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At least 307 records · Page 17

Thermospheric Temperature and Density Variations From Observations and Models

The Global-scale Observations of the Limb and Disk (GOLD)mission in geostationary orbit provides a near synoptic (i.e. concurrent, globally unified, and spatially resolved) view of the thermosphere and ionosphere, allowing to unambiguously distinguish temporal and spatial variations. We have analyzed the thermospheric daytime temperature and column integrated O/N ratio data from GOLD, and compared these observations with the simulation results by NCAR's WACCM-X model and NRL'sMSIS2.0 model. A seasonal pattern is seen, and there are also significant differences between the observations and simulations.

Guiping Liu↗

Objective analysis and assimilation of observational data from FGGE

An objective analysis scheme is presented for the assimilation of meteorological data in which wind, geopotential height, and relative humidity are analyzed on mandatory pressure levels, and surface pressure and temperature are reduced to sea level for analysis. The present analysis/forecast system demonstrates a reasonable degree of forecast skill over the Northern Hemisphere for an ensemble of five-day integrations during the First Special Observing Period of the First GARP Global Experiment (FGGE) The vertical motion field shows outstanding agreement with the large scale synoptic pattern for the sample analysis presented, and the mean meridional circulation portrayed in the FGGE analysis is in close agreement with observational estimates.

Baker, W. E.↗

Global Magnetohydrodynamic Modeling of the Solar Corona

Under this contract, we have continued our investigations of the large scale structure of the solar corona and inner heliosphere using global magnetohydrodynamic (MHD) simulations. These computations have also formed the basis for studies of coronal mass ejections (CMES) using realistic coronal configurations. We have developed a technique for computing realistic magnetohydrodynamic (MHD) computations of the solar corona and inner heliosphere. To perform computations that can be compared with specific observations, it is necessary to incorporate solar observations into the boundary conditions. We have used the Wilcox Solar Observatory synoptic maps (collected during a solar rotation by daily measurements of the line-of-sight magnetic field at central meridian) to specify the radial magnetic field (B,) at the photosphere. For the initial condition, we use a potential magnetic field consistent with the specified distribution of B, at the lower boundary, and a wind solution consistent with the specified plasma density and temperature at the solar surface. Together this initial condition forms a (non-equilibrium) approximation of the state of the solar corona for the time-dependent MHD computation. The MHD equations are then integrated in time to steady state. Here we describe solutions relevant to a recent solar eclipse, as well as Ulysses observations. We have also developed a model configuration of solar minimum, useful for studying CME initiation and propagation.

Linker, Jon A.↗

X-Band Radar and Surface-Based Observations of Cold-Season Precipitation in Western Colorado’s Complex Terrain

Abstract Hydrologic processes associated with intermountain cold-season precipitation in the Upper Colorado River basin have important impacts on avalanche forecasting and water resource management. However, traditional weather radar networks struggle with observations in this complex terrain. Data collected during the Study of Precipitation, the Lower Atmosphere, and the Surface for Hydrometeorology (SPLASH) and its sister campaign, Surface Atmosphere Integrated Field Laboratory (SAIL) in the East River watershed of western Colorado, are used to examine a multistorm period from 23 December 2021 to 1 January 2022 that contributed 35% of the total winter precipitation in this watershed. Dual-polarization X-band radar and disdrometer measurements show ∼30-mm differences in precipitation amount at two sites in proximity over four distinct storm events within the period. Wind patterns, synoptic forcings, microphysical characteristics of precipitation, and surface meteorology are analyzed to explain the observed spatial variability of cold-season precipitation in complex mountainous terrain. Analysis shows that differences over time within this event are mainly accounted for by synoptic forcings, such as frontal passages; differences between sites are accounted for by the impact of variations in local wind patterns on precipitation microphysics. Patterns of surface precipitation intensity are compared and found to be correlated with X-band radar signatures; a relationship between a strong dendritic growth stage and intense low-density surface precipitation is reinforced by this study. This relationship demonstrates the importance of particle growth mechanisms on surface snowfall patterns in high-altitude complex terrain, underscoring the importance of realistic microphysical parameterizations. Significance Statement The amount and density of snowpack from western Colorado winter storms have significant impacts on water resources in the Upper Colorado River basin. Snowpack characteristics are affected by small-scale differences in how snow forms in the atmosphere. These differences are hard to study in the complex terrain of the Rockies, but data from the SPLASH and SAIL field campaigns allows us to investigate how snow crystal formation and mountain-driven wind patterns affect snow near the surface. Our study finds that snow crystal growth varies over small space and time scales and is likely controlled by the terrain beneath a given location and resultant local wind patterns. These results imply that predicting snowpack in the Rockies requires properly representing local wind patterns and crystal growth processes in models.

Heflin, Stella↗

Examination of L-Band Brightness Temperature Forecasts in the SMAP Level-4 Soil Moisture Analysis

The NASA Soil Moisture Active Passive (SMAP) mission [4] has been providing L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations since April 2015. By assimilating the Tb observations into the NASA Catchment land surface model [5] using a spatially distributed ensemble Kalman filter, the NASA Global Modeling and Assimilation Office generates the SMAP Level-4 Soil Moisture (L4_SM) product, which provides global, 3-hourly, 9-km resolution estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture with ~2.5-day latency for use in research and applications [6]. The L4_SM product also includes estimates of soil temperature, land surface fluxes, and assimilation diagnostics such as the model forecast and observed Tb values [7]. The output from the L4_SM system is routinely monitored by the L4_SM team. Such monitoring provides valuable information; instances of unusually large Tb observation-minus-forecast (O-F) residuals can indicate events during which soil moisture conditions are poorly described in the land modeling system [7,8]. For example, repeated occurrences of very large Tb O-F values in central Australia were traced back to deficiencies in the gauge-based precipitation product used in the land modeling system through L4_SM Version 5; this discovery prompted the use, beginning in Version 6, of satellite- and gauge-based precipitation observations outside of North America [9]. Recently, a statistical analysis of the Tb O-F residuals revealed systematic errors in the “tau-omega” L-band radiative transfer model that converts the land-model simulated soil moisture and temperature into the forecast Tb prior to the L4_SM analysis. The L4_SM analysis is built on the ensemble Kalman filter and assumes unbiased forecast errors. The presence of systematic Tb forecast errors could thus adversely impact the quality of the analyzed soil moisture. In this paper, we examine the Tb O-F residuals of the latest Version 7 L4_SM data (Science Version ID Vv7030 and Vv7032) [10,11,12]. In the L4_SM Version 7 algorithm, key parameters of the L-band radiative transfer model, including soil roughness, scattering albedo, and a (seasonally varying) climatology of vegetation opacity, are obtained from the SMAP Level-2 Radiometer retrieval product (Version 5) [1]. Additionally, we also use ground measurements of surface soil moisture and soil temperature from the SMAP core validation sites as in situ reference of soil conditions [2,3]. As part of the L4_SM system calibration, the seasonally-varying bias between the model forecast Tb and the observed values is removed prior to the assimilation of the SMAP Tb observations [7]. That is, the L4_SM system is designed to only correct errors in synoptic-scale and interannual variations from the long-term mean seasonal cycle while maintaining the model’s (potentially erroneous) climatology. The Tb O-F residuals examined here are thus computed using SMAP Tb observations after they are rescaled to the mean seasonal cycle of Tb from the modeling system without SMAP data assimilation. Consequently, the long-term average of the Tb O-F residuals has a global mean of only 0.13 K and locally small values, ranging from -1 to 3 K. Despite the small time-average values of the Tb O-F residuals, the model forecast Tb was nevertheless found to exhibit undesirable systematic errors. At some locations, the time-average Tb O-F values strongly depend on surface soil moisture (SM). At the Yanco SMAP core validation site, for example, the Tb O-F residuals typically range from 5 to 15 K under dry soil moisture conditions (SM < 0.15 m3 m-3) yet are predominantly negative under wet soil moisture conditions (SM > 0.25 m3 m-3), with values ranging from 0 to -40 K. This results in soil moisture analysis increments that persistently make the soil drier under dry SM conditions and persistently make the soil wetter under wet SM conditions, suggesting an error in the dynamic range of the simulated Tb, soil moisture or soil temperature. In this paper, we describe the higher-order systematic Tb forecast errors in more detail, examine their impact on the L4_SM product quality, and explore potential avenues to further improve the L4_SM algorithm.

Rolf Reichle↗

The GEMPAK Barnes interactive objective map analysis scheme

The analysis scheme and meteorological applications of the GEMPAK data analysis and display software system developed by NASA are described. The program was devised to permit objective, versatile, and practical analysis of satellite meteorological data using a minicomputer and a display system with graphics capability. A data area can be selected within the data file for the globe, and data-sparse regions can be avoided. Distances between observations and the nearest observation points are calculated in order to avoid errors when determining synoptic weather conditions. The Barnes (1973) successive correction method is employed to restore the amplitude of small yet resolvable wavelengths suppressed in an initial filtering pass. The rms deviation is then calculated in relation to available measured data. Examples are provided of treatment of VISSR data from the GOES satellite and a study of the impact of incorrect cloud height data on synoptic weather field analysis.

Koch, S. E.↗

Bistatic LIDAR experiment proposed for the shuttle/tethered satellite system missions

A new experiment concept has been proposed for the shuttle/tethered satellite system missions, which can provide high resolution, global density mappings of certain ionospheric species. The technique utilizes bistatic LIDAR to take advantage of the unique dual platform configuration offered by these missions. A tuned, shuttle-based laser is used to excite a column of the atmosphere adjacent to the tethered satellite, while triangulating photometic detectors on the satellite are employed to measure the fluorescence from sections of the column. The fluorescent intensity at the detectors is increased about six decades over both ground-based and monostatic shuttle-based LIDAR sounding of the same region. In addition, the orbital motion of the Shuttle provides for quasi-global mapping unattainable with ground-based observations. Since this technique provides such vastly improved resolution on a synoptic scale, many important middle atmospheric studies, heretofore untenable, may soon be addressed.

Mccomas, D. J.↗

The characterization of an air pollution episode using satellite total ozone measurements

A case study is presented which demonstrates that measurements of total ozone from a space-based platform can be used to study a widespread air pollution episode over the southeastern U.S. In particular, the synoptic-scale distribution of surface-level ozone obtained from an independent analysis of ground-based monitoring stations appears to be captured by the synoptic-scale distribution of total ozone, even though about 90 percent of the total ozone is in the stratosphere. Additional analyses of upper air meteorological data, other satellite imagery, and in situ aircraft measurements of ozone likewise support the fact that synoptic-scale variability of tropospheric ozone is primarily responsible for the observed variability in total ozone under certain conditions. The use of the type of analysis discussed in this study may provide an important technique for understanding the global budget of tropospheric ozone.

Fishman, Jack↗

Seasonal Distributions of Global Ocean Chlorophyll and Nutrients: Analysis with a Coupled Ocean General Circulation Biogeochemical, and Radiative Model

A coupled general ocean circulation, biogeochemical, and radiative model was constructed to evaluate and understand the nature of seasonal variability of chlorophyll and nutrients in the global oceans. The model is driven by climatological meteorological conditions, cloud cover, and sea surface temperature. Biogeochemical processes in the model are determined from the influences of circulation and turbulence dynamics, irradiance availability, and the interactions among three functional phytoplankton groups (diatoms, chorophytes, and picoplankton) and three nutrient groups (nitrate, ammonium, and silicate). Phytoplankton groups are initialized as homogeneous fields horizontally and vertically, and allowed to distribute themselves according to the prevailing conditions. Basin-scale model chlorophyll results are in very good agreement with CZCS pigments in virtually every global region. Seasonal variability observed in the CZCS is also well represented in the model. Synoptic scale (100-1000 km) comparisons of imagery are also in good conformance, although occasional departures are apparent. Agreement of nitrate distributions with in situ data is even better, including seasonal dynamics, except for the equatorial Atlantic. The good agreement of the model with satellite and in situ data sources indicates that the model dynamics realistically simulate phytoplankton and nutrient dynamics on synoptic scales. This is especially true given that initial conditions are homogenous chlorophyll fields. The success of the model in producing a reasonable representation of chlorophyll and nutrient distributions and seasonal variability in the global oceans is attributed to the application of a generalized, processes-driven approach as opposed to regional parameterization, and the existence of multiple phytoplankton groups with different physiological and physical properties. These factors enable the model to simultaneously represent the great diversity of physical, biological, chemical, and radiative environments encountered in the global oceans.

Gregg, Watson W.↗

Impact of Assimilating AIRS Cloud-Cleared Radiances on Atmospheric Dynamics and Boundary Layer Height at High Latitudes

High latitude weather forecasts, on scales ranging from mesoscale to synoptic, present difficulties due, in part, to the sparsity of conventional observations. In addition, the prevalence of extended low-level stratus cloud cover limits the use of infrared data, which are operationally assimilated only in areas unaffected by clouds. Use of cloud-cleared AIRS (Atmospheric Infrared Sounder) radiances (AIRS CCR), allows the assimilation of infrared information in cloudy regions, permitting data ingestion in regions usually undersampled. This study explores the sensitivity of planetary boundary layer height and related atmospheric dynamics to the assimilation of these data in the Goddard Earth Observing System (GEOS, version 5) data assimilation and forecast system during the boreal fall 2014 season using observing system experiments (OSEs). Examined here are comparisons between the current, operational approach of assimilating AIRS clear-sky radiances against the assimilation of CCR. Assimilation of hyperspectral infrared information from AIRS over the Arctic region slightly modifies the lower midtropospheric temperature structure, which in turn contributes to adjustments in geopotential height, affecting the baroclinic instability properties over the entire hemisphere and explaining the overall improvement in global forecast skill.

McGrath-Spangler, E. L.↗

Coronal synoptic temperature maps derived from the Fe XIV/Fe X intensity ratio

The large-scale temperature structure of the low corona is investigated using synoptic temperature maps, derived from the intensity ratio of the green (Fe XIV) and red (Fe X) coronal lines as observed at the National Solar Observatory/Sacramento Peak. This intensity ratio is sensitive to coronal plasma with temperatures in the range of 1-2 MK. The synoptic maps indicate an association between high coronal temperature and the large-scale magnetic field. A comparison with WSO 'source surface' synoptic maps shows that especially when the heliospheric current sheet is stable over several rotations, the large-scale high-temperature features follow the current sheet remarkably well. For recent Carrington rotations temperature maps have been constructed for various heights between 1.15 and 1.45 solar radii. For these maps the correspondence with the current sheet (calculated at 2.5 solar radii) improves with height. Deviations between temperature structure and magnetic structure appears to be largest when the magnetic structure changes rapidly from rotation to rotation.

Hick, P.↗

Simulations of Cyclone Sidr in the Bay of Bengal with a High-Resolution Model: Sensitivity to Large-Scale Boundary Forcing

The predictability of Cyclone Sidr in the Bay of Bengal was explored in terms of track and intensity using the Advanced Research Hurricane Weather Research Forecast (AHW) model. This constitutes the first application of the AHW over an area that lies outside the region of the North Atlantic for which this model was developed and tested. Several experiments were conducted to understand the possible contributing factors that affected Sidr s intensity and track simulation by varying the initial start time and domain size. Results show that Sidr s track was strongly controlled by the synoptic flow at the 500-hPa level, seen especially due to the strong mid-latitude westerly over north-central India. A 96-h forecast produced westerly winds over north-central India at the 500-hPa level that were notably weaker; this likely caused the modeled cyclone track to drift from the observed actual track. Reducing the model domain size reduced model error in the synoptic-scale winds at 500 hPa and produced an improved cyclone track. Specifically, the cyclone track appeared to be sensitive to the upstream synoptic flow, and was, therefore, sensitive to the location of the western boundary of the domain. However, cyclone intensity remained largely unaffected by this synoptic wind error at the 500-hPa level. Comparison of the high resolution, moving nested domain with a single coarser resolution domain showed little difference in tracks, but resulted in significantly different intensities. Experiments on the domain size with regard to the total precipitation simulated by the model showed that precipitation patterns and 10-m surface winds were also different. This was mainly due to the mid-latitude westerly flow across the west side of the model domain. The analysis also suggested that the total precipitation pattern and track was unchanged when the domain was extended toward the east, north, and south. Furthermore, this highlights our conclusion that Sidr was influenced from the west side of the domain. The displacement error was significantly reduced after the domain size from the western model boundary was decreased. Study results demonstrate the capability and need of a high-resolution mesoscale modeling framework for simulating the complex interactions that contribute to the formation of tropical cyclones over the Bay of Bengal region

Kumar, Anil↗

The International Space Station Supports International Polar Year (IPY)

Every day, ISS astronauts photograph designated sites and dynamic events on the Earth's surface using digital cameras equipped with a variety of lenses. Depending on observation parameters, astronauts can collect high resolution (4-6 m pixel size) or synoptic views (lower resolution but covering very large areas) digital data in 3 (red-green-blue) color bands. ISS crews have daily opportunities to document a variety of high-latitude phenomena. Although lighting conditions, ground track and other viewing parameters change with orbital precessions and season, the 51.6o orbital inclination and 400 km altitude of the ISS provide the crew an unique vantage point for collecting image-based data of polar phenomena, including surface observations to roughly 65o latitude, and upper atmospheric observations that reach nearly to the poles. During the 2007-2009 timeframe of the IPY, polar observations will become a scientific focus for the CEO experiment; the experiment is designated ISS-IPY. We solicit requests from scientists for observations from the ISS that are coordinated with or complement ground-based polar studies. The CEO imagery website for ISS-IPY provides an on-line form that allows IPY investigators to interact with CEO scientists and define their imagery requests. This information is integrated into daily communications with the ISS astronauts about their Earth Observations targets. All data collected are cataloged and posted on the website for downloading and assimilation into IPY projects. Examples of imagery and detailed information about scientific observations from the ISS can also be downloaded from the ISS-IPY web site.

Evans, Cynthia A.↗

A synoptic analysis of the first AVE-SESAME '79 period

Key features of a severe convection observed during April 10-11, 1979 as part of the Atmospheric Variability Experiment-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME) are examined. Three-hourly rawinsonde readings from 23 stations were taken, and vertical motion and divergence parameters are considered. The data were converted into a 127 km grid at the surface, and at 50 mb intervals from 900 mb to 100 mb by an objective analysis scheme, while a kinematic method was used to compute vertical motion. A weak upper tropospheric short wave trough was found to propagate from New Mexico into the Texas panhandle, while a jet maximum propagated eastward. The development of a strong wind maximum over Oklahoma and Kansas was associated with a rapid increase in upper-level divergence and the development of a small-scale pressure perturbation in the Texas panhandle, as well as a low-level jet and convergence, which led to rapid changes over the Red River Valley, where stability was decreased.

Moore, J. T.↗

Synoptic study of the corona at meter wavelength

The Mark III Nancay Radioheliograph is used to observe the Sun at 169 MHz with a time resolution of 25 East-West and North-South images per second. When the brightness distribution of the Sun is stable during the eight hours of daily observation, a two dimensional map can be produced using the technique of earth rotation synthesis. The best images are obtained during the period April to August, when the declination of the Sun is high to give a good coverage in the uv plane and a reasonable North-South resolution. The spatial resolution is 1.5' East-West and in summer, 3.5' North-South. The maps are calibrated using Cygnus A as a reference. Examples of the maps are given and discussed.

Lantos, P.↗

The 27-28 October 1986 FIRE cirrus case study - Meteorology and clouds

A detailed case study is conducted of cirrus clouds that were observed intensely over a 36-h period from 1200 UTC October 27 to 0000 UTC October 29, 1986. The clouds varied in density and structure as synoptic and mesoscale features passed through the region. The study seeks to provide a meteorological overview including a synoptic and regional perspective; to document the rawinsonde-resolved atmospheric structure and large-scale forcing associated with the observed cloud systems; and to provide understanding of the relationship between atmospheric structure and the character of the corresponding cloud fields. Regional analyses of the static stability structure and vertical motion are presented and interpreted with respect to the characteristics of the corresponding cloud fields as deduced from satellite and lidar observations. It is suggested that mesoscale organization must be taken into account in parametric treatments of cirrus for large-scale atmospheric models. It is shown that cloud generation typically occurred at multiple levels.

Starr, David O'C.↗

Improved Diagnosis of Precipitation Type with LightGBM Machine Learning

Abstract Existing precipitation-type algorithms have difficulty discerning the occurrence of freezing rain and ice pellets. These inherent biases are not only problematic in operational forecasting but also complicate the development of model-based precipitation-type climatologies. To address these issues, this paper introduces a novel light gradient-boosting machine (LightGBM)-based machine learning precipitation-type algorithm that utilizes reanalysis and surface observations. By comparing it with the Bourgouin precipitation-type algorithm as a baseline, we demonstrate that our algorithm improves the critical success index (CSI) for all examined precipitation types. Moreover, when compared with the precipitation-type diagnosis in reanalysis, our algorithm exhibits increased F1 scores for snow, freezing rain, and ice pellets. Subsequently, we utilize the algorithm to compute a freezing-rain climatology over the eastern United States. The resulting climatology pattern aligns well with observations; however, a significant mean bias is observed. We interpret this bias to be influenced by both the algorithm itself and assumptions regarding precipitation processes, which include biases associated with freezing drizzle, precipitation occurrence, and regional synoptic weather patterns. To mitigate the overall bias, we propose increasing the precipitation cutoff from 0.04 to 0.25 mm h −1 , as it better reflects the precision of precipitation observations. This adjustment yields a substantial reduction in the overall bias. Finally, given the strong performance of LightGBM in predicting mixed precipitation episodes, we anticipate that the algorithm can be effectively utilized in operational settings and for diagnosing precipitation types in climate model outputs. Significance Statement Freezing rain can have significant impacts on transportation and infrastructure, making accurate prediction of precipitation types crucial. In this study, we use a machine learning method known as LightGBM to predict precipitation types. We show that the new algorithm performs better than the existing methods for all precipitation types examined. Additionally, we compute a freezing-rain climatology over the eastern United States. Although the resulting climatology pattern corresponds well to observations, the algorithm overpredicts freezing-rain occurrence. We argue that this bias can be substantially reduced by increasing the precipitation cutoff from 0.04 to 0.25 mm h −1 . Overall, this work highlights the potential of the LightGBM algorithm for both weather forecasting and diagnosing precipitation types in climate models.

Meteorology & Atmospheric Sciences↗

Use of LIDAR systems in measuring certain physical oceanographic parameters

Remote sensing techniques, such as LIDAR, are the only observation methods which are capable of fast scanning over a vast area to produce synoptic views which are necessary for time and space study of the ocean. However, due to the very nature of the way data are collected, all the information thus obtained is confined, to or in the immediate neighborhood of the surface. Nevertheless, all the physical processes in the ocean are controlled mainly by both surface and subsurface parameters; they act and interact among themselves and produce the phenomena we actually observe in time and space. Remote sensing techniques are very effective for those phenomena controlled by surface parameters which account for most of the crucial problems in physical oceanography.

Chen, D. T.↗