Surface Meteorological Station - ANL 10m tower, Goldendale - Reviewed Data
Basic meteorological measurements.
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Basic meteorological measurements.
Basic meteorological measurements
Inducing meteorological corrections into comsic ray intensity
Progress made in the development of a technique for identifying and delinating benthic and shoreline communities using multispectral imagery is described. Images were collected with a multispectral scanner system mounted in a C-47 aircraft. Concurrent with the overflight, ecological ground- and sea-truth information was collected at 19 sites in the bay and on the shore. Preliminary processing of the scanner imagery with a CDC 1604 digital computer provided the optimum channels for discernment among different underwater and coastal objects. Automatic mapping of the benthic plants by multiband imagery and the mapping of isotherms and hydrodynamic parameters by digital model can become an effective predictive ecological tool when coupled together. Using the two systems, it appears possible to predict conditions that could adversely affect the benthic communities. With the advent of the ERTS satellites and space platforms, imagery data could be obtained which, when used in conjunction with water-level and meteorological data, would provide for continuous ecological monitoring.
The meteorological data processing program at the space center is centered on the analysis of geostationary satellite data. Its objectives are to detect and predict severe storms, to improve short range and long range global numerical weather forecasting models, and to develop improved satellite systems. The Image Display and Manipulation System (IDAMS) for earth resources satellite data processing is described, as is the special purpose software package, METPAK, for performing meteorology operations on IDAMS. The Atmospheric and Oceanographic Information Processing System (AOIPS), a dual terminal multiprocessor is also described.
A project is described for providing the accurate initial and verification analyses for the jet stream in regions where general circulation models are known to have large systematic errors, either due to the extreme sparsity of data or to incorrect physical parameterizations. For this purpose, finely spaced aircraft-based meteorological data for the Southwest Asian regions collected for three 10-day periods in the winter of 1988-1989 will be used, together with corresponding data for the North American regions used as a control, to rerun the assimilation cycles and forecast models of the NMC and the NASA Goddard Laboratory for Atmospheres. Data for Southeast Asia will be collected by three carriers with extensive wide-body routes crossing the total region, while data for the North American region will be obtained from the archives of ACARS and GTS.
Global distributions of surface and atmospheric cloud radiative forcing parameters have been derived using parameterized radiation models with satellite meteorological data from the International Satellite Cloud Climatology Project, and directly measured top-of-atmosphere radiative fluxes from the Earth Radiation Budget Experiment. Specifically, shortwave, longwave, and total cloud forcing at the surface, and column-averaged values of longwave cloud forcing of the atmosphere were derived for the midseasonal months of April, July, and October 1985 and January 1986, covering a complete annual cycle. Seasonal variability is illustrated by comparing the results for July 1985 and January 1986, which represent the seasonal extremes. Surface shortwave cloud forcing is always negative, representing a cooling of the surface, with strongest cooling (-120 to -180 W/sq m) occurring over midlatitude storm tracks of the summer hemisphere. Surface longwave cloud forcing is always positive, representing a warming of the surface, with strongest warming (60 to 75 W/sq m) occurring over storm tracks of the winter hemisphere. Zonal averages show the entire summer hemisphere dominated by shortwave cooling, the middle and high latitudes of the winter hemisphere dominated by longwave warming, and a broad zone of transition in between. The globally averaged total cloud forcing amounts to a cooling throughout the year, ranging from a low of about -12 W/sq m for July 1985 to a high of about -25 W/sq m for January 1986. The longwave cloud forcing of the atmosphere shows a strong warming over deep convective regions in the tropics and a moderate cooling outside the tropics, amounting to a weak cooling (-2 to -5 W/sq m) in the global average. Comparisons of the results with general circulation model simulations show broad qualitative agreement regarding the locations of prominent warming and cooling regions. Quantitative comparisons, on the other hand, show significant differences between the magnitudes of warming and cooling in these regions. Most of the larger differences can be attributed to known deficiences of the general circulation model simulations. Comparisons with satellite-derived results of other investigators show much better agreement.
This data package includes a time series of meteorological data (air temperature, relative humidity, barometric pressure, precipitation, wind speed, soil heat flux, incoming shortwave radiation, incoming longwave radiation, outgoing shortwave radiation and outgoing longwave radiation) from the Slate River floodplain outside Crested Butte, Colorado, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The package also includes reference evapotranspiration calculated via the Penman-Monteith equation and an estimate of willow (Salix spp.) evapotranspiration using the method of Irmak et al., J. Hydrology, 2013. Due to two malfunctioning sensors (incoming shortwave radiation from Oct 2020-May 2021 and incoming longwave radiation from May 2021-March 2022), observed net radiation and calculated evapotranspiration are only included from July-October 2020. However, users may be able to extend calculated evapotranspiration using estimates of these two parameters from other sources. Both sensors have been replaced and data beyond 2021 be uploaded to this repository when it is available.Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 3 "*data.csv" files, two for meteorological data for 2020 and 2021 and one for reference evapotranspiration and transpiration data from 2020 ("SLT_OBJ2_PenmanMonteith_2020_data.csv"). Each "*data.csv" file of meteorological data has a corresponding "*_InstallationMethods.csv" file that describes the location, sensor model, sensor serial number and other metadata corresponding to each measured parameter. We also include a Jupyter notebook ("PenmanMonteithET_Calculations.ipynb") that details the assumptions and equations used to calculate daily and hourly reference evapotranspiration and daily willow transpiration from raw meteorological data.
The feasibility of using the data collection system on Earth Technology Satellite-1 to predict wheat leaf rust severity and resulting yield loss was tested. Ground-based data-collection platforms (DCPs), placed in two commercial wheat fields, transmitted to the satellite such meteorological information as maximum and minimum temperature, relative humidity, and hours of free moisture. Meteorological data received from the two DCPs from April 23 to 29 were used to estimate the disease progress curve. Values from the curve were used to predict the percentage decrease in wheat yields resulting from leaf rust. Actual decrease in yield obtained by applying a zinc and maneb spray to control leaf rust, and then comparing yields of the controlled (healthy) and the noncontrolled (rusted) areas. In each field, a 9% decrease in yield was predicted by the DCP-derived data; actual decreases were 12% and 9%.
Meteorological soundings representative of the atmospheric environment at the Kennedy Space Center, Florida and Vandenberg Air Force Base, California, are presented. Synthetic meteorological soundings at Kennedy Space Center, including fall, spring, and a sea breeze, and at Vandenberg Air Force Base (sea breeze with low and high level inversion and stationary upper level troughs) are shown. Soundings of frontal passages are listed. The Titan launch soundings at Kennedy Space Center present a wide range of meteorological conditions, both seasonal and time of day variations. The meteorological data input of altitude, wind speed, wind direction, temperature, and pressure may be used as meteorological inputs for the NASA/MSFC Multilayer Diffusion Model or other models to obtain quantitative estimates of effluent concentrations associated with the potential emission of major combustion products in the lower atmosphere to simulate actual launches of space vehicles. The Titan launch soundings are also of value in terms of rocket effluent measurements for analysis purposes.
The propagation data of JG2AS 40 kHz (Japanese Standard Frequency), Loran C 100 kHz radio waves, and meteorological data were analyzed to study the association of propagation characteristics of LF radio waves with the atmospheric circulation in the mesosphere. The monthly averaged electric fields were depicted on the complex plane for typical summer and winter months, June and November. The locus traced out by the electric field vector during daytime is nearly circular. This is because during daytime the amplitude of the sky wave remains nearly constant while its phase changes in accord with the height change of the reflection layer, and thus the electric field vector traces out a circular locus with its center at the tip of the supposed ground wave vector. The locus has a loop during the sunrise or sunset period, which seems to arise from interference of two waves reflected by two different layers. In June the amplitude of the sky wave decreases rapidly before the dawn or increases after the dusk. In November such rapid change is not observed. During nighttime, the sky wave phase changes in such a way as to suggest that the reflection height moves upwards with time before midnight or lowers after midnight in November. In June it changes similarly before midnight, but after midnight it varies erratically. These characteristics are closely related to the structure of the D region, which is clearly shown by simulating the loci traced out by electric fields.
The Model II variational data assimilation model is the second of the four variational models designed to blend diverse meteorological data into a dynamically constrained data set. Model II differs from Model I in that it includes the thermodynamic equation as the fifth dynamical constraint. Thus, Model II includes all five of the primative equations that govern atmospheric flow for a dry atmosphere.
In this work, we have used the Soil & Water Assessment Tool (SWAT) to examine streamflow variability of the Lower Mekong River Basin (LMRB) associated with changes in the Upper Mekong River Basin (UMRB) inflows. Two hypothetical experiments were formulated and evaluated for the LMRB, where we conducted runoff simulations with multiple inflow changes that include upstream runoff yield increase and decrease scenarios. Streamflow variability of the LMRB was quantified by two streamflow metrics that explain flow variability and predictability, and high flow disturbance. The model experiments were performed for the Lower Mekong River Basin with identical climate, soil, and other watershed characteristics data. Remote sensing precipitation (Tropical Rainfall Measurement Mission, TRMM, and Global Precipitation Measurement mission, GPM), meteorological data as well as spatial data that include a digital elevation model, newly developed soil information (Harmonized World Soil Database, HWSD), and land use and land cover were processed as input to the LMRB model simulations. Observed daily streamflow data along the Lower Mekong River from Chiang Sean, Thailand to Kratie, Cambodia were used for calibration and validation. Our work results suggest that the Lower Mekong River streamflow is highly variable and has a low predictability (Colwell index of about 32%). We found that releasing more water from upstream Mekong during rainfall months by 30% would result in a reduction in the Lower Mekong streamflow predictability by about 21%. This reduction in predictability is mainly attributed to a decrease in the Contingency index. Our work shows that the ability to predict floods/droughts at the Lower Mekong River would be reduced if there is any anticipated change (i.e., increase/decrease) from UMRB releases. Our results also show that releasing more flows from the upstream Mekong would also affect flood duration and the frequency of flood occurrences downstream. The results of this work thus help to quantify the sensitivity of streamflow variability at the Lower Mekong River Basin to upstream anthropogenic changes.
NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data at various temporal levels from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). Data users can access these data either through an intuitive data viewer, image services fully integrable with GIS analysis, connections in the cloud through an Amazon Web Services S3 Bucket, or fully customizable access through an API. Data provided by POWER has been used to remotely monitor solar array fields and integrated in a sizing tool for off-grid solar and storage systems. POWER data has also been coupled with key building decision tools to support design and retrofitting of building energy systems for energy efficiency and reduction of greenhouse gases. POWER is now developing capabilities to provide time series of the projected future evolution of surface quantities important to future energy production and use, such as heating/cooling degree days, temperature, wind speed, and downwelling solar flux. We present here a range of possible future changes in these quantities at locations throughout the continental United States. We show how both average and extreme values of the quantities will evolve from present-day to future climate conditions. We plan to provide these projections for users in the energy and sustainable energy communities.
At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domain has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.
This data set contains observed and modeled evaporation data, eddy covariance data, and supporting information measured at White Bear Lake in the Twin Cities Metropolitan Area near St. Paul, Minnesota, USA. The data package includes csv files containing half-hourly latent heat flux, sensible heat flux, and meteorological data from 2014 to 2016. It also includes csv files containing half-hourly observed evaporation measurements, along with supporting data for validation and retrospective modeling of evaporation. This data was collected to examine current, past, and future lake evaporation to better understand how climate will impact the water balance of lakes within this region.
Continuous, long-term measurements of atmospheric ice-nucleating particles (INPs) that influence clouds and precipitation were conducted to investigate the abundance and variability of ground-level INPs across the world. Three field campaigns were organized by the DOE Atmospheric Radiation Measurement (ARM) program, including Examining INP from Southern Great Plains (ExINP-SGP, 2019), Examining INP from Eastern North Atlantic (ExINP-ENA, 2020 – 2021), and Examining INP from North Slope of Alaska (ExINP-NSA, 2021 – 2024). Additional small-scale supporting field experiments were performed in 2019 and 2021 to collect airborne particulate matter at SGP for complementary laboratory characterization of the particles’ physical and chemical properties [Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY), 2019; ExINP-SGP II, 2021]. In these studies, the PI’s team measured INP concentration with both real-time and laboratory measurements in a wide range of freezing temperatures ($T$ from 0 °C to about –30 °C). This project elucidated spatial variability and seasonality in the abundance of immersion mode active INPs across three ARM sites using a single instrument, a Portable Ice Nucleation Experiment (PINE) chamber version 03 (PINE-03 hereafter). Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient INP abundance, air mass origin region, and meteorological variability. Our findings suggest very high freezing efficiency of INPs at the NSA site across the measured temperatures (ice nucleation active surface site density, $n_s(T)$, $\approx 2 \times 10^{8} - 10^{10}$ m -2 for from –16 to –31 °C), which is a factor of 10 – 1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in autumn using the same instrument; surprisingly high INP abundance ($\ge 1 \text{ L}^{-1}$ at –25 °C) for the examined temperatures throughout the year that PINE-03 did not measure at other sites; and high INP concentration in spring, possibly related to arctic haze episodes.
The 1974 Antarctic large scale sea ice extent is studied from data from Nimbus 2 and 5 and temperature and sea level pressure fields from the Australian Meteorological Data Set. Electrically Scanning Microwave Radiometer data were three-day averaged and compared with 1000 mbar atmospheric pressure and sea level pressure data, also in three-day averages. Each three-day period was subjected to a Fourier analysis and included the mean latitude of the ice extent and the phases and percent variances in terms of the first six Fourier harmonics. Centers of low pressure were found to be generally east of regions which displayed rapid ice growth, and winds acted to extend the ice equatorward. An atmospheric response was also noted as caused by the changing ice cover.