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Jessica M. Erlingis and Ana P. Barros

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This study examines whether and how land–atmosphere interactions can have an impact on nocturnal convection over the southern Great Plains (SGP) through numerical simulations of an intense nocturnal mesoscale convective system (MCS) on 19–20 June 2007 with the Weather Research and Forecasting (WRF) Model. High-resolution nested simulations were conducted using realistic and idealized land surfaces and two planetary boundary layer (PBL) parameterizations (PBLp): Yonsei University (YSU) and Mellor–Yamada–Janjić (MYJ). Differences in timing and amount of MCS precipitation among observations and model results were examined in the light of daytime land–atmosphere interactions, nocturnal prestorm environment, and cold pool strength. At the meso-γ scale, land cover and soil type have as much of an effect on the simulated prestorm environment as the choice of PBLp: MYJ simulations exhibit strong sensitivity to changes in the land surface in contrast to negligible impact in the case of YSU. At the end of the afternoon, as the boundary layer collapses, a more homogeneous and deeper PBL (and stronger low-level shear) is evident for YSU as compared to MYJ when initial conditions and land surface properties are the same. At the meso-β scale, propagation speed is faster and organization (bow echo morphology) and cold pool strength are enhanced when nocturnal PBL heights are higher, and there is stronger low-level shear in the prestorm environment independent of the boundary layer parameterization for different land surface conditions. A comparison of one- and two-way nested MYJ results demonstrates how daytime land–atmosphere interactions modify the prestorm environment remotely through advection of low-level thermodynamic features. This remote feedback strongly impacts the MCS development phase as well as its spatial organization and propagation velocity and, consequently, nocturnal rainfall. These results indicate that synoptic- and meso-α-scale dynamics can play an important role in determining the spatial and temporal scales over which precipitation feedbacks of land–atmosphere interactions emerge regionally. Finally, this study demonstrates the high degree of uncertainty in defining the spatial and temporal scales of land–atmosphere interactions where and when organized convection is dominant.

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Jessica M. Erlingis, Jonathan J. Gourley, and Jeffrey B. Basara

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This study uses backward trajectories derived from North American Regional Reanalysis data for 19 253 flash flood reports during the period 2007–13 published by the National Weather Service to assess the origins of air parcels for flash floods in the conterminous United States. The preferred flow paths for parcels were evaluated seasonally and for six regions of interest: the West Coast, Arizona, the Front Range of the Rocky Mountains, Flash Flood Alley in south-central Texas, the Missouri Valley, and the Appalachians. Parcels were released from vertical columns in the atmosphere at times and locations where there were reported flash floods; these were traced backward in time for 5 days. The temporal and seasonal cycles of flood events in these regions are also explored. The results show the importance of trajectories residing for long periods over oceanic regions such as the Gulf of Mexico and the Caribbean Sea. The flow is generally unidirectional with height in the lower layers of the atmosphere. The trajectory paths from oceanic genesis regions to inland hotspots and their orientation with height provide clues that can assist in the diagnosis of impending flash floods. Part II of this manuscript details the land–atmosphere interactions along the trajectory paths.

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Jessica M. Erlingis, Jonathan J. Gourley, and Jeffrey B. Basara

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Backward trajectories were derived from North American Regional Reanalysis data for 19 253 flash flood reports published by the National Weather Service to determine the along-path contribution of the land surface to the moisture budget for flash flood events in the conterminous United States. The impact of land surface interactions was evaluated seasonally and for six regions: the West Coast, Arizona, the Front Range, Flash Flood Alley, the Missouri Valley, and the Appalachians. Parcels were released from locations that were impacted by flash floods and traced backward in time for 120 h. The boundary layer height was used to determine whether moisture increases occurred within the boundary layer or above it. Moisture increases occurring within the boundary layer were attributed to evapotranspiration from the land surface, and surface properties were recorded from an offline run of the Noah land surface model. In general, moisture increases attributed to the land surface were associated with anomalously high surface latent heat fluxes and anomalously low sensible heat fluxes (resulting in a positive anomaly of evaporative fraction) as well as positive anomalies in top-layer soil moisture. Over the ocean, uptakes were associated with positive anomalies in sea surface temperatures, the magnitude of which varies both regionally and seasonally. Major oceanic surface-based source regions of moisture for flash floods in the United States include the Gulf of Mexico and the Gulf of California, while boundary layer moisture increases in the southern plains are attributable in part to interactions between the land surface and the atmosphere.

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Bailing Li, Matthew Rodell, Christa Peters-Lidard, Jessica Erlingis, Sujay Kumar, and David Mocko

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Estimating diffuse recharge of precipitation is fundamental to assessing groundwater sustainability. Diffuse recharge is also the process through which climate and climate change directly affect groundwater. In this study, we evaluated diffuse recharge over the conterminous United States simulated by a suite of land surface models (LSMs) that were forced using a common set of meteorological input data. Simulated annual recharge exhibited spatial patterns that were similar among the LSMs, with the highest values in the eastern United States and Pacific Northwest. However, the magnitudes of annual recharge varied significantly among the models and were associated with differences in simulated ET, runoff, and snow. Evaluation against two independent datasets did not answer the question of whether the ensemble mean performs the best, due to inconsistency between those datasets. The amplitude and timing of seasonal maximum recharge differed among the models, influenced strongly by model physics governing deep soil moisture drainage rates and, in cold regions, snowmelt. Evaluation using in situ soil moisture observations suggested that true recharge peaks 1–3 months later than simulated recharge, indicating systematic biases in simulating deep soil moisture. However, recharge from lateral flows and through preferential flows cannot be inferred from soil moisture data, and the seasonal cycle of simulated groundwater storage actually compared well with in situ groundwater observations. Long-term trends in recharge were not consistently correlated with either precipitation trends or temperature trends. This study highlights the need to employ dynamic flow models in LSMs, among other improvements, to enable more accurate simulation of recharge.

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Jonathan J. Gourley, Jessica M. Erlingis, Yang Hong, and Ernest B. Wells

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This paper evaluates, for the first time, flash-flood guidance (FFG) values and recently developed gridded FFG (GFFG) used by the National Weather Service (NWS) to monitor and predict imminent flash flooding, which is the leading storm-related cause of death in the United States. It is envisioned that results from this study will be used 1) to establish benchmark performance of existing operational flash-flood prediction tools and 2) to provide information to NWS forecasters that reveals how the existing tools can be readily optimized. Sources used to evaluate the products include official reports of flash floods from the NWS Storm Data database, discharge measurements on small basins available from the U.S. Geological Survey, and witness reports of flash flooding collected during the Severe Hazards Analysis and Verification Experiment. Results indicated that the operational guidance values, with no calibration, were marginally skillful, with the highest critical success index of 0.20 occurring with 3-h GFFG. The false-alarm rates fell and the skill improved to 0.34 when the rainfall was first spatially averaged within basins and then reached 50% of FFG for 1-h accumulation and exceeded 3-h FFG. Although the skill of the GFFG values was generally lower than that of their FFG counterparts, GFFG was capable of detecting the spatial variability of reported flash flooding better than FFG was for a case study in an urban setting.

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Pierre-Emmanuel Kirstetter, Tian-You Yu, Robert Palmer, David Parsons, Hirohiko Ishikawa, and Jessica M. Erlingis
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Jessica M. Erlingis, Jonathan J. Gourley, Pierre-Emmanuel Kirstetter, Emmanouil N. Anagnostou, John Kalogiros, Marios N. Anagnostou, and Walt Petersen

Abstract

During May and June 2014, NOAA X-Pol (NOXP), the National Severe Storms Laboratory’s dual-polarized X-band mobile radar, was deployed to the Pigeon River basin in the Great Smoky Mountains of North Carolina as part of the NASA Integrated Precipitation and Hydrology Experiment. Rain gauges and disdrometers were positioned within the basin to verify precipitation estimates from various radar and satellite precipitation algorithms. First, the performance of the Self-Consistent Optimal Parameterization–Microphysics Estimation (SCOP-ME) algorithm for NOXP was examined using ground instrumentation as validation and was found to perform similarly to or slightly outperform other precipitation algorithms over the course of the intensive observation period (IOP). Radar data were also used to examine ridge–valley differences in radar and microphysical parameters for a case of stratiform precipitation passing over the mountains. Inferred coalescence microphysical processes were found to dominate within the upslope region, while a combination of processes were present as the system propagated over the valley. This suggests that enhanced updrafts aided by orographic lift sustain convection over the upslope regions, leading to larger median drop diameters.

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Steven M. Martinaitis, Jonathan J. Gourley, Zachary L. Flamig, Elizabeth M. Argyle, Robert A. Clark III, Ami Arthur, Brandon R. Smith, Jessica M. Erlingis, Sarah Perfater, and Benjamin Albright

Abstract

There are numerous challenges with the forecasting and detection of flash floods, one of the deadliest weather phenomena in the United States. Statistical metrics of flash flood warnings over recent years depict a generally stagnant warning performance, while regional flash flood guidance utilized in warning operations was shown to have low skill scores. The Hydrometeorological Testbed—Hydrology (HMT-Hydro) experiment was created to allow operational forecasters to assess emerging products and techniques designed to improve the prediction and warning of flash flooding. Scientific goals of the HMT-Hydro experiment included the evaluation of gridded products from the Multi-Radar Multi-Sensor (MRMS) and Flooded Locations and Simulated Hydrographs (FLASH) product suites, including the experimental Coupled Routing and Excess Storage (CREST) model, the application of user-defined probabilistic forecasts in experimental flash flood watches and warnings, and the utility of the Hazard Services software interface with flash flood recommenders in real-time experimental warning operations. The HMT-Hydro experiment ran in collaboration with the Flash Flood and Intense Rainfall (FFaIR) experiment at the Weather Prediction Center to simulate the real-time workflow between a national center and a local forecast office, as well as to facilitate discussions on the challenges of short-term flash flood forecasting. Results from the HMT-Hydro experiment highlighted the utility of MRMS and FLASH products in identifying the spatial coverage and magnitude of flash flooding, while evaluating the perception and reliability of probabilistic forecasts in flash flood watches and warnings.

NSSL scientists and NWS forecasters evaluate new tools and techniques through real-time test bed operations for the improvement of flash flood detection and warning operations.

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Xiaogang He, Hyungjun Kim, Pierre-Emmanuel Kirstetter, Kei Yoshimura, Eun-Chul Chang, Craig R. Ferguson, Jessica M. Erlingis, Yang Hong, and Taikan Oki

Abstract

As a basic form of climate patterns, the diurnal cycle of precipitation (DCP) can provide a key test bed for model reliability and development. In this study, the DCP over West Africa was simulated by the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) during the monsoon season (April–September) of 2005. Three convective parameterization schemes (CPSs), single-layer simplified Arakawa–Schubert (SAS), multilayer relaxed Arakawa–Schubert (RAS), and new Kain–Fritsch (KF2), were evaluated at two horizontal resolutions (20 and 10 km). The Benin mesoscale site was singled out for additional investigation of resolution effects. Harmonic analysis was used to characterize the phase and amplitude of the DCP. Compared to satellite observations, the overall spatial distributions of amplitude were well captured at regional scales. The RSM properly reproduced the observed late afternoon peak over land and the early morning peak over ocean. Nevertheless, the peak time was early. Sensitivity experiments of CPSs showed similar spatial patterns of rainfall totals among the schemes; CPSs mainly affected the amplitude of the diurnal cycle, while the phase was not significantly shifted. There is no clear optimal pairing of resolution and CPS. However, it is found that the sensitivity of DCP to CPSs and resolution varies with the partitioning between convective and stratiform, which implies that appropriate partitioning needs to be considered for future development of CPSs in global or regional climate models.

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Jonathan J. Gourley, Zachary L. Flamig, Humberto Vergara, Pierre-Emmanuel Kirstetter, Robert A. Clark III, Elizabeth Argyle, Ami Arthur, Steven Martinaitis, Galateia Terti, Jessica M. Erlingis, Yang Hong, and Kenneth W. Howard

Abstract

This study introduces the Flooded Locations and Simulated Hydrographs (FLASH) project. FLASH is the first system to generate a suite of hydrometeorological products at flash flood scale in real-time across the conterminous United States, including rainfall average recurrence intervals, ratios of rainfall to flash flood guidance, and distributed hydrologic model–based discharge forecasts. The key aspects of the system are 1) precipitation forcing from the National Severe Storms Laboratory (NSSL)’s Multi-Radar Multi-Sensor (MRMS) system, 2) a computationally efficient distributed hydrologic modeling framework with sufficient representation of physical processes for flood prediction, 3) capability to provide forecasts at all grid points covered by radars without the requirement of model calibration, and 4) an open-access development platform, product display, and verification system for testing new ideas in a real-time demonstration environment and for fostering collaborations.

This study assesses the FLASH system’s ability to accurately simulate unit peak discharges over a 7-yr period in 1,643 unregulated gauged basins. The evaluation indicates that FLASH’s unit peak discharges had a linear and rank correlation of 0.64 and 0.79, respectively, and that the timing of the peak discharges has errors less than 2 h. The critical success index with FLASH was 0.38 for flood events that exceeded action stage. FLASH performance is demonstrated and evaluated for case studies, including the 2013 deadly flash flood case in Oklahoma City, Oklahoma, and the 2015 event in Houston, Texas—both of which occurred on Memorial Day weekends.

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