Search NASA⌕ Search

SEARCH · Search NASA

Results for “meteorological variables”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

The impact of Doppler lidar wind observations on a single-level meteorological analysis

Through the use of observation operators, modern data assimilation systems have the capability to ingest observations of quantities that are not themselves model variables, but are mathematically related to those variables. An example of this are the so-called LOS (line of sight) winds that a Doppler wind Lidar can provide. The model - or data assimilation system - needs information about both components of the horizontal wind vectors, whereas the observations in this case only provide the projection of the wind vector onto a given direction. The analyzed value is then calculated essentially based on a comparison between the observation itself and the model-simulated value of the observed quantity. However, in order to assess the expected impact of such an observing system, it is important to examine the extent to which a meteorological analysis can be constrained by the LOS winds. The answer to this question depends on the fundamental character of the atmospheric flow fields that are analyzed, but more importantly it also depends on the real and assumed error covariance characteristics of these fields. A single-level wind analysis system designed to explore these issues has been built at the NASA Data Assimilation Office. In this system, simulated wind observations can be evaluated in terms of their impact on the analysis quality under various assumptions about their spatial distribution and error characteristics and about the error covariance of the background fields. The basic design of the system will be presented along with experimental results obtained with it. In particular, the value of simultaneously measuring LOS winds along two different directions for a given location will be discussed.

Riishojgaard, L. P.↗

Variability of rainfall over small areas

A preliminary investigation was made to determine estimates of the number of raingauges needed in order to measure the variability of rainfall in time and space over small areas (approximately 40 sq miles). The literature on rainfall variability was examined and the types of empirical relationships used to relate rainfall variations to meteorological and catchment-area characteristics were considered. Relations between the coefficient of variation and areal-mean rainfall and area have been used by several investigators. These parameters seemed reasonable ones to use in any future study of rainfall variations. From a knowledge of an appropriate coefficient of variation (determined by the above-mentioned relations) the number rain gauges needed for the precise determination of areal-mean rainfall may be calculated by statistical estimation theory. The number gauges needed to measure the coefficient of variation over a 40 sq miles area, with varying degrees of error, was found to range from 264 (10% error, mean precipitation = 0.1 in) to about 2 (100% error, mean precipitation = 0.1 in).

Runnels, R. C.↗

Sea Ice Variability in the Sea of Okhotsk from Passive Microwave Satellite Observations

The Sea of Okhotsk, located between 50 and 60 N, is bounded by the Kamchatka Peninsula, Siberia, Sakhalin Island, and the Kuril Island chain and is the largest midlatitude seasonal sea ice zone in the Northern Hemisphere. The winter sea ice cover begins to form in November and expands to cover most of the sea by March. Over the following three months, the ice retreats with only small ice-covered areas remaining by the beginning of June. The sea is ice free or nearly ice free on average for six months of the year, from June through November. The recent compilation of a consistent, long-term record of Northern Hemisphere sea ice extents based on passive microwave satellite observations from the Nimbus 7 Scanning Multichannel Microwave Radiometer and from four Defense Meteorological Satellite Program Special Sensor Microwave Imagers provides the basis for assessing long-term sea ice extent variability in the Sea of Okhotsk. Analysis of this 20-year data record (1979-1998) shows that based on yearly averages the overall extent of the Sea of Okhotsk ice cover is decreasing at the rate of -8.1+/-2.1x10(exp 3) sq km/yr (-17.2%/decade), in contrast to the rate of decrease of -33.3+/-0.7x10(exp 3) sq km/yr (-2.7%/decade) for the Northern Hemisphere as a whole. There is large regional sea ice extent variability of the Arctic ice cover. Two of the nine Arctic regions analyzed, the Bering Sea and the Gulf of St. Lawrence, show increases of 0.8+/-1.4xl0(exp 3) sq km/yr (2.7%/decade) and 1.2+/-0.5xl0(exp 3) sq km/yr (17.1%/decade), respectively. Interestingly, the Sea of Okhotsk and the Gulf of St. Lawrence show about equal percentage changes, but of opposite sign. The Sea of Okhotsk exhibits its greatest percent decrease (-24.3%/decade) during spring (April-June). The year of maximum winter sea ice extent for the Sea of Okhotsk was 1979, whereas the minimum winter sea ice extent occurred in 1984.

Cavalieri, Donald J.↗

Examining the Constellation of Scatterometers and Radiometers for Diurnal and Sub-Diurnal Wind Vector Variability

The constellation of satellite-based ocean surface wind and precipitation observations since 1999 consists of a diverse collection of both sunsynchronous and asynchronous orbiting satellite platforms, both wind vector-capable (e.g., RapidScat, QuikSCAT, ASCAT) and speed-only radiometers (e.g., TRMM and GPM imagers, AMSR-E) The surface wind varies widely throughout the day, owing to various meteorological forcings, such as land/sea temperature differences, coastal forcings, or possible variations associated with tropical convection Where are regions of strongest time-of-day variability?

Turk, F. Joseph (Joe)↗

On the role of the seasonal cycle

The definition of the seasonal cycle as the projection of an atmospheric time series onto a suitably defined subset of orthogonal basis functions guarantees that any atmospheric covariance may be expressed as the sum of a seasonal cycle part and a transient part (where transient refers to departures from the seasonal cycle rather than the time mean). Results are presented for the seasonal cycle contribution to the zonally averaged fluxes of momentum and heat, and for the zonally averaged height variance, in data for: the winter season, the winter season with the Fourier basis set appropriate for the seven-year time series, and the seven-year mean. The Fourier basis set calculation indicates that the interannual variability of the momentum flux is dominated by the interactions between the seasonal cycle and the meteorologically low frequency flow.

Straus, D. M.↗

Characterizing multiscale variability of zero intermittency in spatial rainfall

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

Kumar, Praveen↗

Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have been developed. Errors have been estimated to range from 1K to 5K mainly due to cloud masking problems. With many additional channels available, it is expected that the EOS-Moderate Resolution Imaging Spectroradiometer (MODIS) will provide an improved characterization of clouds and a good discrimination of clouds from snow or ice surfaces.

Comiso, Joey C.↗

Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

Climate Forcing Data↗

Studying Diurnal Variations of Aerosols with NASA MERRA-2 Reanalysis Data

Aerosols play an important role in atmospheric dynamics, climate variations, and Earth's energy cycle by altering the radiation balance in the atmosphere through interaction with clouds, providing fertilizer for forests and canopy, and as a supply of iron to the ocean over long time periods. Studies suggest that much of the feedback between dust aerosols and dynamics is associated with diurnal and synoptic scale variability. However, the lack of sub-daily resolution of aerosols from satellite observations makes it difficult to study the diurnal characteristics, especially over tropical and subtropical regions. Investigation of this topic utilizes over 37 years of simulated global aerosol products from NASA atmospheric reanalysis, in the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data set, available from NASA Goddard Earth Science Data and Information Services Center (GES DISC). MERRA-2 covers the period 1980-present, and is continuing as an ongoing climate analysis. Aerosol assimilation is included throughout the period, using data from MODIS, MISR, AERONET, and AVHRR (in the pre-EOS period). The aerosols are assimilated using the MERRA-2 aerosol model, which interacts directly with radiation parameterization, and is radiatively coupled with atmospheric model dynamics in the Goddard Earth Observing System Model, Version 5 (GEOS-5). Hourly, monthly, and monthly diurnal data are available at spatial resolution of 0.5o x 0.625o (latitude x longitude). By using MERRA-2 hourly and monthly diurnal products, different aerosol diurnal variabilities are observed over North America, Africa, Asia, and Australia, that may be due to different meteorological conditions and aerosol sources. The presentation will also provide an overview of MERRA-2 data services at GES DISC, such as how to find and download data, and how to quickly visualize and analyze data online with Giovanni.

aerosol↗

Southern hemisphere low level wind circulation statistics from the Seasat scatterometer

Analyses of remotely sensed low-level wind vector data over the Southern Ocean are performed. Five-day averages and monthly means are created and the month-to-month variability during the winter (July-September) of 1978 is investigated. The remotely sensed winds are compared to the Australian Bureau of Meteorology (ABM) and the National Meteorological Center (NMC) surface analyses. In southern latitudes the remotely sensed winds are stronger than what the weather services' analyses suggest, indicating under-estimation by ABM and NMC in these regions. The evolution of the low-level jet and the major stormtracks during the season are studied and different flow regimes are identified. The large-scale variability of the meridional flow is studied with the aid of empirical orthogonal function (EOF) analysis. The dominance of quasi-stationary wave numbers 3,4, and 5 in the winter flows is evident in both the EOF analysis and the mean flow. The signature of an exceptionally strong blocking situation is evident in July and the special conditions leading to it are discussed. A very large intraseasonal variability with different flow regimes at different months is documented.

Levy, Gad↗

From BASE-ASIA Toward 7-SEAS: A Satellite-Surface Perspective of Boreal Spring Biomass-Burning Aerosols and Clouds in Southeast Asia

In this paper, we present recent field studies conducted by NASA's SMART-COMMIT (and ACHIEVE, to be operated in 2013) mobile laboratories, jointly with distributed ground-based networks (e.g., AERONET, http://aeronet.gsfc.nasa.gov/ and MPLNET, http://mplnet.gsfc.nasa.gov/) and other contributing instruments over northern Southeast Asia. These three mobile laboratories, collectively called SMARTLabs (cf. http://smartlabs.gsfc.nasa.gov/, Surface-based Mobile Atmospheric Research & Testbed Laboratories) comprise a suite of surface remote sensing and in-situ instruments that are pivotal in providing high spectral and temporal measurements, complementing the collocated spatial observations from various Earth Observing System (EOS) satellites. A satellite-surface perspective and scientific findings, drawn from the BASE-ASIA (2006) field deployment as well as a series of ongoing 7-SEAS (2010-13) field activities over northern Southeast Asia are summarized, concerning (i) regional properties of aerosols from satellite and in situ measurements, (ii) cloud properties from remote sensing and surface observations, (iii) vertical distribution of aerosols and clouds, and (iv) regional aerosol radiative effects and impact assessment. The aerosol burden over Southeast Asia in boreal spring, attributed to biomass burning, exhibits highly consistent spatial and temporal distribution patterns, with major variability arising from changes in the magnitude of the aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from the source regions, the tightly coupled-aerosolecloud system provides a unique, natural laboratory for further exploring the micro- and macro-scale relationships of the complex interactions. The climatic significance is presented through large-scale anti-correlations between aerosol and precipitation anomalies, showing spatial and seasonal variability, but their precise cause-and-effect relationships remain an open-ended question. To facilitate an improved understanding of the regional aerosol radiative effects, which continue to be one of the largest uncertainties in climate forcing, a joint international effort is required and anticipated to commence in springtime 2013 in northern Southeast Asia.

biomass burning aerosols↗

Revised Perturbation Statistics for the Global Scale Atmospheric Model

Magnitudes and scales of atmospheric perturbations about the monthly mean for the thermodynamic variables and wind components are presented by month at various latitudes. These perturbation statistics are a revision of the random perturbation data required for the global scale atmospheric model program and are from meteorological rocket network statistical summaries in the 22 to 65 km height range and NASA grenade and pitot tube data summaries in the region up to 90 km. The observed perturbations in the thermodynamic variables were adjusted to make them consistent with constraints required by the perfect gas law and the hydrostatic equation. Vertical scales were evaluated by Buell's depth of pressure system equation and from vertical structure function analysis. Tables of magnitudes and vertical scales are presented for each month at latitude 10, 30, 50, 70, and 90 degrees.

Justus, C. G.↗

Argentina wheat yield model

Five models based on multiple regression were developed to estimate wheat yields for the five wheat growing provinces of Argentina. Meteorological data sets were obtained for each province by averaging data for stations within each province. Predictor variables for the models were derived from monthly total precipitation, average monthly mean temperature, and average monthly maximum temperature. Buenos Aires was the only province for which a trend variable was included because of increasing trend in yield due to technology from 1950 to 1963.

Callis, S. L.↗

Diurnal and spatial variability of lightning activity in northeastern Colorado and central Florida during the summer

Lightning location data from northeastern Colorado and central Florida for the summer months of 1983 have been studied to ascertain the diurnal development of spatial distributions of flash frequencies. The data sources are discussed, and for both investigated regions, the regional geographic and climatic characteristics, the day-to-day variability of lightning activity, the diurnal cycle over the entire region, the spatial distribution of lightning activity, the diurnal changes of spatial distribution, and the diurnal variation of lightning at individual sites are described in detail. In both regions, the time and space distributions of lightning are modulated by the topographic features and the contrasts of the terrain. Lightning activity is a relatively rare and variable phenomenon in both regions when day-to-day frequencies are considered. There thus must be meteorological parameters that determine the extent and frequency of lightning occurrence.

Lopez, R. E.↗

A 10-Year Climatology of Amazonian Rainfall Derived from Passive Microwave Satellite Observations

In this study we present and describe a satellite-derived precipitation climatology over northern South America using a passive microwave technique, the Goddard Profiling Algorithm. A period of data slightly longer than 10 years is examined. The climatologies take the form of the mean estimated (adjusted) rainfall for a 10-year (+) period, with sub-divisions by month and meteorological season. For the six-year period 1992-1997, when two satellites were in operation, diurnal variability (to the extent it is discerned by four unequally spaced observations) is presented. We find an alternating pattern of morning and maxima stretching from the northeast (Atlantic coast) clear across the continent to the Pacific. The effects of topography, coastlines and geography (river valleys) on the rainfall patterns are clear. Interannual variability is examined by computing the deviations of yearly and warm season (DJF) rainfall from their respective long-term means. Interannual variability of the diurnal nature of the rainfall is presented, and the strong El Nino event of 1997-1998 is discussed.

Negri, Andrew J.↗

Interannual Variability of Seasonal Pblooms in the North Polar Atlantic in Response to Atmospheric Forcing

The year-to-year variability of timing, intensity, and spatial distribution of surface phytoplankton during spring-summer seasons is examined in the north polar region of the Atlantic using satellite-derived chlorophyll a concentration (Chl) over 7 years (1998 2004). Each year phytoplankton bloom differed in onset, temporal evolution, and intensity. This interannual variability is to a large degree controlled by local weather, as indicated by the analysis of coincident meteorological data. The atmospheric forcing was parameterized in terms of the generation rate of turbulent kinetic energy (TKE(sub RT)) supplied from the atmosphere to the ocean. Timing of the bloom is delayed in years with high TKE(sub RT) supplied to the ocean in March. In April, Chl (local and regionally averaged) and TKE(sub RT) are inversely related to one another. The late winter and early spring atmospheric conditions influence the seasonal Chl patterns. The seasonal (April-August) Chl correlates well with net heat flux, wind energy, and TKE(sub RT) in March and April, but the correlation can be negative or positive in different areas of the north polar Atlantic. The correlation between TKE(sub RT) and seasonal Chl is positive in the Greenland Gyre (higher seasonal Chl corresponds to higher TKE(sub RT) in March April) and negative in the regions of East Greenland and North Atlantic/West Spitsbergen Currents. The most likely explanation for the positive correlation between TKE(sub RT) and Chl within the Greenland Gyre is that higher TKE(sub RT) in spring increases the seasonal supply of nutrients into surface waters.

Stramska, Malgorzata↗

Data Assimilation Technology Transfer from Planetary Exploration to Terrestrial Applications

Data assimilation can be a valuable tool for discovery and exploration. Planetary missions--principally polar orbiting spacecraft--are now capable of returning enough information to constrain global dynamical models. However, such missions operate under a number of severe constraints: there is no ground truth to calibrate and validate either the models or the data: and there are limited computational resources available, particularly onboard the spacecraft, for the near real-time processing that is required for aerobraking and other semi-autonomous maneuvers. A modified data assimilation approach, in which the prime analysis variable is the observed quantity (i.e., infrared radiances), has been found to be effective in deriving global meteorology from Mars Global Surveyor Thermal Emission Spectrometer data. It may also be useful in a number of terrestrial applications (e.g. aerosol assimilation).

Houben, Howard↗

Sea Surface Air Pressure Retrieval with MBARS

Global meteorological observations are essential in initialization and assimilation of numerical weather prediction (NWP) models. Many key weather variables such as temperature, humidity, and wind can be relatively well observed by in-situ and remote techniques from surface, suborbital and orbital platforms. However, sea surface air pressure cannot be well-sampled. Over open oceans, the pressure can only be observed by very limited buoys, ships, and oceanic platforms. There is no operational remote sensing method available for the crucial dynamic variable of the Earth’s climate and weather systems. Advanced techniques for global sea level pressure (SLP) observations are urgently needed for improving NWP models, particularly for improvement of severe weather forecasts. Recent studies on the space and airborne Microwave BArometric Radar and Sounder (MBARS) systems provide a great potential to fill the SLP observational gap. The systems studied have three channels with center frequencies at 65.5, 67.76 and 70 GHz. These channels are designed to operate at atmospheric oxygen (O2) absorption bands for column O2 mass measurements. When sea surface returns of spectrally closely-spaced paired channels are measured, surface reflection and atmospheric attenuation other than O2 are very similar, but the difference in O2 absorption is substantial. Thus, the differential absorption loss of this frequency pair leads to measures of atmospheric O2 amount. For the residual absorption loss caused by other agents, a third frequency having the same spectral space to the weak absorption frequency of the first pair can be used, which forms the second pair and produces the same residual as the first pair. Removal of the residual of this second pair from the first pair can further mitigate environmental impacts. Thus, this 3-channel approach will provide precise O2 amount retrievals. Since oxygen is well mixed in the atmosphere, the column air mass or SLP can be obtained. Currently, MBARS is rapidly maturing its advanced technology. An upcoming airborne field flight campaign is planned in late 2024. The 3-channel approach will be use in SLP retrievals. This MBARS team will discuss the physics-based SLP retrieval technique and report latest progresses in this upcoming AGU annual meeting.

O2 differential absorption↗