Atmospheric water vapor content from satellite radiation measurements
Methods used to infer atmospheric water vapor content from Tiros satellite measurements in absorption band of water vapor
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Methods used to infer atmospheric water vapor content from Tiros satellite measurements in absorption band of water vapor
The K34 tower site (2.609 S, 60.209 W, 130 masl), located within the Tropical Silviculture Experimental Station (EEST, also known as ZF2) research station, in an area of undisturbed tropical forest (Araújo et al. 2002). It features long term measurements using micrometeorological, eddy covariance, and soil instrumentation, among others. This dataset covers January 2012 to December 2017, and includes air temperature (TA, ℃) and air relative humidity (RH, %), measured with thermohygrometers (HC2S3, Campbell Scientific, Logan, UT, USA) deployed above the canopy at the top of the tower (at 51.1 m height), and net radiation (NETRAD, W m-2) using an NR-LITE sensor (Kipp & Zonen, Delft, Netherlands), also at the top of the tower (at 35.0 m above the canopy). The soil moisture data included here is from a soil profile located approximately 12 m from the tower, and covers the period between February 2015 and September 2016. Volumetric soil water content (SWC, m3 m-3) measurements used Water Content Reflectometers (CS655 Campbell Scientific, Logan, UT, USA) at six depths: 10 cm, 20 cm, 30 cm, 40 cm, 60 cm, and 100 cm. Data are included in .csv files, and the text file ZF2-K34_Tower_headers.txt provides descriptions of data file headers.
Industrial humidity sensor measures volume fraction of water in air via its effect on speed of sound. Only portion of sensor exposed to sensed atmosphere is pair of stainless-steel tubes, one containing dry air and other containing moist air. Counters measure intervals between reflected pulses. Sensor rugged enough for use in harsh environments like those used to control drying of paper in paper mills, where most humidity sensors do not survive.
This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulations for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micrometeorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5, but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLMs still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions.
The NASA/GSFC Atmospheric Lidar for Validation/Interagency Collaboration and Education (ALVICE) participated in the Measurements of Humidity And Validation Experiments (MOHAVE 209) campaign hosted at the JPL/Table Mountain Facility in Southern California. This field campaign brought together a large number of water vapor measuring instruments in an effort to inter-compare and validate numerous water vapor technologies in use within the Network for the Detection of Atmospheric Composition Change (NDACC). A central focus of the campaign was to perform validation of Raman lidar systems in use within NDACC. ALVICE is one of the mobile intercomparison lidar instruments within NDACC and MOHAVE provided an excellent opportunity to test and validate the measurements of this system. At the workshop, we will present recent analysis results of ALVICE lidar measurements and put them in the context of the full field campaign,
A high-performance Raman lidar operating in the UV portion of the spectrum has been used to acquire, for the first time using a single lidar, simultaneous airborne profiles of the water vapor mixing ratio, aerosol backscatter, aerosol extinction, aerosol depolarization and research mode measurements of cloud liquid water, cloud droplet radius, and number density. The Raman Airborne Spectroscopic Lidar (RASL) system was installed in a Beechcraft King Air B200 aircraft and was flown over the mid-Atlantic United States during July August 2007 at altitudes ranging between 5 and 8 km. During these flights, despite suboptimal laser performance and subaperture use of the telescope, all RASL measurement expectations were met, except that of aerosol extinction. Following the Water Vapor Validation Experiment Satellite/Sondes (WAVES_2007) field campaign in the summer of 2007, RASL was installed in a mobile trailer for groundbased use during the Measurements of Humidity and Validation Experiment (MOHAVE-II) field campaign held during October 2007 at the Jet Propulsion Laboratory s Table Mountain Facility in southern California. This ground-based configuration of the lidar hardware is called Atmospheric Lidar for Validation, Interagency Collaboration and Education (ALVICE). During theMOHAVE-II field campaign, during which only nighttime measurements were made, ALVICE demonstrated significant sensitivity to lower-stratospheric water vapor. Numerical simulation and comparisons with a cryogenic frost-point hygrometer are used to demonstrate that a system with the performance characteristics of RASL ALVICE should indeed be able to quantify water vapor well into the lower stratosphere with extended averaging from an elevated location like Table Mountain. The same design considerations that optimize Raman lidar for airborne use on a small research aircraft are, therefore, shown to yield significant dividends in the quantification of lower-stratospheric water vapor. The MOHAVE-II measurements, along with numerical simulation, were used to determine that the likely reason for the suboptimal airborne aerosol extinction performance during theWAVES_2007 campaign was amisaligned interference filter. With full laser power and a properly tuned interference filter,RASL is shown to be capable ofmeasuring themain water vapor and aerosol parameters with temporal resolutions of between 2 and 45 s and spatial resolutions ranging from 30 to 330 m from a flight altitude of 8 km with precision of generally less than 10%, providing performance that is competitive with some airborne Differential Absorption Lidar (DIAL) water vapor and High Spectral Resolution Lidar (HSRL) aerosol instruments. The use of diode-pumped laser technology would improve the performance of an airborne Raman lidar and permit additional instrumentation to be carried on board a small research aircraft. The combined airborne and ground-based measurements presented here demonstrate a level of versatility in Raman lidar that may be impossible to duplicate with any other single lidar technique.
Abstract. Aerosol hygroscopic growth plays an important role in atmospheric particle chemistry and the effects of aerosol on radiation and hence climate. The hygroscopic growth is often characterized by a growth factor probability density function (GF-PDF), where the growth factor is defined as the ratio of the particle size at a specified relative humidity to its dry size. Parametric, least-squares methods are the most widely used algorithms for inverting the GF-PDF from measurements of the humidified tandem differential mobility analyzer (HTDMA) and have been recently applied to the GF-PDF inversion from measurements of the humidity-controlled fast integrated mobility spectrometer (HFIMS). However, these least-squares methods suffer from noise amplification due to the lack of regularization in solving the ill-posed problem, resulting in significant fluctuations in the retrieved GF-PDF and even occasional failures of convergence. In this study, we introduce nonparametric, regularized methods to invert the aerosol GF-PDF and apply them to HFIMS measurements. Based on the HFIMS kernel function, the forward convolution is transformed into a matrix-based form, which facilitates the application of the nonparametric inversion methods with regularizations, including Tikhonov regularization and Twomey's iterative regularization. Inversions of the GF-PDF using the nonparameteric methods with regularization are demonstrated using HFIMS measurements simulated from representative GF-PDFs of ambient aerosols. The characteristics of reconstructed GF-PDFs resulting from different inversion methods, including previously developed least-squares methods, are quantitatively compared. The result shows that Twomey's method generally outperforms other inversion methods. The capabilities of Twomey's method in reconstructing the pre-defined GF-PDFs and recovering the mode parameters are validated.
Sensors and feedback systems are critical to life support flight systems and life support systems research. New sensor capabilities can allow for new system architectures to be considered, and can facilitate dramatic improvements in system performance. This paper will describe three opportunities for biosensor researchers to develop sensors that will enable life support system improvements. The first opportunity relates to measuring physical, chemical, and biological parameters in the Space Station Water Processing System. Measuring pH, iodine, total organic carbon, microbiological activity, total dissolved solids, or conductivity with a safe, effective, stable, reliable microsensor could benefit the water processing system considerably. Of special interest is a sensor which can monitor biological contamination rapidly. The second opportunity relates to sensing microbiological contamination and water condensation on the surface of large inflatable structures. It is the goal of large inflatable structures used for habitation to take advantage of the large surface area of the structure and reject waste heat passively through the walls of the structure. Too much heat rejection leads to a cold spot with water condensation, and eventually microbiological contamination. A distributed sensor system that can measure temperature, humidity, and microbiological contamination across a large surface would benefit designers of large inflatable habitable structures. The third opportunity relates to sensing microbial bioreactors used for waste water processing and reuse. Microbiological bioreactors offer considerable advantages in weight and power compared to adsorption bed based systems when used for long periods of time. Managing and controlling bioreactors is greatly helped if distributed microsensors measured the biological populations continuously in many locations within the bioreactor. Nitrifying bacteria are of special interest to bioreactor designers, and any sensors that could measure the populations of these types of bacteria would help the control and operation of bioreactors. J
The thermal, compositional and electrical properties of the lunar regolith, such as the triboelectric properties of lunar dust, the volatile content and the thermophysical properties of the polar regolith are essential to understand from a scientific perspective as well as for resource extraction and hazard mitigation. Understanding these properties specifically requires in situ measurement, as these properties are inherent in the ambient environment. With the Lunar In situ Regolith Analyzer (LIRA) we will combine mature surface sensor technologies from previous spacecraft missions (TECP) with new sensors (ClO4- ) and battery capability to achieve a compact in situ analysis package. The surface instrument suite is adapted for lunar conditions from a sensor developed as part of the Microscopy, Electrochemistry, and Conductivity Analyzer (MECA) instrument on the 2007 Mars Phoenix mission, as well as supplemental sensors. • The Thermal and Electrical Conductivity Probe (TECP), flown on MECA/Phoenix, which measures heat capacity, thermal conductivity, electrical resistance, and electrical permittivity between needles inserted into the soil. The TECP also measured atmospheric humidity, a capability that will be retained to search for subsurface H2O ice. The Mars TECP weighed 100-gram and by definition was at TRL 9. The lunar version (LIRA) is TRL 4. • The Perchlorate (ClO4) sensor is based on the fluorescence property of perchlorate (Mg, Fe, Na). We added a light source to excite the perchlorate (ClO4) and a photo diode to collect the emission wavelength. A sun-shade over the photo diode blocks out the ambient light during day light hours. The unifying goal of LIRA is to deliver a complete, integrated experiment suite that investigates properties that must be measured in situ, and provides the capability to power the suite at night or in PSRs, as well as a means to simulate aspects of the diurnal transition by delivering an optical pulse to the surface with intensity comparable to sunlight. We describe the scientific context of LIRA, touching on the electrical state of the near-surface environment, the thermal properties of the undisturbed regolith, and the distribution, geochemistry, and mobility of water. We also address the exploration implications of the work, examining hazards and resources in the context of strategic knowledge gaps (SKGs).
Abstract Water vapor supersaturation in clouds is a random variable that drives activation and growth of cloud droplets. The Pi Convection–Cloud Chamber generates a turbulent cloud with a microphysical steady state that can be varied from clean to polluted by adjusting the aerosol injection rate. The supersaturation distribution and its moments, e.g., mean and variance, are investigated for varying cloud microphysical conditions. High-speed and collocated Eulerian measurements of temperature and water vapor concentration are combined to obtain the temporally resolved supersaturation distribution. This allows quantification of the contributions of variances and covariances between water vapor and temperature. Results are consistent with expectations for a convection chamber, with strong correlation between water vapor and temperature; departures from ideal behavior can be explained as resulting from dry regions on the warm boundary, analogous to entrainment. The saturation ratio distribution is measured under conditions that show monotonic increase of liquid water content and decrease of mean droplet diameter with increasing aerosol injection rate. The change in liquid water content is proportional to the change in water vapor concentration between no-cloud and cloudy conditions. Variability in the supersaturation remains even after cloud droplets are formed, and no significant buffering is observed. Results are interpreted in terms of a cloud microphysical Damköhler number (Da), under conditions corresponding to , i.e., the slow-microphysics regime. This implies that clouds with very clean regions, such that is satisfied, will experience supersaturation fluctuations without them being buffered by cloud droplet growth. Significance Statement The saturation ratio (humidity) in clouds controls the growth rate and formation of cloud droplets. When air in a turbulent cloud mixes, the humidity varies in space and time throughout the cloud. This is important because it means cloud droplets experience different growth histories, thereby resulting in broader size distributions. It is often assumed that growth and evaporation of cloud droplets buffers out some of the humidity variations. Measuring these variations has been difficult, especially in the field. The purpose of this study is to measure the saturation ratio distribution in clouds with a range of conditions. We measure the in-cloud saturation ratio using a convection cloud chamber with clean to polluted cloud properties. We found in clouds with low concentrations of droplets that the variations in the saturation ratio are not suppressed.
During the course of this project, we performed exhaustive research and development of SO3/H2SO4 sensing technology for coal-fired power plant applications (Figure 1). The development culminated in a successful field campaign of a prototype continuous real-time H2SO4 monitor at a coal-fired power plant (TRL 6) accomplishing the primary goal of the project. The developed sensors utilize tunable laser absorption spectroscopy (TLAS) operating in the mid-infrared (Mid-IR) wavelength region, which is the so-called “molecular fingerprint” region. Systems operating in the Mid-IR have orders of magnitude more sensitivity than systems operating at shorter wavelengths, such as near-infrared (NIR). However, NIR systems are more widespread due to more mature supporting technology (e.g., fiber optics, optical components, etc.). In this project, we not only produced a specific Mid-IR sensor, we also advanced Mid-IR sensor technology in general through the development and demonstration of such supporting technology. In this project, we also developed proprietary broad tuning lasers enabling the ability to effectively measure SO3, H2SO4, H2O, and SO2. Different molecular species have unique spectral signatures that can be probed with lasers operating at different wavelengths. Standard TLAS uses relatively narrow wavelength tuning distributed feedback (DFB) lasers, which can typically only target a single species with narrow features, and are not appropriate for species with broad features, such as SO3 or H2SO4. In contrast, by developing unique, broad-tuning laser technology, we were able to measure these species, as well as SO2 and H2O simultaneously. Furthermore, to enable real-time analysis at a power plant, we modified a commercially available heated gas cell to operate in the Mid-IR wavelength range and fiber coupled the lasers to enable remote delivery of the beams. To generate reference data (library spectra), our collaborators at the University of California Irvine (UCI) developed a catalytic SO3 generation facility. It is worth mentioning that representative H2SO4 and SO3 Mid-IR spectra are not a part of any publicly available database and the data generated under this project is a valuable resource in and of itself. In addition, based on the UCI study we determined that detection of SO3 is complicated by the very strong SO2 absorption. For that reason, we concentrated on H2SO4 detection. Since SO3 and H2SO4 exist in a flue gas in a state of equilibrium, which depends on temperature and humidity, by measuring water concentration and controlling the temperature of the gas cell, we developed an approach to determine SO3 concentration from the H2SO4 measurement. During the development phase of the project, we performed three testing campaigns at our collaborator’s FERCo flue gas facility with conditions representative of the coal-fired power plant (~ 40ppm SO3, 1700ppm to 2800 ppm SO2, 10% water) with the exception of particulate matter. After three test campaigns at FERCo we performed field testing at Harrison Power Station. The final system was mounted on a duct and measured H2SO4, SO2 and water. The tests were highly successful with a demonstrated real-time H2SO4 precision of 1 ppm with a 1 second update. Our collaborators at EPRI conducted an industry survey and determined that there is a very high interest for the SO3/H2SO4 monitoring in the power generation industry as well as in heavy industries in general. Furthermore, work performed by OptoKnowledge beyond the scope of this project under a synergistic DOE SBIR determined another approach to SO3 detection. We applied for Phase II on this SBIR for development a of versatile SO3/H2SO4 sensor but were not selected. We are currently looking for another opportunity to leverage all the technological advancements produced by this project including but not limited to the flue gas facility at UCI, the hardware and software developed, and relationships with FERCo, EPRI CEMTEK, and Harrison Station.
Conventional altimeters include nadir looking colocated 18-37 GHz microwave radiometer to measure wet tropospheric path delay. These have reduced accuracy in coastal zone (within ~50 km from land) and do not provide wet path delay over land. The addition of high frequency channels to Jason-class radiometer will improve retrievals in coastal regions and enable retrievals over land. High-frequency window channels, 90, 130 and 166 GHz are optimum for improving performance in coastal region and channels on 183 GHz water vapor line are ideal for over-land retrievals.
Sound absorption coefficients in air as function of humidity at frequencies below 1000 cps
Effect of environmental temperatures and relative humidities on curing times of polyurethane and polysulfide potting compounds
Humidity sensor for transient studies of hydrogen oxygen fuel cell
Absorption of sound in air as function of humidity and temperature
Michelson interferometer to obtain vertical temperature and humidity profile from Nimbus satellite
Michelson type interferometer for Nimbus meteorological satellite to obtain vertical temperature, humidity and ozone profile