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At least 127 records · Page 7

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

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.

Owe, Manfred↗

Investigation of Thermospheric and Ionospheric Changes during Ionospheric Storms with Satellite and Ground-Based Data and Modeling

The purpose of this proposed research is to improve our basic understanding of the causes of ionospheric storm behavior in the midlatitude F region ionosphere. This objective will be achieved by detailed comparisons between ground based measurements of the peak electron density (N(sub m)F(sub 2)), Atmosphere Explorer satellite measurements of ion and neutral composition, and output from the Field Line Interhemispheric Plasma (FLIP) model. The primary result will be a better understanding of changes in the neutral densities and ion chemistry during magnetic storms that will improve our capability to model the weather of the ionosphere which will be needed as a basis for ionospheric prediction. Specifically, this study seeks to answer the following questions: (1) To what extent are negative ionospheric storm phases caused by changes in the atomic to molecular ratio? (2) Are the changes in neutral density ratio due to increased N2, or decreased O, or both? (3) Are there other chemical processes (e.g., excited N2) that increase O+ loss rates during negative storms? (4) Do neutral density altitude distributions differed from hydrostatic equilibrium? (5) Why do near normal nighttime densities often follow daytime depletions of electron density; and (6) Can changes in h(sub m)F2 fully account for positive storm phases? To answer these questions, we plan to combine ground-based and space-based measurements with the aid of our ionospheric model which is ideally suited to this purpose. These proposed studies will lead to a better capability to predict long term ionospheric variability, leading to better predictions of ionospheric weather.

Richards, Philip G.↗

Small error dynamics and the predictability of atmospheric flows

In this paper, linear small-error theory is applied to the study of weather predictability. A simple baroclinic shear model and a barotropic channel model with a localized jet are used as examples. It is shown that increase in error on synoptic forecast time scales is controlled by rapidly growing perturbations that are not of normal mode form. Unpredictable regimes are not necessarily associated with larger exponential growth rates than are relatively more predictable regimes. Model problems illustrating baroclinic and barotropic dynamics suggest that asymptotic measures of divergence in phase space, while applicable in the limit of infinite time, may not be appropriate over time intervals addressed by present synoptic forecast.

Farrell, Brian F.↗

Ground-Based Lidar Measurements of Aerosols During ACE-2 Instrument Description, Results, and Comparisons with Other Ground-Based and Airborne Measurements

A micro-pulse lidar system (MPL) was used to measure the vertical and horizontal distribution or aerosols during the Aerosol Characterization Experiment 2 (ACE-2) in June and July of 1997. The MPL measurements were made at the Izana observatory (IZO), a weather station located on a mountain ridge (28 deg 18'N, 16 deg 30'W, 2367 m asl) near the center of the island of Tenerife, Canary Islands. The MPL was used to acquire aerosol backscatter, extinction, and optical depth profiles for normal background periods and periods influenced by Saharan dust from North Africa. System tests and calibration procedures are discussed, and in analysis of aerosol optical profiles acquired during ACE-2 is presented. MPL data taken during normal IZO conditions (no dust) showed that upslope aerosols appeared during the day and dissipated at night and that the layers were mostly confined to altitudes a few hundred meters above IZO. MPL data taken during a Saharan dust episode on 17 July showed that peak aerosol extinction values were an order of magnitude greater than molecular scattering over IZO. and that the dust layers extended to 5 km asl. The value of the dust backscatter-extinction ratio was determined to be 0.027 + 0.007 per sr. Comparisons of the MPL data with data from other co-located instruments showed good agreement during the dust episode.

Welton, Ellsworth J.↗

High-Resolution Mapping of Nitrogen Oxide Emissions in Large US Cities From TROPOMI Retrievals of Tropospheric Nitrogen Dioxide Columns

Satellite-derived spatiotemporal patterns of nitrogen oxide (NO x ) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NO x emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO 2 ) retrievals. The accuracy of the coupled method is validated through application to synthetic NO 2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = −0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R=0.88 ± 0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = −0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.

NOx emissions↗

Research on diabatic initialization

The objective of this research project is to contribute to improvement in the synoptic analyses in the tropics for numerical weather prediction and climate research. In addition to a prediction model, four dimensional data assimilation systems have two principal components. One is objective analysis and the other is initialization. Various methods of objective analysis are designed primarily to analyze the mass and rotational wind fields. Methods of initialization are developed to obtain the irrotational wind and its associated vertical velocity field which are balanced with the mass field and free from meteorological noise. There are essentially three approaches to the problem of initialization: quasi-geostrophic theory, bounded derivative method and nonlinear normal mode method. In the midlatitudes, these approaches generally produce satisfactory results even without diabatic effects for large-scale motions. In the tropics, the situation is quite different from that in the midlatitudes. Because of a small magnitude of the Coriolis parameter and a weak horizontal temperature gradient in the tropics, any method of initialization must incorporate diabatic effects. In fact, it can be said that understanding the problem of diabatic initialization is the key to improving the analysis and weather forecasting in the tropics.

Kasahara, Akira↗

The use of a vegetation index for assessment of the urban heat island effect

A vegetation index and radiative surface temperature were derived from NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) data for the Seattle, WA region from 28 June through 4 July 1991. The vegetation index and surface temperature values were computed for locations of weather observation stations within the region and compared to observed minimum air temperatures. These comparisons were used to evaluate the use of AVHRR data to assess the influence of the urban environment on observed minimum air temperatures (the urban heat island effect). AVHRR derived normalized difference vegetation index (NDVI) and radiant surface temperature data from a one week composite product were both related significantly to observed minimum temperatures, however, the vegetation index accounted for a greater amount of the spatial variation observed in mean minimum temperatures. The difference in the NDVI between urban and rural regions appears to be an indicator of the difference in surface properties (i.e., evaporation and heat storage capacity) between the two environments that are responsible for differences in urban and rural minimum temperatures.

Gallo, K. P.↗

Interannual Variations of Shallow Firn Temperature at Greenland Summit

Firn-temperature profiles are calculated in a thermal model using continuous surface temperatures derived from Automatic Weather Station (AWS) data and passive microwave data in the Greenland Summit region during the period 1987-1999. The results show that significant interannual variations of mean summer (June to August) and annual temperatures occur in the top 15 m, in addition to the normal seasonal cycle of firn temperature. At 5 m depth, the seasonal cycle is damped to 13% of the surface seasonal amplitude, but even at 15 m about 1% or 0.6 C of the seasonal cycle persists. Both summer and mean annual temperatures decrease from 1987 to 1992, followed by a general increasing trend. Interannual variability is 5 C at the surface, but only is only dampened to 3.2 C at 10 m depth and 0.7 C at 15 m depth. Dampening of the interannual variability with depth is slower than dampening of the seasonal cycle, because of the longer time constant of the interannual variation. The warmer spring and summer temperatures experienced in the top 5 m, due to both the seasonal cycle and interannual variations, affect the rate of firn densification, which is non-linearly dependent on temperature. During the 12 year period 1987-1999, the mean annual surface temperature is -29.2 C, and the mean annual 15 m temperature is -30. 1 C, which is more than 1 C warmer than a 15-m borehole temperature representing the period of about 1959 and warmer than the best-fit temperature history by Alley and Koci back to 1500 A.D..

Jun, Li↗

Ground-Based Lidar Measurements of Aerosols During ACE-2: Instrument Description, Results, and Comparisons with Other Ground-Based and Airborne Measurements

A micro-pulse lidar system (MPL) was used to measure the vertical and horizontal distribution of aerosols during the Aerosol Characterization Experiment 2 (ACE-2) in June and July of 1997. The MPL measurements were made at the Izana observatory (IZO), a weather station located on a mountain ridge (28 deg 18 min N, 16 deg 30 min W, 2367 m asl) near the center of the island of Tenerife, Canary Islands. The MPL was used to acquire aerosol backscatter, extinction, and optical depth profiles for normal background periods and periods influenced by Saharan dust from North Africa. System tests and calibration procedures are discussed, and an analysis of aerosol optical profiles acquired during ACE-2 is presented. MPL data taken during normal IZO conditions (no dust) showed that upslope aerosols appeared during the day and dissipated at night and that the layers were mostly confined to altitudes a few hundred meters above IZO. MPL data taken during a Saharan dust episode on 17 July showed that peak aerosol extinction values were an order of magnitude greater than molecular scattering over IZO, and that the dust layers extended to 5 km asl. The value of the dust backscatter-extinction ratio was determined to be 0.027 +/- 0.007 sr(exp -1). Comparisons of the MPL data with data from other collocated instruments showed good agreement during the dust episode.

Welton, Ellsworth J.↗

Weather analysis and interpretation procedures developed for the US/Canada wheat and barley exploratory experiment

Procedures and techniques for providing analyses of meteorological conditions at segments during the growing season were developed for the U.S./Canada Wheat and Barley Exploratory Experiment. The main product and analysis tool is the segment-level climagraph which depicts temporally meteorological variables for the current year compared with climatological normals. The variable values for the segment are estimates derived through objective analysis of values obtained at first-order station in the region. The procedures and products documented represent a baseline for future Foreign Commodity Production Forecasting experiments.

Trenchard, M. H.↗

No Launch Before Its Time

Aura is an Earth-observing satellite developed to help us study the quality of the air we breathe. It will look at the state of the ozone and the atmospheric composition in regards to the Earth's changing climate. I headed to California on July 5, 2004. The plan was that the satellite would launch on the tenth, but we had a few problems getting it off. This was the fifty-ninth launch of my career, and it was also a little different than most of my previous launches. Most of the time it's weather that postpones a launch; there aren't usually that many technical issues this late in the game. This time. however, we had several problems, equally split between the launch vehicle and the spacecraft. I remember a member of the crew asking me, 'Is this normal?' And in my experience, it wasn't.

Townsend, Bill↗

Some effects of adverse weather conditions on performance of airplane antiskid braking systems

The performance of current antiskid braking systems operating under adverse weather conditions was analyzed in an effort to both identify the causes of locked-wheel skids which sometimes occur when the runway is slippery and to find possible solutions to this operational problem. This analysis was made possible by the quantitative test data provided by recently completed landing research programs using fully instrumented flight test airplanes and was further supported by tests performed at the Langley aircraft landing loads and traction facility. The antiskid system logic for brake control and for both touchdown and locked-wheel protection is described and its response behavior in adverse weather is discussed in detail with the aid of available data. The analysis indicates that the operational performance of the antiskid logic circuits is highly dependent upon wheel spin-up acceleration and can be adversely affected by certain pilot braking inputs when accelerations are low. Normal antiskid performance is assured if the tire-to-runway traction is sufficient to provide high wheel spin-up accelerations or if the system is provided a continuous, accurate ground speed reference. The design of antiskid systems is complicated by the necessity for tradeoffs between tire braking and cornering capabilities, both of which are necessary to provide safe operations in the presence of cross winds, particularly under slippery runway conditions.

Horne, W. B.↗

Satellite-Based Characterization of Convection and Impacts from the Catastrophic 10 August 2020 Midwest U.S. Derecho

The catastrophic derecho that occurred on 10 August 2020 across the Midwest United States caused billions of dollars of damage to both urban and rural infrastructure as well as agricultural crops, most notably across the state of Iowa. This paper documents the complex evolution of the derecho through the use of low-Earth orbit passive-microwave imager and GOES-16satellite-derived products complemented by products derived from NEXRAD weather radar observations. Additional satellite sensors including optical imagers and synthetic aperture radar (SAR) were used to observe impacts to the power grid and agriculture in Iowa. SAR improved the identification and quantification of damaged corn and soybeans, as compared to true-color composites and Normalized Difference Vegetation Index (NDVI). A statistical approach to identify damaged corn and soybean crops from SAR was created with estimates of 1.97 million acres of damaged corn and 1.40 million acres of damaged soybeans in the state of Iowa. The damage estimates generated by this study were comparable to estimates produced by others after the derecho, including two commercial agricultural companies.

Derecho↗

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

Grass, David↗

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

Zhu, Jiang↗

Extensional tectonics during the igneous emplacement of the mafic-ultramafic rocks of the Barberton greenstone belt

The simatic rocks (Onverwacht Group) of the Barberton greenstone belt are part of the Jamestown ophiolite complex. This ophiolite, together with its thick sedimentary cover occupies a complex thrust belt. Field studies have identified two types of early faults which are entirely confined to the simatic rocks and are deformed by the later thrusts and associated folds. The first type of fault (F1a) is regional and always occurs in the simatic rocks along and parallel to the lower contacts of the ophiolite-related cherts (Middle Marker and equivalent layers). These fault zones have previously been referred to both as flaser-banded gneisses and as weathering horizons. In general the zones range between 1-30m in thickness. Displacements along these zones are difficult to estimate, but may be in the order of 1-100 km. The structures indicate that the faults formed close to horizontal, during extensional shear and were therefore low angle normal faults. F1a zones overlap in age with the formation of the ophiolite complex. The second type of faults (F1b) are vertical brittle-ductile shear zones, which crosscut the complex at variable angles and cannot always be traced from plutonic to overlying extrusive (pillowed) simatic rocks. F1b zones are also apparently of penecontemporaneous origin with the intrusive-extrusive igneous processs. F1b zones may either represent transform fault-type activity or represent root zones (steepened extensions) of F1a zones. Both fault types indicate extensive deformation in the rocks of the greenstone belt prior to compressional overthrust tectonics.

Dewit, M. J.↗

Predictions of Solar Cycle 24: How are We Doing?

Predictions of solar activity are an essential part of our Space Weather forecast capability. Users are requiring usable predictions of an upcoming solar cycle to be delivered several years before solar minimum. A set of predictions of the amplitude of Solar Cycle 24 accumulated in 2008 ranged from zero to unprecedented levels of solar activity. The predictions formed an almost normal distribution, centered on the average amplitude of all preceding solar cycles. The average of the current compilation of 105 predictions of the annual-average sunspot number is 106 +/- 31, slightly lower than earlier compilations but still with a wide distribution. Solar Cycle 24 is on track to have a below-average amplitude, peaking at an annual sunspot number of about 80. Our need for solar activity predictions and our desire for those predictions to be made ever earlier in the preceding solar cycle will be discussed. Solar Cycle 24 has been a below-average sunspot cycle. There were peaks in the daily and monthly averaged sunspot number in the Northern Hemisphere in 2011 and in the Southern Hemisphere in 2014. With the rapid increase in solar data and capability of numerical models of the solar convection zone we are developing the ability to forecast the level of the next sunspot cycle. But predictions based only on the statistics of the sunspot number are not adequate for predicting the next solar maximum. I will describe how we did in predicting the amplitude of Solar Cycle 24 and describe how solar polar field predictions could be made more accurate in the future.

Pesnell, William D.↗

Image-data-processing for earth resources - An overview

A total remote-sensing system comprises four distinct operations: data-acquisition, archiving, production, and dissemination of individual products, and extraction of the required information. The Landsat satellite system acquires data in several spectral bands, with a ground resolution of 80 meters (currently) or 30 meters (future). Radiometric and geometric corrections are normally applied, after which the data may be enhanced for photointerpretation or analyzed by computer. The accuracy of the analysis model for either is important. The extraction of information from remotely sensed data will generally be dependent on the use of it with other data such as maps or, perhaps, weather information. Methods are being developed to use the various data together in geographic data systems. The availability of remotely sensed data has encouraged the development of new models or analysis procedures for the use of this information.

Billingsley, F. C.↗