This study explores an analog-based method to generate an ensemble [analog ensemble (AnEn)] in which the probability distribution of the future state of the atmosphere is estimated with a set of past observations that correspond to the best analogs of a deterministic numerical weather prediction (NWP). An analog for a given location and forecast lead time is defined as a past prediction, from the same model, that has similar values for selected features of the current model forecast. The AnEn is evaluated for 0–48-h probabilistic predictions of 10-m wind speed and 2-m temperature over the contiguous United States and against observations provided by 550 surface stations, over the 23 April–31 July 2011 period. The AnEn is generated from the Environment Canada (EC) deterministic Global Environmental Multiscale (GEM) model and a 12–15-month-long training period of forecasts and observations. The skill and value of AnEn predictions are compared with forecasts from a state-of-the-science NWP ensemble system, the 21-member Regional Ensemble Prediction System (REPS). The AnEn exhibits high statistical consistency and reliability and the ability to capture the flow-dependent behavior of errors, and it has equal or superior skill and value compared to forecasts generated via logistic regression (LR) applied to both the deterministic GEM (as in AnEn) and REPS [ensemble model output statistics (EMOS)]. The real-time computational cost of AnEn and LR is lower than EMOS.

This study documents the global distribution and characteristics of diurnally varying low-level jets (LLJs), including their horizontal, vertical, and temporal structure, with a special emphasis on highlighting the underlying commonalities and unique qualities of the various nocturnal jets. Two tools are developed to accomplish this goal. The first is a 21-yr global reanalysis performed with the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5) using a horizontal grid spacing of 40 km. A unique characteristic of the reanalysis is the availability of hourly three-dimensional output, which permits the full diurnal cycle to be analyzed. Furthermore, the horizontal grid spacing of 40 km better resolves many physiographic features that host LLJs than other widely used global reanalyses. This makes possible a detailed examination of the systematic onset and cessation of the jets, including time-height representations of the diurnal cycle. The second tool is an index of nocturnal LLJ (NLLJ) activity based upon the vertical structure of the wind's temporal variation, where the temporal variation is defined in local time. The first available objectively constructed global maps of recurring NLLJs are created from this index, where the various NLLJs can be simultaneously viewed at or near their peak time. These maps not only highlight all of the locations where NLLJs are known to recur, but they also reveal a number of new jets.The authors examine the basic mechanisms that give rise to the NLLJs identified in four disparate locations, each having a profound influence on the regional climate. The first, the extensively studied Great Plains NLLJ, is used to confirm the veracity of the global analysis and the index of NLLJ activity. It also provides context for three of the many newly identified NLLJs: 1) Tarim Pendi in northwest China; 2) Ethiopia in eastern Africa; and 3) Namibia-Angola in southwest Africa. Jets in these four regions illustrate the variety of physiographic and thermal forcing mechanisms that can produce NLLJs.

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Given the rapid increase in the use of operational mesoscale models to satisfy different specialized needs, it is important for the community to share ideas and solutions for meeting the many associated challenges that encompass science, technology, education, and training. As a contribution toward this objective, this paper begins a series that reports on the characteristics and performance of an operational mesogammascale weather analysis and forecasting system that has been developed for use by the U.S. Army Test and Evaluation Command. During the more than five years that this four-dimensional weather system has been in use at seven U.S. Army test ranges, valuable experience has been gained about the production and effective use of high-resolution model products for satisfying a variety of needs. This paper serves as a foundation for the rest of the papers in the series by describing the operational requirements for the system, the data assimilation and forecasting system characteristics, and the forecaster training that is required for the finescale products to be used effectively.&& The National Center for Atmospheric Research is sponsored by the National Science Foundation.

The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge is how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, 'building the bridge' means developing models for the so-called 'terra incognita,' a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to guide future research in this area. mesoscale model at~4 km horizontal resolution (a), nested down with WRF to 1.67 and 0.55 km resolution, and introducing microscale speedups with WAsP at 100 m resolution (b). (Reprinted with permission from Ref 35.