Abstract

The period July–December 1964 in the tropical western Pacific was marked by strong fluctuations in the meridional wind component with periods ranging from 4–6 days. This paper describes an intensive study of these disturbances, using spectrum-analysis techniques on time series of radiosonde data.

Two types of disturbances appear to be involved. One of these, prevalent at Canton Island, is characterized by upward phase propagation in the lower troposphere and downward phase propagation above 200 mb. It has previously been suggested that this wave may be the tropospheric manifestation of the mixed Rossby- gravity wave. A second type of disturbance, prevalent at stations further west, is marked by an absence of vertical phase propagation. Latent heat release may be important in its energetics.

Abstract

The output of pulsed and AC output anemometers suffer from discretization noise when such anemometers are sampled at fast rates (>1 Hz). This paper describes the construction of an optimal filter designed to reduce this noise. By comparing the filtered output from an AC output cup anemometer with a nearby cup anemometer whose output is free from discretization noise, it is shown that the filter significantly reduces the noise. Wind speed time series obtained from the two anemometers are quite similar. Next, deconvolution is applied to the filtered time series to account for the anemometer response. Spectra from the deconvolved time series and a time series measured by a nearby sonic anemometer are compared, and for high-speed flows the spectra from the two instruments match quite well. The time series are also very similar; however, the cup anemometer generally cannot respond to the quick bursts of speed seen by the sonic anemometer. The filtering and deconvolution methods presented here are most appropriate for the high-speed flows relevant to wind energy studies. These methods make it possible to use inexpensive, rugged cup anemometers to measure a high-speed, turbulent wind field up to a frequency of about 5 Hz.

Abstract

Missing observations at airports can cause delays in commercial and general aviation in the United States owing to Federal Aviation Administration (FAA) safety regulations. The Environmental Modeling Center (EMC) has provided interpolated temperature data from the National Oceanic and Atmospheric Administration’s Real-Time Mesoscale Analysis (RTMA) at airport locations throughout the United States since 2015, with these data substituting for missing temperature observations and mitigating impacts on air travel. A quality assessment of the RTMA is performed to determine if the RTMA could be used in a similar fashion for other weather observations, such as 10-m wind, ceiling, and visibility. Retrospective, data-denial experiments are used to perform the quality assessment by withholding observations from FAA-specified airports. Outliers seen in the RTMA ceiling and visibility analyses during events meeting or exceeding instrument flight rules suggest the RTMA should not be substituted for missing ceiling and visibility observations at this time. The RTMA is a suitable replacement for missing temperature observations for a subset of airports throughout most of the CONUS and Alaska, but not at all stations. Likewise, the RTMA is a suitable substitute for missing surface pressure observations at a subset of airports, with notable exceptions in regions of complex terrain. The RTMA may also be a suitable substitute for missing wind speed observations, provided the wind speed is ≤15 kt (1 kt ≈ 0.51 m s⁻¹). Overall, these results suggest the potential for RTMA to substitute for additional missing observations while highlighting priority areas of future work for improving the RTMA.

During May–July 2000, the Severe Thunderstorm Electrification and Precipitation Study (STEPS) occurred in the High Plains, near the Colorado–Kansas border. STEPS aimed to achieve a better understanding of the interactions between kinematics, precipitation, and electrification in severe thunderstorms. Specific scientific objectives included 1) understanding the apparent major differences in precipitation output from supercells that have led to them being classified as low precipitation (LP), classic or medium precipitation, and high precipitation; 2) understanding lightning formation and behavior in storms, and how lightning differs among storm types, particularly to better understand the mechanisms by which storms produce predominantly positive cloud-to-ground (CG) lightning; and 3) verifying and improving microphysical interpretations from polarimetric radar. The project involved the use of a multiple-Doppler polarimetric radar network, as well as a time-of-arrival very high frequency (VHF) lightning mapping system, an armored research aircraft, electric field meters carried on balloons, mobile mesonet vehicles, instruments to detect and classify transient luminous events (TLEs; e.g., sprites and blue jets) over thunderstorms, and mobile atmospheric sounding equipment. The project featured significant collaboration with the local National Weather Service office in Goodland, Kansas, as well as outreach to the general public. The project gathered data on a number of different cases, including LP storms, supercells, and mesoscale convective systems, among others. Many of the storms produced mostly positive CG lightning during significant portions of their lifetimes and also exhibited unusual electrical structures with opposite polarity to ordinary thunderstorms. The field data from STEPS is expected to bring new advances to understanding of supercells, positive CG lightning, TLEs, and precipitation formation in convective storms.

We review the progress of tropospheric trace gas observations and address the need for additional measurement capabilities as recommended by the National Research Council. Tropospheric measurements show pollution in the Northern Hemisphere as a result of fossil fuel burning and a strong seasonal dependence with the largest amounts of carbon monoxide and nitrogen dioxide in the winter and spring. In the summer, when photochemistry is most intense, photochemically generated ozone is found in large concentrations over and downwind from where anthropogenic sources are largest, such as the eastern United States and eastern China. In the tropics and the subtropics, where photon flux is strong throughout the year, trace gas concentrations are driven by the abundance of the emissions. The largest single tropical source of pollution is biomass burning, as can be seen readily in carbon monoxide measurements, but lightning and biogenic trace gases may also contribute to trace gas variability. Although substantive progress has been achieved in seasonal and global mapping of a few tropospheric trace gases, satellite trace gas observations with considerably better temporal and spatial resolution are essential to forecasting air quality at the spatial and temporal scales required by policy makers. The concurrent use of atmospheric composition measurements for both scientific and operational purposes is a new paradigm for the atmospheric chemistry community. The examples presented illustrate both the promise and challenge of merging satellite information with in situ observations in state-of-the-art data assimilation models.

A series of water vapor intensive observation periods (WVIOPs) were conducted at the Atmospheric Radiation Measurement (ARM) site in Oklahoma between 1996 and 2000. The goals of these WVIOPs are to characterize the accuracy of the operational water vapor observations and to develop techniques to improve the accuracy of these measurements.

The initial focus of these experiments was on the lower atmosphere, for which the goal is an absolute accuracy of better than 2% in total column water vapor, corresponding to ~1 W m⁻² of infrared radiation at the surface. To complement the operational water vapor instruments during the WVIOPs, additional instrumentation including a scanning Raman lidar, microwave radiometers, chilled-mirror hygrometers, a differential absorption lidar, and ground-based solar radiometers were deployed at the ARM site. The unique datasets from the 1996, 1997, and 1999 experiments have led to many results, including the discovery and characterization of a large (> 25%) sonde-to-sonde variability in the water vapor profiles from Vaisala RS-80H radiosondes that acts like a height-independent calibration factor error. However, the microwave observations provide a stable reference that can be used to remove a large part of the sonde-to-sonde calibration variability. In situ capacitive water vapor sensors demonstrated agreement within 2% of chilled-mirror hygrometers at the surface and on an instrumented tower. Water vapor profiles retrieved from two Raman lidars, which have both been calibrated to the ARM microwave radiometer, showed agreement to within 5% for all altitudes below 8 km during two WVIOPs. The mean agreement of the total precipitable water vapor from different techniques has converged significantly from early analysis that originally showed differences up to 15%. Retrievals of total precipitable water vapor (PWV) from the ARM microwave radiometer are now found to be only 3% moister than PWV derived from new GPS results, and about 2% drier than the mean of radiosonde data after a recently defined sonde dry-bias correction is applied. Raman lidar profiles calibrated using tower-mounted chilled-mirror hygrometers confirm the expected sensitivity of microwave radiometer data to water vapor changes, but it is drier than the microwave radiometer (MWR) by 0.95 mm for all PWV amounts. However, observations from different collocated microwave radiometers have shown larger differences than expected and attempts to resolve the remaining inconsistencies (in both calibration and forward modeling) are continuing.

The paper concludes by outlining the objectives of the recent 2000 WVIOP and the ARM–First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX), the latter of which switched the focus to characterizing upper-tropospheric humidity measurements.