Since drought and excessive rainfall can have significant socioeconomic impacts, it is important to have accurate high-resolution gridded datasets that can help improve analysis and forecasting of these conditions. One such widely used dataset is the Parameter-Elevation Regressions on Independent Slopes Model (PRISM). PRISM uses a digital elevation model (DEM) to obtain gridded elevation analyses and then uses a regression analysis along with approximately 15 000 surface precipitation measurements to produce a 4-km resolution daily precipitation product over the conterminous United States. The U.S. Climate Reference Network (USCRN) consists of 114 stations that take highly accurate meteorological measurements across all regions of the United States. A comparison between the USCRN and PRISM was performed using data from 2006 to 2018. There were good comparisons between the two datasets across nearly all seasons and regions; most mean daily differences were <1 mm, with most absolute daily differences ~5 mm. The most general characteristics were for a net dry bias in the PRISM data in the Southwest and a net moist bias in the southern United States. Verifying the PRISM dataset provides us with confidence it can be used with estimates of evapotranspiration, high-resolution gridded soil properties, and vegetation datasets to produce a daily gridded soil moisture product for operational use in the analyses and prediction of drought and excessive soil moisture conditions.
Rotary-wing small unmanned aircraft systems (sUAS) are increasingly being used for sampling thermodynamic and chemical properties of the Earth’s atmospheric boundary layer (ABL) because of their ability to measure at high spatial and temporal resolutions. Therefore, they have the potential to be used for long-term quasi-continuous monitoring of the ABL, which is critical for improving ABL parameterizations and improving numerical weather prediction (NWP) models through data assimilation. Before rotary-wing aircraft can be used for these purposes, however, their performance and the sensors used therein must be adequately characterized. In the present study, we describe recent calibration and validation procedures for thermodynamic sensors used on two rotary-wing aircraft: A DJI S-1000 and MD4-1000. These evaluations indicated a high level of confidence in the on-board measurements. We then used these measurements to characterize the spatiotemporal variability of near-surface (up to 300-m AGL) temperature and moisture fields as a component of two recent field campaigns: The Verification of the Origins of Rotation in Tornadoes Experiment in the Southeast U.S. (VORTEX-SE) in Alabama, and the Land Atmosphere Feedback Experiment (LAFE) in northern Oklahoma.
On the afternoon and evening of 22 May 2002, high-resolution observations of the boundary layer (BL) and a dryline were obtained in the eastern Oklahoma and Texas panhandles during the International H2O Project. Using overdetermined multiple-Doppler radar syntheses in concert with a Lagrangian analysis of water vapor and temperature fields, the 3D kinematic and thermodynamic structure of the dryline and surrounding BL have been analyzed over a nearly 2-h period. The dryline is resolved as a strong (2–4 g kg−1 km−1) gradient of water vapor mixing ratio that resides in a nearly north–south-oriented zone of convergence. Maintained through frontogenesis, the dryline is also located within a gradient of virtual potential temperature, which induces a persistent, solenoidally forced secondary circulation. Initially quasi-stationary, the dryline retrogrades to the west during early evening and displays complicated substructures including small wavelike perturbations that travel from south to north at nearly the speed of the mean BL flow. A second, minor dryline has similar characteristics to the first, but has weaker gradients and circulations. The BL adjacent to the dryline exhibits complicated structures, consisting of combinations of open cells, horizontal convective rolls, and transverse rolls. Strong convergence and vertical motion at the dryline act to lift moisture, and high-based cumulus clouds are observed in the analysis domain. Although the top of the analysis domain is below the lifted condensation level height, vertical extrapolation of the moisture fields generally agrees with cloud locations. Mesoscale vortices that move along the dryline induce a transient eastward dryline motion due to the eastward advection of dry air following misocyclone passage. Refractivity-based moisture and differential reflectivity analyses are used to help interpret the Lagrangian analyses.
1 September 2017 in Journal of Atmospheric and Oceanic Technology
Upscaling point measurements from micrometeorological towers is a challenging task that is important for a variety of applications, for example, in process studies of convection initiation, carbon and energy budget studies, and the improvement of model parameterizations. In the present study, a technique was developed to determine the horizontal variability in sensible heat flux H surrounding micrometeorological towers. The technique was evaluated using 15-min flux observations, as well as measurements of land surface temperature and air temperature obtained from small unmanned aircraft systems (sUAS) conducted during a one-day measurement campaign. The computed H was found to be comparable to the micrometeorological measurements to within 5–10 W m−2. Furthermore, when comparing H computed using this technique with H determined using large-eddy simulations (LES), differences of <10 W m−2 were typically found. Thus, implementing this technique using observations from sUAS will help determine sensible heat flux variability at horizontal spatial scales larger than can be provided from flux tower measurements alone.
Cumulus formation and convection initiation are examined near a cold front–dryline “triple point” intersection on 24 May 2002 during the International H2O Project (IHOP). A new Lagrangian objective analysis technique assimilates in situ measurements using time-dependent Doppler-derived 3D wind fields, providing output 3D fields of water vapor mixing ratio, virtual potential temperature, and lifted condensation level (LCL) and water-saturated (i.e., cloud) volumes on a subdomain of the radar analysis grid. The radar and Lagrangian analyses reveal the presence of along-wind (i.e., longitudinal) and cross-wind (i.e., transverse) roll circulations in the boundary layer (BL). A remarkable finding of the evolving radar analyses is the apparent persistence of both transverse rolls and individual updraft, vertical vorticity, and reflectivity cores for periods of up to 30 min or more while moving approximately with the local BL wind. Satellite cloud images and single-camera ground photogrammetry imply that clouds tend to develop either over or on the downwind edge of BL updrafts, with a tendency for clouds to elongate and dissipate in the downwind direction relative to cloud layer winds due to weakening updrafts and mixing with drier overlying air. The Lagrangian and radar wind analyses support a parcel continuity principle for cumulus formation, which requires that rising moist air parcels achieve their LCL before moving laterally out of the updraft. Cumuli form within penetrative updrafts in the elevated residual layer (ERL) overlying the moist BL east of the triple point, but remain capped by a convection inhibition (CIN)-bearing layer above the ERL. Dropsonde data suggest the existence of a convergence line about 80 km east of the triple point where deep lifting of BL moisture and locally reduced CIN together support convection initiation.