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The GASP atmospheric trace constituent data cover atmospheric ozone, carbon monoxide, condensation nuclei, clouds, and related meteorological and flight information obtained during October 28-31, 1977. Reported herein are flight routes and dates, instrumentation, data processing procedures, and data tape specifications.
During the 1977 ITCZ (Intertropical Convergence Zone) experiment in Panama two aircraft and numerous balloon-borne radiosonde instruments were equipped to measure pressure and temperature. The experiment was a coordinated effort to evaluate the meteorological conditions that prevailed from July 17 through 31, 1977. A critical analysis of the data collected on one of the aircraft (the Lear jet) operating at altitudes to 13,000 m for about 2 hr each day during most days of the experiment is presented. The discussion includes a comparison of the vertical profiles of potential temperature obtained from the Learjet with those obtained from balloons launched at Ft. Sherman. Time histories of pressure, temperature, and potential temperature, as observed from the Learjet are also presented.
Current techniques available for the in situ measurement of ambient trace gas species, particulate composition, and particulate size distribution are reviewed. The operational specifications of the various techniques are described. Most of the techniques described are those that have been used in airborne applications or show promise of being adaptable to airborne applications. Some of the instruments described are specialty items that are not commercially-available. In situ measurement techniques for several meteorological parameters important in the study of the distribution and transport of ambient air pollutants are discussed. Some remote measurement techniques for meteorological parameters are also discussed. State-of-the-art measurement capabilities are compared with a list of capabilities and specifications desired by NASA for ambient measurements in the global troposphere.
Data from meteorological stations show that surface air temperatures in the 1980s are the warmest in the history of instrumental records. The four warmest years on record are all in the 1980s, with the warmest years in the analysis being 1981 and 1987. The rate of warming between the mid-1960s and the present is higher than that which occurrred in the previous period of rapid warming between the 1880s and 1940.
One of the most important uses of acoustic propagation models lies in the area of detection and tracking of vehicles. Propagation models are used to compute transmission losses in performance prediction models and to analyze the results of past experiments. Vehicles can also provide the means for cost effective experiments to measure acoustic propagation conditions over significant ranges. In order to properly correlate the information provided by the experimental data and the propagation models, the following issues must be taken into consideration: the phenomenology of the vehicle noise sources must be understood and characterized; the vehicle's location or 'ground truth' must be accurately reproduced and synchronized with the acoustic data; and sufficient meteorological data must be collected to support the requirements of the propagation models. The experimental procedures and instrumentation needed to carry out propagation experiments are discussed. Illustrative results are presented for two cases. First, a helicopter was used to measure propagation losses at a range of 1 to 10 Km. Second, a heavy diesel-powered vehicle was used to measure propagation losses in the 300 to 2200 m range.
The GOES-I Image Navigation and Registration (INR) system will fly on the next generation of NOAA geostationary meteorological satellites. This system uses observations of stars and earth landmarks made by the Imager and Sounder Instruments themselves to determine the orbit, attitude, and misalignment state of the spacecraft and instruments. An extensive program of simulation and analysis has been conducted to assess the expected performance of the INR system. This paper discusses these activities and presents some computer simulation results showing expected system performance under a variety of conditions including station-keeping.
The Airborne Arctic Stratospheric Expedition had two primary objectives: to study the production and loss mechanisms of ozone in the north polar stratosphere and to study the effect on ozone distribution of the Arctic Polar Vortex and of the cold temperatures associated with the formation of Polar Stratospheric Clouds. Two specially instrumented NASA aircraft were flown over the Arctic region. Each aircraft flew to acquire data on the meteorological, chemical and cloud physical phenomena that occur in the polar stratosphere during winter. The chemical processes which occur in the polar stratosphere during winter were also observed and studied. The data acquired are being analyzed.
Following an ESA preliminary study on the possible areas of European participation in the future international exploration of Mars and a recent ESA in-depth scientific and technical assessment study, MARSNET was selected for further phase-A studies as a potential European contribution to such exploration. The MARSNET mission consists of a network of small stations to be landed on the surface of Mars. All surface stations will have identical design and payload, and will be located several thousand km apart from each other. The required operational lifetime on the surface of Mars for all landers is one Martian year (687 days) to carry out long-term meteorological and seismological measurements. The availability of a data relay orbiter at low altitude is assumed. The instruments are mounted on a platform under the semi-hard lander solar array. The main scientific goals of the mission during the atmospheric descent and on the surface are outlined.
Backscatter cross section measurements from the ERS-1 Active Microwave Instrument (AMI) scatterometer were reprocessed to vector winds using the Freilich-Dunbar model function and a meteorologically aided ambiguity removal scheme. This consistent data set was used to examine the wind field over the Southern Ocean from 20 to 60 deg South. The large number of ERS-1 measurements allows relatively accurate calculation of annual mean wind, stress, and curl fields as well as overall statistics of the winds at mid to high southern latitudes. The long duration of the data time series allows preliminary examination of low frequency (semi annual) wind variability.
Total ozone measurements with the Dobson No. 104 (D 104) have been performed at the Meteorological Observatory Hohenpeissenberg since 1967. A critical review of this time series and the comparison with other instruments like TOMS or Brewer spectrophotometer revealed some intervals with uncertainties. Especially in the early eighties a monthly mean bias of about minus 3 percent to TOMS-data with annual variations depending on the mean sun-height exists. An extreme amplitude of 5.6 percent occurs in 1980 with minus 0.76 percent (February) and minus 6.36 percent (July). Two different methods were applied to reprocess the Dobson data set. A comparison of the differently recalculated data showed, that the application of N-corrections by means of the standard-lamp tests starting from the reference values of the Arosa Intercomparison 1986 yields better results than the N-corrections based on a Langley-pilot of the Arosa Intercomparison 1978. The extreme amplitude of the year 1980 is now reduced to 3.02 percent. There is still a slight drift in the monthly and yearly mean differences between TOMS and revised Dobson data. It cannot be excluded, that the satellite data may be responsible for the trend.
Atmospheric aerosol backscatter, beta, variability gives a direct indication of aerosol loading. Since aerosol variability is governed by regional sources and sinks as well as affected by its transport due to meteorological conditions, it is important to characterize this loading at different locations and times. Lidars are sensitive instruments that can effectively provide high-resolution, large-scale sampling of the atmosphere remotely by measuring aerosol beta, thereby capturing detailed temporal and spatial variability of aerosol loading, Although vertical beta profiles are usually obtained by pulsed lidars, airborne-focused CW lidars, with high sensitivity and short time integration, can provide higher resolution sampling in the vertical, thereby revealing detailed structure of aerosol layers. During the 1995 NASA Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission, NASA MSFC airborne-focused CW CO2 Doppler lidars, operating at 9.1 and 10.6-micrometers wavelength, obtained high resolution in situ aerosol beta measurements to characterize aerosol variability. The observed variability in beta at 9.1-micrometers wavelength with altitude is presented as well as comparison with some pulsed lidar profiles.
In the Fall of 1997 the Atmospheric Radiation Measurement (ARM) program held an intensive observation period (IOP) to study atmospheric aerosols using in situ and remote sensing techniques at its Southern Great Plains (SGP) site near Lamont, Oklahoma. As part of this experiment five automated, tracking sunphotometers were present to measure total column aerosol optical depth over the three-week period. which included many clear days or parts of days that were clear. The World Meteorological Organization (WMO 1993) has recommended a comparison of tracking sunphotometers to assess the ability of different instruments to arrive at similar aerosol optical depths. It was further recommended that the comparison be staged at a clean mountain site. In fact, this comparison has not occurred, but the comparison that we describe in this paper is representative of what contemporary instruments may accomplish in an environment more typical of sites where aerosols measurements will be required. The measurements were made over the period 15 September to 5 October 1997. The aerosol loading varied from extremely clean to moderately turbid conditions. In the next section the instruments will be described along with a brief explanation of the calibration techniques. The third section contains the results compared graphically on moderately turbid and fairly clean days and in a table representing the whole period. The paper ends with a section of discussion and a summary of the results.
Accurate observations of surface ocean vector winds (OVW) with high spatial and temporal resolution are required for understanding and predicting tropical cyclones. As NASA's QuikSCAT and Navy's WindSat operate beyond their design life, many members of the weather and climate science communities recognize the importance of developing new observational technologies and strategies to meet the essential need for OVW information to improve hurricane intensity and location forecasts. The Hurricane Imaging Radiometer (HIRAD) is an innovative technology development which offers new and unique remotely sensed satellite observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR), which is the only proven remote sensing technique for observing tropical cyclone (TC) ocean surface wind speeds and rain rates. The proposed HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology. This sensor will operate over 4-7 GHz (C-band frequencies) where the required TC remote sensing physics has been validated by both SFMR and WindSat radiometers. The instrument is described in more detail in a paper by Jones et al. presented to the Tropical Meteorology Special Symposium at this AMS Annual Meeting. Simulated HIRAD passes through a simulation of hurricane Frances are being developed to demonstrate HIRAD estimation of surface wind speed over a wide swath in the presence of heavy rain. These are currently being used in "quick" OSSEs (Observing System Simulation Experiments) with H'Wind analyses as the discriminating tool. The H'Wind analysis, a product of the Hurricane Research Division of NOAA's Atlantic , Oceanographic and Meteorological Laboratory, brings together wind measurements from a variety of observation platforms into an objective analysis of the distribution of wind speeds in a tropical cyclone. This product is designed to improve understanding of the extent and strength of the wind field, and to improve the assessment of hurricane intensity. See http://www.aoml.noaa._ov/hrd/data sub/wind.html. Observations have been simulated from both aircraft altitudes and space. The simulated flight patterns for the aircraft platform cases have been designed to duplicate the timing and flight patterns used in routine NOAA and USAF hurricane surveillance flights, and the spaceborne case simulates a TRMM orbit and altitude.
This software enables easy comparison of ground- and space-based radar observations. The software was initially designed to compare ground radar reflectivity from operational, ground based Sand C-band meteorological radars with comparable measurements from the Tropical Rainfall Measuring Mission (TRMM) satellite s Precipitation Radar (PR) instrument. The software is also applicable to other ground-based and space-based radars. The ground and space radar volume matching and comparison software was developed in response to requirements defined by the Ground Validation System (GVS) of Goddard s Global Precipitation Mission (GPM) project. This software innovation is specifically concerned with simplifying the comparison of ground- and spacebased radar measurements for the purpose of GPM algorithm and data product validation. This software is unique in that it provides an operational environment to routinely create comparison products, and uses a direct geometric approach to derive common volumes of space- and ground-based radar data. In this approach, spatially coincident volumes are defined by the intersection of individual space-based Precipitation Radar rays with the each of the conical elevation sweeps of the ground radar. Thus, the resampled volume elements of the space and ground radar reflectivity can be directly compared to one another.
Results of mission simulation studies are presented for a laser-based atmospheric [82 sounder. The simulations are based on real-time carbon cycle process modeling and data analysis. The mission concept corresponds to the Active Sensing of [82 over Nights, Days, and Seasons (ASCENDS) recommended by the US National Academy of Sciences Decadal Survey of Earth Science and Applications from Space. One prerequisite for meaningful quantitative sensor evaluation is realistic CO2 process modeling across a wide range of scales, i.e., does the model have representative spatial and temporal gradients? Examples of model comparison with data will be shown. Another requirement is a relatively complete description of the atmospheric and surface state, which we have obtained from meteorological data assimilation and satellite measurements from MODIS and [ALIPS0. We use radiative transfer model calculations, an instrument model with representative errors ' and a simple retrieval approach to complete the cycle from "nature" run to "pseudo-data" CO2, Several mission and instrument configuration options are examined/ and the sensitivity to key design variables is shown. We use the simulation framework to demonstrate that within reasonable technological assumptions for the system performance, relatively high measurement precision can be obtained, but errors depend strongly on environmental conditions as well as instrument specifications. Examples are also shown of how the resulting pseudo - measurements might be used to address key carbon cycle science questions.
This study compared peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at CCAFS/KSC and VAFB for weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The legacy CCAFS/KSC and VAFB weather tower wind instruments are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. Mechanical and ultrasonic wind measuring techniques are known to cause differences in the statistics of peak wind speed as shown in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between the RSA ultrasonic and legacy mechanical sensors to determine if there are significant differences. Note that the instruments were sited outdoors under naturally varying conditions and that this comparison was not designed to verify either technology. Approximately 3 weeks of mechanical and ultrasonic wind data from each range from May and June 2005 were used in this study. The CCAFS/KSC data spanned the full diurnal cycle, while the VAFB data were confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on five different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The ten towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The ultrasonic sensors were collocated at the same vertical levels as the mechanical sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with mechanical sensors were compared. The 1- minute average wind speed/direction and the 1-second peak wind speed/direction were compared.
Satellite instruments have proven especially capable at monitoring the quantity of airborne particles in columns of atmosphere, globally. This chapter describes the principles of satellite measurements and retrieval algorithms, and surveys current instruments and their capabilities. We outline the issues associated with retrieval algorithms, such as surface characterization and aerosol proximity to clouds, and the challenges with interpretation of the results. The relationship between measured aerosol properties and climate-relevant aerosol properties simulated in models is outlined, as well as how measurements are used to evaluate models. Most space-based aerosol instruments are passive sensors that measure reflected sunlight at multiple wavelengths, some at multiple viewing angles. A few are active sensors that send out their own laser light and measure the returned signal. Except when clouds are present, the excess amount of light scattered back to space, beyond that expected from the surface and atmospheric gas, is attributed to aerosol. Satellite measurements are used in many ways in aerosol research. They often provide the only method for monitoring hazardous phenomena such as major wildfire and volcanic eruption plumes, especially in remote areas. Stable, long-term, near-global-scale satellite data records make it possible to identify regional and global aerosol trends. Aerosol radiative effects on climate can be quantified on a near-global scale and used to estimate the strength of aerosol–radiation and aerosol–cloud interactions as well as to evaluate climate model simulations of these interactions. Aerosol-type mapping from satellite imagery is helpful for source attribution, model validation, and to constrain particle light-absorption properties that are essential for radiative forcing calculations. The range of aerosol properties retrieved from satellite observations has grown considerably since the first global estimates of aerosol optical depth (τ a) over ocean were made in the late 1970s. Methods for retrieving particle size and light-absorption properties were explored in the 1990s using multispectral, multi-angle observations, and polarization in visible and near-infrared wavelengths. Sensitivity to particle light absorption, primarily from black or brown carbon content, improved with the inclusion of UV channels, and sensitivity to very thin aerosol layers in the upper troposphere and lower stratosphere was advanced with the use of limb-sounding instruments and active sensors. There are limitations to every measurement technique, including satellite aerosol remote sensing. For wide-swath, passive instruments, aerosol retrievals near clouds can present substantial challenges as far as 15 km away due to cloud-scattered light contaminating the signal. In nearly all cases, retrievals over bright snow and ice surfaces are precluded because surface reflectance uncertainties can overwhelm the aerosol signal. Similarly, meteorological cloud is identified and masked out where possible. Data from passive sensors also lack vertical resolution except those that view toward the limb or where multi-angle imagery is acquired over plumes from wildfires, erupting volcanoes, and wind-blown dust. Yet, passive sensors provide vastly more coverage than the active instruments that mitigate these issues. Particle microphysical information is qualitative from all remote sensing techniques, relying on proxies to infer particle composition, hygroscopicity, and the amount of light-absorbing material. Further, particles smaller than about 200 nm diameter cannot be distinguished from atmospheric gas molecules with remote sensing, which hinders studies of cloud condensation nuclei and their effects on clouds. Most satellite instruments dedicated to aerosol observations are in low-Earth, near-polar, sun-synchronous orbits, which means they cross the equator at the same local time each day. Most are set on cycles that repeat approximately every 16 days, which makes it difficult to monitor aerosol evolution locally. Geostationary satellites make it possible to observe changes occurring from minutes to hours over regions up to 8000 km in size, but lack coverage of high latitudes, and often provide more limited constraints on aerosol properties. Ground-truth data are vital for satellite aerosol-retrieval validation. The AErosol RObotic NETwork (AERONET) of sun photometers was created in 1993 and has become an established global network of over 350 instruments for validating satellite measurements. The network, as well as global networks of ground-based lidars, solar flux radiometers and other sun photometers, are widely used for evaluating global satellite retrievals and model simulations. NASA's Earth Observing System (EOS) program beginning in 1999 led to improvements in reliability, spatial resolution, and spectral resolution (and hence, to improved particle size discrimination and light absorption properties). Satellite payloads include advanced broad-swath and multi-angle imagers, along with the first space-based active sensor focused largely on long-term aerosol monitoring. Since about 2002, Europe's SENTINEL and operational meteorological satellite fleets are also providing sustained aerosol observations, with planned continuation until at least 2030. Satellite remote sensing instruments offer valuable data for evaluating aerosol representations in global climate models. They have been used to assess aerosol optical and physical properties, trends and distributions, and are applied increasingly as direct model constraints in data assimilation to create global aerosol reanalysis products. Aerosol optical depth is the most common quantity adopted for routine model evaluation, including multiwavelength data to loosely constrain particle-size distributions. These evaluations of multiple models have revealed general biases in their regional aerosol amounts and seasonal patterns of transport and removal. Although satellite measurements have near-global coverage, substantial errors can be introduced into the model observation comparison unless attention is paid to spatial and temporal collocation, cloud screening, subgrid-scale variability, and measurement uncertainties that vary with retrieval conditions.
Deploying environmental monitoring instruments in the marine environment can be challenging, facing challenges around device survivability, biofouling and corrosion, and consistent data collection. This project explores the use of data fusion – the process of integrating multiple data sources to produce more consistent, accurate, and useful information – to build a consistent long-term monitoring system at the Marine and Coastal Research Laboratory (MCRL) in Sequim, Washington. Unused instruments that had been acquired from past projects were inventoried and deployments planned on the MCRL pier and floating dock. A total of 8 instruments were deployed including a tide gauge, hydrophone, acoustic Doppler current profiler (ADCP), photosynthetically active radiation (PAR) sensors, meteorological station, and three water quality sensors. Deployments were planned to be well-protected around the pier structure and a maintenance schedule was created for cleaning and recalibration. An automated data pipeline was created to aggregate data on edge computers that push data to Amazon Web Services (AWS) cloud storage every 15 minutes, performing automated quality control and data transformations using the Time Series Data Analytical Toolkit (TSDAT). Continued efforts are underway to maintain this system into the future, take a data-driven approach to maintenance scheduling, improve the reliability of the system, and share the data with a variety of end-users.