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This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z07 refers to the seventh height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z06 refers to the sixth height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z05 refers to the fifth height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z04 refers to the fourth height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z03 refers to the third height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z02 refers to the second height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site G. Z01 refers to the first height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z06 refers to the sixth height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z01 refers to the first height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z04 refers to the fourth height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z05 refers to the fifth height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z03 refers to the third height position of the iMet-XQ2 mounted on the tethered balloon.
This dataset contains meteorological measurements including temperature, pressure, and relative humidity at multiple heights deployed on tethered balloon system at AWAKEN site A1. Z02 refers to the second height position of the iMet-XQ2 mounted on the tethered balloon.
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The Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project is concerned with ocean color satellite sensor data intercomparison and merger for biological and interdisciplinary studies of the global oceans. Imagery from different ocean color sensors can now be processed by a single software package using the same algorithms, adjusted by different sensor spectral characteristics, and the same ancillary meteorological and environmental data. This enables cross-comparison and validation of the data derived from satellite sensors and, consequently, creates continuity in ocean color information on both the temporal and spatial scale. The next step in this process is the integration of in situ ocean and atmospheric parameters to enable cross-validation and further refinement of the ocean color methodology. The SIMBIOS Project Office accomplishments during 2000 year are summarized under satellite data processing, data product validation, SeaWiFS Bio-Optical Archive and Storage System (SeaBASS) database, supporting services, sun photometers and calibration activities, and calibration round robins. These accomplishments are described.
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To improve snowpack estimates in Community Land Model version 4 (CLM4), the Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover fraction (SCF) was assimilated into the Community Land Model version 4 (CLM4) via the Data Assimilation Research Testbed (DART). The interface between CLM4 and DART is a flexible, extensible approach to land surface data assimilation. This data assimilation system has a large ensemble (80-member) atmospheric forcing that facilitates ensemble-based land data assimilation. We use 40 randomly chosen forcing members to drive 40 CLM members as a compromise between computational cost and the data assimilation performance. The localization distance, a parameter in DART, was tuned to optimize the data assimilation performance at the global scale. Snow water equivalent (SWE) and snow depth are adjusted via the ensemble adjustment Kalman filter, particularly in regions with large SCF variability. The root-mean-square error of the forecast SCF against MODIS SCF is largely reduced. In DJF (December-January-February), the discrepancy between MODIS and CLM4 is broadly ameliorated in the lower-middle latitudes (2345N). Only minimal modifications are made in the higher-middle (4566N) and high latitudes, part of which is due to the agreement between model and observation when snow cover is nearly 100. In some regions it also reveals that CLM4-modeled snow cover lacks heterogeneous features compared to MODIS. In MAM (March-April-May), adjustments to snowmove poleward mainly due to the northward movement of the snowline (i.e., where largest SCF uncertainty is and SCF assimilation has the greatest impact). The effectiveness of data assimilation also varies with vegetation types, with mixed performance over forest regions and consistently good performance over grass, which can partly be explained by the linearity of the relationship between SCF and SWE in the model ensembles. The updated snow depth was compared to the Canadian Meteorological Center (CMC) data. Differences between CMC and CLM4 are generally reduced in densely monitored regions.
Supercooled Large Droplet (SLD) icing conditions were implicated in at least one recent aircraft crash, and have been associated with other aircraft incidents. Inflight encounters with SLD can result in ice accreting on unprotected areas of the wing where it can not be removed. Because this ice can adversely affect flight characteristics of some aircraft, there has been concern about flight safety in these conditions. The FAA held a conference on in-flight icing in 1996 where the state of knowledge concerning SLD was explored. One outcome of these meetings was an identified need to acquire SLD flight research data, particularly in the Great Lakes Region. The flight research data was needed by the FAA to develop a better understanding of the meteorological characteristics associated with SLD and facilitate an assessment of existing aircraft icing certification regulations with respect to SLD. In response to this need, NASA, the Federal Aviation Administration (FAA), and the National Center for Atmospheric Research (NCAR) conducted a cooperative icing flight research program to acquire SLD flight research data. The NASA Glenn Research Center's Twin Otter icing research aircraft was flown throughout the Great Lakes region during the winters of 1996-97 and 1997-98 to acquire SLD icing and meteorological data. The NASA Twin Otter was instrumented to measure cloud microphysical properties (particle size, LWC (Liquid Water Content), temperature, etc.), capture images of wing and tail ice accretion, and then record the resultant effect on aircraft performance due to the ice accretion. A satellite telephone link enabled the researchers onboard the Twin Otter to communicate with NCAR meteorologists. who provided real-time guidance into SLD icing conditions. NCAR meteorologists also provided preflight SLD weather forecasts that were used to plan the research flights, and served as on-board researchers. This document contains an evaluation of the tools and techniques NCAR forecasters used to predict the location of SLD icing conditions during the winter of 1997-1998. The objectives of this report are to: (1) assess the tools used to forecast in-flight icing. (2) assess the success/failure rate of the forecasts, and (3) discuss suggested changes to forecast techniques.