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Michael R. Weber and C. Bruce Baker

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Michael N. Baker and Derek M. Cunnold

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A contour advection technique, contour advection with surgery (CAS), is applied to the Northern Hemisphere Arctic vortex during several dynamically active periods in midwinter and at several different levels in the stratosphere. The ability of the technique to accurately depict vortex evolution is assessed. Isentropic potential vorticity (PV) is used as the dynamic tracer, and observed winds on isentropic surfaces are used to advect the PV contours. Results of the current study show that while it may provide a continuous view of vortex evolution that is spatially and temporally consistent, quantitative information regarding vortex area change derived from CAS is of limited utility. The results are shown to be somewhat sensitive to subtle differences in the wind and PV fields for quantities (such as area) that develop slowly in time. Increasing the temporal resolution of the advecting wind field does not appear to improve the agreement between CAS results and model or observed data. The poor correspondence between the area changes from CAS and those derived from analyzed data suggests that diabatic effects during most of these events are important. Percentage differences between the CAS and the analyzed PV contours are more pronounced above the lower region of the stratosphere, and a large part of the differences are acquired in the first day of a CAS calculation. Contour length parameters such as e-folding time are relatively insensitive to uncertainties in the initial conditions, suggesting that quantities that change rapidly (as length does) are better determined by CAS; however, the filamentary structure contributes little to vortex area results.

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Temple R. Lee, Michael Buban, Edward Dumas, and C. Bruce Baker

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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.

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Michael S. Buban, Temple R. Lee, and C. Bruce Baker

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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.

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Temple R. Lee, Michael Buban, David D. Turner, Tilden P. Meyers, and C. Bruce Baker

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The High-Resolution Rapid Refresh (HRRR) model became operational at the National Centers for Environmental Prediction (NCEP) in 2014 but the HRRR’s performance over certain regions of the coterminous United States has not been well studied. In the present study, we evaluated how well version 2 of the HRRR, which became operational at NCEP in August 2016, simulates the near-surface meteorological fields and the surface energy balance at two locations in northern Alabama. We evaluated the 1-, 3-, 6-, 12-, and 18-h HRRR forecasts, as well as the HRRR’s initial conditions (i.e., the 0-h initial fields) using meteorological and flux observations obtained from two 10-m micrometeorological towers installed near Belle Mina and Cullman, Alabama. During the 8-month model evaluation period, from 1 September 2016 to 30 April 2017, we found that the HRRR accurately simulated the observations of near-surface air and dewpoint temperature (R 2 > 0.95). When comparing the HRRR output with the observed sensible, latent, and ground heat flux at both sites, we found that the agreement was weaker (R 2 ≈ 0.7), and the root-mean-square errors were much larger than those found for the near-surface meteorological variables. These findings help motivate the need for additional work to improve the representation of surface fluxes and their coupling to the atmosphere in future versions of the HRRR to be more physically realistic.

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John H. Sorensen, Michael K. Lindell, Earl J. Baker, and William P. Lehman

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Hurricane evacuation warnings from local officials are one of the most significant determinants of households’ evacuation departure times. Consequently, it is important to know how long after the National Hurricane Center (NHC) issues a hurricane watch or warning that local officials wait to issue evacuation warnings. The distribution of local evacuation warning issuance delays determined from poststorm assessment data shows a wide range of warning issuance delay times over an 85-h time span, although the vast majority of times fall within a 40-h window. Nearly 30% of the jurisdictions issued evacuation warnings before an NHC hurricane warning. Only 5% delayed the decision for more than 25 h after the NHC hurricane warning. The curves for warning issuance delays, using both the NHC watch and NHC warning issuance times as reference points, are very different from the warning issuance curves observed for the rapid-onset events. The hurricane data exhibit much more of an “S shape” than the exponential shape that is seen for rapid-onset data. Instead, curves for three different types of storm tracks, defined by a perpendicular/parallel dimension and a straight/meandering dimension, follow three noticeably different logistic distributions. The data also indicate that warnings were issued significantly earlier for coastal counties than for inland counties. These results have direct practical value to analysts that are calculating evacuation time estimates for coastal jurisdictions. Moreover, they suggest directions for future research on the reasons for the timing of local officials’ hurricane evacuation decisions.

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Louis W. Uccellini, Paul J. Kocin, Joseph Sienkiewicz and, Robert Kistler, and Michael Baker

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Fred Sanders' career extended over 55 yr, touching upon many of the revolutionary transformations in the field of meteorology during that period. In this paper, his contributions to the transformation of synoptic meteorology, his research into the nature of explosive cyclogenesis, and related advances in the ability to predict these storms are reviewed. In addition to this review, the current status of forecasting oceanic cyclones 4.5 days in advance is presented, illustrating the progress that has been made and the challenges that persist, especially for forecasting those extreme extratropical cyclones that are marked by surface wind speeds exceeding hurricane force. Last, Fred Sanders' participation in a forecast for the historic 1947 snowstorm (that produced snowfall amounts in the New York City area that set records at that time) is reviewed along with an attempt to use today's operational global model to simulate this storm using data that were available at the time. The study reveals the predictive limitations involved with this case based on the scarcity of upper-air data in 1947, while confirming Fred Sanders' forecasting skills when dealing with these types of major storm events, even as a young aviation forecaster at New York's LaGuardia Airport.

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Howard J. Diamond, Thomas R. Karl, Michael A. Palecki, C. Bruce Baker, Jesse E. Bell, Ronald D. Leeper, David R. Easterling, Jay H. Lawrimore, Tilden P. Meyers, Michael R. Helfert, Grant Goodge, and Peter W. Thorne

The year 2012 marks a decade of observations undertaken by the U.S. Climate Reference Network (USCRN) under the auspices of NOAA's National Climatic Data Center and Atmospheric Turbulence and Diffusion Division. The network consists of 114 sites across the conterminous 48 states, with additional sites in Alaska and Hawaii. Stations are installed in open (where possible), rural sites very likely to have stable land-cover/use conditions for several decades to come. At each site a suite of meteorological parameters are monitored, including triple redundancy for the primary air temperature and precipitation variables and for soil moisture/temperature. Instrumentation is regularly calibrated to National Institute for Standards and Technology (NIST) standards and maintained by a staff of expert engineers. This attention to detail in USCRN is intended to ensure the creation of an unimpeachable record of changes in surface climate over the United States for decades to come. Data are made available without restriction for all public, private, and government use. This article describes the rationale for the USCRN, its implementation, and some of the highlights of the first decade of operations. One critical use of these observations is as an independent data source to verify the existing U.S. temperature record derived from networks corrected for nonhomogenous histories. Future directions for the network are also discussed, including the applicability of USCRN approaches for networks monitoring climate at scales from regional to global. Constructive feedback from end users will allow for continued improvement of USCRN in the future and ensure that it continues to meet stakeholder requirements for precise climate measurements.

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Yongjiu Dai, Xubin Zeng, Robert E. Dickinson, Ian Baker, Gordon B. Bonan, Michael G. Bosilovich, A. Scott Denning, Paul A. Dirmeyer, Paul R. Houser, Guoyue Niu, Keith W. Oleson, C. Adam Schlosser, and Zong-Liang Yang

The Common Land Model (CLM) was developed for community use by a grassroots collaboration of scientists who have an interest in making a general land model available for public use and further development. The major model characteristics include enough unevenly spaced layers to adequately represent soil temperature and soil moisture, and a multilayer parameterization of snow processes; an explicit treatment of the mass of liquid water and ice water and their phase change within the snow and soil system; a runoff parameterization following the TOPMODEL concept; a canopy photo synthesis-conductance model that describes the simultaneous transfer of CO2 and water vapor into and out of vegetation; and a tiled treatment of the subgrid fraction of energy and water balance. CLM has been extensively evaluated in offline mode and coupling runs with the NCAR Community Climate Model (CCM3). The results of two offline runs, presented as examples, are compared with observations and with the simulation of three other land models [the Biosphere-Atmosphere Transfer Scheme (BATS), Bonan's Land Surface Model (LSM), and the 1994 version of the Chinese Academy of Sciences Institute of Atmospheric Physics LSM (IAP94)].

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Jesse E. Bell, Michael A. Palecki, C. Bruce Baker, William G. Collins, Jay H. Lawrimore, Ronald D. Leeper, Mark E. Hall, John Kochendorfer, Tilden P. Meyers, Tim Wilson, and Howard J. Diamond

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The U.S. Climate Reference Network (USCRN) is a network of climate-monitoring stations maintained and operated by the National Oceanic and Atmospheric Administration (NOAA) to provide climate-science-quality measurements of air temperature and precipitation. The stations in the network were designed to be extensible to other missions, and the National Integrated Drought Information System program determined that the USCRN could be augmented to provide observations that are more drought relevant. To increase the network’s capability of monitoring soil processes and drought, soil observations were added to USCRN instrumentation. In 2011, the USCRN team completed at each USCRN station in the conterminous United States the installation of triplicate-configuration soil moisture and soil temperature probes at five standards depths (5, 10, 20, 50, and 100 cm) as prescribed by the World Meteorological Organization; in addition, the project included the installation of a relative humidity sensor at each of the stations. Work is also under way to eventually install soil sensors at the expanding USCRN stations in Alaska. USCRN data are stewarded by the NOAA National Climatic Data Center, and instrument engineering and performance studies, installation, and maintenance are performed by the NOAA Atmospheric Turbulence and Diffusion Division. This article provides a technical description of the USCRN soil observations in the context of U.S. soil-climate–measurement efforts and discusses the advantage of the triple-redundancy approach applied by the USCRN.

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