Kenneth W. Howard

The pronounced maximum in rainfall during the warm season over southwestern North America has been noted by various investigators. In the United States this is most pronounced over New Mexico and southern Arizona; however, it is but an extension of a much larger-scale phenomenon that appears to be centered over northwestern Mexico. This phenomenon, herein termed the “Mexican monsoon,” is described from analyses of monthly mean rainfall, geostationary satellite imagery, and rawinsonde data. In particular, the authors note the geographical extent and magnitude of the summer rains, the rapidity of their onset, and the timing of the month of maximum rainfall. Finally, the difficulty in explaining the observed precipitation distribution and its timing from monthly mean upper-air wind and moisture patterns is discussed.

Abstract Rapid advancements of computer technologies in recent years made the real-time transferring and integration of high-volume, multisource data at a centralized location a possibility. The Multi-Radar Multi-Sensor (MRMS) system recently implemented at the National Centers for Environmental Prediction demonstrates such capabilities by integrating about 180 operational weather radars from the conterminous United States and Canada into a seamless national 3D radar mosaic with very high spatial (1 km) and temporal (2 min) resolution. The radar data can be integrated with high-resolution numerical weather prediction model data, satellite data, and lightning and rain gauge observations to generate a suite of severe weather and quantitative precipitation estimation (QPE) products. This paper provides an overview of the initial operating capabilities of MRMS QPE products.

The National Mosaic and Multi-sensor QPE (Quantitative Precipitation Estimation), or “NMQ”, system was initially developed from a joint initiative between the National Oceanic and Atmospheric Administration's National Severe Storms Laboratory, the Federal Aviation Administration's Aviation Weather Research Program, and the Salt River Project. Further development has continued with additional support from the National Weather Service (NWS) Office of Hydrologic Development, the NWS Office of Climate, Water, and Weather Services, and the Central Weather Bureau of Taiwan. The objectives of NMQ research and development (R&D) are 1) to develop a hydrometeorological platform for assimilating different observational networks toward creating high spatial and temporal resolution multisensor QPEs for f lood warnings and water resource management and 2) to develop a seamless high-resolution national 3D grid of radar reflectivity for severe weather detection, data assimilation, numerical weather prediction model verification, and aviation product development. Through about ten years of R&D, a real-time NMQ system has been implemented (http://nmq.ou.edu). Since June 2006, the system has been generating high-resolution 3D reflectivity mosaic grids (31 vertical levels) and a suite of severe weather and QPE products in real-time for the conterminous United States at a 1-km horizontal resolution and 2.5 minute update cycle. The experimental products are provided in real-time to end users ranging from government agencies, universities, research institutes, and the private sector and have been utilized in various meteorological, aviation, and hydrological applications. Further, a number of operational QPE products generated from different sensors (radar, gauge, satellite) and by human experts are ingested in the NMQ system and the experimental products are evaluated against the operational products as well as independent gauge observations in real time. The NMQ is a fully automated system. It facilitates systematic evaluations and advances of hydrometeorological sciences and technologies in a real-time environment and serves as a test bed for rapid science-to-operation infusions. This paper describes scientific components of the NMQ system and presents initial evaluation results and future development plans of the system.

Subsurface flow within a single riffle of a low‐gradient gravel bed stream was modeled in three dimensions using MODFLOW, a finite difference groundwater flow model. Model simulations showed that exchange flows can only occur in this low‐gradient, gaining stream because of a zone of alluvial sediment around the stream that has much higher permeability than the surrounding catchment ( K = 10 −4 m s −1 , compared with K = 10 −6 to 10 −8 m s −1 ). The key factors controlling exchange flow within the alluvial zone were identified as the hydraulic conductivity of the alluvium, the hydraulic gradient between upstream and downstream ends of the riffle, and the flux of groundwater entering the alluvium from the sides and beneath. In the study riffle each of these factors changes with season, causing a reversal of flow paths in the alluvium and a reduction in exchange flows from about 0.2–0.5 m 3 d −1 per meter stream length in summer to about 0.008–0.04 m 3 d −1 per meter stream length during fall to spring. The model also revealed that exchange flows are up to twice as strong, but more variable, at the sides of the stream than near the center, and that vertical flow paths beneath the channel are more persistent under the range of conditions modeled than lateral flow paths into the banks.

Terrain and radar beam-elevation data are used to examine the spatial coverage provided by the national operational network of Doppler weather radars. This information is of importance to a wide variety of users, and potential users, of radar data from the national network. Charts generated for radar coverage at 3 and 5 km above mean sea level show that radar surveillance near 700 and 500 hPa is very limited for some portions of the contiguous United States. Radar coverage charts at heights of 1, 2, and 3 km above ground level illustrate the extent of low-level radar data gathered above the actual land surface. These maps indicate how restricted the national radar network coverage is at low levels, which limits the usefulness of the radar data, especially for quantitative precipitation estimation. The analyses also identify several regions of the contiguous United States in which weather phenomena are sampled by many adjacent radars. Thus, these regions are characterized by very comprehensive radar information that could be used in many kinds of research studies.