Micro Weather Stations for Mars
A global network of weather stations will be needed to characterize the near-surface environment on Mars.
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A global network of weather stations will be needed to characterize the near-surface environment on Mars.
The pypromice Python package is for processing and handling observation datasets from automated weather stations (AWS). It is primarily aimed at users of AWS data from the Geological Survey of Denmark and Greenland (GEUS), which collects and distributes in situ weather station observations to the cryospheric science research community. Functionality in pypromice is primarily handled using two key open-source Python packages, xarray (Hoyer & Hamman, 2017) and pandas (The pandas development team, 2020). A defined processing workflow is included in pypromice for transforming original AWS observations (Level 0, L0) to a usable, CF-convention-compliant dataset (Level 3, L3) (Figure 1). Intermediary processing levels (L1,L2) refer to key stages in the workflow, namely the conversion of variables to physical measurements and variable filtering (L1), cross-variable corrections and user-defined data flagging and fixing (L2), and derived variables (L3). Information regarding the station configuration is needed to perform the processing, such as instrument calibration coefficients and station type (one-boom tripod or two-boom mast station design, for example), which are held in a toml configuration file. Two example configuration files are provided with pypromice , which are also used in the package’s unit tests. More detailed documentation of the AWS design, instrumentation, and processing steps are described in Fausto et al. (2021).
A global network of weather stations will be needed to characterize the near-surface environment on Mars. Here, we review the scientific and measurement objectives of this network. We also show how these objectives can be met within the cost-constrained Mars Surveyor Program by augmenting the Mars Pathfinder-derived landers with large numbers of very small (less than 5 liter), low-mass (less than 5 kg), low-power, low-cost Mini-meteorological stations. Each station would include instruments for measuring atmospheric. pressures, temperatures, wind velocities, humidity, and airborne dust abundance. They would also include a data handling, telemetry, power, atmospheric entry, and deployment systems in a rugged package capable of direct entry and a high-impact landing. In this paper, we describe these systems and summarize the data-taking strategies and data volumes needed to achieve the surface meteorology objectives for Mars.
An autonomous, low-power atmospheric lidar instrument is being developed at NASA Goddard Space Flight Center. This compact, portable lidar will operate continuously in a temperature controlled enclosure, charge its own batteries through a combination of a small rugged wind generator and solar panels, and transmit its data from remote locations to ground stations via satellite. A network of these instruments will be established by co-locating them at remote Automatic Weather Station (AWS) sites in Antarctica under the auspices of the National Science Foundation (NSF). The NSF Office of Polar Programs provides support to place the weather stations in remote areas of Antarctica in support of meteorological research and operations. The AWS meteorological data will directly benefit the analysis of the lidar data while a network of ground based atmospheric lidar will provide knowledge regarding the temporal evolution and spatial extent of Type la polar stratospheric clouds (PSC). These clouds play a crucial role in the annual austral springtime destruction of stratospheric ozone over Antarctica, i.e. the ozone hole. In addition, the lidar will monitor and record the general atmospheric conditions (transmission and backscatter) of the overlying atmosphere which will benefit the Geoscience Laser Altimeter System (GLAS). Prototype lidar instruments have been deployed to the Amundsen-Scott South Pole Station (1995-96, 2000) and to an Automated Geophysical Observatory site (AGO 1) in January 1999. We report on data acquired with these instruments, instrument performance, and anticipated performance of the AWS Lidar.
In this Technical Publication, we describe the model functionality and analyze its application to the seasonal and interannual variations of phytoplankton, nutrients, pCO2 and CO2 concentrations in the eastern subarctic Pacific at Ocean Weather Station P (OWSP, 50 deg. N 145 deg. W). We use a verified one-dimensional ecosystem model, coupled with newly incorporated carbon flux and carbon chemistry components, to simulate 22 years (1958-1980) of pCO2 and CO2 variability at Ocean Weather Station P (OWS P). This relatively long period of simulation verifies and extends the findings of previous studies using an explicit approach for the biological component and realistic coupling with the carbon flux dynamics. The slow currents and the horizontally homogeneous ocean in the subarctic Pacific make OWS P one of the best available candidates for modeling the chemistry of the upper ocean in one dimension. The chlorophyll and ocean currents composite for 1998 illustrates this premise. The chlorophyll concentration map was derived from SeaWiFS data and the currents are from an OGCM simulation (from R. Murtugudde).
Viking Lander meteorology measurements show that the Martian planetary boundary layer (PBL) has large diurnal and seasonal variations in pressure, wind velocity, relative humidity, and airborne dust loading. An even larger range of conditions was inferred from remote sensing observations acquired by the Mariner 9 and Viking orbiters. Numerical models indicate that these changes may be accompanied by dramatic vertical and horizontal wind shears (100 m/s/km) and rapid changes in the static stability. In-situ measurements from a relatively small number surface stations could yield global constraints on the Martian climate and atmospheric general circulation by providing ground truth for remote sensing instruments on orbiters. A more complete understanding of the meteorology of the PBL is an essential precursor to manned missions to Mars because this will be their working environment. In-situ measurements are needed for these studies because the spatial and temporal scales that characterize the important meteorological processes near the surface cannot be resolved from orbit. The Mars Environmental Survey (MESUR) Program will provide the first opportunity to deploy a network of surface weather stations for a comprehensive investigation of the Martian PBL. The feasibility and utility of a network of micro-weather stations for making in-situ meteorological measurements in the Martian PBL are assessed.
We compare the surface temperatures at Dome Concordia (DomeC) deduced from AIRS data and two Automatic Weather Stations at Concordia Station: AWS8989 , which has been in operation since December 1996, and AWS.it, for which data are available between January and November 2005. The AWS8989 readings are on average 3 K warmer than the AWS.it readings, with a warmer bias in the Antarctic summer than in the winter season. Although AIRS measures the skin brightness temperature, while the AWS reports the temperature of the air at 3 meter above the surface, the AIRS measurements agree well with the AWS.it readings for all data and separately for the summer and winter seasons, if data taken in the presence of strong surface inversions are filtered out. This can be done by deducing the vertical temperature gradient above the surface directly from the AIRS temperature sounding channels or indirectly by noting that extreme vertical gradients near the surface are unlikely if the wind speed is more than a few meters per second. Since the AIRS measurements are very well calibrated, the agreement with AWS.it is very encouraging. The warmer readings of AWS8989 are likely due to thermal contamination of the AWS8989 site by the increasing activity at Concordia Station. Data from an AWS.it quality station could be used for the evaluation of radiometric accuracy and stability of polar orbiting sounders at low temperatures. Unfortunately, data from AWS.it was available only for a limited time. The thermal contamination of the AWS8989 data makes long-term trends deduced from AWS8989 and possibly results about the rapid Antarctic warming deduced from other research stations on Antarctica suspect. AIRS is the first hyperspectral infrared sounder designed in support of weather forecasting and climate research. It was launched in May 2002 on the EOS Aqua spacecraft into a 704 km altitude polar sun-synchronous orbit. The lifetime of AIRS, estimated before launch to be at least 5 years is, based on the latest evaluation, limited by the amount of attitude control gas on the EOS Aqua spacecraft, which is expected to last through 2015.
Advances in electronics and instrument technology over the past thirty years have enabled a new concept for NASA missions, an evolution from large Voyager-class spacecraft to smaller, less costly Discovery and Explorer missions. By taking advantage of micromachining and micro-instrumentation, this reduction in size can be accomplished without requiring a sacrifice in performance. In some cases, the small payload will enable new types of missions which would be otherwise inconceivable. A microweather station is envisioned as an enabling technology for a network of weather stations on Mars for measuring wind, temperature, pressure, humidity, and aerosol concentration in the Martian planetary boundary layer...
Improved in situ meteorological measurements in the troposphere and stratosphere are needed for studies of weather and climate, both as a primary data source and as validation for remote sensing instruments. Following the initial development and successful flight validation of the surface acoustic wave (SAW) hygrometer, the micro weather station program was directed toward the development of an integrated instrument, capable of accurate, in situ profiling of the troposphere, and small enough to fly on a radiosonde balloon for direct comparison with standard radiosondes. On April 23, 1998, working with Frank Schmidlin and Bob Olson of Wallops Island Flight Facility, we flew our instrument in a dual payload experiment, for validation and direct comparison with a Vaisala radiosonde. During that flight, the SAW dewpoint hygrometer measured frostpoint down to -76T at 44,000 feet. Using a laptop computer in radio contact with the balloon, we monitored data in real time, issued the cutdown command, and recovered the payload less than an hour after landing in White Sands Missile Range, 50 miles from the launch site in Hatch, New Mexico. Future flights will extend the intercomparison, and attempt to obtain in situ meteorological profiles from the surface through the tropopause. The SAW hygrometer was successfully deployed on the NASA DC8 as part of NASA's Third Convection and Moisture Experiment (CAMEX-3) during August and September, 1998. This field campaign was devoted to the study of hurricane tracking and intensification using NASA-funded aircraft. In situ humidity data from the SAW hygrometer are currently being analyzed and compared with data from other instruments on the DC8 and ER2 aircraft. Additional information is contained in the original.
A ground based, autonomous, low power atmospheric lidar instrument is being developed at NASA Goddard Space Flight Center. We report on the design and anticipated performance of the proposed instrument and show data from two prototype lidar instruments previously deployed to Antarctica.
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City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.
City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.
The feasibility of using radio frequency receivers to collect data from automated weather stations to model fluxes of latent heat, sensible heat, and radiation using routine weather data collected by automated weather stations was tested and the estimated fluxes were compared with fluxes measured over wheat. The model Cupid was used to model the fluxes. Two or more automated weather stations, interrogated by radio frequency and other means, were utilized to examine some of the climatic variability of the First ISLSCP (International Satellite Land-Surface Climatology Project) Field Experiment (FIFE) site, to measure and model reflected and emitted radiation streams from various locations at the site and to compare modeled latent and sensible heat fluxes with measured values. Some bidirectional reflected and emitted radiation data were collected from 23 locations throughout the FIFE site. Analysis of these data along with analysis of the measured sensible and latent heat fluxes is just beginning.
Variability in micrometeorological conditions and their influence on estimated reference evapotranspiration (RET) rates were evaluated across a heterogeneous urban environment. Micrometeorological data sets (incoming solar radiation, air temperature, relative humidity and wind speed) were collected over a one-year period at six weather stations in New York City, NY (USA). Weather stations are located at four new urban green space monitoring sites and two airports. Reference evapotranspiration (RET) rates were estimated from the micrometeorological data sets for a short reference surface at a daily time-step using the ASCE Standardized Reference Evapotranspiration Equation, a Penman-Monteith based combination equation. Nonparametric comparative statistical analyses (Kruskal-Wallis) revealed statistically significant differences (at significance level α = 0.05) in micrometeorological conditions and estimated RET rates between the six sites. On a cumulative annual basis, estimated RET varied by up to 40 percent between the sites. A new technique for adjusting weather data collected at one location (e.g. regional airports) for use at another location (e.g. interior engineered urban green spaces) was evaluated. The study highlights the importance, for accurate estimation of ET, of onsite micrometeorological data sets, but concludes that additional research is needed to more thoroughly characterize micrometeorological variability across heterogeneous urban environments, and also to evaluate the influence of non-meteorological determinants, e.g. vegetation type, soil/media type, media moisture conditions and anthropogenic heat fluxes, on urban ET.
Large, permanently-manned space platforms can provide exciting opportunities for discoveries in basic plasma and geoplasma sciences. The potential for these discoveries will depend very critically on the properties of the platform, its subsystems, and their abilities to fulfill a spectrum of scientific requirements. With this in mind, the planning of space station research initiatives and the development of attendant platform engineering should allow for the identification of critical science and technology issues that must be clarified far in advance of space station program implementation. An attempt is made to contribute to that process, with a perspective that looks to the development of the space station as a permanently-manned Spaceborne Ionospheric Weather Station. The development of this concept requires a synergism of science and technology which leads to several critical design issues. To explore the identification of these issues, the development of the concept of an Ionospheric Weather Station will necessarily touch upon a number of diverse areas. These areas are discussed.
The Atlas San Juan Mission was conducted in February 2004 with the main objectives of observing the Urban Heat Island of San Juan, providing high resolution data of the land use for El Yunque Rain Forest and for calibrating remote sensors. The mission was coordinated with NASA staff members at Marshall, Stennis, Goddard, and Glenn. The Airborne Thermal and Land Applications Sensor (ATLAS) from NASA/Stennis, that operates in the visual and IR bands, was used as the main sensor and was flown over Puerto Rico in a Lear 23 jet plane. To support the data gathering effort by the ATLAS sensor, remote sensing observations and upper air soundings were conducted along with the deployment of a number of ground based weather stations and temperature sensors. This presentation focuses in the analysis of this complementary data for the Atlas San Juan Mission. Upper air data show that during the days of the mission the Caribbean mid and high atmospheres were relatively dry and highly stable reflecting positive surface lifted index, a necessary condition to conduct this suborbital campaign. Surface wind patterns at levels below 850mb were dominated by the easterly trades, while the jet stream at the edge of the troposphere dominated the westerly wind at levels above 500mb. The jet stream remained at high latitudes reducing the possibility of fronts. In consequence, only 8.4 mm of precipitation were reported during the entire mission. Observation of soundings located about 150 km apart reflected minimum variations of the boundary layer across the island for levels below 850 meters and a uniform atmosphere for higher levels. The weather stations and the temperature sensors were placed at strategic locations to observe variations across the urban and rural landscapes. Time series plot of the stations' data show that heavily urbanized commercial areas have higher air temperatures than urban and suburban residential areas, and much higher temperatures than rural areas. Temperature differences [dT(U-R)] were obtained by subtracting the values of several stations from a reference urban station, located in the commercial area of San Juan. These time series show that the UHI peaks during the morning between 10:00am and noon to an average of 4.5 C, a temporal pattern not previously observed in similar studies for continental cities. It is also observed a high variability of the UHI with the precipitation patterns even for short events. These results may be a reflection of a large land use density by low level buildings with an apparent absence of significant heat storage effects in the urban areas, and the importance of the surrounding soil and vegetation moisture in controlling the urban tropical climate. The ATLAS data was used to determine albedo and surface temperature patterns on a 10m scale for the study area. These data were used to calibrate the spatial distribution of the surface temperature when using remote sensing images from MODIS (Moderate Resolution Imaging Spectroradiometer). Surface temperatures were estimated using the land surface temperature product MOD11_L2 distributed by the Land Process Distributed Active Archive Center (LP DAAC). These results show the maximum, minimum and average temperatures in San Juan and in the entire Island at a resolution of 1 km. The information retrieved from MODIS for land surface temperatures reflected similar temporal and spatial variations as the weather stations and ATLAS measurements with a highest absolute offset of about 5 C due to the differences between surface and air temperatures.