Abstract

This paper describes aspects of tropical interannual ocean/atmosphere variability in the NCAR Community Climate System Model Version 2.0 (CCSM2). The CCSM2 tropical Pacific Ocean/atmosphere system exhibits much stronger biennial variability than is observed. However, a canonical correlation analysis technique decomposes the simulated boreal winter tropical Pacific sea surface temperature (SST) variability into two modes, both of which are related to atmospheric variability during the preceding boreal winter. The first mode of ocean/atmosphere variability is related to the strong biennial oscillation in which La Niña–related sea level pressure (SLP) conditions precede El Niño–like SST conditions the following winter. The second mode of variability indicates that boreal winter tropical Pacific SST anomalies can also be initiated by SLP anomalies over the subtropical central and eastern North Pacific 12 months earlier.

The evolution of both modes is characterized by recharge/discharge within the equatorial subsurface temperature field. For the first mode of variability, this recharge/discharge produces a lag between the basin-average equatorial Pacific isotherm depth anomalies and the isotherm–slope anomalies, equatorial SSTs, and wind stress fields. Significant anomalies are present up to a year before the boreal winter SLP variations and two years prior to the boreal winter ENSO-like events. For the second canonical factor pattern, the recharge/discharge mechanism is induced concurrent with the boreal winter SLP pattern approximately one year prior to the ENSO-like events, when isotherms initially deepen and change their slope across the basin. A rapid deepening of the isotherms in the eastern equatorial Pacific and a warming of the overlying SST anomalies then occurs during the subsequent 12 months.

Abstract

A forecaster-interactive capability was added to an automated convective storm nowcasting system [Auto-Nowcaster (ANC)] to allow forecasters to enhance the performance of 1-h nowcasts of convective storm initiation and evolution produced every 6 min. This Forecaster-Over-The-Loop (FOTL-ANC) system was tested at the National Weather Service Fort Worth–Dallas, Texas, Weather Forecast Office during daily operations from 2005 to 2010. The forecaster’s role was to enter the locations of surface convergence boundaries into the ANC prior to dissemination of nowcasts to the Center Weather Service Unit. Verification of the FOTL-ANC versus ANC (no human) nowcasts was conducted on the convective scale. Categorical verification scores were computed for 30 subdomains within the forecast domain. Special focus was placed on subdomains that included convergence boundaries for evaluation of forecaster involvement and impact on the FOTL-ANC nowcasts. The probability of detection of convective storms increased by 20%–60% with little to no change observed in the false-alarm ratios. Bias values increased from 0.8–1.0 to 1.0–3.0 with human involvement. The accuracy of storm nowcasts notably improved with forecaster involvement; critical success index (CSI) values increased from 0.15–0.25 (ANC) to 0.2–0.4 (FOTL-ANC). Over short time periods, CSI values as large as 0.6 were also observed. This study demonstrated definitively that forecaster involvement led to positive improvement in the nowcasts in most cases while causing no degradation in other cases; a few exceptions are noted. Results show that forecasters can play an important role in the production of rapidly updated, convective storm nowcasts for end users.

Abstract

Given the increasing use of the term “flash drought” by the media and scientific community, it is prudent to develop a consistent definition that can be used to identify these events and to understand their salient characteristics. It is generally accepted that flash droughts occur more often during the summer owing to increased evaporative demand; however, two distinct approaches have been used to identify them. The first approach focuses on their rate of intensification, whereas the second approach implicitly focuses on their duration. These conflicting notions for what constitutes a flash drought (i.e., unusually fast intensification vs short duration) introduce ambiguity that affects our ability to detect their onset, monitor their development, and understand the mechanisms that control their evolution. Here, we propose that the definition for “flash drought” should explicitly focus on its rate of intensification rather than its duration, with droughts that develop much more rapidly than normal identified as flash droughts. There are two primary reasons for favoring the intensification approach over the duration approach. First, longevity and impact are fundamental characteristics of drought. Thus, short-term events lasting only a few days and having minimal impacts are inconsistent with the general understanding of drought and therefore should not be considered flash droughts. Second, by focusing on their rapid rate of intensification, the proposed “flash drought” definition highlights the unique challenges faced by vulnerable stakeholders who have less time to prepare for its adverse effects.

Abstract

This study examines the evolution of soil moisture, evapotranspiration, vegetation, and atmospheric conditions during an unusual flash drought–flash recovery sequence that occurred across the south-central United States during 2015. This event was characterized by a period of rapid drought intensification (flash drought) during late summer that was terminated by heavy rainfall at the end of October that eliminated the extreme drought conditions over a 2-week period (flash recovery). A detailed analysis was performed using time series of environmental variables derived from meteorological, remote sensing, and land surface modeling datasets. Though the analysis revealed a similar progression of cascading effects in each region, characteristics of the flash drought such as its onset time, rate of intensification, and vegetation impacts differed between regions due to variations in the antecedent conditions and the atmospheric anomalies during its growth. Overall, flash drought signals initially appeared in the near-surface soil moisture, followed closely by reductions in evapotranspiration. Total column soil moisture deficits took longer to develop, especially in the western part of the region where heavy rainfall during the spring and early summer led to large moisture surpluses. Large differences were noted in how land surface models in the North American Land Data Assimilation System depicted soil moisture evolution during the flash drought; however, the models were more similar in their assessment of conditions during the flash recovery period. This study illustrates the need to use multiple datasets to track the evolution and impacts of rapidly evolving flash drought and flash recovery events.

Abstract

Proper modeling of the turbulent heat fluxes over lakes is critical for accurate predictions of lake-effect snowfall (LES). However, model evaluation of such a process has not been possible because of the lack of direct flux measurements over lakes. The authors conducted the first-ever comparison of the turbulent latent and sensible heat fluxes between state-of-the-art numerical models and direct flux measurements over Lake Erie, focusing on a record LES event in southwest New York in November 2014. The model suite consisted of numerical models that were operationally and experimentally used to provide nowcasts and forecasts of weather and lake conditions. The models captured the rise of the observed turbulent heat fluxes, while the peak values varied significantly. This variation resulted in an increased spread of simulated lake temperature and cumulative evaporation as the representation of the model uncertainty. The water budget analysis of the atmospheric model results showed that the majority of the moisture during this event came from lake evaporation rather than a larger synoptic system. The unstructured-grid Finite-Volume Community Ocean Model (FVCOM) simulations, especially those using the Coupled Ocean–Atmosphere Response Experiment (COARE)-Met Flux algorithm, presented better agreement with the observed fluxes likely due to the model’s capability in representing the detailed spatial patterns of the turbulent heat fluxes and the COARE algorithm’s more realistic treatment of the surface boundary layer than those in the other models.

Abstract

Lake-effect convective snowstorms frequently produce high-impact, hazardous winter weather conditions downwind of the North American Great Lakes. During lake-effect snow events, the lake surfaces can cool rapidly, and in some cases, notable development of ice cover occurs. Such rapid changes in the lake-surface conditions are not accounted for in existing operational weather forecast models, such as the National Oceanic and Atmospheric Administration’s (NOAA) High-Resolution Rapid Refresh (HRRR) model, resulting in reduced performance of lake-effect snow forecasts. As a milestone to future implementations in the Great Lakes Operational Forecast System (GLOFS) and HRRR, this study examines the one-way linkage between the hydrodynamic-ice model [the Finite-Volume Community Ocean Model coupled with the unstructured grid version of the Los Alamos Sea Ice Model (FVCOM-CICE), the physical core model of GLOFS] and the atmospheric model [the Weather Research and Forecasting (WRF) Model, the physical core model of HRRR]. The realistic representation of lake-surface cooling and ice development or its fractional coverage during three lake-effect snow events was achieved by feeding the FVCOM-CICE simulated lake-surface conditions to WRF (using a regional configuration of HRRR), resulting in the improved simulation of the turbulent heat fluxes over the lakes and resulting snow water equivalent in the downwind areas. This study shows that the one-way coupling is a practical approach that is well suited to the operational environment, as it requires little to no increase in computational resources yet can result in improved forecasts of regional weather and lake conditions.

Abstract

Land surface processes play an important role in the West African monsoon variability. In addition, the evolution of hydrological systems in this region, and particularly the increase of surface water and runoff coefficients observed since the 1950s, has had a strong impact on water resources and on the occurrence of floods events. This study addresses results from phase 2 of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project (ALMIP2), carried out to evaluate the capability of different state-of-the-art land surface models to reproduce surface processes at the mesoscale. Evaluation of runoff and water fluxes over the Mali site is carried out through comparison with runoff estimations over endorheic watersheds as well as evapotranspiration (ET) measurements. Three remote-sensing-based ET products [ALEXI, MODIS, and Global Land Evaporation Amsterdam Model (GLEAM)] are also analyzed. It is found that, over deep sandy soils, surface runoff is generally overestimated, but the ALMIP2 multimodel mean reproduces in situ measurements of ET and water stress events rather well. However, ALMIP2 models are generally unable to distinguish among the two contrasted hydrological systems typical of the study area. Employing as input a soil map that explicitly represents shallow soils improves the representation of water fluxes for the models that can account for their representation. Shallow soils are shown to be also quite challenging for remote-sensing-based ET products, even if their effect on evaporative loss was captured by the diagnostic thermal-based ALEXI. A better representation of these soils, in soil databases, model parameterizations, and remote sensing algorithms, is fundamental to improve the estimation of water fluxes in this part of the Sahel.

Abstract

This study examines the role of processes transporting tracers across the Polar Front (PF) in the depth interval between the surface and major topographic sills, which this study refers to as the “PF core.” A preindustrial control simulation of an eddying climate model coupled to a biogeochemical model [GFDL Climate Model, version 2.6 (CM2.6)– simplified version of the Biogeochemistry with Light Iron Nutrients and Gas (miniBLING) 0.1° ocean model] is used to investigate the transport of heat, carbon, oxygen, and phosphate across the PF core, with a particular focus on the role of mesoscale eddies. The authors find that the total transport across the PF core results from a ubiquitous Ekman transport that drives the upwelled tracers to the north and a localized opposing eddy transport that induces tracer leakages to the south at major topographic obstacles. In the Ekman layer, the southward eddy transport only partially compensates the northward Ekman transport, while below the Ekman layer, the southward eddy transport dominates the total transport but remains much smaller in magnitude than the near-surface northward transport. Most of the southward branch of the total transport is achieved below the PF core, mainly through geostrophic currents. This study finds that the eddy-diffusive transport reinforces the southward eddy-advective transport for carbon and heat, and opposes it for oxygen and phosphate. Eddy-advective transport is likely to be the leading-order component of eddy-induced transport for all four tracers. However, eddy-diffusive transport may provide a significant contribution to the southward eddy heat transport due to strong along-isopycnal temperature gradients.

In the surface layer over the ocean the Monin–Obukhov similarity theory is often applied to construct vertical profiles of pressure, temperature, humidity, and wind speed. In this context, the rough boundary layer is derived from empirical relations where ocean wave characteristics are neglected. For seas where wind speed is less than ~ 10 m s⁻¹ there is excellent agreement for both meteorological and microwave propagation theory and measurements. However, recent evidence indicates that even small waves perturb these profiles. It is, therefore, hypothesized that mechanical forcing by sea waves is responsible for modifying scalar profiles in the lowest portion of the surface layer, thereby reducing the effects of evaporation ducting on microwave signal propagation. This hypothesis, that a rough sea surface modifies the evaporation duct, was the primary motivation for the Rough Evaporation Duct (RED) experiment.

RED was conducted off of the Hawaiian Island of Oahu from late August to mid-September 2001. The Scripps Institution of Oceanography Research Platform Floating Instrument Platform, moored about 10 km off the northeast coast of Oahu, hosted the primary meteorological sensor suites and the transmitters for both the microwave and the infrared propagation links. Two land sites were instrumented—one with microwave receivers and the other with an infrared receiver—two buoys were deployed, a small boat was instrumented, and two aircraft flew various tracks to sense both sea and atmospheric conditions.

Through meteorological and propagation measurements, RED achieved a number of its objectives. First, although we did not experience the desired conditions of simultaneous high seas, high winds, and large surface gradients of temperature and humidity necessary to significantly affect the evaporation duct, observations verify that waves do modify the scalars within the air–sea surface layer. Second, an intriguing and controversial result is the lack of agreement of the scalar profile constants with those typically observed over land. Finally, as expected for the conditions encountered during RED (trade wind, moderate seas, unstable), we show that the Monin–Obukhov similarity theory, combined with high-quality meteorological measurements, can be used by propagation models to accurately predict microwave signal levels.