of the large-scale crop model and the H08 model. The former projected that changes in temperature and precipitation due to future climate change would give rise to increasing the water stress in crops. Nevertheless, the latter projected that the increasing amount of agricultural water resources in the watershed would supply sufficient amount of water for irrigation, consequently reduce the water stress. The integrated model demonstrated the importance of taking into account the water circulation in watershed when predicting the regional crop production.

Land use and topography influence in a complex terrain area: A high resolution mesoscale modelling study over the Eastern Pyrenees using the WRF model

NASA Astrophysics Data System (ADS)

Jiménez-Esteve, B.; Udina, M.; Soler, M. R.; Pepin, N.; Miró, J. R.

2018-04-01

Different types of land use (LU) have different physical properties which can change local energy balance and hence vertical fluxes of moisture, heat and momentum. This in turn leads to changes in near-surface temperature and moisture fields. Simulating atmospheric flow over complex terrain requires accurate local-scale energy balance and therefore model grid spacing must be sufficient to represent both topography and land-use. In this study we use both the Corine Land Cover (CLC) and United States Geological Survey (USGS) land use databases for use with the Weather Research and Forecasting (WRF) model and evaluate the importance of both land-use classification and horizontal resolution in contributing to successful modelling of surface temperatures and humidities observed from a network of 39 sensors over a 9 day period in summer 2013. We examine case studies of the effects of thermal inertia and soil moisture availability at individual locations. The scale at which the LU classification is observed influences the success of the model in reproducing observed patterns of temperature and moisture. Statistical validation of model output demonstrates model sensitivity to both the choice of LU database used and the horizontal resolution. In general, results show that on average, by a) using CLC instead of USGS and/or b) increasing horizontal resolution, model performance is improved. We also show that the sensitivity to these changes in the model performance shows a daily cycle.

The Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT)

NASA Technical Reports Server (NTRS)

Epp, Chirold D.; Smith, Thomas B.

2007-01-01

As NASA plans to send humans back to the Moon and develop a lunar outpost, technologies must be developed to place humans and cargo safely, precisely, repeatedly, on the lunar surface with the capability to avoid surface hazards. Exploration Space Architecture Study requirements include the need for global lunar surface access with safe, precise landing without lighting constraints on terrain that may have landing hazards for human scale landing vehicles. Landing accuracies of perhaps 1,000 meters for sortie crew missions to 10 s of meters for Outpost class missions are required. The Autonomous precision Landing Hazard Avoidance Technology (ALHAT) project will develop the new and unique descent and landing Guidance, Navigation and Control (GNC) hardware and software technologies necessary for these capabilities. The ALHAT project will qualify a lunar descent and landing GNC system to a Technology Readiness Level (TRL) of 6 capable of supporting lunar crewed, cargo, and robotic missions. The (ALHAT) development project was chartered by NASA Headquarters in October 2006. The initial effort to write a project plan and define an ALHAT Team was followed by a fairly aggressive research and analysis effort to determine what technologies existed that could be developed and applied to the lunar landing problems indicated above. This paper describes the project development, research, analysis and concept evolution that has occurred since the assignment of the project. This includes the areas of systems engineering, GNC, sensors, sensor algorithms, simulations, fielding testing, laboratory testing, Hardware-In-The-Loop testing, system avionics and system certification concepts.

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

Photogrammetric Measurements of CEV Airbag Landing Attenuation Systems

NASA Technical Reports Server (NTRS)

Barrows, Danny A.; Burner, Alpheus W.; Berry, Felecia C.; Dismond, Harriett R.; Cate, Kenneth H.

2008-01-01

High-speed photogrammetric measurements are being used to assess the impact dynamics of the Orion Crew Exploration Vehicle (CEV) for ground landing contingency upon return to earth. Test articles representative of the Orion capsule are dropped at the NASA Langley Landing and Impact Research (LandIR) Facility onto a sand/clay mixture representative of a dry lakebed from elevations as high as 62 feet (18.9 meters). Two different types of test articles have been evaluated: (1) half-scale metal shell models utilized to establish baseline impact dynamics and soil characterization, and (2) geometric full-scale drop models with shock-absorbing airbags which are being evaluated for their ability to cushion the impact of the Orion CEV with the earth s surface. This paper describes the application of the photogrammetric measurement technique and provides drop model trajectory and impact data that indicate the performance of the photogrammetric measurement system.

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

Using the Space-Borne NASA Scatterometer (NSCAT) to Determine The Frozen and Thawed Seasons of a Boreal Landscape

NASA Technical Reports Server (NTRS)

Frolking, S.; McDonald, K. C.; Kimball, J. S.; Way, J. B.; Zimmermann, R.; Running, S. W.

1998-01-01

We hypothesize that the strong sensitivity of radar backscatter to surface dielectric properties, and hence to the phase (solid or liquid) of any water near the surface, should make space-borne radar observations a powerful tool for large-scale spatial monitoring of the freeze/thaw state of the land surface, and thus ecosystem growing season length.

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

NASA Technical Reports Server (NTRS)

Pokhrel, Yadu N.; Hanasaki, Naota; Wada, Yoshihide; Kim, Hyungjun

2016-01-01

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

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.

Preliminary Assessment of Mars Exploration Rover Landing Site Predictions

NASA Technical Reports Server (NTRS)

Golombek, M.; Grant, J.; Parker, T.; Crisp, J.; Squyres, S.; Carr, M.; Haldemann, A.; Arvidson, R.; Ehlmann, B.; Bell, J.

2004-01-01

Selection of the Mars Exploration Rover (MER) landing sites took place over a three year period in which engineering constraints were identified, 155 possible sites were downselected to the final two, surface environments and safety considerations were developed, and the potential science return at the sites was considered. Landing sites in Gusev crater and Meridiani Planum were selected because they appeared acceptably safe for MER landing and roving and had strong morphologic and mineralogical indicators of liquid water in their past and thus appeared capable of addressing the science objectives of the MER missions, which are to determine the aqueous, climatic, and geologic history of sites on Mars where conditions may have been favorable to the preservation of evidence of possible pre-biotic or biotic processes. Engineering constraints important to the selection included: latitude (10 N-15 S) for maximum solar power; elevation (<-1.3 km) for sufficient atmosphere to slow the lander; low horizontal winds, shear and turbulence in the last few kilometers to minimize horizontal velocity; low 10-m scale slopes to reduce airbag spinup and bounce; moderate rock abundance to reduce abrasion or stroke-out of the airbags; and a radar-reflective, load-bearing and trafficable surface safe for landing and roving that is not dominated by fine-grained dust. In selecting the MER landing sites these engineering constraints were addressed via comprehensive evaluation of surface and atmospheric characteristics from existing remote sensing data and models as well as targeted orbital information acquired from Mars Global Surveyor and Mars Odyssey. This evaluation resulted in a number of predictions of the surface characteristics of the sites, which are tested in this abstract. Relating remote sensing signatures to surface characteristics at landing sites allows these sites to be used as ground truth for the orbital data, is essential for selecting and validating landing sites for future missions, and is required for correctly interpreting the surfaces and materials globally present on Mars.

Application of LANDSAT-2 data to the implementation and enforcement of the Pennsylvania Surface Mining Conservation and Reclamation Act

NASA Technical Reports Server (NTRS)

Russell, O. R. (Principal Investigator); Nichols, D. A.; Anderson, R.

1977-01-01

The author has identified the following significant results. Evaluation of LANDSAT imagery indicates severe limitations in its utility for surface mine land studies. Image stripping resulting from unequal detector response on satellite degrades the image quality to the extent that images of scales larger than 1:125,000 are of limited value for manual interpretation. Computer processing of LANDSAT data to improve image quality is essential; the removal of scanline stripping and enhancement of mine land reflectance data combined with color composite printing permits useful photographic enlargements to approximately 1:60,000.

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.

Impacts of large scale afforestation on regional climate: a case study in the Kubuqi Desert, Inner Mongolia based on WRF model

NASA Astrophysics Data System (ADS)

Wang, L.; Lin, G.; Feng, D.; Chen, S.; Schultz, N. M.; Fu, C.; Wei, Z.; Yin, C.; Wang, W.; Lee, X.

2017-12-01

To better design climate mitigation strategies, it is important to understand the response of regional climatic indicators and related biophysical forcings to large scale afforestation projects. The response of surface temperature (Ts) caused by afforestation activities in the Kubuqi Desert, Inner Mongolia, China is simulated by the weather research and forecasting (WRF) model and the temperature changes (ΔTs) are decomposed into contributions from changes in surface albedo, surface roughness, Bowen ratio and ground heat flux using the intrinsic biophysical mechanism (IBPM). The 30-m resolution land cover maps of the Kubuqi Desert corresponding to 2000 and 2010 conditions are analyzed and the major land use changes are found to be an increase in the area of grassland (6%) and shrubland (15%), but a decrease in the area of bare land (21%) owed to the aerial seeding afforestation activities organized by Elion Resources Group, Co. and local government agencies. Our WRF simulations show that during winter, the increased cover of vegetation mainly has a warming effect (0.38 K) in the daytime due to the changes in albedo (0.24 K) and Bowen ratio (0.15 K). In the nighttime, the vegetation has a slight warming effect (0.2 K) mainly caused by energy redistribution associated with roughness change (0.2 K) as a result of vegetation turbulence, which brought heat from aloft to the surface. Although both roughness change (-0.35 K) and Bowen ratio change (-0.35 K) have cooling effects during summer days, the warming effect caused by radiative forcing (0.93 K) dominates the ΔTs. During summer nights, the change in surface temperature is not significant. Our findings demonstrate that the large-scale afforestation project in the Kubuqi Desert during a decade alters the regional surface temperature and the analysis of biophysical forcings changes using WRF simulation provides useful information for developing climate change mitigation strategies in semi-arid and arid regions.

A framework for global diurnally-resolved observations of Land Surface Temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Remedios, J.; Pinnock, S.

2013-12-01

Land surface temperature (LST) is the radiative skin temperature of the land, and is one of the key parameters in the physics of land-surface processes on regional and global scales. Being a key boundary condition in land surface models, which determine the surface to atmosphere fluxes of heat, water and carbon; thus influencing cloud cover, precipitation and atmospheric chemistry predictions within Global models, the requirement for global diurnal observations of LST is well founded. Earth Observation satellites offer an opportunity to obtain global coverage of LST, with the appropriate exploitation of data from multiple instruments providing a capacity to resolve the diurnal cycle on a global scale. Here we present a framework for the production of global, diurnally resolved, data sets for LST which is a key request from users of LST data. We will show how the sampling of both geostationary and low earth orbit data sets could conceptually be employed to build combined, multi-sensor, pole-to-pole data sets. Although global averages already exist for individual instruments and merging of geostationary based LST is already being addressed operationally (Freitas, et al., 2013), there are still a number of important challenges to overcome. In this presentation, we will consider three of the issues still open in LST remote sensing: 1) the consistency amongst retrievals; 2) the clear-sky bias and its quantification; and 3) merging methods and the propagation of uncertainties. For example, the combined use of both geostationary earth orbit (GEO) and low earth orbit (LEO) data, and both infra-red and microwave data are relatively unexplored but are necessary to make the most progress. Hence this study will suggest what is state-of-the-art and how considerable advances can be made, accounting also for recent improvements in techniques and data quality. The GlobTemperature initiative under the Data User Element of ESA's 4th Earth Observation Envelope Programme (2013-2017), which aims to support the wider uptake of global-scale satellite LST by the research and operational user communities, will be a particularly important element in the development and subsequent provision of global diurnal LST. This new project, with its emphasis on promoting the coherence and openness of interactions within the LST and user communities, will be well placed to deliver appropriate data, engage a wide audience and hence be a key promoter of LST research and development for the LST community. References Freitas, S.C., Trigo, I.F., Macedo, J., Barroso, C., Silva, R., & Perdigao, R., 2013, Land surface temperature from multiple geostationary satellites, International Journal of Remote Sensing, 34, 3051-3068.

Scaling of surface energy fluxes using remotely sensed data

NASA Astrophysics Data System (ADS)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates derived from data taken at about 400-m resolution (the operational scale at El Reno) were susceptible to large error due to mixing of surface types. The El Reno experiments show that accurate instantaneous estimates of ET require precise image alignment and image resolutions finer than landscape operational scale. These findings are valuable for the design of sensors and experiments to quantify spatially-varying hydrologic processes.

Effects of land use on lake nutrients: The importance of scale, hydrologic connectivity, and region

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales.

Effects of Land Use on Lake Nutrients: The Importance of Scale, Hydrologic Connectivity, and Region

PubMed Central

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Wagner, Tyler; Webster, Katherine E.; Bremigan, Mary Tate

2015-01-01

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales. PMID:26267813

Snow driven Radiative Forcing in High Latitude Areas of Disturbance Using Higher Resolution Albedo Products from Landsat and Sentinel-2

NASA Astrophysics Data System (ADS)

Erb, A.; Li, Z.; Schaaf, C.; Wang, Z.; Rogers, B. M.

2017-12-01

Land surface albedo plays an important role in the surface energy budget and radiative forcing by determining the proportion of absorbed incoming solar radiation available to drive photosynthesis and surface heating. In Arctic regions, albedo is particularly sensitive to land cover and land use change (LCLUC) and modeling efforts have shown it to be the primary driver of effective radiative forcing from the biogeophysical effects of LCLUC. In boreal forests, the effects of these changes are complicated during snow covered periods when newly exposed, highly reflective snow can serve as the primary driver of radiative forcing. In Arctic biomes disturbance scars from fire, pest and harvest can remain in the landscape for long periods of time. As such, understanding the magnitude and persistence of these disturbances, especially in the shoulder seasons, is critical. The Landsat and Sentinel-2 Albedo Products couple 30m and 20m surface reflectances with concurrent 500m BRDF Products from the MODerate resolution Imaging Spectroradiometer (MODIS). The 12 bit radiometric fidelity of Sentinel-2 and Landsat-8 allow for the inclusion of high-quality, unsaturated albedo calculations over snow covered surfaces at scales more compatible with fragmented landscapes. Recent work on the early spring albedo of fire scars has illustrated significant post-fire spatial heterogeneity of burn severity at the landscape scale and highlights the need for a finer spatial resolution albedo record. The increased temporal resolution provided by multiple satellite instruments also allows for a better understanding of albedo dynamics during the dynamic shoulder seasons and in historically difficult high latitude locations where persistent cloud cover limits high quality retrievals. Here we present how changes in the early spring albedo of recent boreal forest disturbance in Alaska and central Canada affects landscape-scale radiative forcing. We take advantage of the long historical Landsat record to examine pre-disturbance albedo trends and to link historical land cover and disturbance history to post-disturbance early spring albedo values. We examine the impact of landscape heterogeneity on albedo in the growing and dormant seasons and quantify the effects of snow exposure changes from over-story canopy loss.

Evaluating Weather Research and Forecasting Model Sensitivity to Land and Soil Conditions Representative of Karst Landscapes

NASA Astrophysics Data System (ADS)

Johnson, Christopher M.; Fan, Xingang; Mahmood, Rezaul; Groves, Chris; Polk, Jason S.; Yan, Jun

2018-03-01

Due to their particular physiographic, geomorphic, soil cover, and complex surface-subsurface hydrologic conditions, karst regions produce distinct land-atmosphere interactions. It has been found that floods and droughts over karst regions can be more pronounced than those in non-karst regions following a given rainfall event. Five convective weather events are simulated using the Weather Research and Forecasting model to explore the potential impacts of land-surface conditions on weather simulations over karst regions. Since no existing weather or climate model has the ability to represent karst landscapes, simulation experiments in this exploratory study consist of a control (default land-cover/soil types) and three land-surface conditions, including barren ground, forest, and sandy soils over the karst areas, which mimic certain karst characteristics. Results from sensitivity experiments are compared with the control simulation, as well as with the National Centers for Environmental Prediction multi-sensor precipitation analysis Stage-IV data, and near-surface atmospheric observations. Mesoscale features of surface energy partition, surface water and energy exchange, the resulting surface-air temperature and humidity, and low-level instability and convective energy are analyzed to investigate the potential land-surface impact on weather over karst regions. We conclude that: (1) barren ground used over karst regions has a pronounced effect on the overall simulation of precipitation. Barren ground provides the overall lowest root-mean-square errors and bias scores in precipitation over the peak-rain periods. Contingency table-based equitable threat and frequency bias scores suggest that the barren and forest experiments are more successful in simulating light to moderate rainfall. Variables dependent on local surface conditions show stronger contrasts between karst and non-karst regions than variables dominated by large-scale synoptic systems; (2) significant sensitivity responses are found over the karst regions, including pronounced warming and cooling effects on the near-surface atmosphere from barren and forested land cover, respectively; (3) the barren ground in the karst regions provides conditions favourable for convective development under certain conditions. Therefore, it is suggested that karst and non-karst landscapes should be distinguished, and their physical processes should be considered for future model development.

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

NASA Technical Reports Server (NTRS)

Reichle, Rolf

2009-01-01

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

"Detecting people"

NASA Astrophysics Data System (ADS)

Arneth, A.; Pugh, T.; Krause, A.; Bayer, A.; Lindeskog, M.

2015-12-01

Land-use change (LUC) is known to significantly affect biogeochemical cycles as well as surface energy partitioning - with important implications, ranging from understanding present-day measurements, to simulations of climate change and impacts on ecosystems, to assessments of the mitigation potential of land-based mitigation policies on ecosystems. When connecting observations of surface-atmosphere interactions and modelling at different scales, two important issues in this context are: legacy effects (e.g., to what degree and for how long does past LUC at a given location affect vegetation structure, CO2 fluxes and carbon pools), and sub-grid variability of the land-use change per se (e.g., whether bi-directional information about changes are taken into consideration). Both are important when bridging between scales (in time and in space) to enhance long-term observation networks. This contribution to the session will be very much from a process-based modelling perspective. Using a second generation dynamic global vegetation model we will show how different land-use histories impact vegetation and soil recovery (carbon pool-size, fluxes) differently, depending on the type of previous land-use, its length, and on the type of biome. We also study the difference between "gross" and "net" LUC accounting for simulated carbon cycling. Two important aspects, considering the session's objectives, are: 1) When establishing and developing observation networks, land-use history is key information for the interpretation of measured fluxes and needs to be collected and made available;, 2) Observation networks that "operate" solely in the natural science domain need to increasingly seek cooperation with socio-economic observations (such as land-use change, land management) in order to gain better understanding of coupled socio-ecological systems.

Efficiently modelling urban heat storage: an interface conduction scheme in an urban land surface model (aTEB v2.0)

NASA Astrophysics Data System (ADS)

Lipson, Mathew J.; Hart, Melissa A.; Thatcher, Marcus

2017-03-01

Intercomparison studies of models simulating the partitioning of energy over urban land surfaces have shown that the heat storage term is often poorly represented. In this study, two implicit discrete schemes representing heat conduction through urban materials are compared. We show that a well-established method of representing conduction systematically underestimates the magnitude of heat storage compared with exact solutions of one-dimensional heat transfer. We propose an alternative method of similar complexity that is better able to match exact solutions at typically employed resolutions. The proposed interface conduction scheme is implemented in an urban land surface model and its impact assessed over a 15-month observation period for a site in Melbourne, Australia, resulting in improved overall model performance for a variety of common material parameter choices and aerodynamic heat transfer parameterisations. The proposed scheme has the potential to benefit land surface models where computational constraints require a high level of discretisation in time and space, for example at neighbourhood/city scales, and where realistic material properties are preferred, for example in studies investigating impacts of urban planning changes.

Technical note: 3-hourly temporal downscaling of monthly global terrestrial biosphere model net ecosystem exchange

DOE PAGES

Fisher, Joshua B.; Sikka, Munish; Huntzinger, Deborah N.; ...

2016-07-29

Here, the land surface provides a boundary condition to atmospheric forward and flux inversion models. These models require prior estimates of CO 2 fluxes at relatively high temporal resolutions (e.g., 3-hourly) because of the high frequency of atmospheric mixing and wind heterogeneity. However, land surface model CO 2 fluxes are often provided at monthly time steps, typically because the land surface modeling community focuses more on time steps associated with plant phenology (e.g., seasonal) than on sub-daily phenomena. Here, we describe a new dataset created from 15 global land surface models and 4 ensemble products in the Multi-scale Synthesis andmore » Terrestrial Model Intercomparison Project (MsTMIP), temporally downscaled from monthly to 3-hourly output. We provide 3-hourly output for each individual model over 7 years (2004–2010), as well as an ensemble mean, a weighted ensemble mean, and the multi-model standard deviation. Output is provided in three different spatial resolutions for user preferences: 0.5° × 0.5°, 2.0° × 2.5°, and 4.0° × 5.0° (latitude × longitude).« less

Intercomparison of land-surface parameterizations launched

NASA Astrophysics Data System (ADS)

Henderson-Sellers, A.; Dickinson, R. E.

One of the crucial tasks for climatic and hydrological scientists over the next several years will be validating land surface process parameterizations used in climate models. There is not, necessarily, a unique set of parameters to be used. Different scientists will want to attempt to capture processes through various methods “for example, Avissar and Verstraete, 1990”. Validation of some aspects of the available (and proposed) schemes' performance is clearly required. It would also be valuable to compare the behavior of the existing schemes [for example, Dickinson et al., 1991; Henderson-Sellers, 1992a].The WMO-CAS Working Group on Numerical Experimentation (WGNE) and the Science Panel of the GEWEX Continental-Scale International Project (GCIP) [for example, Chahine, 1992] have agreed to launch the joint WGNE/GCIP Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS). The principal goal of this project is to achieve greater understanding of the capabilities and potential applications of existing and new land-surface schemes in atmospheric models. It is not anticipated that a single “best” scheme will emerge. Rather, the aim is to explore alternative models in ways compatible with their authors' or exploiters' goals and to increase understanding of the characteristics of these models in the scientific community.

Assessing the impact of future land use and land cover changes on climate over Brazilian semiarid

NASA Astrophysics Data System (ADS)

Cunha, A. M.; Alvalá, R. S.; Kubota, P. Y.; Vieira, R.

2013-12-01

The continental surface vegetal cover has been considerably changed by human activities, mainly through natural vegetation conversion in grasslands. Such changes in surface cover may impact the regional and global climates, through of the changes in biophysical processes and CO2 exchanges between vegetation and atmosphere. In recent decades, most of the Brazilian territory has been presenting transformation in the land use/cover spatial patterns. The typical vegetation of the Brazilian semiarid, known as caatinga (closed shrubland) had been replaced by pasture lands. Based on that, the main objective of this work was to investigate the impacts of future land cover and land use changes (LCLUC) on surface processes and on the climate of Brazilian semiarid region. Numerical experiments using the AGCM/CPTEC/IBIS were performed in order to investigate the impacts of LCLUC on the climate of Brazilian semiarid due to the replacement of natural vegetation by pasture and degraded areas. The climate impacts of LUCC were assessed using climate simulations considering two scenarios of vegetation distribution: i) Potential Vegetation (Control) and ii) Future scenario of the vegetation: maximum pasture limited by areas of desert and semidesert. These degraded areas were obtained from the future projection of the biome distribution in South America developed by Salazar Velasquez (2009) using CPTEC PVMReg and emission scenarios A2 of the Intergovernmental Panel on Climate Change (IPCC). In general, the simulation results showed that the LCLUC, due to the changes in relevant surface variables, has caused alterations in local and neighborhood regions climate. The LCLUC leads to a decrease in mean rainfall during dry season at study area. A meridional dipole pattern with near surface temperature increase (reduction) in the northern (southern) areas of semiarid was found. The results also highlight that LUCC led to changes in the components of the surface energy and carbon balance. These results suggest that LCLUC, even on a small scale in Brazil's semiarid region, can cause climate impacts, in local and regional scale. Finally, we highlight that the diagnosis of the evolution of LUCC and its climatic implications are essential to guide policy makers in regard to resources application and on policies development, in order to achieve a better management and planning for this important region of the country.

Monitoring the Global Soil Moisture Climatology Using GLDAS/LIS

NASA Astrophysics Data System (ADS)

Meng, J.; Mitchell, K.; Wei, H.; Gottschalck, J.

2006-05-01

Soil moisture plays a crucial role in the terrestrial water cycle through governing the process of partitioning precipitation among infiltration, runoff and evaporation. Accurate assessment of soil moisture and other land states, namely, soil temperature, snowpack, and vegetation, is critical in numerical environmental prediction systems because of their regulation of surface water and energy fluxes between the surface and atmosphere over a variety of spatial and temporal scales. The Global Land Data Assimilation System (GLDAS) is developed, jointly by NASA Goddard Space Flight Center (GSFC) and NOAA National Centers for Environmental Prediction (NCEP), to perform high-quality global land surface simulation using state-of-art land surface models and further minimizing the errors of simulation by constraining the models with observation- based precipitation, and satellite land data assimilation techniques. The GLDAS-based Land Information System (LIS) infrastructure has been installed on the NCEP supercomputer that serves the operational weather and climate prediction systems. In this experiment, the Noah land surface model is offline executed within the GLDAS/LIS infrastructure, driven by the NCEP Global Reanalysis-2 (GR2) and the CPC Merged Analysis of Precipitation (CMAP). We use the same Noah code that is coupled to the operational NCEP Global Forecast System (GFS) for weather prediction and test bed versions of the NCEP Climate Forecast System (CFS) for seasonal prediction. For assessment, it is crucial that this uncoupled GLDAS/Noah uses exactly the same Noah code (and soil and vegetation parameters therein), and executes with the same horizontal grid, landmask, terrain field, soil and vegetation types, seasonal cycle of green vegetation fraction and surface albedo as in the coupled GFS/Noah and CFS/Noah. This execution is for the 25-year period of 1980-2005, starting with a pre-execution 10-year spin-up. This 25-year GLDAS/Noah global land climatology will be used for both climate variability assessment and as a source of land initial conditions for ensemble CFS/Noah seasonal hindcast experiments. Finally, this GLDAS/Noah climatology will serve as the foundation for a global drought/flood monitoring system that includes near realtime daily updates of the global land states.

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).

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

NASA Technical Reports Server (NTRS)

Robertson, F. R.; Bosilovich, M. G.; Roberts, J. B.; Reichle, R. H.; Adler, R.; Ricciardulli, L.; Berg, W.; Huffman, G. J.

2013-01-01

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Influence of crop type specification and spatial resolution on empirical modeling of field-scale Maize and Soybean carbon fluxes in the US Great Plains

NASA Astrophysics Data System (ADS)

McCombs, A. G.; Hiscox, A.; Wang, C.; Desai, A. R.

2016-12-01

A challenge in satellite land surface remote-sensing models of ecosystem carbon dynamics in agricultural systems is the lack of differentiation by crop type and management. This generalization can lead to large discrepancies between model predictions and eddy covariance flux tower observations of net ecosystem exchange of CO2 (NEE). Literature confirms that NEE varies remarkably among different crop types making the generalization of agriculture in remote sensing based models inaccurate. Here, we address this inaccuracy by identifying and mapping net ecosystem exchange (NEE) in agricultural fields by comparing bulk modeling and modeling by crop type, and using this information to develop empirical models for future use. We focus on mapping NEE in maize and soybean fields in the US Great Plains at higher spatial resolution using the fusion of MODIS and LandSAT surface reflectance. MODIS observed reflectance was downscaled using the ESTARFM downscaling methodology to match spatial scales to those found in LandSAT and that are more appropriate for carbon dynamics in agriculture fields. A multiple regression model was developed from surface reflectance of the downscaled MODIS and LandSAT remote sensing values calibrated against five FLUXNET/AMERIFLUX flux towers located on soybean and/or maize agricultural fields in the US Great Plains with multi-year NEE observations. Our new methodology improves upon bulk approximates to map and model carbon dynamics in maize and soybean fields, which have significantly different photosynthetic capacities.

Surficial geologic map of the Heath-Northfield-Southwick-Hampden 24-quadrangle area in the Connecticut Valley region, west-central Massachusetts

USGS Publications Warehouse

Stone, Janet R.; DiGiacomo-Cohen, Mary L.

2010-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in west-central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text, quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Norton-Manomet-Westport-Sconticut Neck 23-quadrangle area in southeast Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.; DiGiacomo-Cohen, Mary L.; Kincare, Kevin A.

2012-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 23 7.5-minute quadrangles (919 mi2 total) in southeastern Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Mount Grace-Ashburnham-Monson-Webster 24-quadrangle area in central Massachusetts

USGS Publications Warehouse

Stone, Janet R.

2013-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction-aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Physically Accurate Soil Freeze-Thaw Processes in a Global Land Surface Scheme

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Haverd, Vanessa

2018-01-01

The model Soil-Litter-Iso (SLI) calculates coupled heat and water transport in soil. It was recently implemented into the Australian land surface model CABLE, which is the land component of the Australian Community Climate and Earth System Simulator (ACCESS). Here we extended SLI to include accurate freeze-thaw processes in the soil and snow. SLI provides thence an implicit solution of the energy and water balances of soil and snow as a standalone model and within CABLE. The enhanced SLI was tested extensively against theoretical formulations, laboratory experiments, field data, and satellite retrievals. The model performed well for all experiments at wide-ranging temporal and spatial scales. SLI melts snow faster at the end of the cold season compared to observations though because there is no subgrid variability within SLI given by the implicit, coupled solution of energy and water. Combined CABLE-SLI shows very realistic dynamics and extent of permafrost on the Northern hemisphere. It illustrated, however, also the limits of possible comparisons between large-scale land surface models and local permafrost observations. CABLE-SLI exhibits the same patterns of snow depth and snow water equivalent on the Northern hemisphere compared to satellite-derived observations but quantitative comparisons depend largely on the given meteorological input fields. Further extension of CABLE-SLI with depth-dependence of soil carbon will allow realistic projections of the development of permafrost and frozen carbon stocks in a changing climate.

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.

Surficial Geologic Map of the Clinton-Concord-Grafton-Medfield 12-Quadrangle Area in East Central Massachusetts

USGS Publications Warehouse

Stone, Janet R.; Stone, Byron D.

2006-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of twelve 7.5-minute quadrangles (total 660 square miles) in east-central Massachusetts. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (grain size, sedimentary structures, mineral and rock-particle composition), constructional geomorphic features, stratigraphic relationships, and age. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions. This compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock, and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), a regional map at 1:50,000 scale (PDF), quadrangle maps at 1:24,000 scale (12 PDF files), GIS data layers (ArcGIS shapefiles), scanned topographic base maps (TIF), metadata for the GIS layers, and a readme.txt file.

Global Precipitation Measurement (GPM) Ground Validation (GV) Science Implementation Plan

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Hou, Arthur Y.

2008-01-01

For pre-launch algorithm development and post-launch product evaluation Global Precipitation Measurement (GPM) Ground Validation (GV) goes beyond direct comparisons of surface rain rates between ground and satellite measurements to provide the means for improving retrieval algorithms and model applications.Three approaches to GPM GV include direct statistical validation (at the surface), precipitation physics validation (in a vertical columns), and integrated science validation (4-dimensional). These three approaches support five themes: core satellite error characterization; constellation satellites validation; development of physical models of snow, cloud water, and mixed phase; development of cloud-resolving model (CRM) and land-surface models to bridge observations and algorithms; and, development of coupled CRM-land surface modeling for basin-scale water budget studies and natural hazard prediction. This presentation describes the implementation of these approaches.

Evaluation of coarse scale land surface remote sensing albedo product over rugged terrain

NASA Astrophysics Data System (ADS)

Wen, J.; Xinwen, L.; You, D.; Dou, B.

2017-12-01

Satellite derived Land surface albedo is an essential climate variable which controls the earth energy budget and it can be used in applications such as climate change, hydrology, and numerical weather prediction. The accuracy and uncertainty of surface albedo products should be evaluated with a reliable reference truth data prior to applications. And more literatures investigated the validation methods about the albedo validation in a flat or homogenous surface. However, the albedo performance over rugged terrain is still unknow due to the validation method limited. A multi-validation strategy is implemented to give a comprehensive albedo validation, which will involve the high resolution albedo processing, high resolution albedo validation based on in situ albedo, and the method to upscale the high resolution albedo to a coarse scale albedo. Among them, the high resolution albedo generation and the upscale method is the core step for the coarse scale albedo validation. In this paper, the high resolution albedo is generated by Angular Bin algorithm. And a albedo upscale method over rugged terrain is developed to obtain the coarse scale albedo truth. The in situ albedo located 40 sites in mountain area are selected globally to validate the high resolution albedo, and then upscaled to the coarse scale albedo by the upscale method. This paper takes MODIS and GLASS albedo product as a example, and the prelimarily results show the RMSE of MODIS and GLASS albedo product over rugged terrain are 0.047 and 0.057, respectively under the RMSE with 0.036 of high resolution albedo.

Animal taxa contrast in their scale-dependent responses to land use change in rural Africa.

PubMed

Foord, Stefan Hendrik; Swanepoel, Lourens Hendrik; Evans, Steven William; Schoeman, Colin Stefan; Erasmus, Barend Frederik N; Schoeman, M Corrie; Keith, Mark; Smith, Alain; Mauda, Evans Vusani; Maree, Naudene; Nembudani, Nkhumeleni; Dippenaar-Schoeman, Anna Sophia; Munyai, Thinandavha Caswell; Taylor, Peter John

2018-01-01

Human-dominated landscapes comprise the bulk of the world's terrestrial surface and Africa is predicted to experience the largest relative increase over the next century. A multi-scale approach is required to identify processes that maintain diversity in these landscapes. Here we identify scales at which animal diversity responds by partitioning regional diversity in a rural African agro-ecosystem between one temporal and four spatial scales. Human land use practices are the main driver of diversity in all seven animal assemblages considered, with medium sized mammals and birds most affected. Even the least affected taxa, bats and non-volant small mammals (rodents), responded with increased abundance in settlements and agricultural sites respectively. Regional turnover was important to invertebrate taxa and their response to human land use was intermediate between that of the vertebrate extremes. Local scale (< 300 m) heterogeneity was the next most important level for all taxa, highlighting the importance of fine scale processes for the maintenance of biodiversity. Identifying the triggers of these changes within the context of functional landscapes would provide the context for the long-term sustainability of these rapidly changing landscapes.

Animal taxa contrast in their scale-dependent responses to land use change in rural Africa

PubMed Central

Swanepoel, Lourens Hendrik; Evans, Steven William; Schoeman, Colin Stefan; Erasmus, Barend Frederik N.; Schoeman, M. Corrie; Keith, Mark; Smith, Alain; Mauda, Evans Vusani; Maree, Naudene; Nembudani, Nkhumeleni; Dippenaar-Schoeman, Anna Sophia; Munyai, Thinandavha Caswell; Taylor, Peter John

2018-01-01

Human-dominated landscapes comprise the bulk of the world’s terrestrial surface and Africa is predicted to experience the largest relative increase over the next century. A multi-scale approach is required to identify processes that maintain diversity in these landscapes. Here we identify scales at which animal diversity responds by partitioning regional diversity in a rural African agro-ecosystem between one temporal and four spatial scales. Human land use practices are the main driver of diversity in all seven animal assemblages considered, with medium sized mammals and birds most affected. Even the least affected taxa, bats and non-volant small mammals (rodents), responded with increased abundance in settlements and agricultural sites respectively. Regional turnover was important to invertebrate taxa and their response to human land use was intermediate between that of the vertebrate extremes. Local scale (< 300 m) heterogeneity was the next most important level for all taxa, highlighting the importance of fine scale processes for the maintenance of biodiversity. Identifying the triggers of these changes within the context of functional landscapes would provide the context for the long-term sustainability of these rapidly changing landscapes. PMID:29738559

Water Balance in the Amazon Basin from a Land Surface Model Ensemble

NASA Technical Reports Server (NTRS)

Getirana, Augusto C. V.; Dutra, Emanuel; Guimberteau, Matthieu; Kam, Jonghun; Li, Hong-Yi; Decharme, Bertrand; Zhang, Zhengqiu; Ducharne, Agnes; Boone, Aaron; Balsamo, Gianpaolo;

Soil Structure - A Neglected Component of Land-Surface Models

NASA Astrophysics Data System (ADS)

Fatichi, S.; Or, D.; Walko, R. L.; Vereecken, H.; Kollet, S. J.; Young, M.; Ghezzehei, T. A.; Hengl, T.; Agam, N.; Avissar, R.

2017-12-01

Soil structure is largely absent in most standard sampling and measurements and in the subsequent parameterization of soil hydraulic properties deduced from soil maps and used in Earth System Models. The apparent omission propagates into the pedotransfer functions that deduce parameters of soil hydraulic properties primarily from soil textural information. Such simple parameterization is an essential ingredient in the practical application of any land surface model. Despite the critical role of soil structure (biopores formed by decaying roots, aggregates, etc.) in defining soil hydraulic functions, only a few studies have attempted to incorporate soil structure into models. They mostly looked at the effects on preferential flow and solute transport pathways at the soil profile scale; yet, the role of soil structure in mediating large-scale fluxes remains understudied. Here, we focus on rectifying this gap and demonstrating potential impacts on surface and subsurface fluxes and system wide eco-hydrologic responses. The study proposes a systematic way for correcting the soil water retention and hydraulic conductivity functions—accounting for soil-structure—with major implications for near saturated hydraulic conductivity. Modification to the basic soil hydraulic parameterization is assumed as a function of biological activity summarized by Gross Primary Production. A land-surface model with dynamic vegetation is used to carry out numerical simulations with and without the role of soil-structure for 20 locations characterized by different climates and biomes across the globe. Including soil structure affects considerably the partition between infiltration and runoff and consequently leakage at the base of the soil profile (recharge). In several locations characterized by wet climates, a few hundreds of mm per year of surface runoff become deep-recharge accounting for soil-structure. Changes in energy fluxes, total evapotranspiration and vegetation productivity are less significant but they can reach up to 10% in specific locations. Significance for land-surface and hydrological modeling and implications for distributed domains are discussed.

A Bayesian Framework for Coupled Estimation of Key Unknown Parameters of Land Water and Energy Balance Equations

NASA Astrophysics Data System (ADS)

Farhadi, L.; Abdolghafoorian, A.

2015-12-01

The land surface is a key component of climate system. It controls the partitioning of available energy at the surface between sensible and latent heat, and partitioning of available water between evaporation and runoff. Water and energy cycle are intrinsically coupled through evaporation, which represents a heat exchange as latent heat flux. Accurate estimation of fluxes of heat and moisture are of significant importance in many fields such as hydrology, climatology and meteorology. In this study we develop and apply a Bayesian framework for estimating the key unknown parameters of terrestrial water and energy balance equations (i.e. moisture and heat diffusion) and their uncertainty in land surface models. These equations are coupled through flux of evaporation. The estimation system is based on the adjoint method for solving a least-squares optimization problem. The cost function consists of aggregated errors on state (i.e. moisture and temperature) with respect to observation and parameters estimation with respect to prior values over the entire assimilation period. This cost function is minimized with respect to parameters to identify models of sensible heat, latent heat/evaporation and drainage and runoff. Inverse of Hessian of the cost function is an approximation of the posterior uncertainty of parameter estimates. Uncertainty of estimated fluxes is estimated by propagating the uncertainty for linear and nonlinear function of key parameters through the method of First Order Second Moment (FOSM). Uncertainty analysis is used in this method to guide the formulation of a well-posed estimation problem. Accuracy of the method is assessed at point scale using surface energy and water fluxes generated by the Simultaneous Heat and Water (SHAW) model at the selected AmeriFlux stations. This method can be applied to diverse climates and land surface conditions with different spatial scales, using remotely sensed measurements of surface moisture and temperature states

Global water balances reconstructed by multi-model offline simulations of land surface models under GSWP3 (Invited)

NASA Astrophysics Data System (ADS)

Oki, T.; KIM, H.; Ferguson, C. R.; Dirmeyer, P.; Seneviratne, S. I.

2013-12-01

As the climate warms, the frequency and severity of flood and drought events is projected to increase. Understanding the role that the land surface will play in reinforcing or diminishing these extremes at regional scales will become critical. In fact, the current development path from atmospheric (GCM) to coupled atmosphere-ocean (AOGCM) to fully-coupled dynamic earth system models (ESMs) has brought new awareness to the climate modeling community of the abundance of uncertainty in land surface parameterizations. One way to test the representativeness of a land surface scheme is to do so in off-line (uncoupled) mode with controlled, high quality meteorological forcing. When multiple land schemes are run in-parallel (with the same forcing data), an inter-comparison of their outputs can provide the basis for model confidence estimates and future model refinements. In 2003, the Global Soil Wetness Project Phase 2 (GSWP2) provided the first global multi-model analysis of land surface state variables and fluxes. It spanned the decade of 1986-1995. While it was state-of-the art at the time, physical schemes have since been enhanced, a number of additional processes and components in the water-energy-eco-systems nexus can now be simulated, , and the availability of global, long-term observationally-based datasets that can be used for forcing and validating models has grown. Today, the data exists to support century-scale off-line experiments. The ongoing follow-on to GSWP2, named GSWP3, capitalizes on these new feasibilities and model functionalities. The project's cornerstone is its century-scale (1901-2010), 3-hourly, 0.5° meteorological forcing dataset that has been dynamically downscaled from the Twentieth Century Reanalysis and bias-corrected using monthly Climate Research Unit (CRU) temperature and Global Precipitation Climatology Centre (GPCC) precipitation data. However, GSWP3 also has an important long-term future climate component that spans the 21st century. Forcings for this period are produced from a select number of GCM-representative concentration pathways (RCPs) pairings. GSWP3 is specifically directed towards addressing the following key science questions: 1. How have interactions between eco-hydrological processes changed in the long term within a changing climate? 2. What is /will be the state of the water, energy, and carbon balances over land in the 20th and 21st centuries and what are the implications of the anticipated changes for human society in terms of freshwater resources, food productivity, and biodiversity? 3. How do the state-of-the-art land surface modeling systems perform and how can they be improved? In this presentation, we present preliminary results relevant to science question two, including: revised best-estimate global hydrological cycles for the retrospective period, inter-comparisons of modeled terrestrial water storage in large river basins and satellite remote-sensing estimates from the Gravity Recovery and Climate Experiment (GRACE), and the impacts of climate and anthropogenic changes during the 20th century on the long-term trend of water availability and scarcity.

Surficial Geologic Map of the Pocasset-Provincetown-Cuttyhunk-Nantucket 24-Quadrangle Area of Cape Cod and Islands, Southeast Massachusetts

USGS Publications Warehouse

Stone, Byron D.; DiGiacomo-Cohen, Mary L.

2006-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (555 mi2 total) in southeast Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. On Cape Cod and adjacent islands, these materials completely cover the bedrock surface. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relations, and age. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

[The progress in retrieving land surface temperature based on thermal infrared and microwave remote sensing technologies].

PubMed

Zhang, Jia-Hua; Li, Xin; Yao, Feng-Mei; Li, Xian-Hua

2009-08-01

Land surface temperature (LST) is an important parameter in the study on the exchange of substance and energy between land surface and air for the land surface physics process at regional and global scales. Many applications of satellites remotely sensed data must provide exact and quantificational LST, such as drought, high temperature, forest fire, earthquake, hydrology and the vegetation monitor, and the models of global circulation and regional climate also need LST as input parameter. Therefore, the retrieval of LST using remote sensing technology becomes one of the key tasks in quantificational remote sensing study. Normally, in the spectrum bands, the thermal infrared (TIR, 3-15 microm) and microwave bands (1 mm-1 m) are important for retrieval of the LST. In the present paper, firstly, several methods for estimating the LST on the basis of thermal infrared (TIR) remote sensing were synthetically reviewed, i. e., the LST measured with an ground-base infrared thermometer, the LST retrieval from mono-window algorithm (MWA), single-channel algorithm (SCA), split-window techniques (SWT) and multi-channels algorithm(MCA), single-channel & multi-angle algorithm and multi-channels algorithm & multi-angle algorithm, and retrieval method of land surface component temperature using thermal infrared remotely sensed satellite observation. Secondly, the study status of land surface emissivity (epsilon) was presented. Thirdly, in order to retrieve LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, have been developed recently, and the LST retrieval method from passive microwave remotely sensed data was also introduced. Finally, the main merits and shortcomings of different kinds of LST retrieval methods were discussed, respectively.

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.

Multi-scale, multi-model assessment of projected land allocation

NASA Astrophysics Data System (ADS)

Vernon, C. R.; Huang, M.; Chen, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.

2017-12-01

Effects of land use and land cover change (LULCC) on climate are generally classified into two scale-dependent processes: biophysical and biogeochemical. An extensive amount of research has been conducted related to the impact of each process under alternative climate change futures. However, these studies are generally focused on the impacts of a single process and fail to bridge the gap between sector-driven scale dependencies and any associated dynamics. Studies have been conducted to better understand the relationship of these processes but their respective scale has not adequately captured overall interdependencies between land surface changes and changes in other human-earth systems (e.g., energy, water, economic, etc.). There has also been considerable uncertainty surrounding land use land cover downscaling approaches due to scale dependencies. Demeter, a land use land cover downscaling and change detection model, was created to address this science gap. Demeter is an open-source model written in Python that downscales zonal land allocation projections to the gridded resolution of a user-selected spatial base layer (e.g., MODIS, NLCD, EIA CCI, etc.). Demeter was designed to be fully extensible to allow for module inheritance and replacement for custom research needs, such as flexible IO design to facilitate the coupling of Earth system models (e.g., the Accelerated Climate Modeling for Energy (ACME) and the Community Earth System Model (CESM)) to integrated assessment models (e.g., the Global Change Assessment Model (GCAM)). In this study, we first assessed the sensitivity of downscaled LULCC scenarios at multiple resolutions from Demeter to its parameters by comparing them to historical LULC change data. "Optimal" values of key parameters for each region were identified and used to downscale GCAM-based future scenarios consistent with those in the Land Use Model Intercomparison Project (LUMIP). Demeter-downscaled land use scenarios were then compared to the default LUMIP scenarios to illustrate the uncertainties in projected LULC as a result of difference in downscaling algorithms. Our results show that such uncertainties could propagate to other components in ACME and CESM and lead to significant differences in simulated water and biogeochemical cycles.

Characterizing an Integrated Annual Global Measure of the Earth's Maximum Land Surface Temperatures from 2003 to 2012 Reveals Strong Biogeographic Influences

NASA Astrophysics Data System (ADS)

Mildrexler, D. J.; Zhao, M.; Running, S. W.

2014-12-01

Land Surface Temperature (LST) is a good indicator of the surface energy balance because it is determined by interactions and energy fluxes between the atmosphere and the ground. The variability of land surface properties and vegetation densities across the Earth's surface changes these interactions and gives LST a unique biogeographic influence. Natural and human-induced disturbances modify the surface characteristics and alter the expression of LST. This results in a heterogeneous and dynamic thermal environment. Measurements that merge these factors into a single global metric, while maintaining the important biophysical and biogeographical factors of the land surface's thermal environment are needed to better understand integrated temperature changes in the Earth system. Using satellite-based LST we have developed a new global metric that focuses on one critical component of LST that occurs when the relationship between vegetation density and surface temperature is strongly coupled: annual maximum LST (LSTmax). A 10 year evaluation of LSTmax histograms that include every 1-km pixel across the Earth's surface reveals that this integrative measurement is strongly influenced by the biogeographic patterns of the Earth's ecosystems, providing a unique comparative view of the planet every year that can be likened to the Earth's thermal maximum fingerprint. The biogeographical component is controlled by the frequency and distribution of vegetation types across the Earth's land surface and displays a trimodal distribution. The three modes are driven by ice covered polar regions, forests, and hot desert/shrubland environments. In ice covered areas the histograms show that the heat of fusion results in a convergence of surface temperatures around the melting point. The histograms also show low interannual variability reflecting two important global land surface dynamics; 1) only a small fraction of the Earth's surface is disturbed in any given year, and 2) when considered at the global scale, the positive and negative climate forcings resulting from the aggregate effects of the loss of vegetation to disturbances and the regrowth from natural succession are roughly in balance. Changes in any component of the histogram can be tracked and would indicate a major change in the Earth system.

Emergence of new hydrologic regimes of surface water resources in the conterminous United States under future warming

NASA Astrophysics Data System (ADS)

Leng, Guoyong; Huang, Maoyi; Voisin, Nathalie; Zhang, Xuesong; Asrar, Ghassem R.; Leung, L. Ruby

2016-11-01

Despite the importance of surface water to people and ecosystems, few studies have explored detectable changes in surface water supply in a changing climate, given its large natural variability. Here we analyze runoff projections from the Variable Infiltration Capacity hydrological model driven by 97 downscaled and bias-corrected Coupled Model Intercomparison Project Phase 5 climate projections over the conterminous United States (CONUS). Our results show that more than 40% of the CONUS land area will experience significant changes in the probability distribution functions (i.e. PDFs) of summer and winter runoff by the end of the 21st century, which may pose great challenges to future surface water supply. Sub-basin mean runoff PDFs are projected to change significantly after 2040s depending on the emission scenarios, with earliest occurrence in the Pacific Northwest and northern California regions. When examining the response as a function of changes in the global mean temperature (ΔGMT), a linear relationship is revealed at the 95% confidence level. Generally, 1 °C increase of GMT leads to 11% and 17% more lands experiencing changes in summer and winter runoff PDFs, respectively. Such changes in land fraction scale with ΔGMT at the country scale independent of emission scenarios, but the same relationship does not necessarily hold at sub-basin scales, due to the larger role of atmospheric circulation changes and their uncertainties on regional precipitation. Further analyses show that the emergence of significant changes in sub-basin runoff PDFs is indicative of the emergence of new hydrology regimes and it is dominated by the changes in variability rather than shift in the mean, regardless of the emission scenarios.

High Resolution Land Use Land Cover Classification using Landsat Earth Observation Data for the Continental Africa

NASA Astrophysics Data System (ADS)

Midekisa, A.; Bennet, A.; Gething, P. W.; Holl, F.; Andrade-Pacheco, R.; Savory, D. J.; Hugh, S. J.

2016-12-01

Spatially detailed and temporally dynamic land use land cover data is necessary to monitor the state of the land surface for various applications. Yet, such data at a continental to global scale is lacking. Here, we developed high resolution (30 meter) annual land use land cover layers for the continental Africa using Google Earth Engine. To capture ground truth training data, high resolution satellite imageries were visually inspected and used to identify 7, 212 sample Landsat pixels that were comprised entirely of one of seven land use land cover classes (water, man-made impervious surface, high biomass, low biomass, rock, sand and bare soil). For model validation purposes, 80% of points from each class were used as training data, with 20% withheld as a validation dataset. Cloud free Landsat 7 annual composites for 2000 to 2015 were generated and spectral bands from the Landsat images were then extracted for each of the training and validation sample points. In addition to the Landsat spectral bands, spectral indices such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used as covariates in the model. Additionally, calibrated night time light imageries from the National Oceanic and Atmospheric Administration (NOAA) were included as a covariate. A decision tree classification algorithm was applied to predict the 7 land cover classes for the periods 2000 to 2015 using the training dataset. Using the validation dataset, classification accuracy including omission error and commission error were computed for each land cover class. Model results showed that overall accuracy of classification was high (88%). This high resolution land cover product developed for the continental Africa will be available for public use and can potentially enhance the ability of monitoring and studying the state of the Earth's surface.

Utility of an image-based canopy reflectance modeling tool for remote estimation and LAI and leaf chlorophyll content at regional scales

USDA-ARS?s Scientific Manuscript database

Radiance data recorded by remote sensors function as a unique source for monitoring the terrestrial biosphere and vegetation dynamics at a range of spatial and temporal scales. A key challenge is to relate the remote sensing signal to critical variables describing land surface vegetation canopies su...

Comparative Perspectives on Recent Trends in Land Surface Dynamics in the Grasslands of North and South America

NASA Astrophysics Data System (ADS)

Henebry, G. M.; Valle De Carvalho E Oliveira, P.; Zheng, B.; de Beurs, K.; Owsley, B.

2015-12-01

In our current era of intensive earth observation the time is ripe to shift away from studies relying on single sensors or single products to the synergistic use of multiple sensors and products at complementary spatial, temporal, and spectral scales. The use of multiple time series can not only reveal hotspots of change in land surface dynamics, but can indicate plausible proximate causes of the changes and suggest their possible consequences. Here we explore recent trends in the land surface dynamics of exemplary semi-arid grasslands in the western hemisphere, including the shortgrass prairie of eastern Colorado and New Mexico, the sandhills prairie of Nebraska, the "savana gramineo-lenhosa" variety of cerrado in central Brazil, and the pampas of Argentina. Observational datasets include (1) NBAR-based vegetation indices, land surface temperature, and evapotranspiration from MODIS, (2) air temperature, water vapor, and vegetation optical depth from AMSR-E and AMSR2, (3) surface air temperature, water vapor, and relative humidity from AIRS, and (4) surface shortwave, longwave, and total net flux from CERES. The spatial resolutions of these nested data include 500 m, 1000 m, 0.05 degree, 25 km, and 1 degree. We apply the nonparametric Seasonal Kendall trend test to each time series independently to identify areas of significant change. We then examine polygons of co-occurrence of significant change in two or more types of products using the surface radiation and energy budgets as guides to interpret the multiple changes. Changes occurring across broad areas are more likely to be of climatic origin; whereas, changes that are abrupt in space and time and of limited area are more likely anthropogenic. Results illustrate the utility of considering multiple remote sensing products as complementary views of land surface dynamics.

Deriving Scaling Factors Using a Global Hydrological Model to Restore GRACE Total Water Storage Changes for China's Yangtze River Basin

NASA Technical Reports Server (NTRS)

Long, Di; Yang, Yuting; Yoshihide, Wada; Hong, Yang; Liang, Wei; Chen, Yaning; Yong, Bin; Hou, Aizhong; Wei, Jiangfeng; Chen, Lu

2015-01-01

This study used a global hydrological model (GHM), PCR-GLOBWB, which simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface water, to generate scaling factors by mimicking low-pass filtering of GRACE signals. Signal losses in GRACE data were subsequently restored by the scaling factors from PCR-GLOBWB. Results indicate greater spatial heterogeneity in scaling factor from PCR-GLOBWB and CLM4.0 than that from GLDAS-1 Noah due to comprehensive simulation of surface and subsurface water storage changes for PCR-GLOBWB and CLM4.0. Filtered GRACE total water storage (TWS) changes applied with PCR-GLOBWB scaling factors show closer agreement with water budget estimates of TWS changes than those with scaling factors from other land surface models (LSMs) in China's Yangtze River basin. Results of this study develop a further understanding of the behavior of scaling factors from different LSMs or GHMs over hydrologically complex basins, and could be valuable in providing more accurate TWS changes for hydrological applications (e.g., monitoring drought and groundwater storage depletion) over regions where human-induced interactions between surface water and subsurface water are intensive.

Multi-Scale Fractal Analysis of Image Texture and Pattern

NASA Technical Reports Server (NTRS)

Emerson, Charles W.

1998-01-01

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Global Scale Attribution of Anthropogenic and Natural Dust Sources and their Emission Rates Based on MODIS Deep Blue Aerosol Products

NASA Technical Reports Server (NTRS)

Ginoux, Paul; Prospero, Joseph M.; Gill, Thomas E.; Hsu, N. Christina; Zhao, Ming

2012-01-01

Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Here we present a global-scale high-resolution (0.1 deg) mapping of sources based on Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue estimates of dust optical depth in conjunction with other data sets including land use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contributions to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic sources account for 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75% in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrublands and agricultural lands. Since anthropogenic dust sources are associated with land use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.

Monitoring and Assessment of US Drylands

NASA Astrophysics Data System (ADS)

Washington-Allen, R. A.; Johnson, J. S.; van Riper, C.; Modala, N. R.; Barnes, M.; Brademan, C.; Bruton, R.; Delgado, A.; Kim, J.; March, R.; Saenz, N.; Srinivasan, S.; Reeves, M. C.

2012-12-01

Monitoring of drylands requires time scales of 15 years or more in order to replicate twice the major climatic phenomena such as El Niño that have both proximal and ultimate consequences in this ecosystems. Spatially, federal agencies such as the USFS must comply with laws that request they report the condition and trend of US drylands at the national spatial scale. The MODIS sensor on both TERRA and AQUA platforms has been collecting data operational data since 2000 that include value added products such as the enhanced vegetation index (EVI), leaf area index (LAI), Land Cover, Burn Area, and net primary productivity (NPP) that can provide multiple indicators of Dryland condition and trend for now 13-years. Consequently, this sensor meets the space and time criteria necessary to begin monitoring US drylands. Additionally, the USDA National Agricultural Statistics Service has been collecting data on the spatial distribution and numbers of livestock including sheep, goats, and cattle, since the 1890's and contemporary and reconstructed climatic records at national scales go back even further in time. Time series data on climatic and land management drivers provides a basis for assessment of the causes of possible land degradation. We provide here an assessment of US Dryland condition and trend in regards to multiple indicators including land cover change in patch dynamics, NPP, and land surface temperature. For instance we show that from 2000 to 2011 US Drylands exhibit a net carbon gain that is reflected in increased connectivity of US grasslands, but conversely a decrease in surface temperatures that are indicative of increased woody encroachment. We also show that both climate, particularly drought, and livestock grazing are drivers of these dynamics.

Modeling the hydrologic effects of land and water development interventions: a case study of the upper Blue Nile river basin

NASA Astrophysics Data System (ADS)

Haregeweyn, Nigussie; Tsunekawa, Atsushi; Tsubo, Mitsuru; Meshesha, Derege; Adgo, Enyew; Poesen, Jean; Schütt, Brigitta

2014-05-01

Over 67% of the Ethiopian landmass has been identified as very vulnerable to climate variability and land degradation. These problems are more prevalent in the Upper Blue Nile (UBN, often called Abay) river basin covering a drainage area of about 199,800 km2. The UBN River runs from Lake Tana (NW Ethiopia) to the Ethiopia-Sudan border. To enhance the adaptive capacity to the high climate variability and land degradation in the basin, different land and water management measures (stone/soil bunds, runoff collector trenches, exclosures) have been extensively implemented, especially since recent years. Moreover, multipurpose water harvesting schemes including the Grand Ethiopian Renaissance Dam (GERD, reservoir area of ca. 4000 km2) and 17 other similar projects are being or to be implemented by 2025. However, impact studies on land and water management aspects rarely include detailed hydrological components especially at river basin scale, although it is generally regarded as a major determinant of hydrological processes. The main aim of this study is therefore to model the significance of land and water management interventions in surface runoff response at scale of UBN river basin and to suggest some recommendations. Spatially-distributed annual surface runoff was simulated for both present-day and future (2025) land and water management conditions using calibrated values of the proportional loss model in ArcGIS environment. Average annual rainfall map (1998-2012) was produced from calibrated TRMM satellite source and shows high spatial variability of rainfall ranging between ca. 1000 mm in the Eastern part of the basin to ca. 2000 mm in the southern part of the basin. Present-day land use day condition was obtained from Abay Basin Master Plan study. The future land use map was created taking into account the land and water development interventions to be implemented by 2025. Under present-day conditions, high spatial variability of annual runoff depth was observed in the basin ranging from 80 mm in the central part of the basin to over 1700 mm in water bodies. This variation is mainly controlled by variation in surface conditions and areal-extent of each land use type, and rainfall depth. For a specific land use type, runoff depth is found to increase with elevation as this in turn directly influences the rainfall distribution. By 2025, due to the land and water management interventions, total runoff depth in the basin could decrease by up to 40%. Following the conversion of other land use types to water bodies due to the medium to large-scale water harvesting schemes such as GERD reservoir, runoff response in those specific parts of the basin could increase by over 200%. Sub-basins have been prioritized for future land and water management interventions. Further study remains necessary to understand the downstream impacts of those interventions on runoff and sediment discharges. Keywords: Land and water management; Upper Blue Nile; Grand Ethiopian Renaissance Dam; Spatial variability of runoff; Downstream impact.

Geochemical signature of land-based activities in Caribbean coral surface samples

USGS Publications Warehouse

Prouty, N.G.; Hughen, K.A.; Carilli, J.

2008-01-01

Anthropogenic threats, such as increased sedimentation, agrochemical run-off, coastal development, tourism, and overfishing, are of great concern to the Mesoamerican Caribbean Reef System (MACR). Trace metals in corals can be used to quantify and monitor the impact of these land-based activities. Surface coral samples from the MACR were investigated for trace metal signatures resulting from relative differences in water quality. Samples were analyzed at three spatial scales (colony, reef, and regional) as part of a hierarchical multi-scale survey. A primary goal of the paper is to elucidate the extrapolation of information between fine-scale variation at the colony or reef scale and broad-scale patterns at the regional scale. Of the 18 metals measured, five yielded statistical differences at the colony and/or reef scale, suggesting fine-scale spatial heterogeneity not conducive to regional interpretation. Five metals yielded a statistical difference at the regional scale with an absence of a statistical difference at either the colony or reef scale. These metals are barium (Ba), manganese (Mn), chromium (Cr), copper (Cu), and antimony (Sb). The most robust geochemical indicators of land-based activities are coral Ba and Mn concentrations, which are elevated in samples from the southern region of the Gulf of Honduras relative to those from the Turneffe Islands. These findings are consistent with the occurrence of the most significant watersheds in the MACR from southern Belize to Honduras, which contribute sediment-laden freshwater to the coastal zone primarily as a result of human alteration to the landscape (e.g., deforestation and agricultural practices). Elevated levels of Cu and Sb were found in samples from Honduras and may be linked to industrial shipping activities where copper-antimony additives are commonly used in antifouling paints. Results from this study strongly demonstrate the impact of terrestrial runoff and anthropogenic activities on coastal water quality in the MACR. ?? 2008 Springer-Verlag.

Soil moisture from ground-based networks and the North American Land Data Assimilation System Phase 2 Model: Are the right values somewhere in between?

NASA Astrophysics Data System (ADS)

Caldwell, T. G.; Scanlon, B. R.; Long, D.; Young, M.

2013-12-01

Soil moisture is the most enigmatic component of the water balance; nonetheless, it is inherently tied to every component of the hydrologic cycle, affecting the partitioning of both water and energy at the land surface. However, our ability to assess soil water storage capacity and status through measurement or modeling is challenged by error and scale. Soil moisture is as difficult to measure as it is to model, yet land surface models and remote sensing products require some means of validation. Here we compare the three major soil moisture monitoring networks across the US, including the USDA Soil Climate Assessment Network (SCAN), NOAA Climate Reference Network (USCRN), and Cosmic Ray Soil Moisture Observing System (COSMOS) to the soil moisture simulated using the North American Land Data Assimilation System (NLDAS) Phase 2. NLDAS runs in near real-time on a 0.125° (12 km) grid over the US, producing ensemble model outputs of surface fluxes and storage. We focus primarily on soil water storage (SWS) in the upper 0-0.1 m zone from the Noah Land Surface Model and secondarily on the effects of error propagation from atmospheric forcing and soil parameterization. No scaling of the observational data was attempted. We simply compared the extracted time series at the nearest grid center from NLDAS and assessed the results by standard model statistics including root mean square error (RMSE) and mean bias estimate (MBE) of the collocated ground station. Observed and modeled data were compared at both hourly and daily mean coordinated universal time steps. In all, ~300 stations were used for 2012. SCAN sites were found to be particularly troublesome at 5- and 10-cm depths. SWS at 163 SCAN sites departed significantly from Noah with a mean R2 of 0.38 × 0.0.23, a mean RMSE of 14.9 mm with a MBE of -13.5 mm. SWS at 111 USCRN sites has a mean R2 of 0.53 × 0.20, a mean RMSE of 8.2 mm with a MBE of -3.7 mm relative to Noah. Finally, 62 COSMOS sites, the instrument with the largest measurement footprint (0.03 km2), we calculated a mean R2 of 0.53 × 0.21, a mean RMSE of 9.7 mm with a MBE of -0.3 mm. Forcing errors and textural misclassifications correlate well with model biases, indicating that scale and structural errors are equally present in NLDAS. Scaling issues aside, these confounding errors make cal/val missions, such as NASA's upcoming Soil Moisture Active Passive (SMAP) mission, problematic without significant quality control and maintenance of for our monitoring networks. Land surface models, such as NLDAS-2, may provide valuable insight into our soil moisture data and somewhere in between the real values likely exist.

Trajectory-based change detection for automated characterization of forest disturbance dynamics

Treesearch

Robert E. Kennedy; Warren B. Cohen; Todd A. Schroeder

2007-01-01

Satellite sensors are well suited to monitoring changes on the Earth's surface through provision of consistent and repeatable measurements at a spatial scale appropriate for many processes causing change on the land surface. Here, we describe and test a new conceptual approach to change detection of forests using a dense temporal stack of Landsat Thematic Mapper (...

Fallow land effects on land-atmosphere interactions in California drought

NASA Astrophysics Data System (ADS)

Lu, Y.; Melton, F. S.; Kueppers, L. M.

2015-12-01

The recent drought in California increased the area of fallow land, which is cropland not planted or irrigated per normal agricultural practice. The effects of fallow land on land-atmosphere interactions in drought years are not well studied, but theoretically should alter local energy balance and surface climate relative to normal years, which in turn could affect neighboring cropland. We examined these effects using a regional climate model (Weather Research and Forecasting model) coupled with a dynamic crop growth model (Community Land Model) that has an irrigation scheme to study the effects of fallow land in 2014, an extreme drought year in California. In our study, we used satellite-derived maps of cultivated and fallowed acreage, and defined summer fallow land in 2014 as the reduced percentage of cultivated land for each grid cell relative to the 2011 cultivated area (2011 was the most recent year following a winter with average or above average precipitation). Using a sensitivity experiment that kept large-scale climate boundary conditions constant, we found that fallow land resulted in even dryer and warmer weather that worsened the drought impact. Fallow land increased 2-meter air temperature by 0.1- 4 °C with 0-80% fallow land, mainly due to an increase in nighttime temperature. Fallow land warmed the atmosphere up to 850hpa during the day, and after sunset, the warmed atmosphere emitted downward longwave radiation that prevented the surface from rapidly cooling, and therefore resulted in warmer nights. Fallow land reduced near surface relative humidity by 5-30% and increased vapor pressure deficit by 0.5-2 kPa. These drier conditions increased the irrigation water demand in the nearby cropland: crops required 1-25% more irrigation with 10-80% fallow land within the same 10km grid cell. Our study suggests that fallow land has large impacts on land-atmosphere interactions and increases irrigation requirements in nearby cropland.

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

PubMed

Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

2016-12-01

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations. Copyright © 2016 Elsevier B.V. All rights reserved.

Using Land Surface Phenology to Detect Land Use Change in the Northern Great Plains

NASA Astrophysics Data System (ADS)

Nguyen, L. H.; Henebry, G. M.

2017-12-01

The Northern Great Plains of the US have been undergoing many types of land cover / land use change over the past two decades, including expansion of irrigation, conversion of grassland to cropland, biofuels production, urbanization, and fossil fuel mining. Much of the literature on these changes has relied on post-classification change detection based on a limited number of observations per year. Here we demonstrate an approach to characterize land dynamics through land surface phenology (LSP) by synergistic use of image time series at two scales. Our study areas include regions of interest (ROIs) across the Northern Great Plains located within Landsat path overlap zones to boost the number of valid observations (free of clouds or snow) each year. We first compute accumulated growing degree-days (AGDD) from MODIS 8-day composites of land surface temperature (MOD11A2 and MYD11A2). Using Landsat Collection 1 surface reflectance-derived vegetation indices (NDVI, EVI), we then fit at each pixel a downward convex quadratic model linking the vegetation index to each year's progression of AGDD. This quadratic equation exhibits linearity in a mathematical sense; thus, the fitted models can be linearly mixed and unmixed using a set of LSP endmembers (defined by the fitted parameter coefficients of the quadratic model) that represent "pure" land cover types with distinct seasonal patterns found within the region, such as winter wheat, spring wheat, maize, soybean, sunflower, hay/pasture/grassland, developed/built-up, among others. Information about land cover corresponding to each endmember are provided by the NLCD (National Land Cover Dataset) and CDL (Cropland Data Layer). We use linear unmixing to estimate the likely proportion of each LSP endmember within particular areas stratified by latitude. By tracking the proportions over the 2001-2011 period, we can quantify various types of land transitions in the Northern Great Plains.

Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

NASA Astrophysics Data System (ADS)

Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

2017-12-01

A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

Downscaling of Remotely Sensed Land Surface Temperature with multi-sensor based products

NASA Astrophysics Data System (ADS)

Jeong, J.; Baik, J.; Choi, M.

2016-12-01

Remotely sensed satellite data provides a bird's eye view, which allows us to understand spatiotemporal behavior of hydrologic variables at global scale. Especially, geostationary satellite continuously observing specific regions is useful to monitor the fluctuations of hydrologic variables as well as meteorological factors. However, there are still problems regarding spatial resolution whether the fine scale land cover can be represented with the spatial resolution of the satellite sensor, especially in the area of complex topography. To solve these problems, many researchers have been trying to establish the relationship among various hydrological factors and combine images from multi-sensor to downscale land surface products. One of geostationary satellite, Communication, Ocean and Meteorological Satellite (COMS), has Meteorological Imager (MI) and Geostationary Ocean Color Imager (GOCI). MI performing the meteorological mission produce Rainfall Intensity (RI), Land Surface Temperature (LST), and many others every 15 minutes. Even though it has high temporal resolution, low spatial resolution of MI data is treated as major research problem in many studies. This study suggests a methodology to downscale 4 km LST datasets derived from MI in finer resolution (500m) by using GOCI datasets in Northeast Asia. Normalized Difference Vegetation Index (NDVI) recognized as variable which has significant relationship with LST are chosen to estimate LST in finer resolution. Each pixels of NDVI and LST are separated according to land cover provided from MODerate resolution Imaging Spectroradiometer (MODIS) to achieve more accurate relationship. Downscaled LST are compared with LST observed from Automated Synoptic Observing System (ASOS) for assessing its accuracy. The downscaled LST results of this study, coupled with advantage of geostationary satellite, can be applied to observe hydrologic process efficiently.

Interpretation, compilation and field verification procedures in the CARETS project

USGS Publications Warehouse

Alexander, Robert H.; De Forth, Peter W.; Fitzpatrick, Katherine A.; Lins, Harry F.; McGinty, Herbert K.

1975-01-01

The production of the CARETS map data base involved the development of a series of procedures for interpreting, compiling, and verifying data obtained from remote sensor sources. Level II land use mapping from high-altitude aircraft photography at a scale of 1:100,000 required production of a photomosaic mapping base for each of the 48, 50 x 50 km sheets, and the interpretation and coding of land use polygons on drafting film overlays. CARETS researchers also produced a series of 1970 to 1972 land use change overlays, using the 1970 land use maps and 1972 high-altitude aircraft photography. To enhance the value of the land use sheets, researchers compiled series of overlays showing cultural features, county boundaries and census tracts, surface geology, and drainage basins. In producing Level I land use maps from Landsat imagery, at a scale of 1:250,000, interpreters overlaid drafting film directly on Landsat color composite transparencies and interpreted on the film. They found that such interpretation involves pattern and spectral signature recognition. In studies using Landsat imagery, interpreters identified numerous areas of change but also identified extensive areas of "false change," where Landsat spectral signatures but not land use had changed.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

NASA Astrophysics Data System (ADS)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

Spatial patterns and temporal dynamics of global scale climate-groundwater interactions

NASA Astrophysics Data System (ADS)

Cuthbert, M. O.; Gleeson, T. P.; Moosdorf, N.; Schneider, A. C.; Hartmann, J.; Befus, K. M.; Lehner, B.

2017-12-01

The interactions between groundwater and climate are important to resolve in both space and time as they influence mass and energy transfers at Earth's land surface. Despite the significance of these processes, little is known about the spatio-temporal distribution of such interactions globally, and many large-scale climate, hydrological and land surface models oversimplify groundwater or exclude it completely. In this study we bring together diverse global geomatic data sets to map spatial patterns in the sensitivity and degree of connectedness between the water table and the land surface, and use the output from a global groundwater model to assess the locations where the lateral import or export of groundwater is significant. We also quantify the groundwater response time, the characteristic time for groundwater systems to respond to a change in boundary conditions, and map its distribution globally to assess the likely dynamics of groundwater's interaction with climate. We find that more than half of the global land surface significantly exports or imports groundwater laterally. Nearly 40% of Earth's landmass has water tables that are strongly coupled to topography with water tables shallow enough to enable a bi-directional exchange of moisture with the climate system. However, only a small proportion (around 12%) of such regions have groundwater response times of 100 years or less and have groundwater fluxes that would significantly respond to rapid environmental changes over this timescale. We last explore fundamental relationships between aridity, groundwater response times and groundwater turnover times. Our results have wide ranging implications for understanding and modelling changes in Earth's water and energy balance and for informing robust future water management and security decisions.

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.

Shifting relative importance of climatic constraints on land surface phenology

NASA Astrophysics Data System (ADS)

Garonna, Irene; de Jong, Rogier; Stöckli, Reto; Schmid, Bernhard; Schenkel, David; Schimel, David; Schaepman, Michael E.

2018-02-01

Land surface phenology (LSP), the study of seasonal dynamics of vegetated land surfaces from remote sensing, is a key indicator of global change, that both responds to and influences weather and climate. The effects of climatic changes on LSP depend on the relative importance of climatic constraints in specific regions—which are not well understood at global scale. Understanding the climatic constraints that underlie LSP is crucial for explaining climate change effects on global vegetation phenology. We used a combination of modelled and remotely-sensed vegetation activity records to quantify the interplay of three climatic constraints on land surface phenology (namely minimum temperature, moisture availability, and photoperiod), as well as the dynamic nature of these constraints. Our study examined trends and the relative importance of the three constrains at the start and the end of the growing season over eight global environmental zones, for the past three decades. Our analysis revealed widespread shifts in the relative importance of climatic constraints in the temperate and boreal biomes during the 1982-2011 period. These changes in the relative importance of the three climatic constraints, which ranged up to 8% since 1982 levels, varied with latitude and between start and end of the growing season. We found a reduced influence of minimum temperature on start and end of season in all environmental zones considered, with a biome-dependent effect on moisture and photoperiod constraints. For the end of season, we report that the influence of moisture has on average increased for both the temperate and boreal biomes over 8.99 million km2. A shifting relative importance of climatic constraints on LSP has implications both for understanding changes and for improving how they may be modelled at large scales.

Surface knowledge and risks to landing and roving - The scale problem

NASA Technical Reports Server (NTRS)

Bourke, Roger D.

1991-01-01

The role of surface information in the performance of surface exploration missions is discussed. Accurate surface models based on direct measurements or inference are considered to be an important component in mission risk management. These models can be obtained using high resolution orbital photography or a combination of laser profiling, thermal inertia measurements, and/or radar. It is concluded that strategies for Martian exploration should use high confidence models to achieve maximum performance and low risk.

Uncertainties of Large-Scale Forcing Caused by Surface Turbulence Flux Measurements and the Impacts on Cloud Simulations at the ARM SGP Site

NASA Astrophysics Data System (ADS)

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

2017-12-01

Two types of instruments, the eddy correlation flux measurement system (ECOR) and the energy balance Bowen ratio system (EBBR), are used at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site to measure surface latent and sensible fluxes. ECOR and EBBR typically sample different land surface types, and the domain-mean surface fluxes derived from ECOR and EBBR are not always consistent. The uncertainties of the surface fluxes will have impacts on the derived large-scale forcing data and further affect the simulations of single-column models (SCM), cloud-resolving models (CRM) and large-eddy simulation models (LES), especially for the shallow-cumulus clouds which are mainly driven by surface forcing. This study aims to quantify the uncertainties of the large-scale forcing caused by surface turbulence flux measurements and investigate the impacts on cloud simulations using long-term observations from the ARM SGP site.

Hydro-meteorological processes on the Qinghai - Tibet Plateau observed from space

NASA Astrophysics Data System (ADS)

Menenti, Massimo; Colin, Jerome; Jia, Li; D'Urso, Guido; Foken, Thomas; Immerzeel, Walter; Jha, Ramakar; Liu, Qinhuo; Liu, Changming; Ma, Yaoming; Sobrino, Jose Antonio; Yan, Guangjian; Pelgrum, Henk; Porcu, Federico; Wang, Jian; Wang, Jiemin; Shen, Xueshun; Su, Zhongbo; Ueno, Kenichi

2014-05-01

The Qinghai - Tibet Plateau is characterized by a significant intra-annual variability and spatial heterogeneity of surface conditions. Snow and vegetation cover, albedo, surface temperature and wetness change very significantly during the year and from place to place. The influence of temporal changes on convective events and the onset of the monsoon has been documented by ground based measurements of land - atmosphere exchanges of heat and water. The state of the land surface over the entire Plateau can be determined by space observation of surface albedo, temperature, snow and vegetation cover and soil moisture. Fully integrated use of satellite and ground observations is necessary to support water resources management in SE Asia and to clarify the roles of the interactions between the land surface and the atmosphere over the Tibetan Plateau in the Asian monsoon system. New or significantly improved algorithms have been developed and evaluated against ground measurements. Variables retrieved include land surface properties, rain rate, aerosol optical depth, water vapour, snow cover and water equivalent, soil moisture and lake level. The three years time series of gap-free daily and hourly evaporation derived from geostationary data collected by the FY-2D satellite was a major achievement. The hydrologic modeling system has been implemented and applied to the Qinghai Tibet Plateau and the headwaters of the major rivers in South and East Asia. Case studies on response of atmospheric circulation and specifically of convective activity to land surface conditions have been completed and the controlling land surface conditions and processes have been documented. Two new drought indicators have been developed: Normalized Temperature Anomaly Index (NTAI) and Normalized Vegetation Anomaly Index (NVAI). Case study in China and India showed that these indicators capture effectively drought severity and evolution. A new method has been developed for monitoring and early warning of flooded areas at the regional scale.

Emerging ecological datasets with application for modeling North American dust emissions

NASA Astrophysics Data System (ADS)

McCord, S.; Stauffer, N. G.; Garman, S.; Webb, N.

2017-12-01

In 2011 the US Bureau of Land Management (BLM) established the Assessment, Inventory and Monitoring (AIM) program to monitor the condition of BLM land and to provide data to support evidence-based management of multi-use public lands. The monitoring program shares core data collection methods with the Natural Resources Conservation Service's (NRCS) National Resources Inventory (NRI), implemented on private lands nationally. Combined, the two programs have sampled >30,000 locations since 2003 to provide vegetation composition, vegetation canopy height, the size distribution of inter-canopy gaps, soil texture and crusting information on rangelands and pasture lands across North America. The BLM implements AIM on more than 247.3 million acres of land across the western US, encompassing major dust source regions of the Chihuahuan, Sonoran, Mojave and Great Basin deserts, the Colorado Plateau, and potential high-latitude dust sources in Alaska. The AIM data are publicly available and can be used to support modeling of land surface and boundary-layer processes, including dust emission. While understanding US dust source regions and emission processes has been of national interest since the 1930s Dust Bowl, most attention has been directed to the croplands of the Great Plains and emission hot spots like Owens Lake, California. The magnitude, spatial extent and temporal dynamics of dust emissions from western dust source areas remain highly uncertain. Here, we use ensemble modeling with empirical and physically-based dust emission schemes applied to AIM monitoring data to assess regional-scale patterns of aeolian sediment mass fluxes and dust emissions. The analysis enables connections to be made between dust emission rates at source and other indicators of ecosystem function at the landscape scale. Emerging ecological datasets like AIM provide new opportunities to evaluate aeolian sediment transport responses to land surface conditions, potential interactions with disturbances (e.g., fire) and ecological change (e.g., invasive species), and the impacts of anthropogenic land use and land cover change.

Reconstructed Historical Land Cover and Biophysical Parameters for Studies of Land-Atmosphere Interactions within the Eastern United States

NASA Technical Reports Server (NTRS)

Steyaert, Louis T.; Knox, Robert G.

2007-01-01

The local environment where we live within the Earth's biosphere is often taken for granted. This environment can vary depending on whether the land cover is a forest, grassland, wetland, water body, bare soil, pastureland, agricultural field, village, residential suburb, or an urban complex with concrete, asphalt, and large buildings. In general, the type and characteristics of land cover influence surface temperatures, sunlight exposure and duration, relative humidity, wind speed and direction, soil moisture amount, plant life, birds, and other wildlife in our backyards. The physical and biological properties (biophysical characteristics) of land cover help to determine our surface environment because they directly affect surface radiation, heat, and soil moisture processes, and also feedback to regional weather and climate. Depending on the spatial scale and land use intensity, land cover changes can have profound impacts on our local and regional environment. Over the past 350 years, the eastern half of the United States, an area extending from the grassland prairies of the Great Plains to the Gulf and Atlantic coasts, has experienced extensive land cover and land use changes that began with land clearing in the 1600s, led to extensive deforestation and intensive land use practices by 1920, and then evolved to the present-day landscape. Determining the consequences of such land cover changes on regional and global climate is a major research issue. Such research requires detailed historical land cover data and modeling experiments simulating historical climates. Given the need to understand the effects of historical land cover changes in the eastern United States, some questions include: - What were the most important land cover transformations and how did they alter biophysical characteristics of the land cover at key points in time since the mid-1600s? - How have land cover and land use changes over the past 350 years affected the land surface environment including surface weather, hydrologic, and climatic variability? - How do the potential effects of regional human-induced land cover change on the environment compare to similar changes that are caused by the natural variations of the Earth's climate system? To help answer these questions, we reconstructed a fractional land cover and biophysical parameter dataset for the eastern United States at 1650, 1850, 1920, and 1992 time-slices. Each land cover fraction is associated with a biophysical parameter class, a suite of parameters defining the biophysical characteristics of that kind of land cover. This new dataset is designed for use in computer models of land-atmosphere interactions, to understand and quantify the effects of historical land cover changes on the water, energy, and carbon cycles

Local variance for multi-scale analysis in geomorphometry.

PubMed

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-07-15

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements.

Local variance for multi-scale analysis in geomorphometry

PubMed Central

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-01-01

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements. PMID:21779138

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Qian, I.; Lau, W.; Shie, C.-L.; Starr, David (Technical Monitor)

2002-01-01

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/ South China Sea (SCS)/China, N. America and S. America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-C loud Exchange (PLACE) land surface model. PLACE allows for the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1997 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Wang, Y.; Lau, W.; Jia, Y.; Johnson, D.; Shie, C.-L.; Einaudi, Franco (Technical Monitor)

2001-01-01

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/South China Sea (SCS)/China, North America and South America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, PLACE allows for the effect A vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1991 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the South China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Land and federal mineral ownership coverage for the Uinta Basin, Wasatch Plateau and surrounding areas, northeastern Utah

USGS Publications Warehouse

Biewick, L.H.; Green, G.A.

1999-01-01

This Arc/Info coverage contains land status and Federal and State mineral ownership for approximately 25,900 square miles in northeastern Utah. The polygon coverage (which is also provided here as a shapefile) contains three attributes of ownership information for each polygon. One attribute indicates whether the surface is State owned, privately owned, consists of Tribal and Indian lands, or, if Federally owned, which Federal agency manages the land surface. Another attribute indicates where the Utah School and Institutional Trust Lands Administration (SITLA) maintains full or partial subsurface mineral rights. The third attribute indicates which energy minerals, if any, are owned by the Federal govenment. This coverage is based on land management status and Federal and State mineral ownership data compiled by the U.S. Geological Survey (USGS), the former U.S. Bureau of Mines (USBM), and the Utah School and Institutional Trust Lands Administration at a scale of 1:100,000. This coverage was compiled primarily to serve the USGS National Oil and Gas Resource Assessment Project in the Uinta-Piceance Basin Province and the USGS National Coal Resource Assessment Project in the Colorado Plateau.

Influence of Land Cover Heterogeneity, Land-Use Change and Management on the Regional Carbon Cycle in the Upper Midwest USA as Evaluated by High-Density Observations and a Dynamic Ecosystem Model

NASA Astrophysics Data System (ADS)

Desai, A. R.; Bolstad, P. V.; Moorcroft, P. R.; Davis, K. J.

2005-12-01

The interplay between land use change, forest management and land cover variability complicates the ability to characterize regional scale (10-1000 km) exchange of carbon dioxide between the land surface and atmosphere in heterogeneous landscapes. An attempt was made to observe and model these factors and their influence on the regional carbon cycle across the upper Midwest USA. A high density of eddy-covariance carbon flux, micrometeorology, carbon dioxide mixing ratio, stand-scale biometry and canopy component flux observations have been occurring in this area as part of the Chequamegon Ecosystem-Atmosphere Study. Observations limited to sampling only dominant stands and coarse-resolution biogeochemical models limited to biome-scale parameterization neither accurately capture the variability of carbon fluxes measured by the network of eddy covariance towers nor match the regional-scale carbon flux inferred from very tall tower eddy covariance measurements and multi-site upscaling. Analysis of plot level biometric data, U.S. Forest Service Forest Inventory Analysis data and high-resolution land cover data around the tall tower revealed significant variations in vegetation type, stand age, canopy stocking and structure. Wetlands, clearcuts and recent natural disturbances occur in characteristic small non-uniformly distributed patches that aggregate to form more than 30% of the landscape. The Ecosystem Demography model, a dynamic ecosystem model that incorporates vegetation heterogeneity, canopy structure, stand age, disturbance, land use change and forest management, was parameterized with regional biometric data and meteorology, historical records of land management and high-resolution satellite land cover maps. The model will be used to examine the significance of past land use change, natural disturbance history and current forest management in explaining landscape structure and regional carbon fluxes observed in the region today.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2017-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-2018, https://www.eustaceproject.eu) we have developed an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. This includes developing new "Big Data" analysis methods as the data volumes involved are considerable. We will present recent progress along this road in the EUSTACE project, i.e.: • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Aeroacoustic Analysis of a Simplified Landing Gear

NASA Technical Reports Server (NTRS)

Lockard, David P.; Khorrami, Mehdi, R.; Li, Fei

2004-01-01

A hybrid approach is used to investigate the noise generated by a simplified landing gear without small scale parts such as hydraulic lines and fasteners. The Ffowcs Williams and Hawkings equation is used to predict the noise at far-field observer locations from flow data provided by an unsteady computational fluid dynamics calculation. A simulation with 13 million grid points has been completed, and comparisons are made between calculations with different turbulence models. Results indicate that the turbulence model has a profound effect on the levels and character of the unsteadiness. Flow data on solid surfaces and a set of permeable surfaces surrounding the gear have been collected. Noise predictions using the porous surfaces appear to be contaminated by errors caused by large wake fluctuations passing through the surfaces. However, comparisons between predictions using the solid surfaces with the near-field CFD solution are in good agreement giving confidence in the far-field results.

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.

Measurements and Modeling of Turbulent Fluxes during Persistent Cold Air Pool Events in Salt Lake Valley, Utah

NASA Astrophysics Data System (ADS)

Ivey, C. E.; Sun, X.; Holmes, H.

2017-12-01

Land surface processes are important in meteorology and climate research since they control the partitioning of surface energy and water exchange at the earth's surface. The surface layer is coupled to the planetary boundary layer (PBL) by surface fluxes, which serve as sinks or sources of energy, moisture, momentum, and atmospheric pollutants. Quantifying the surface heat and momentum fluxes at the land-atmosphere interface, especially for different surface land cover types, is important because they can further influence the atmospheric dynamics, vertical mixing, and transport processes that impact local, regional, and global climate. A cold air pool (CAP) forms when a topographic depression (i.e., valley) fills with cold air, where the air in the stagnant layer is colder than the air aloft. Insufficient surface heating, which is not able to sufficiently erode the temperature inversion that forms during the nighttime stable boundary layer, can lead to the formation of persistent CAPs during wintertime. These persistent CAPs can last for days, or even weeks, and are associated with increased air pollution concentrations. Thus, realistic simulations of the land-atmosphere exchange are meaningful to achieve improved predictions of the accumulation, transport, and dispersion of air pollution concentrations. The focus of this presentation is on observations and modeling results using turbulence data collected in Salt Lake Valley, Utah during the 2010-2011 wintertime Persistent Cold Air Pool Study (PCAPS). Turbulent fluxes and the surface energy balance over seven land use types are quantified. The urban site has an energy balance ratio (EBR) larger than one (1.276). Negative Bowen ratio (-0.070) is found at the cropland site. In addition to turbulence observations, half-hourly WRF simulated net radiation, latent heat, sensible heat, ground heat fluxes during one persistent CAP event are evaluated using the PCAPS observations. The results show that sensible and latent heat fluxes during the CAP event are overestimated. The sensitivity of WRF results to large-scale forcing datasets, PBL schemes and land surface models (LSMs) are also investigated. The optimal WRF configuration for simulating surface turbulent fluxes and atmospheric mixing during CAP events is determined.

HAPEX-Sahel: A large-scale study of land-atmosphere interactions in the semi-arid tropics

NASA Technical Reports Server (NTRS)

Gutorbe, J-P.; Lebel, T.; Tinga, A.; Bessemoulin, P.; Brouwer, J.; Dolman, A.J.; Engman, E. T.; Gash, J. H. C.; Hoepffner, M.; Kabat, P.

1994-01-01

The Hydrologic Atmospheric Pilot EXperiment in the Sahel (HAPEX-Sahel) was carried out in Niger, West Africa, during 1991-1992, with an intensive observation period (IOP) in August-October 1992. It aims at improving the parameteriztion of land surface atmospheric interactions at the Global Circulation Model (GCM) gridbox scale. The experiment combines remote sensing and ground based measurements with hydrological and meteorological modeling to develop aggregation techniques for use in large scale estimates of the hydrological and meteorological behavior of large areas in the Sahel. The experimental strategy consisted of a period of intensive measurements during the transition period of the rainy to the dry season, backed up by a series of long term measurements in a 1 by 1 deg square in Niger. Three 'supersites' were instrumented with a variety of hydrological and (micro) meteorological equipment to provide detailed information on the surface energy exchange at the local scale. Boundary layer measurements and aircraft measurements were used to provide information at scales of 100-500 sq km. All relevant remote sensing images were obtained for this period. This program of measurements is now being analyzed and an extensive modelling program is under way to aggregate the information at all scales up to the GCM grid box scale. The experimental strategy and some preliminary results of the IOP are described.

Consequences of land use and land cover change

USGS Publications Warehouse

Slonecker, E. Terrence; Barnes, Christopher; Karstensen, Krista; Milheim, Lesley E.; Roig-Silva, Coral M.

2013-01-01

The U.S. Geological Survey (USGS) Climate and Land Use Change Mission Area is one of seven USGS mission areas that focuses on making substantial scientific "...contributions to understanding how Earth systems interact, respond to, and cause global change". Using satellite and other remotely sensed data, USGS scientists monitor patterns of land cover change over space and time at regional, national, and global scales. These data are analyzed to understand the causes and consequences of changing land cover, such as economic impacts, effects on water quality and availability, the spread of invasive species, habitats and biodiversity, carbon fluctuations, and climate variability. USGS scientists are among the leaders in the study of land cover, which is a term that generally refers to the vegetation and artificial structures that cover the land surface. Examples of land cover include forests, grasslands, wetlands, water, crops, and buildings. Land use involves human activities that take place on the land. For example, "grass" is a land cover, whereas pasture and recreational parks are land uses that produce a cover of grass.

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.

Initialization of soil-water content in regional-scale atmospheric prediction models

NASA Technical Reports Server (NTRS)

Smith, Christopher B.; Lakhtakia, Mercedes; Capehart, William J.; Carlson, Toby N.

1994-01-01

The purpose of this study is to demonstrate the feasibility of determining the soil-water content fields required as initial conditions for land surface components within atmospheric prediction models. This is done using a model of the hydrologic balance and conventional meteorological observations, land cover, and soils information. A discussion is presented of the subgrid-scale effects, the integration time, and the choice of vegetation type on the soil-water content patterns. Finally, comparisons are made between two The Pennsylvania State University/National Center for Atmospheric Research mesoscale model simulations, one using climatological fields and the other one using the soil-moisture fields produced by this new method.

Land surface modeling in convection permitting simulations

NASA Astrophysics Data System (ADS)

van Heerwaarden, Chiel; Benedict, Imme

2017-04-01

The next generation of weather and climate models permits convection, albeit at a grid spacing that is not sufficient to resolve all details of the clouds. Whereas much attention is being devoted to the correct simulation of convective clouds and associated precipitation, the role of the land surface has received far less interest. In our view, convective permitting simulations pose a set of problems that need to be solved before accurate weather and climate prediction is possible. The heart of the problem lies at the direct runoff and at the nonlinearity of the surface stress as a function of soil moisture. In coarse resolution simulations, where convection is not permitted, precipitation that reaches the land surface is uniformly distributed over the grid cell. Subsequently, a fraction of this precipitation is intercepted by vegetation or leaves the grid cell via direct runoff, whereas the remainder infiltrates into the soil. As soon as we move to convection permitting simulations, this precipitation falls often locally in large amounts. If the same land-surface model is used as in simulations with parameterized convection, this leads to an increase in direct runoff. Furthermore, spatially non-uniform infiltration leads to a very different surface stress, when scaled up to the course resolution of simulations without convection. Based on large-eddy simulation of realistic convection events at a large domain, this study presents a quantification of the errors made at the land surface in convection permitting simulation. It compares the magnitude of the errors to those made in the convection itself due to the coarse resolution of the simulation. We find that, convection permitting simulations have less evaporation than simulations with parameterized convection, resulting in a non-realistic drying of the atmosphere. We present solutions to resolve this problem.

Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)

NASA Astrophysics Data System (ADS)

Turner, Andrew; Bhat, Gs; Evans, Jonathan; Marsham, John; Martin, Gill; Parker, Douglas; Taylor, Chris; Bhattacharya, Bimal; Madan, Ranju; Mitra, Ashis; Mrudula, Gm; Muddu, Sekhar; Pattnaik, Sandeep; Rajagopal, En; Tripathi, Sachida

2015-04-01

The monsoon supplies the majority of water in South Asia, making understanding and predicting its rainfall vital for the growing population and economy. However, modelling and forecasting the monsoon from days to the season ahead is limited by large model errors that develop quickly, with significant inter-model differences pointing to errors in physical parametrizations such as convection, the boundary layer and land surface. These errors persist into climate projections and many of these errors persist even when increasing resolution. At the same time, a lack of detailed observations is preventing a more thorough understanding of monsoon circulation and its interaction with the land surface: a process governed by the boundary layer and convective cloud dynamics. The INCOMPASS project will support and develop modelling capability in Indo-UK monsoon research, including test development of a new Met Office Unified Model 100m-resolution domain over India. The first UK detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the surface, boundary layer structure and atmospheric profiles to go with detailed information on the timing of monsoon rainfall. Observations will be focused on transects in the northern plains of India (covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones) and across the Western Ghats and rain shadow in southern India (including transitions from land to ocean and across orography). A pilot observational campaign is planned for summer 2015, with the main field campaign to take place during spring/summer 2016. This project will advance our ability to forecast the monsoon, through a programme of measurements and modelling that aims to capture the key surface-atmosphere feedback processes in models. The observational analysis will allow a unique and unprecedented characterization of monsoon processes that will feed directly into model development at the UK Met Office and Indian NCMRWF, through model evaluation at a range of scales and leading to model improvement by working directly with parametrization developers. The project will institute a new long-term series of measurements of land surface fluxes, a particularly unconstrained observation for India, through eddy covariance flux towers. Combined with detailed land surface modelling using the Joint UK Land Environment Simulator (JULES) model, this will allow testing of land surface initialization in monsoon forecasts and improved land-atmosphere coupling.

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.

Analysis of Local Slopes at the InSight Landing Site on Mars

NASA Astrophysics Data System (ADS)

Fergason, R. L.; Kirk, R. L.; Cushing, G.; Galuszka, D. M.; Golombek, M. P.; Hare, T. M.; Howington-Kraus, E.; Kipp, D. M.; Redding, B. L.

2017-10-01

To evaluate the topography of the surface within the InSight candidate landing ellipses, we generated Digital Terrain Models (DTMs) at lander scales and those appropriate for entry, descent, and landing simulations, along with orthoimages of both images in each stereopair, and adirectional slope images. These products were used to assess the distribution of slopes for each candidate ellipse and terrain type in the landing site region, paying particular attention to how these slopes impact InSight landing and engineering safety, and results are reported here. Overall, this region has extremely low slopes at 1-meter baseline scales and meets the safety constraints of the InSight lander. The majority of the landing ellipse has a mean slope at 1-meter baselines of 3.2°. In addition, a mosaic of HRSC, CTX, and HiRISE DTMs within the final landing ellipse (ellipse 9) was generated to support entry, descent, and landing simulations and evaluations. Several methods were tested to generate this mosaic and the NASA Ames Stereo Pipeline program dem_mosaic produced the best results. For the HRSC-CTX-HiRISE DTM mosaic, more than 99 % of the mosaic has slopes less than 15°, and the introduction of artificially high slopes along image seams was minimized.

Analysis of local slopes at the InSight landing site on Mars

USGS Publications Warehouse

Fergason, Robin L.; Kirk, Randolph L.; Cushing, Glen; Galuszka, Donna M.; Golombek, Matthew P.; Hare, Trent M.; Howington-Kraus, Elpitha; Kipp, Devin M; Redding, Bonnie L.

2017-01-01

To evaluate the topography of the surface within the InSight candidate landing ellipses, we generated Digital Terrain Models (DTMs) at lander scales and those appropriate for entry, descent, and landing simulations, along with orthoimages of both images in each stereopair, and adirectional slope images. These products were used to assess the distribution of slopes for each candidate ellipse and terrain type in the landing site region, paying particular attention to how these slopes impact InSight landing and engineering safety, and results are reported here. Overall, this region has extremely low slopes at 1-meter baseline scales and meets the safety constraints of the InSight lander. The majority of the landing ellipse has a mean slope at 1-meter baselines of 3.2°. In addition, a mosaic of HRSC, CTX, and HiRISE DTMs within the final landing ellipse (ellipse 9) was generated to support entry, descent, and landing simulations and evaluations. Several methods were tested to generate this mosaic and the NASA Ames Stereo Pipeline program dem_mosaic produced the best results. For the HRSC-CTX-HiRISE DTM mosaic, more than 99 % of the mosaic has slopes less than 15°, and the introduction of artificially high slopes along image seams was minimized.

Estimation of land surface evapotranspiration with A satellite remote sensing procedure

USGS Publications Warehouse

Irmak, A.; Ratcliffe, I.; Ranade, P.; Hubbard, K.G.; Singh, Ramesh K.; Kamble, B.; Kjaersgaard, J.

2011-01-01

There are various methods available for estimating magnitude and trends of evapotranspiration. Bowen ratio energy balance system and eddy correlation techniques offer powerful alternatives for measuring land surface evapotranspiration. In spite of the elegance, high accuracy, and theoretical attractions of these techniques for measuring evapotranspiration, their practical use over large areas can be limited due to the number of sites needed and the related expense. Application of evapotranspiration mapping from satellite measurements can overcome the limitations. The objective of this study was to utilize the METRICTM (Mapping Evapotranspiration at High Resolution using Internalized Calibration) model in Great Plains environmental settings to understand water use in managed ecosystems on a regional scale. We investigated spatiotemporal distribution of a fraction of reference evapotranspiration (ETrF) using eight Landsat 5 images during the 2005 and 2006 growing season for path 29, row 32. The ETrF maps generated by METRICTM allowed us to follow the magnitude and trend in ETrF for major land-use classes during the growing season. The ETrF was lower early in the growing season for agricultural crops and gradually increased as the normalized difference vegetation index of crops increased, thus presenting more surface area over which water could transpire toward the midseason. Comparison of predictions with Bowen ratio energy balance system measurements at Clay Center, NE, showed that METRICTM performed well at the field scale for predicting evapotranspiration from a cornfield. If calibrated properly, the model could be a viable tool to estimate water use in managed ecosystems in subhumid climates at a large scale.

AVIRIS Land-Surface Mapping in Support of the Boreal Ecosystem-Atmosphere Study (BOREAS)

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Gamon, John; Keightley, Keir; Prentiss, Dylan; Reith, Ernest; Green, Robert

2001-01-01

A key scientific objective of the original Boreal Ecosystem-Atmospheric Study (BOREAS) field campaign (1993-1996) was to obtain the baseline data required for modeling and predicting fluxes of energy, mass, and trace gases in the boreal forest biome. These data sets are necessary to determine the sensitivity of the boreal forest biome to potential climatic changes and potential biophysical feedbacks on climate. A considerable volume of remotely-sensed and supporting field data were acquired by numerous researchers to meet this objective. By design, remote sensing and modeling were considered critical components for scaling efforts, extending point measurements from flux towers and field sites over larger spatial and longer temporal scales. A major focus of the BOREAS follow-on program is concerned with integrating the diverse remotely sensed and ground-based data sets to address specific questions such as carbon dynamics at local to regional scales. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has the potential of contributing to BOREAS through: (1) accurate retrieved apparent surface reflectance; (2) improved landcover classification; and (3) direct assessment of biochemical/biophysical information such as canopy liquid water and chlorophyll concentration through pigment fits. In this paper, we present initial products for major flux tower sites including: (1) surface reflectance of dominant cover types; (2) a land-cover classification developed using spectral mixture analysis (SMA) and Multiple Endmember Spectral Mixture Analysis (MESMA); and (3) liquid water maps. Our goal is to compare these land-cover maps to existing maps and to incorporate AVIRIS image products into models of photosynthetic flux.

Vertical Landing Aerodynamics of Reusable Rocket Vehicle

NASA Astrophysics Data System (ADS)

Nonaka, Satoshi; Nishida, Hiroyuki; Kato, Hiroyuki; Ogawa, Hiroyuki; Inatani, Yoshifumi

The aerodynamic characteristics of a vertical landing rocket are affected by its engine plume in the landing phase. The influences of interaction of the engine plume with the freestream around the vehicle on the aerodynamic characteristics are studied experimentally aiming to realize safe landing of the vertical landing rocket. The aerodynamic forces and surface pressure distributions are measured using a scaled model of a reusable rocket vehicle in low-speed wind tunnels. The flow field around the vehicle model is visualized using the particle image velocimetry (PIV) method. Results show that the aerodynamic characteristics, such as the drag force and pitching moment, are strongly affected by the change in the base pressure distributions and reattachment of a separation flow around the vehicle.

Mechanics of aeolian processes: Soil erosion and dust production

NASA Technical Reports Server (NTRS)

Mehrabadi, M. M.

1989-01-01

Aeolian (wind) processes occur as a result of atmosphere/land-surface system interactions. A thorough understanding of these processes and their physical/mechanical characterization on a global scale is essential to monitoring global change and, hence, is imperative to the fundamental goal of the Earth observing system (Eos) program. Soil erosion and dust production by wind are of consequence mainly in arid and semi arid regions which cover 36 percent of the Earth's land surface. Some recent models of dust production due to wind erosion of agricultural soils and the mechanics of wind erosion in deserts are reviewed and the difficulties of modeling the aeolian transport are discussed.

Vegetation Interaction Enhances Interdecadal Climate Variability in the Sahel

NASA Technical Reports Server (NTRS)

Zeng, Ning; Neelin, J. David; Lau, William K.-M.

1999-01-01

The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature (SST) variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 80s.

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

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China.

PubMed

Wang, Zhuoran; Zhao, Gengxing; Gao, Mingxiu; Chang, Chunyan

2017-02-01

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0-15, 15-30, 30-45 and 45-60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.

A Thermal Imaging Instrument with Uncooled Detectors

NASA Astrophysics Data System (ADS)

Joseph, A. T.; Barrentine, E. M.; Brown, A. D.

2017-12-01

In this work, we perform an instrument concept study for sustainable thermal imaging over land with uncooled detectors. The National Research Council's Committee on Implementation of a Sustained Land Imaging Program has identified the inclusion of a thermal imager as critical for both current and future land imaging missions. Such an imaging instrument operating in two bands located at approximately 11 and 12 microns (for example, in Landsat 8, and also Landsat 9 when launched) will provide essential information for furthering our hydrologic understanding at scales of human influence, and produce field-scale moisture information through accurate retrievals of evapotranspiration (ET). Landsat 9 is slated to recycle the TIRS-2 instrument launched with Landsat 8 that uses cooled quantum well infrared photodetectors (QWIPs), hence requiring expensive and massive cryocooler technology to achieve its required spectral and spatial accuracies. Our goal is to conceptualize and develop a thermal imaging instrument which leverages recent and imminent technology advances in uncooled detectors. Such detector technology will offer the benefit of greatly reduced instrument cost, mass, and power at the expense of some acceptable loss in detector sensitivity. It would also allow a thermal imaging instrument to be fielded on board a low-cost platform, e.g., a CubeSat. Sustained and enhanced land imaging is crucial for providing high-quality science data on change in land use, forest health, crop status, environment, and climate. Accurate satellite mapping of ET at the agricultural field scale (the finest spatial scale of the environmental processes of interest) requires high-quality thermal data to produce the corresponding accurate land surface temperature (LST) retrievals used to drive an ET model. Such an imaging instrument would provide important information on the following: 1) the relationship between land-use and land/water management practices and water use dynamics; 2) the interconnections between anthropogenic water management and changes in hydrologic budget at scales of human influence; and 3) complimentary field-scale moisture values for interpreting coarser resolution datasets. There is a clear need for continuing innovation in thermal remote sensing detector technology.

COMPARISON OF HYDROLOGIC RESPONSES AT DIFFERENT WATERSHED SCALES

EPA Science Inventory

Land surface hydrology controls runoff production and the associated transport of sediments, and a wide variety of anthropogenic organic chemicals, and nutrients from upland landscape areas and hillslopes to streams and other water bodies. Based on interactions between landscape ...

Changes in Land Surface Water Dynamics since the 1990s and Relation to Population Pressure

NASA Technical Reports Server (NTRS)

Prigent, C.; Papa, F.; Aires, F.; Jimenez, C.; Rossow, W. B.; Matthews, E.

2012-01-01

We developed a remote sensing approach based on multi-satellite observations, which provides an unprecedented estimate of monthly distribution and area of land-surface open water over the whole globe. Results for 1993 to 2007 exhibit a large seasonal and inter-annual variability of the inundation extent with an overall decline in global average maximum inundated area of 6% during the fifteen-year period, primarily in tropical and subtropical South America and South Asia. The largest declines of open water are found where large increases in population have occurred over the last two decades, suggesting a global scale effect of human activities on continental surface freshwater: denser population can impact local hydrology by reducing freshwater extent, by draining marshes and wetlands, and by increasing water withdrawals. Citation: Prigent, C., F. Papa, F. Aires, C. Jimenez, W. B. Rossow, and E. Matthews (2012), Changes in land surface water dynamics since the 1990s and relation to population pressure, in section 4, insisting on the potential applications of the wetland dataset.

Cities as selective land predators? A lesson on urban growth, deregulated planning and sprawl containment.

PubMed

Colantoni, Andrea; Grigoriadis, Efstathios; Sateriano, Adele; Venanzoni, Giuseppe; Salvati, Luca

2016-03-01

The present study investigates changes in the use of land caused by the expansion of an informal city in the Mediterranean region (Athens, Greece) and it proposes a simplified methodology to assess selective land take at the scale of municipalities. The amount of land take over twenty years (1987-2007) for cropland, sparsely vegetated areas and natural land was compared with the surface area of the respective class at the beginning of the study period (1987). Indicators of selective land take by class were correlated with socioeconomic indicators at the scale of municipalities to verify the influence of the local context and the impact of urban planning on land take processes. Evidence indicates that urban expansion into fringe land consumes primarily cropland and sparse vegetation in the case of the Athens' metropolitan region. Cropland and sparse vegetation were consumed proportionally more than the respective availability in 16 municipalities out of 60. Agricultural land take was positively correlated with population density and growth rate, rate of participation to the job market and road density. Sparse vegetation land take was observed in municipalities with predominance of high density settlements. As a result of second-home expansion in coastal municipalities, natural land was converted to urban use in proportion to the availability in the landscape. Urban planning seems to have a limited impact on selective land take. Copyright © 2015 Elsevier B.V. All rights reserved.

Impact of fire on global land carbon, water, and energy budgets and climate during the 20th century through changing ecosystems

NASA Astrophysics Data System (ADS)

Li, F.; Lawrence, D. M.; Bond-Lamberty, B. P.; Levis, S.

2016-12-01

Fire is an integral Earth system process and the primary form of terrestrial ecosystem disturbance on a global scale. Here we provide the first quantitative assessment and understanding on fire's impact on global land carbon, water, and energy budgets and climate through changing ecosystems. This is done by quantifying the difference between 20th century fire-on and fire-off simulations using the Community Earth System Model (CESM1.2). Results show that fire decreases the net carbon gain of global terrestrial ecosystems by 1.0 Pg C/yr averaged across the 20th century, as a result of biomass and peat burning (1.9 Pg C/yr) partly offset by changing gross primary productivity, respiration, and land-use carbon loss (-0.9 Pg C/yr). In addition, fire's effect on global carbon budget intensifies with time. Fire significantly reduces land evapotranspiration (ET) by 600 km3/yr and increases runoff, but has limited impact on precipitation. The impact on ET and runoff is most clearly seen in the tropical savannas, African rainforest, and some boreal and Southern Asian forests mainly due to fire-induced reduction in the vegetation canopy. It also weakens both the significant upward trend in global land ET prior to the 1950s and the downward trend from 1950 to 1985 by 35%. Fire-induced changes in land ecosystems affects global energy budgets by significantly reducing latent heating and surface net radiation. Fire changes surface radiative budget dominantly by raising surface upward longwave radiation and net longwave radiation. It also increases the global land average surface air temperature (Tas) by 0.04°C, and significantly increases wind speed and decreases surface relative humidity. The fire-induced change in wind speed, Tas, and relative humidity implies a positive feedback loop between fire and climate. Moreover, fire-induced changes in land ecosystems contribute 20% of strong global land warming during 1910-1940, which provides a new mechanism for the early 20th century global land warming. The results emphasize the importance of fire disturbance in the Earth's carbon, water, and energy cycles and climate by changing terrestrial ecosystems.

Global discrimination of land cover types from metrics derived from AVHRR pathfinder data

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

DeFries, R.; Hansen, M.; Townshend, J.

1995-12-01

Global data sets of land cover are a significant requirement for global biogeochemical and climate models. Remotely sensed satellite data is an increasingly attractive source for deriving these data sets due to the resulting internal consistency, reproducibility, and coverage in locations where ground knowledge is sparse. Seasonal changes in the greenness of vegetation, described in remotely sensed data as changes in the normalized difference vegetation index (NDVI) throughout the year, have been the basis for discriminating between cover types in previous attempts to derive land cover from AVHRR data at global and continental scales. This study examines the use ofmore » metrics derived from the NDVI temporal profile, as well as metrics derived from observations in red, infrared, and thermal bands, to improve discrimination between 12 cover types on a global scale. According to separability measures calculated from Bhattacharya distances, average separabilities improved by using 12 of the 16 metrics tested (1.97) compared to separabilities using 12 monthly NDVI values alone (1.88). Overall, the most robust metrics for discriminating between cover types were: mean NDVI, maximum NDVI, NDVI amplitude, AVHRR Band 2 (near-infrared reflectance) and Band 1 (red reflectance) corresponding to the time of maximum NDVI, and maximum land surface temperature. Deciduous and evergreen vegetation can be distinguished by mean NDVI, maximum NDVI, NDVI amplitude, and maximum land surface temperature. Needleleaf and broadleaf vegetation can be distinguished by either mean NDVI and NDVI amplitude or maximum NDVI and NDVI amplitude.« less

Towards a high resolution, integrated hydrology model of North America: Diagnosis of feedbacks between groundwater and land energy fluxes at continental scales.

NASA Astrophysics Data System (ADS)

Maxwell, Reed; Condon, Laura

2016-04-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Model results suggest that partitioning of plant transpiration to bare soil evaporation is a function of water table depth and later groundwater flow. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

Spatial and temporal connections in groundwater contribution to evaporation

NASA Astrophysics Data System (ADS)

Lam, A.; Karssenberg, D.; van den Hurk, B. J. J. M.; Bierkens, M. F. P.

2011-08-01

In climate models, lateral terrestrial water fluxes are usually neglected. We estimated the contribution of vertical and lateral groundwater fluxes to the land surface water budget at a subcontinental scale, by modeling convergence of groundwater and surfacewater fluxes. We present a hydrological model of the entire Danube Basin at 5 km resolution, and use it to show the importance of groundwater for the surface climate. Results show that the contribution of groundwater to evaporation is significant, and can locally be higher than 30 % in summer. We demonstrate through the same model that this contribution also has important temporal characteristics. A wet episode can influence groundwater contribution to summer evaporation for several years afterwards. This indicates that modeling groundwater flow has the potential to augment the multi-year memory of climate models. We also show that the groundwater contribution to evaporation is local by presenting the groundwater travel times and the magnitude of groundwater convergence. Throughout the Danube Basin the lateral fluxes of groundwater are negligible when modeling at this scale and resolution. This suggests that groundwater can be adequately added in land surface models by including a lower closed groundwater reservoir of sufficient size with two-way interaction with surface water and the overlying soil layers.

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Quattrochi, Dale A.

2000-01-01

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Landsat Evapotranspiration for Historical Field-scale Water Use (1984-2015) in the Upper Rio Grande River Basin

NASA Astrophysics Data System (ADS)

Senay, G. B.; Schauer, M.; Singh, R. K.; Friedrichs, M.

2017-12-01

Field-scale water use maps derived from evapotranspiration (ET) can characterize water use patterns and the impacts of water management decisions. This project generated historical (1984-2015) Landsat-based ET maps for the entire Upper Rio Grande basin which makes this one of the largest regions in the United States with remotely sensed historical ET at Landsat resolution. More than 10,000 Landsat images spanning 32 years were processed using the Operational Simplified Surface Energy Balance (SSEBop) model which integrates weather data and remotely sensed images to estimate monthly and annual ET. Time-series analysis focused on three water-intensive study areas within the basin: the San Luis Valley in Colorado, irrigated fields along the Rio Grande River near Albuquerque, NM, and irrigated fields near Las Cruces, NM. Preliminary analysis suggests land use changes result in declining water use in irrigated areas of the basin which corresponds with increases in land surface temperatures. Time-series analysis of water use patterns at multiple temporal and spatial scales demonstrates the impact of water management decisions on the availability of water in the basin. Comparisons with cropland data from the USDA (NASS CDL) demonstrate how water use for particular crop types changes over time in response to land use changes and shifts in water management. This study illustrates a useful application of "Big Data" earth observation science for quantifying impacts of climate and land use changes on water availability within the United States as well as applications in planning water resource allocation, managing water rights, and sustaining agricultural production in the Upper Rio Grande basin.

The impact of land use on microbial surface water pollution.

PubMed

Schreiber, Christiane; Rechenburg, Andrea; Rind, Esther; Kistemann, Thomas

2015-03-01

Our knowledge relating to water contamination from point and diffuse sources has increased in recent years and there have been many studies undertaken focusing on effluent from sewage plants or combined sewer overflows. However, there is still only a limited amount of microbial data on non-point sources leading to diffuse pollution of surface waters. In this study, the concentrations of several indicator micro-organisms and pathogens in the upper reaches of a river system were examined over a period of 16 months. In addition to bacteria, diffuse pollution caused by Giardia lamblia and Cryptosporidium spp. was analysed. A single land use type predestined to cause high concentrations of all microbial parameters could not be identified. The influence of different land use types varies between microbial species. The microbial concentration in river water cannot be explained by stable non-point effluent concentrations from different land use types. There is variation in the ranking of the potential of different land use types resulting in surface water contamination with regard to minimum, median and maximum effects. These differences between median and maximum impact indicate that small-scale events like spreading manure substantially influence the general contamination potential of a land use type and may cause increasing micro-organism concentrations in the river water by mobilisation during the next rainfall event. Copyright © 2014 Elsevier GmbH. All rights reserved.

Regional Climate Modeling and Remote Sensing to Characterize Impacts of Civil War Driven Land Use Change on Regional Hydrology and Climate

NASA Astrophysics Data System (ADS)

Maksimowicz, M.; Masarik, M. T.; Brandt, J.; Flores, A. N.

2016-12-01

Land use/land cover (LULC) change directly impacts the partitioning of surface mass and energy fluxes. Regional-scale weather and climate are potentially altered by LULC if the resultant changes in partitioning of surface energy fluxes are extensive enough. Dynamics of land use, particularly those related to the social dimensions of the Earth System, are often simplified or not represented in regional land-atmosphere models. This study explores the role of LULC change on a regional hydroclimate system, focusing on potential hydroclimate changes arising from an extended civil conflict in Mozambique. Civil war from 1977-1992 in Mozambique led to land use change at a regional scale as a result of the collapse of large herbivore populations due to poaching. Since the war ended, farming has increased, poaching was curtailed, and animal populations were reintroduced. In this study LULC in a region encompassing Gorongosa is classified at three instances between 1977 to 2015 using Landsat imagery. We use these derived LULC datasets to inform lower boundary conditions in the Weather Research and Forecasting (WRF) model. To quantify potential hydrometeorological changes arising from conflict-driven land use change, we performed a factorial-like experiment by mixing input LULC maps and atmospheric forcing data from before, during, and after the civil war. Analysis of the Landsat data shows measurable land cover change from 1977-present as tree cover encroached into grasslands. Initial tests show corresponding sensitivities to different LULC schemes within the WRF model. Preliminary results suggest that the war did indeed impact regional hydroclimate in a significant way via its direct and indirect impacts on land-atmosphere interactions. Results of this study suggest that LULC change arising from regional conflicts are a potentially understudied, yet important human process to capture in both regional reanalyses and climate change projections.

Responses of surface ozone air quality to anthropogenic nitrogen deposition in the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Zhao, Yuanhong; Zhang, Lin; Tai, Amos P. K.; Chen, Youfan; Pan, Yuepeng

2017-08-01

Human activities have substantially increased atmospheric deposition of reactive nitrogen to the Earth's surface, inducing unintentional effects on ecosystems with complex environmental and climate consequences. One consequence remaining unexplored is how surface air quality might respond to the enhanced nitrogen deposition through surface-atmosphere exchange. Here we combine a chemical transport model (GEOS-Chem) and a global land model (Community Land Model, CLM) to address this issue with a focus on ozone pollution in the Northern Hemisphere. We consider three processes that are important for surface ozone and can be perturbed by the addition of atmospheric deposited nitrogen - namely, emissions of biogenic volatile organic compounds (VOCs), ozone dry deposition, and soil nitrogen oxide (NOx) emissions. We find that present-day anthropogenic nitrogen deposition (65 Tg N a-1 to the land), through enhancing plant growth (represented as increases in vegetation leaf area index, LAI, in the model), could increase surface ozone from increased biogenic VOC emissions (e.g., a 6.6 Tg increase in isoprene emission), but it could also decrease ozone due to higher ozone dry deposition velocities (up to 0.02-0.04 cm s-1 increases). Meanwhile, deposited anthropogenic nitrogen to soil enhances soil NOx emissions. The overall effect on summer mean surface ozone concentrations shows general increases over the globe (up to 1.5-2.3 ppbv over the western US and South Asia), except for some regions with high anthropogenic NOx emissions (0.5-1.0 ppbv decreases over the eastern US, western Europe, and North China). We compare the surface ozone changes with those driven by the past 20-year climate and historical land use changes. We find that the impacts from anthropogenic nitrogen deposition can be comparable to the climate- and land-use-driven surface ozone changes at regional scales and partly offset the surface ozone reductions due to land use changes reported in previous studies. Our study emphasizes the complexity of biosphere-atmosphere interactions, which can have important implications for future air quality prediction.

LOLA Project Artists

NASA Image and Video Library

1965-08-10

Artists used paintbrushes and airbrushes to recreate the lunar surface on each of the four models comprising the LOLA simulator. Project LOLA or Lunar Orbit and Landing Approach was a simulator built at Langley to study problems related to landing on the lunar surface. It was a complex project that cost nearly 2 million dollars. James Hansen wrote: This simulator was designed to provide a pilot with a detailed visual encounter with the lunar surface the machine consisted primarily of a cockpit, a closed-circuit TV system, and four large murals or scale models representing portions of the lunar surface as seen from various altitudes. The pilot in the cockpit moved along a track past these murals which would accustom him to the visual cues for controlling a spacecraft in the vicinity of the moon. Unfortunately, such a simulation--although great fun and quite aesthetic--was not helpful because flight in lunar orbit posed no special problems other than the rendezvous with the LEM, which the device did not simulate. Not long after the end of Apollo, the expensive machine was dismantled. (p. 379) Ellis J. White described the simulator as follows: Model 1 is a 20-foot-diameter sphere mounted on a rotating base and is scaled 1 in. 9 miles. Models 2,3, and 4 are approximately 15x40 feet scaled sections of model 1. Model 4 is a scaled-up section of the Crater Alphonsus and the scale is 1 in. 200 feet. All models are in full relief except the sphere. -- Published in James R. Hansen, Spaceflight Revolution: NASA Langley Research Center From Sputnik to Apollo, (Washington: NASA, 1995), p. 379 Ellis J. White, Discussion of Three Typical Langley Research Center Simulation Programs, Paper presented at the Eastern Simulation Council (EAI s Princeton Computation Center), Princeton, NJ, October 20, 1966.

LOLA Project

NASA Image and Video Library

1964-10-28

Artists used paintbrushes and airbrushes to recreate the lunar surface on each of the four models comprising the LOLA simulator. Project LOLA or Lunar Orbit and Landing Approach was a simulator built at Langley to study problems related to landing on the lunar surface. It was a complex project that cost nearly $2 million dollars. James Hansen wrote: "This simulator was designed to provide a pilot with a detailed visual encounter with the lunar surface; the machine consisted primarily of a cockpit, a closed-circuit TV system, and four large murals or scale models representing portions of the lunar surface as seen from various altitudes. The pilot in the cockpit moved along a track past these murals which would accustom him to the visual cues for controlling a spacecraft in the vicinity of the moon. Unfortunately, such a simulation--although great fun and quite aesthetic--was not helpful because flight in lunar orbit posed no special problems other than the rendezvous with the LEM, which the device did not simulate. Not long after the end of Apollo, the expensive machine was dismantled." (p. 379) Ellis J. White further described LOLA in his paper "Discussion of Three Typical Langley Research Center Simulation Programs," "Model 1 is a 20-foot-diameter sphere mounted on a rotating base and is scaled 1 in. = 9 miles. Models 2,3, and 4 are approximately 15x40 feet scaled sections of model 1. Model 4 is a scaled-up section of the Crater Alphonsus and the scale is 1 in. = 200 feet. All models are in full relief except the sphere." -- Published in James R. Hansen, Spaceflight Revolution, NASA SP-4308, p. 379; Ellis J. White, "Discussion of Three Typical Langley Research Center Simulation Programs," Paper presented at the Eastern Simulation Council (EAI's Princeton Computation Center), Princeton, NJ, October 20, 1966.

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhuosen; King, Michael D.

2012-01-01

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhousen; King, Michael D.

2011-01-01

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Propulsion engineering study for small-scale Mars missions

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

Whitehead, J.

1995-09-12

Rocket propulsion options for small-scale Mars missions are presented and compared, particularly for the terminal landing maneuver and for sample return. Mars landing has a low propulsive {Delta}v requirement on a {approximately}1-minute time scale, but at a high acceleration. High thrust/weight liquid rocket technologies, or advanced pulse-capable solids, developed during the past decade for missile defense, are therefore more appropriate for small Mars landers than are conventional space propulsion technologies. The advanced liquid systems are characterize by compact lightweight thrusters having high chamber pressures and short lifetimes. Blowdown or regulated pressure-fed operation can satisfy the Mars landing requirement, but hardwaremore » mass can be reduced by using pumps. Aggressive terminal landing propulsion designs can enable post-landing hop maneuvers for some surface mobility. The Mars sample return mission requires a small high performance launcher having either solid motors or miniature pump-fed engines. Terminal propulsion for 100 kg Mars landers is within the realm of flight-proven thruster designs, but custom tankage is desirable. Landers on a 10 kg scale also are feasible, using technology that has been demonstrated but not previously flown in space. The number of sources and the selection of components are extremely limited on this smallest scale, so some customized hardware is required. A key characteristic of kilogram-scale propulsion is that gas jets are much lighter than liquid thrusters for reaction control. The mass and volume of tanks for inert gas can be eliminated by systems which generate gas as needed from a liquid or a solid, but these have virtually no space flight history. Mars return propulsion is a major engineering challenge; earth launch is the only previously-solved propulsion problem requiring similar or greater performance.« less

Comparison of Effects of a Proprioceptive Exercise Program in Water and on Land the Balance of Chronic Stroke Patients

PubMed Central

Han, Seul Ki; Kim, Myung Chul; An, Chang Sik

2013-01-01

[Purpose] The purpose of this study was to compare changes in balance ability of land exercise and underwater exercise on chronic stroke patients. [Subjects] A total of 60 patients received exercise for 40 minutes, three times a week, for 6 weeks. [Methods] Subjects from both groups performed general conventional treatment during the experimental period. In addition, all subjects engaged in extra treatment sessions. This extra treatment consisted of unstable surface exercise. The underwater exercise group used wonder boards in a pool (depth 1.1m, water temperature 33.5 °C, air temperature 27 °C) dedicated to underwater exercise, and the land exercise group used balance mats. [Result] The joint position sense, sway area, Berg Balance Scale showed significant improvements in both groups. However, the joint position sense test, sway area, and Berg Balance Scale showed there was more improvement in the underwater exercise group than in the land exercise group. [Conclusion] The results suggest that underwater exercise is more effective than land exercise at improving the joint position sense and balance of stroke patients. PMID:24259761

Comparison of effects of a proprioceptive exercise program in water and on land the balance of chronic stroke patients.

PubMed

Han, Seul Ki; Kim, Myung Chul; An, Chang Sik

2013-10-01

[Purpose] The purpose of this study was to compare changes in balance ability of land exercise and underwater exercise on chronic stroke patients. [Subjects] A total of 60 patients received exercise for 40 minutes, three times a week, for 6 weeks. [Methods] Subjects from both groups performed general conventional treatment during the experimental period. In addition, all subjects engaged in extra treatment sessions. This extra treatment consisted of unstable surface exercise. The underwater exercise group used wonder boards in a pool (depth 1.1m, water temperature 33.5 °C, air temperature 27 °C) dedicated to underwater exercise, and the land exercise group used balance mats. [Result] The joint position sense, sway area, Berg Balance Scale showed significant improvements in both groups. However, the joint position sense test, sway area, and Berg Balance Scale showed there was more improvement in the underwater exercise group than in the land exercise group. [Conclusion] The results suggest that underwater exercise is more effective than land exercise at improving the joint position sense and balance of stroke patients.

Soil Moisture Initialization Error and Subgrid Variability of Precipitation in Seasonal Streamflow Forecasting

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Walker, Gregory K.; Mahanama, Sarith P.; Reichle, Rolf H.

2013-01-01

Offline simulations over the conterminous United States (CONUS) with a land surface model are used to address two issues relevant to the forecasting of large-scale seasonal streamflow: (i) the extent to which errors in soil moisture initialization degrade streamflow forecasts, and (ii) the extent to which a realistic increase in the spatial resolution of forecasted precipitation would improve streamflow forecasts. The addition of error to a soil moisture initialization field is found to lead to a nearly proportional reduction in streamflow forecast skill. The linearity of the response allows the determination of a lower bound for the increase in streamflow forecast skill achievable through improved soil moisture estimation, e.g., through satellite-based soil moisture measurements. An increase in the resolution of precipitation is found to have an impact on large-scale streamflow forecasts only when evaporation variance is significant relative to the precipitation variance. This condition is met only in the western half of the CONUS domain. Taken together, the two studies demonstrate the utility of a continental-scale land surface modeling system as a tool for addressing the science of hydrological prediction.

Toward irrigation retrieval by combining multi-sensor remote sensing data into a land surface model over a semi-arid region

NASA Astrophysics Data System (ADS)

Malbéteau, Y.; Lopez, O.; Houborg, R.; McCabe, M.

2017-12-01

Agriculture places considerable pressure on water resources, with the relationship between water availability and food production being critical for sustaining population growth. Monitoring water resources is particularly important in arid and semi-arid regions, where irrigation can represent up to 80% of the consumptive uses of water. In this context, it is necessary to optimize on-farm irrigation management by adjusting irrigation to crop water requirements throughout the growing season. However, in situ point measurements are not routinely available over extended areas and may not be representative at the field scale. Remote sensing approaches present as a cost-effective technique for mapping and monitoring broad areas. By taking advantage of multi-sensor remote sensing methodologies, such as those provided by MODIS, Landsat, Sentinel and Cubesats, we propose a new method to estimate irrigation input at pivot-scale. Here we explore the development of crop-water use estimates via these remote sensing data and integrate them into a land surface modeling framework, using a farm in Saudi Arabia as a demonstration of what can be achieved at larger scales.

Comparing evapotranspiration from Eddy covariance measurements, water budgets, remote sensing, and land surface models over Canada a, b

DOE PAGES

Wang, Shusen; Pan, Ming; Mu, Qiaozhen; ...

2015-07-29

Here, this study compares six evapotranspiration ET products for Canada's landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of datamore » quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November-February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.« less

Comparing evapotranspiration from Eddy covariance measurements, water budgets, remote sensing, and land surface models over Canada a, b

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

Wang, Shusen; Pan, Ming; Mu, Qiaozhen

Here, this study compares six evapotranspiration ET products for Canada's landmass, namely, eddy covariance EC measurements; surface water budget ET; remote sensing ET from MODIS; and land surface model (LSM) ET from the Community Land Model (CLM), the Ecological Assimilation of Land and Climate Observations (EALCO) model, and the Variable Infiltration Capacity model (VIC). The ET climatology over the Canadian landmass is characterized and the advantages and limitations of the datasets are discussed. The EC measurements have limited spatial coverage, making it difficult for model validations at the national scale. Water budget ET has the largest uncertainty because of datamore » quality issues with precipitation in mountainous regions and in the north. MODIS ET shows relatively large uncertainty in cold seasons and sparsely vegetated regions. The LSM products cover the entire landmass and exhibit small differences in ET among them. Annual ET from the LSMs ranges from small negative values to over 600 mm across the landmass, with a countrywide average of 256 ± 15 mm. Seasonally, the countrywide average monthly ET varies from a low of about 3 mm in four winter months (November-February) to 67 ± 7 mm in July. The ET uncertainty is scale dependent. Larger regions tend to have smaller uncertainties because of the offset of positive and negative biases within the region. More observation networks and better quality controls are critical to improving ET estimates. Future techniques should also consider a hybrid approach that integrates strengths of the various ET products to help reduce uncertainties in ET estimation.« less

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.

Hindcasting 2000 years of Pacific sea and land surface temperature changes

NASA Astrophysics Data System (ADS)

Friedel, M. J.

2010-12-01

Studies of climate variability often rely on surface temperature change anomalies. Here regional Pacific sea and land surface temperature data were extended from a century to millennial scale using a type of unsupervised artificial neural network. In this approach, the imputation of annual climate fields was done based on the nonlinear and self-organized relations among modern (1897-2003) sea and land temperature and paleo-proxy (0-2000) land-based Palmer Drought Severity Index data vectors. Stochastic crossvalidation (using median values from 30 Monte Carlo trials) of the model revealed that predictions of temperature change over the regions of 00N30N, 30N60N, 60N-90N, and 60S-60N latitude were globally unbiased and highly correlated (Spearman Rho > 0.94) with the modern observations. The prediction uncertainty was characterized as nonlinear with minor (<5%) local bias attributed to unaccounted for measurement uncertainty. Quantile modeling of the reconstructed temperature change data revealed interruptions in the long-term climate record by short-term changes that coincided with the so-called Medieval Warm Period (~900 to ~1250) and Little Ice Age (~1400 to ~1850). These interruptions were present at all latitudes but the structure shifted toward lower magnitudes as the region moved toward the equator. In all cases, the maximum temperature change was slightly greater than during the Medieval Warm Period. These findings demonstrated that the El Niño Southern Oscillation operated over a continuum of temporal and spatial scales. These findings have broad economic, political, and social implications with respect to developing water resource policies.

SWOT: The Surface Water and Ocean Topography Mission. Wide- Swath Altimetric Elevation on Earth

NASA Technical Reports Server (NTRS)

Fu, Lee-Lueng (Editor); Alsdorf, Douglas (Editor); Morrow, Rosemary; Rodriguez, Ernesto; Mognard, Nelly

2012-01-01

The elevation of the surface of the ocean and freshwater bodies on land holds key information on many important processes of the Earth System. The elevation of the ocean surface, called ocean surface topography, has been measured by conventional nadirlooking radar altimeter for the past two decades. The data collected have been used for the study of large-scale circulation and sea level change. However, the spatial resolution of the observations has limited the study to scales larger than about 200 km, leaving the smaller scales containing substantial kinetic energy of ocean circulation that is responsible for the flux of heat, dissolved gas and nutrients between the upper and the deep ocean. This flux is important to the understanding of the ocean's role in regulatingfuture climate change.The elevation of the water bodies on land is a key parameter required for the computation of storage and discharge of freshwater in rivers, lakes, and wetlands. Globally, the spatial and temporal variability of water storage and discharge is poorly known due to the lack of well-sampled observations. In situ networks measuring river flows are declining worldwide due to economic and political reasons. Conventional altimeter observations suffers from the complexity of multiple peaks caused by the reflections from water, vegetation canopy and rough topography, resulting in much less valid data over land than over the ocean. Another major limitation is the large inter track distance preventing good coverage of rivers and other water bodies.This document provides descriptions of a new measurement technique using radar interferometry to obtain wide-swath measurement of water elevation at high resolution over both the ocean and land. Making this type of measurement, which addresses the shortcomings of conventional altimetry in both oceanographic and hydrologic applications, is the objective of a mission concept called Surface Water and Ocean Topography (SWOT), which was recommended by the National Research Council's first decadal survey of NASA's Earth science program. This document provides wide-ranging examples of research opportunities in oceanography and land hydrology that would be enabled by the new type of measurement. Additional applications in many other branches of Earth System science ranging from ocean bathymetry to sea ice dynamics are also discussed. Many of the technical issues in making the measurement are discussed as well. Also presented is a preliminary design of the SWOT Mission concept, which is being jointly developed by NASA and CNES, with contributions from the Canadian Space Agency.

Sub-grid scale precipitation in ALCMs: re-assessing the land surface sensitivity using a single column model

NASA Astrophysics Data System (ADS)

Pitman, Andrew J.; Yang, Zong-Liang; Henderson-Sellers, Ann

1993-10-01

The sensitivity of a land surface scheme to the distribution of precipitation within a general circulation model's grid element is investigated. Earlier experiments which showed considerable sensitivity of the runoff and evaporation simulation to the distribution of precipitation are repeated in the light of other results which show no sensitivity of evaporation to the distribution of precipitation. Results show that while the earlier results over-estimated the sensitivity of the surface hydrology to the precipitation distribution, the general conclusion that the system is sensitive is supported. It is found that changing the distribution of precipitation from falling over 100% of the grid square to falling over 10% leads to a reduction in evaporation from 1578 mm y-1 to 1195 mm y -1 while runoff increases from 278 mm y-1 to 602 mm y-1. The sensitivity is explained in terms of evaporation being dominated by available energy when precipitation falls over nearly the entire grid square, but by moisture availability (mainly intercepted water) when it falls over little of the grid square. These results also indicate that earlier work using stand-alone forcing to drive land surface schemes ‘off-line’, and to investigate the sensitivity of land surface codes to various parameters, leads to results which are non-repeatable in single column simulations.

Noah-MP-Crop: Enhancing cropland representation in the community land surface modeling system

NASA Astrophysics Data System (ADS)

Liu, X.; Chen, F.; Barlage, M. J.; Zhou, G.; Niyogi, D.

2015-12-01

Croplands are important in land-atmosphere interactions and in modifying local and regional weather and climate. Despite their importance, croplands are poorly represented in the current version of the coupled Weather Research and Forecasting (WRF)/ Noah land-surface modeling system, resulting in significant surface temperature and humidity biases across agriculture- dominated regions of the United States. This study aims to improve the WRF weather forecasting and regional climate simulations during the crop growing season by enhancing the representation of cropland in the Noah-MP land model. We introduced dynamic crop growth parameterization into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at both the field and regional scales with multiple crop biomass datasets, surface fluxes and soil moisture/temperature observations. We also integrated a detailed cropland cover map into WRF, enabling the model to simulate corn and soybean field across the U.S. Great Plains. Results show marked improvement in the Noah-MP-Crop performance in simulating leaf area index (LAI), crop biomass, soil temperature, and surface fluxes. Enhanced cropland representation is not only crucial for improving weather forecasting but can also help assess potential impacts of weather variability on regional hydrometeorology and crop yields. In addition to its applications to WRF, Noah-MP-Crop can be applied in high-spatial-resolution regional crop yield modeling and drought assessments

Effects of Land Surface Heterogeneity on Simulated Boundary-Layer Structures from the LES to the Mesoscale

NASA Astrophysics Data System (ADS)

Poll, Stefan; Shrestha, Prabhakar; Simmer, Clemens

2017-04-01

Land heterogeneity influences the atmospheric boundary layer (ABL) structure including organized (secondary) circulations which feed back on land-atmosphere exchange fluxes. Especially the latter effects cannot be incorporated explicitly in regional and climate models due to their coarse computational spatial grids, but must be parameterized. Current parameterizations lead, however, to uncertainties in modeled surface fluxes and boundary layer evolution, which feed back to cloud initiation and precipitation. This study analyzes the impact of different horizontal grid resolutions on the simulated boundary layer structures in terms of stability, height and induced secondary circulations. The ICON-LES (Icosahedral Nonhydrostatic in LES mode) developed by the MPI-M and the German weather service (DWD) and conducted within the framework of HD(CP)2 is used. ICON is dynamically downscaled through multiple scales of 20 km, 7 km, 2.8 km, 625 m, 312 m, and 156 m grid spacing for several days over Germany and partial neighboring countries for different synoptic conditions. We examined the entropy spectrum of the land surface heterogeneity at these grid resolutions for several locations close to measurement sites, such as Lindenberg, Jülich, Cabauw and Melpitz, and studied its influence on the surface fluxes and the evolution of the boundary layer profiles.

Understanding the Impact of Ground Water Treatment and Evapotranspiration Parameterizations in the NCEP Climate Forecast System (CFS) on Warm Season Predictions

NASA Astrophysics Data System (ADS)

Ek, M. B.; Yang, R.

2016-12-01

Skillful short-term weather forecasts, which rely heavily on quality atmospheric initial conditions, have a fundamental limit of about two weeks owing to the chaotic nature of the atmosphere. Useful forecasts at sub-seasonal to seasonal time scales, on the other hand, require well-simulated large-scale atmospheric response to slowly varying lower boundary forcings from both the ocean and land surface. The critical importance of ocean has been recognized, where the ocean indices have been used in a variety of climate applications. In contrast, the impact of land surface anomalies, especially soil moisture and associated evaporation, has been proven notably difficult to demonstrate. The Noah Land Surface Model (LSM) is the land component of NCEP CFS version 2 (CFSv2) used for seasonal predictions. The Noah LSM originates from the Oregon State University (OSU) LSM. The evaporation control in the Noah LSM is based on the Penman-Monteith equation, which takes into account the solar radiation, relative humidity, air temperature, and soil moisture effects. The Noah LSM is configured with four soil layers with a fixed depth of 2 meters and free drainage at the bottom soil layer. This treatment assumes that the soil water table depth is well within the specified range, and also potentially misrepresents the soil moisture memory effects at seasonal time scales. To overcome the limitation, an unconfined aquifer is attached to the bottom of the soil to allow the water table to move freely up and down. In addition, in conjunction with the water table, an alternative Ball-Berry photosynthesis-based evaporation parameterization is examined to evaluate the impact from using a different evaporation control methodology. Focusing on the 2011 and 2012 intense summer droughts in the central US, seasonal ensemble forecast experiments with early May initial conditions are carried out for the two years using an enhanced version of CFSv2, where the atmospheric component of the CFSv2 is coupled to the Noah Multiple-Parameterization (Noah-MP) land model. The Noah-MP has different options for ground water and evaporation control parameterizations. The differences will be presented and results will be discussed.

Geomorphic degradations on the surface of venus: an analysis of venera 9 and venera 10 data.

PubMed

Florensky, C P; Ronca, L B; Basilevsky, A T

1977-05-20

On the basis of the physical and chemical measurements made on the surface of Venus and transmitted back to Earth by the Soviet automatic landers Venera 9 and Venera 10, a geomorphically inactive environment should be expected. An analysis of the television photographs reveals, however, that at least two processes of degradation occur. One operates on a scale of decimeters to meters and is responsible for the fracturing of a layered source rock and the subsequent downslope movement of the fragments. Mass-wasting, perhaps activated by venusian quakes or by unknown geological processes, is likely to be the agent. Another geomorphic degradation process occurs on the scale of a centimeter or less and is responsible for the rounding of edges and the pitting of rock surfaces. The agents of this process are not known, but atmospheric action, perhaps in connection with volcanic episodes, may be the cause. From a geomorphic point of view, the landscape of the Venera 9 landing site can be considered young and that of the Venera 10 landing site, mature.

Remote sensing of a coupled carbon-water-energy-radiation balances from the Globe to plot scales

NASA Astrophysics Data System (ADS)

Ryu, Y.; Jiang, C.; Huang, Y.; Kim, J.; Hwang, Y.; Kimm, H.; Kim, S.

2016-12-01

Advancements in near-surface and satellite remote sensing technologies have enabled us to monitor the global terrestrial ecosystems at multiple spatial and temporal scales. An emergent challenge is how to formulate a coupled water, carbon, energy, radiation, and nitrogen cycles from remote sensing. Here, we report Breathing Earth System Simulator (BESS), which coupled radiation (shortwave, longwave, PAR, diffuse PAR), carbon (gross primary productivity, ecosystem respiration, net ecosystem exchange), water (evaporation), and energy (latent and sensible heat) balances across the global land at 1 km resolution, 8 daily between 2000 and 2015 using multiple satellite remote sensing. The performance of BESS was tested against field observations (FLUXNET, BSRN) and other independent products (MPI-BGC, MODIS, GLASS). We found that the coupled model, BESS showed on par with, or better performance than the other products which computed land surface fluxes individually. Lastly, we show one plot-level study conducted in a paddy rice to demonstrate how to couple radiation, carbon, water, nitrogen balances with a series of near-surface spectral sensors.

Crustal evolution inferred from Apollo magnetic measurements

NASA Technical Reports Server (NTRS)

Dyal, P.; Daily, W. D.; Vanyan, L. L.

1978-01-01

Magnetic field and solar wind plasma density measurements were analyzed to determine the scale size characteristics of remanent fields at the Apollo 12, 15, and 16 landing sites. Theoretical model calculations of the field-plasma interaction, involving diffusion of the remanent field into the solar plasma, were compared to the data. The information provided by all these experiments shows that remanent fields over most of the lunar surface are characterized by spatial variations as small as a few kilometers. Large regions (50 to 100 km) of the lunar crust were probably uniformly magnetized during early crustal evolution. Bombardment and subsequent gardening of the upper layers of these magnetized regions left randomly oriented, smaller scale (5 to 10 km) magnetic sources close to the surface. The larger scale size fields of magnitude approximately 0.1 gammas are measured by the orbiting subsatellite experiments and the small scale sized remanent fields of magnitude approximately 100 gammas are measured by the surface experiments.

Large-scale shrimp farming in coastal wetlands of Venezuela, South America: Causes and consequences of land-use conflicts

NASA Astrophysics Data System (ADS)

Sebastiani, Mirady; González, Sara Elena; Castillo, María Mercedes; Alvizu, Pablo; Oliveira, María Albertina; Pérez, Jorge; Quilici, Antonio; Rada, Martín; Yáber, María Carolina; Lentino, Miguel

1994-09-01

In Venezuela, large-scale shrimp farming began in the 1980s. By 1987, the Ministry of Environment and Natural Resources (MARNR) had received 14 proposals for approval. A developer illegally started the construction of ponds at the Píritu Lagoon in the State of Anzoátegui before the authorization process was completed. This action triggered a land-use conflict. This study identifies the causes for public protest and determines the consequences of this conflict for land-use management. The results show that public protest was based on the impacts of the partial construction of ponds. These impacts were related to direct removal of wetlands, interruption of natural patterns of surface flows, and alteration of feeding grounds of some bird species with migratory status. Consequences were identified in relation to the role that nongovernmental organizations (NGOs) play in land-use conflicts and the actions that MARNR could take in the future to prevent and solve similar situations.

Effect of canopy and topography induced wakes on land-atmosphere fluxes of momentum and scalars

NASA Astrophysics Data System (ADS)

Markfort, C. D.; Zhang, W.; Porté-Agel, F.; Stefan, H. G.

2012-04-01

Wakes shed from natural and anthropogenic landscape features affect land-atmosphere fluxes of momentum and scalars, including water vapor and trace gases (e.g. CO2). Canopies and bluff bodies, such as forests, buildings and topography, cause boundary layer flow separation, and lead to a break down of standard Monin-Obukhov similarity relationships in the atmospheric boundary layer (ABL). Wakes generated by these land surface features persist for significant distances (>100 typical length scales) and affect a large fraction of the Earth's terrestrial surface. This effect is currently not accounted for in land-atmosphere models, and little is known about how heterogeneity of wake-generating features affect land surface fluxes. Additionally flux measurements, made in wake-affected regions, do not satisfy the homogeneous flow requirements for the standard eddy correlation (EC) method. This phenomenon, often referred to as wind sheltering, has been shown to affect momentum and kinetic energy fluxes at the lake-atmosphere interface (Markfort et al. 2010). This presentation will highlight results from controlled wind tunnel experiments of neutral and thermally stratified boundary layers, using particle image velocimetry (PIV) and custom x-wire/cold-wire anemometry, to understand how the physical structure of upstream bluff bodies and porous canopies as well as how thermal stability affect the flow separation zone, boundary layer recovery and surface fluxes. We have found that there is a nonlinear relationship between canopy length/porosity and flow separation downwind of a canopy to clearing transition. Results will provide the basis for new parameterizations to account for wake effects on land-atmosphere fluxes and corrections for the EC measurements over open fields, lakes, and wetlands. Key words: Atmospheric boundary layer; Wakes; Stratification; Land-Atmosphere Parameterization; Canopy

Geographic analysis and monitoring at the United States Geological Survey

USGS Publications Warehouse

Findley, J.

2003-01-01

The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey assesses the Nation's land surface at a variety of spatial and temporal scales to understand the rates, causes, and consequences of natural and human-induced processes and their interactions that affect the landscape over time. The program plays an important role in developing National Map tools and application. The GAM is a science and synthesis program that not only assesses the rates of changes to the Earth's land surface, but also provides reports on the status and trends of the Nation's land resources on a periodic basis, produces a land-use and land- cover database for the periodically updated map and data set-the Geographic Face of the Nation, and conducts research leading to improved understanding and knowledge about geographic processes. Scientific investigations provide comprehensive information needed to understand the environmental, resource, and economic consequences of landscape change. These analyses responds to the needs of resource managers and offers the American public baseline information to help them understand the dynamic nature of our national landscape and to anticipate the opportunities and consequences of our actions.

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.

Elucidating Carbon Exchange at the Regional Scale Via Airborne Eddy Covariance Flux Measurements

NASA Astrophysics Data System (ADS)

Hannun, R. A.; Wolfe, G. M.; Kawa, S. R.; Newman, P. A.; Hanisco, T. F.; Diskin, G. S.; DiGangi, J. P.; Nowak, J. B.; Barrick, J. D. W.; Thornhill, K. L., II; Noormets, A.; Vargas, R.; Clark, K. L.; Kustas, W. P.

2017-12-01

Direct flux observations from aircraft provide a unique tool for probing greenhouse gas (GHG) sources and sinks on a regional scale. Airborne eddy covariance, which relies on high-frequency, simultaneous measurements of fluctuations in concentration and vertical wind speed, is a robust method for quantifying surface-atmosphere exchange. We have assembled and flown an instrument payload onboard the NASA C-23 Sherpa aircraft capable of measuring CO2, CH4, H2O, and heat fluxes. Flights for the Carbon Airborne Flux Experiment (CARAFE) took place during September 2016 and May 2017 based out of Wallops Flight Facility, VA. Flight tracks covered a variety of ecosystems and land-use types in the Mid-Atlantic, including forests, croplands, and wetlands. Carbon fluxes are derived using eddy covariance and wavelet analysis. Our results show a strong drawdown of CO2 and near-zero CH4 emissions from crops and dry-land forest, but seasonally strong CH4 flux from wetland forest. CARAFE flux data will also be compared with observations from several flux towers along the flight path to complement the airborne measurements. We will further assess the effects of land surface type and seasonal variability in carbon exchange. Regional-scale flux observations from CARAFE supply a useful constraint for improving top-down and bottom up estimates of carbon sources and sinks.