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At least 127 records · Page 7

Comparison of remote measurements of infrared surface temperatures and microwave soil moisture

Scatterometric measurements of active microwave soil water content and radiometric measurements of thermal IR surface temperatures were made simultaneously fron an aircraft flying 400 m over an agricultural region of France after harvesting. The surface temperatures were used to deterine soil moisture availability estimates according to the Carlson (1986) model. Surface temperature or soil moisture availability and microwave soil moisture were correlated. The standard error in the IR temperature and soil moisture availability due to influences other than soil moisture is found to be + or - 2 C. The standard deviation of the temperature/moisture availability is greater than this standard error. It is shown that correlations between soil water content and moisture availability improve with increasing spatial or temporal variance in the measure surface temperatures.

Perry, Eileen M.↗

Seasonal nitrous oxide flux from an intensively managed pasture in a humid subtropical ecosystem

Nitrous oxide (N2O) flux from vented chambers was measured over intensively and minimally managed bermuda grass hay meadows in a humid, subtropical ecosystem for several years during scheduled sampling protocol following harvest, fertilization and rainfall events while measuring diel N2O emissions once during each of 5 seasonal day growth cycles which divided each calendar year. Soil pools of nitrite NO2(-), nitrate NO3(-), and ammonia (NH3) were measured in soil samples taken at 2 and 10 cm depths during each emission collection to determine transformations of the nitrogen pools coupled with N2O emissions. The highest diel N2O emission occur midday in the Spring cycle, measuring 9.0 g N/ha/d only for several weeks, while emissions dropped to less than 1.0 g N/ha/day during hot, dry, and colder months. Intensively managed meadows (4 fertilizations and harvests per year plus pest management) induced higher seasonal N2O emissions than minimal treatment (1 fertilization and harvest) averaging 2.75 and 5.97 g N/ha/day. Nitrous oxide emission data as responses to soil parameters and environmental parameters were also measured where air temperature, soil moisture, and fertilization were the most powerful factors.

Brams, Eugene A.↗

Numerical Model Studies of the Martian Mesoscale Circulations

Studies concerning mesoscale topographical effects on Martian flows examined low-level jets in the near equatorial latitudes and the dynamical intensification of flow by steep terrain. Continuation of work from previous years included evaluating the dissipation of cold air mass outbreaks due to enhanced sensible heat flux, further sensitivity and scaling evaluations for generalization of the characteristics of Martian mesoscale circulation caused by horizontal sensible heat-flux gradients, and evaluations of the significance that non-uniform surface would have on enhancing the polar CO2 ice sublimation during the spring. The sensitivity of maximum and minimum atmospheric temperatures to changes in wind speed, surface albedo, and deep soil temperature was investigated.

Segal, M.↗

Sulfur Cycle

Among the general categories of tropospheric sulfur sources, anthropogenic sources have been quantified the most accurately. Research on fluxes of sulfur compounds from volcanic sources is now in progress. Natural sources of reduced sulfur compounds are highly variable in both space and time. Variables, such as soil temperature, hydrology (tidal and water table), and organic flux into the soil, all interact to determine microbial production and subsequent emissions of reduced sulfur compounds from anaerobic soils and sediments. Available information on sources of COS, CS2, DMS, and H2S to the troposphere in the following paragraphs are summarized; these are the major biogenic sulfur species with a clearly identified role in tropospheric chemistry. The oxidation of SO2 to H2SO4 can often have a significant impact on the acidity of precipitation. A schematic representation of some important transformations and sinks for selected sulfur species is illustrated.

Hariss, R.↗

Inversion of parameters for semiarid regions by a neural network

Microwave brightness temperatures obtained from a passive radiative transfer model are inverted through use of a neural network. The model is applicable to semiarid regions and produces dual-polarized brightness temperatures for 6.6-, 10.7-, and 37-GHz frequencies. A range of temperatures is generated by varying three geophysical parameters over acceptable ranges: soil moisture, vegetation moisture, and soil temperature. A multilayered perceptron (MLP) neural network is trained with a subset of the generated temperatures, and the remaining temperatures are inverted using a backpropagation method. Several synthetic terrains are devised and inverted by the network under local constraints. All the inversions show good agreement with the original geophysical parameters, falling within 5 percent of the actual value of the parameter range.

Zurk, Lisa M.↗

Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at ~3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

land surface modeling↗

A scheme for computing surface layer turbulent fluxes from mean flow surface observations

A physical model and computational scheme are developed for generating turbulent surface stress, sensible heat flux and humidity flux from mean velocity, temperature and humidity at some fixed height in the atmospheric surface layer, where conditions at this reference level are presumed known from observations or the evolving state of a numerical atmospheric circulation model. The method is based on coupling the Monin-Obukov surface layer similarity profiles which include buoyant stability effects on mean velocity, temperature and humidity to a force-restore formulation for the evolution of surface soil temperature to yield the local values of shear stress, heat flux and surface temperature. A self-contained formulation is presented including parameterizations for solar and infrared radiant fluxes at the surface. Additional parameters needed to implement the scheme are the thermal heat capacity of the soil per unit surface area, surface aerodynamic roughness, latitude, solar declination, surface albedo, surface emissivity and atmospheric transmissivity to solar radiation.

Hoffert, M. I.↗

Simultaneous field measurements of biogenic emissions of nitric oxide and nitrous oxide

Seasonal and diurnal emissions of NO and N2O from agricultural sites in Jamestown, Virginia and Boulder, Colorado are estimated in terms of soil temperature; percent moisture; and exchangeable nitrate, nitrite, and ammonium concentrations. The techniques and procedures used to analyze the soil parameters are described. The spatial and temporal variability of the NO and N2O emissions is studied. A correlation between NO fluxes in the Virginia sample and nitrate concentration, temperature, and percent moisture is detected, and NO fluxes for the Colorado site correspond with temperature and moisture. It is observed that the N2O emissions are only present when percent moisture approaches or exceeds the field capacity of the soil. The data suggest that NO is produced primarily by nitrification in aerobic soils, and N2O is formed by denitrification in anaerobic soils.

Anderson, Iris Cofman↗

Physiochemical, site, and bidirectional reflectance factor characteristics of uniformly moist soils

The author has identified the following significant results. The bidirectional reflectance factor (0.5 micron to 2.3 micron wavelength interval) and physiochemical properties of over 500 soils from 39 states, Brazil and Spain were measured. Site characteristics of soil temperature regime and moisture zone were used as selection criteria. Parent material and internal drainage were noted for each soil. At least five general types of soil reflectance curves were identified based primarily on the presence or absence of ferric iron absorption bands, organic matter content, and soil drainage characteristics. Reflectance in 10 bands across the spectrum was found to be negatively correlated with the natural log of organic matter content.

Stoner, E. R.↗

Role of Boreal Vegetation in Controlling Ecosystem Processes and Feedbacks to Climate

In the field, dark respiration rates are greatest in cores from more northerly locations. This is due in part to greater amounts of dwarf shrub biomass in the more northerly cores, but also to differences in soil organic matter quality. Laboratory incubations of these soils under common conditions show some evidence for greater pools of available carbon in soils from more northerly tundra sites, although the most northerly site does not fit this pattern for reasons which are unclear at this time. While field measurements of cores transplanted among different vegetation types at the same location (Toolik Lake) show relatively small differences in whole ecosystem carbon flux, laboratory incubation of these same soils shows that there are large differences in soil respiration rates under common conditions. This is presumably due to differences in organic matter quality. Microenvironmental site factors (temperature, soil moisture, degree of anaerobiosis, etc.) may be responsible for evening out these differences in the field. These site factors, which differ with slope, aspect, and drainage within a given location along the latitudinal gradient, appear to exert at least as strong a control over carbon fluxes as do macroclimatic factors among sites across the latitudinal gradient. While our field measurements indicate that, in the short term, warming will tend to increase ecosystem losses Of CO2 via respiration more than they will increase plant gross assimilation, the degree to which different topographically-defined plant communities will respond is likely to vary.

Chapin, F. S., III↗

Accelerating Net Terrestrial Carbon Uptake During the Warming Hiatus Due to Reduced Respiration

The recent warming hiatus presents an excellent opportunity to investigate climate sensitivity of carbon cycle processes. Here we combine satellite and atmospheric observations to show that the rate of net biome productivity (NBP) has significantly accelerated from - 0.007 +/- 0.065 PgC yr(exp -2) over the warming period (1982 to 1998) to 0.119 +/- 0.071 PgC yr(exp -2) over the warming hiatus (19982012). This acceleration in NBP is not due to increased primary productivity, but rather reduced respiration that is correlated (r = 0.58; P = 0.0007) and sensitive ( y = 4.05 to 9.40 PgC yr(exp -1) per C) to land temperatures. Global land models do not fully capture this apparent reduced respiration over the warming hiatus; however, an empirical model including soil temperature and moisture observations better captures the reduced respiration.

Ballantyne, Ashley↗

Variation in energy balance components from six sites in a native prairie for three years

Six automatic stations were used to evaluate the surface energy and radiation balances on a native prairie near Manhattan, Kansas, using the Bowen ratio technique for a total of 300 days. Data were taken during the periods from May 26 to October 16, 1987, May 10 to September 18, 1988, and July 21 to August 13, 1989. The station site locations were selected to represent burned and unburned treatments on ridges, valley bottoms, and slopes with various aspects. The measured variables were (1) air and wet bulb temperatures at two heights, (2) net radiation, (3) solar radiation (up and down), (4) total hemispherical radiation (up and down), (5) diffuse radiation, (6) soil heat flow and soil temperature, (7) wind speed, (8) wind direction, and (9) precipitation. Energy balance components at the sites were compared for the 3 years. The variation between sites and years was small, even though some sites were as much as 10 km apart and the years had different rainfall amounts. The average values for the four summer intensive field campaigns (IFCs) were as follows: albedo, 0.2; ratio of net radiation to solar radiation, 62 percent; evaporation equivalent, 4 mm/d; Bowen ratio, 0.32; evaporation fraction, 70 percent; and the ratio of evaporation to solar energy, 40 percent. These values were different for the fall IFC. The latent and sensible heat fluxes were more variable than the radiation terms reflecting soil moisture differences between IFCs.

Fritschen, Leo J.↗

Microwave radiometer measurements of soil moisture content

A unique set of radiometer measurements is presented, recorded during a 1000-h day and night monitoring of irrigated fields from fully saturated to completely dry. Radiometer measurements were recorded at 2.8-cm (X-band) and 21.4-cm (L-band) wavelengths for a range of incident angles from nadir to 50 deg. Soil moisture and soil temperature profile measurements were recorded to a depth of 15 cm. The test site was located in east-central Texas on a clay soil (Miller clay). Three bare-surface plots were used, each having a distinctly different surface roughness. Vegetated plots were also measured. The data quantify the sensitivity of microwave radiometer measurements to soil moisture variations, the effect of surface roughness on the measurement, and the influence of surface vegetation.

Newton, R. W.↗

L Band Brightness Temperature Observations Over a Corn Canopy During the Entire Growth Cycle

During a field campaign covering the 2002 corn growing season, a dual polarized tower mounted L-band (1.4 GHz) radiometer (LRAD) provided brightness temperature (T(sub B)) measurements at preset intervals, incidence and azimuth angles. These radiometer measurements were supported by an extensive characterization of land surface variables including soil moisture, soil temperature, vegetation biomass, and surface roughness. During the period from May 22, 2002 to August 30, 2002 a range of vegetation water content (W) of 0.0 to 4.3 kg/square m, ten days of radiometer and ground measurements were available. Using this data set, the effects of corn vegetation on surface emissions are investigated by means of a semi-empirical radiative transfer model. Additionally, the impact of roughness on the surface emission is quantified using T(sub B) measurements over bare soil conditions. Subsequently, the estimated roughness parameters, ground measurements and horizontally (H)-polarized T(sub B) are employed to invert the H-polarized transmissivity (gamma-h) for the monitored corn growing season.

Joseph, Alicia T.↗

Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

soil moisture↗

BOREAS TGB-1/TGB-3 Water Table and Peat Temperature Data over the NSA

The BOREAS TGB-1 and TGB-3 teams collected several data sets that contributed to understanding the measured trace gas fluxes over sites in the NSA. This data set contains continuous and manual measurements of water level and air and soil temperatures at the four subsites within the NSA Tower Fen site complex. The measurements were taken to understand the thermal and hydrological gradients associated with each plant community present in the fen. Measurements were taken from May to September 1994 and May to October 1996. The data are provided in tabular ASCII files.

Bubier, Jill L.↗

Estimating Surface Soil Moisture from SMAP Observations Using a Neural Network Technique

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m(exp. 3)m(exp. -3), 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m(exp. 3)m(exp. -3), 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Soil Moisture Remote Sensing↗

An Analytical Calibration Approach for the Polarimetric Airborne C Band Radiometer

Passive microwave remote sensing is sensitive to the quantity and distribution of water in soil and vegetation. During summer 2000, the Microwave Geophysics Group at the University of Michigan conducted the 7th Radiobrightness Energy Balance Experiment (REBEX-7) over a corn canopy in Michigan. Long time series of brightness temperatures, soil moisture and micrometeorology on the plot scale were taken. This paper addresses the calibration of the NASA GSFC polarimetric airborne C band microwave radiometer (ACMR) that participated in REBEX-7. Passive polarimeters are typically calibrated using an end-to-end approach based upon a standard artificial target or a well-known geophysical target. Analyzing the major internal functional subsystems offers a different perspective. The primary goal of this approach is to provide a transfer function that not only describes the system in its entirety but also accounts for the contributions of each subsystem toward the final modified Stokes parameters. This approach also serves as a realistic instrument simulator, a useful tool for future designs. The ACMR architecture can be partitioned into several functional subsystems. Each subsystem was extensively measured and the estimated parameters were imported into the overall system model. We will present the results of polarimetric antenna measurements, the instrument model as well as four Stokes observations from REBEX-7 using a first order inversion.

Pham, Hanh↗