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Abstract
Mesoscale model simulations have been performed of the second episode of gravity waves observed in great detail in previous studies on 11–12 July 1981 during the Cooperative Convective Precipitation Experiment. The dominant wave simulated by the model was mechanically forced by the strong updraft associated with a mountain–plains solenoid (MPS). As this updraft impinged upon a stratified shear layer above the deep, well-mixed boundary layer that developed due to strong sensible heating over the Absaroka Mountains, the gravity wave was created. This wave rapidly weakened as it propagated eastward. However, explosive convection developed directly over the remnant gravity wave as an eastward-propagating density current produced by a rainband generated within the MPS leeside convergence zone merged with a westward-propagating density current in eastern Montana. The greatly strengthened cool pool resulting from this new convection then generated a bore wave that appeared to be continuous with the movement of the incipient gravity wave as it propagated across Montana and the Dakotas.
The nonlinear balance equation and Rossby number were computed to explore the role of geostrophic adjustment in the forecast gravity wave generation, as suggested in previous studies of this wave event. These fields did indicate flow imbalance, but this was merely the manifestation of the MPS-forced gravity wave. Thus, the imbalance indicator fields provided no lead time for predicting wave occurrence.
Several sensitivity tests were performed to study the role of diabatic processes and topography in the initiation of the flow imbalance and the propagating gravity waves. When diabatic effects owing to precipitation were prevented, a strong gravity wave still was generated in the upper troposphere within the region of imbalance over the mountains. However, it did not have a significant impact because moist convection was necessary to maintain wave energy in the absence of an efficient wave duct. No gravity waves were present in either a simulation that disallowed surface sensible heating, or the “flat terrain” simulation, because the requisite MPS forcing could not occur.
This study highlights difficulties encountered in attempting to model the generation of observed gravity waves over complex terrain in the presence of strong diabatic effects. The complex interactions that occurred between the sensible heating over complex terrain, the incipient gravity wave, and convection highlight the need for much more detailed observations between wave generation regions over mountains and the plains downstream of such regions.
Abstract
Mesoscale model simulations have been performed of the second episode of gravity waves observed in great detail in previous studies on 11–12 July 1981 during the Cooperative Convective Precipitation Experiment. The dominant wave simulated by the model was mechanically forced by the strong updraft associated with a mountain–plains solenoid (MPS). As this updraft impinged upon a stratified shear layer above the deep, well-mixed boundary layer that developed due to strong sensible heating over the Absaroka Mountains, the gravity wave was created. This wave rapidly weakened as it propagated eastward. However, explosive convection developed directly over the remnant gravity wave as an eastward-propagating density current produced by a rainband generated within the MPS leeside convergence zone merged with a westward-propagating density current in eastern Montana. The greatly strengthened cool pool resulting from this new convection then generated a bore wave that appeared to be continuous with the movement of the incipient gravity wave as it propagated across Montana and the Dakotas.
The nonlinear balance equation and Rossby number were computed to explore the role of geostrophic adjustment in the forecast gravity wave generation, as suggested in previous studies of this wave event. These fields did indicate flow imbalance, but this was merely the manifestation of the MPS-forced gravity wave. Thus, the imbalance indicator fields provided no lead time for predicting wave occurrence.
Several sensitivity tests were performed to study the role of diabatic processes and topography in the initiation of the flow imbalance and the propagating gravity waves. When diabatic effects owing to precipitation were prevented, a strong gravity wave still was generated in the upper troposphere within the region of imbalance over the mountains. However, it did not have a significant impact because moist convection was necessary to maintain wave energy in the absence of an efficient wave duct. No gravity waves were present in either a simulation that disallowed surface sensible heating, or the “flat terrain” simulation, because the requisite MPS forcing could not occur.
This study highlights difficulties encountered in attempting to model the generation of observed gravity waves over complex terrain in the presence of strong diabatic effects. The complex interactions that occurred between the sensible heating over complex terrain, the incipient gravity wave, and convection highlight the need for much more detailed observations between wave generation regions over mountains and the plains downstream of such regions.
Abstract
Over the course of his career, Fuqing Zhang drew vital new insights into the dynamics of meteorologically significant mesoscale gravity waves (MGWs), including their generation by unbalanced jet streaks, their interaction with fronts and organized precipitation, and their importance in midlatitude weather and predictability. Zhang was the first to deeply examine “spontaneous balance adjustment”—the process by which MGWs are continuously emitted as baroclinic growth drives the upper-level flow out of balance. Through his pioneering numerical model investigation of the large-amplitude MGW event of 4 January 1994, he additionally demonstrated the critical role of MGW–moist convection interaction in wave amplification. Zhang’s curiosity-turned-passion in atmospheric science covered a vast range of topics and led to the birth of new branches of research in mesoscale meteorology and numerical weather prediction. Yet, it was his earliest studies into midlatitude MGWs and their significant impacts on hazardous weather that first inspired him. Such MGWs serve as the focus of this review, wherein we seek to pay tribute to his groundbreaking contributions, review our current understanding, and highlight critical open science issues. Chief among such issues is the nature of MGW amplification through feedback with moist convection, which continues to elude a complete understanding. The pressing nature of this subject is underscored by the continued failure of operational numerical forecast models to adequately predict most large-amplitude MGW events. Further research into such issues therefore presents a valuable opportunity to improve the understanding and forecasting of this high-impact weather phenomenon, and in turn, to preserve the spirit of Zhang’s dedication to this subject.
Abstract
Over the course of his career, Fuqing Zhang drew vital new insights into the dynamics of meteorologically significant mesoscale gravity waves (MGWs), including their generation by unbalanced jet streaks, their interaction with fronts and organized precipitation, and their importance in midlatitude weather and predictability. Zhang was the first to deeply examine “spontaneous balance adjustment”—the process by which MGWs are continuously emitted as baroclinic growth drives the upper-level flow out of balance. Through his pioneering numerical model investigation of the large-amplitude MGW event of 4 January 1994, he additionally demonstrated the critical role of MGW–moist convection interaction in wave amplification. Zhang’s curiosity-turned-passion in atmospheric science covered a vast range of topics and led to the birth of new branches of research in mesoscale meteorology and numerical weather prediction. Yet, it was his earliest studies into midlatitude MGWs and their significant impacts on hazardous weather that first inspired him. Such MGWs serve as the focus of this review, wherein we seek to pay tribute to his groundbreaking contributions, review our current understanding, and highlight critical open science issues. Chief among such issues is the nature of MGW amplification through feedback with moist convection, which continues to elude a complete understanding. The pressing nature of this subject is underscored by the continued failure of operational numerical forecast models to adequately predict most large-amplitude MGW events. Further research into such issues therefore presents a valuable opportunity to improve the understanding and forecasting of this high-impact weather phenomenon, and in turn, to preserve the spirit of Zhang’s dedication to this subject.
On the Use of Unmanned Aircraft for Sampling Mesoscale Phenomena in the Preconvective Boundary LayerAbstract
The potential value of small unmanned aircraft systems (UAS) for monitoring the preconvective environment and providing useful information in real time to weather forecasters for evaluation at a National Weather Service (NWS) Forecast Office are addressed. The general goal was to demonstrate whether a combination of fixed-wing and rotary-wing UAS can provide detailed, accurate, and useful measurements of the boundary layer important for determining the potential for convection initiation (CI). Two field operations were held: a validation study in which the UAS data were compared with collocated measurements made by mobile rawinsondes and ground-based remote sensing systems and a real-time experiment held to evaluate the potential value of the UAS observations in an operationally relevant environment. Vertical profile measurements were made by the rotary-wing UAS at two mesonet sites every 30 min up to 763 m (2500 ft) AGL in coordination with fixed-wing UAS transects between the sites. The results showed the ability of the fixed-wing UAS to detect significant spatial gradients in temperature, moisture, and winds. Although neither of two different types of rotary-wing UAS measurements were able to strictly meet the requirements for sensor accuracy, one of the systems came very close to doing so. UAS sensor accuracy, methods for retrieving the winds, and challenges in assessing the representativeness of the observations are highlighted. Interesting mesoscale phenomena relevant to CI forecasting needs are revealed by the UAS. Issues needing to be overcome for UAS to ever become a NOAA operational observing system are discussed.
Abstract
The potential value of small unmanned aircraft systems (UAS) for monitoring the preconvective environment and providing useful information in real time to weather forecasters for evaluation at a National Weather Service (NWS) Forecast Office are addressed. The general goal was to demonstrate whether a combination of fixed-wing and rotary-wing UAS can provide detailed, accurate, and useful measurements of the boundary layer important for determining the potential for convection initiation (CI). Two field operations were held: a validation study in which the UAS data were compared with collocated measurements made by mobile rawinsondes and ground-based remote sensing systems and a real-time experiment held to evaluate the potential value of the UAS observations in an operationally relevant environment. Vertical profile measurements were made by the rotary-wing UAS at two mesonet sites every 30 min up to 763 m (2500 ft) AGL in coordination with fixed-wing UAS transects between the sites. The results showed the ability of the fixed-wing UAS to detect significant spatial gradients in temperature, moisture, and winds. Although neither of two different types of rotary-wing UAS measurements were able to strictly meet the requirements for sensor accuracy, one of the systems came very close to doing so. UAS sensor accuracy, methods for retrieving the winds, and challenges in assessing the representativeness of the observations are highlighted. Interesting mesoscale phenomena relevant to CI forecasting needs are revealed by the UAS. Issues needing to be overcome for UAS to ever become a NOAA operational observing system are discussed.
Abstract
Detailed moisture observations from a ground-based Raman lidar and special radiosonde data of two disturbances associated with a dissipating gust front are presented. A synthesis of the lidar data with conventional meteorological data, in conjunction with theoretical calculations and comparison to laboratory studies, leads to the conclusion that the disturbances seen in both the lidar and accompanying barograph data represent a weak gravity current and an associated undular bore. The disturbances display excellent coherence over hundreds of kilometers upstream of the lidar site. Bore formation occurs at the leading edge of the gust front coincidentally with the rapid weakening of the gravity current. Analysis suggests that the bore was generated by the collapse of the gravity current into a stable, nocturnal inversion layer, and subsequently propagated along this wave guide at nearly twice the speed of the gravity current.
The Raman lidar provided detailed measurements of the vertical structure of the bore and its parent generation mechanism. A mean bore depth of 1.9 km is revealed by the lidar, whereas a depth of 2.2 km is predicted from hydraulic theory. Observed and calculated bore speeds were also found to agree reasonably well with one another (∼ ±20%). Comparison of these observations with those of internal bores generated by thunderstorms in other studies reveals that this bore was exceedingly strong, being responsible for nearly tripling the height of a surface-based inversion that had existed ahead of the bore and dramatically increasing the depth of the moist layer due to strong vertical mixing. Subsequent appearance of the relatively shallow gravity current underneath this mixed region resulted in the occurrence of an elevated mixed layer, as confirmed with the special radiosonde measurements.
A synthesis of the lidar and radiosonde observations indicates that bore-induced parcel displacements attenuated rapidly at the same height as the level of strongest wave trapping predicted from the theory of Crook. This trapping mechanism, which is due to the existence of a low-level jet, results in a long-lived bore, and seems to he a common phenomenon in the environment of thunderstorm-generated bores and solitary waves. Despite the weakening of a capping inversion by this strong and persistent bore, analysis indicates that the 30-min averaged lifting of 0.7 m s−1 was confined to a too shallow layer near the surface to trigger deep convection, and could only produce scattered low clouds as deduced from the lidar measurements.
Abstract
Detailed moisture observations from a ground-based Raman lidar and special radiosonde data of two disturbances associated with a dissipating gust front are presented. A synthesis of the lidar data with conventional meteorological data, in conjunction with theoretical calculations and comparison to laboratory studies, leads to the conclusion that the disturbances seen in both the lidar and accompanying barograph data represent a weak gravity current and an associated undular bore. The disturbances display excellent coherence over hundreds of kilometers upstream of the lidar site. Bore formation occurs at the leading edge of the gust front coincidentally with the rapid weakening of the gravity current. Analysis suggests that the bore was generated by the collapse of the gravity current into a stable, nocturnal inversion layer, and subsequently propagated along this wave guide at nearly twice the speed of the gravity current.
The Raman lidar provided detailed measurements of the vertical structure of the bore and its parent generation mechanism. A mean bore depth of 1.9 km is revealed by the lidar, whereas a depth of 2.2 km is predicted from hydraulic theory. Observed and calculated bore speeds were also found to agree reasonably well with one another (∼ ±20%). Comparison of these observations with those of internal bores generated by thunderstorms in other studies reveals that this bore was exceedingly strong, being responsible for nearly tripling the height of a surface-based inversion that had existed ahead of the bore and dramatically increasing the depth of the moist layer due to strong vertical mixing. Subsequent appearance of the relatively shallow gravity current underneath this mixed region resulted in the occurrence of an elevated mixed layer, as confirmed with the special radiosonde measurements.
A synthesis of the lidar and radiosonde observations indicates that bore-induced parcel displacements attenuated rapidly at the same height as the level of strongest wave trapping predicted from the theory of Crook. This trapping mechanism, which is due to the existence of a low-level jet, results in a long-lived bore, and seems to he a common phenomenon in the environment of thunderstorm-generated bores and solitary waves. Despite the weakening of a capping inversion by this strong and persistent bore, analysis indicates that the 30-min averaged lifting of 0.7 m s−1 was confined to a too shallow layer near the surface to trigger deep convection, and could only produce scattered low clouds as deduced from the lidar measurements.
Abstract
A large number of predictions from a regional numerical weather prediction model known as the Mesoscale Atmospheric Simulation System (MASS 2.0) am verified against routinely collected observations to determine the model's predictive skill and its most important systematic errors at the synoptic scale. The model's forecast fields are smoothed to obtain synoptic-scale fields that can be compared objectively with the observation. A total of 23 (28) separate 12 h (24 h) forecasts of atmospheric flow patterns over the United States are evaluated from real-time simulations made during the period 2 April-2 July 1982. The model's performance is compared to that of the National Meteorological Centers operational Limited-area Fine Mesh (LFM) model for this period. Temporal variations in normalized forecast skill statistics are synthesized with the mean spatial distribution of daily model forecast errors in order to determine synoptic-scale systematic errors.
The mesoscale model produces synoptic-scale forecasts at an overall level of performance equivalent to that of the LFM model. Lower tropospheric mass fields are, for the most part, predicted significantly better by the MASS 2.0 model, but it is outperformed by the LFM at and above 500 mb. The greatest improvement made by the mesoscale model is a 73% reduction of cold bias in LFM forecasts of the 1000–500 mb thickness field, primarily over the western United States. The LFM bias is the combined result of model overforecasts of surface anticyclone intensity and underforecasts of surface cyclone intensity and nearby 500 mb geopotential heights.
The poorer forecasts by the MASS 2.0 model in the middle and upper troposphere result primarily from a systematic mass loss which occurs only under a certain synoptic flow pattern termed the mass loss regime. Problems with specification of the lateral boundary conditions and, to a lesser extent, erroneous computation of the map factor seemed to contribute most to the systematic mass loss. This error is very significant since MASS 2.0 performance either equaled or surpassed that of the LFM model in forecasts of virtually every meteorological field studied when mass loss regime days were excluded from the sample.
Two other important systematic errors in MASS model forecasts are investigated. Underforecasts of moisture over the Gulf Coast states are found to be due in large part to a negative bias in the moisture initialization. Also, overforecasts of surface cyclone intensity and 1000–500 mb thickness values over the Plains states are traced to excessive latent beating resulting from the absence of a cumulus parameterization scheme in the model. Awareness of these synoptic-scale forecasts errors enables more effective use to be made of the (unfiltered) mesoscale forecast fields, which are evaluated in the companion paper by Koch.
Abstract
A large number of predictions from a regional numerical weather prediction model known as the Mesoscale Atmospheric Simulation System (MASS 2.0) am verified against routinely collected observations to determine the model's predictive skill and its most important systematic errors at the synoptic scale. The model's forecast fields are smoothed to obtain synoptic-scale fields that can be compared objectively with the observation. A total of 23 (28) separate 12 h (24 h) forecasts of atmospheric flow patterns over the United States are evaluated from real-time simulations made during the period 2 April-2 July 1982. The model's performance is compared to that of the National Meteorological Centers operational Limited-area Fine Mesh (LFM) model for this period. Temporal variations in normalized forecast skill statistics are synthesized with the mean spatial distribution of daily model forecast errors in order to determine synoptic-scale systematic errors.
The mesoscale model produces synoptic-scale forecasts at an overall level of performance equivalent to that of the LFM model. Lower tropospheric mass fields are, for the most part, predicted significantly better by the MASS 2.0 model, but it is outperformed by the LFM at and above 500 mb. The greatest improvement made by the mesoscale model is a 73% reduction of cold bias in LFM forecasts of the 1000–500 mb thickness field, primarily over the western United States. The LFM bias is the combined result of model overforecasts of surface anticyclone intensity and underforecasts of surface cyclone intensity and nearby 500 mb geopotential heights.
The poorer forecasts by the MASS 2.0 model in the middle and upper troposphere result primarily from a systematic mass loss which occurs only under a certain synoptic flow pattern termed the mass loss regime. Problems with specification of the lateral boundary conditions and, to a lesser extent, erroneous computation of the map factor seemed to contribute most to the systematic mass loss. This error is very significant since MASS 2.0 performance either equaled or surpassed that of the LFM model in forecasts of virtually every meteorological field studied when mass loss regime days were excluded from the sample.
Two other important systematic errors in MASS model forecasts are investigated. Underforecasts of moisture over the Gulf Coast states are found to be due in large part to a negative bias in the moisture initialization. Also, overforecasts of surface cyclone intensity and 1000–500 mb thickness values over the Plains states are traced to excessive latent beating resulting from the absence of a cumulus parameterization scheme in the model. Awareness of these synoptic-scale forecasts errors enables more effective use to be made of the (unfiltered) mesoscale forecast fields, which are evaluated in the companion paper by Koch.
Abstract
To improve severe thunderstorm prediction, a novel pseudo-observation and assimilation approach involving water vapor mass mixing ratio is proposed to better initialize NWP forecasts at convection-resolving scales. The first step of the algorithm identifies areas of deep moist convection by utilizing the vertically integrated liquid water (VIL) derived from three-dimensional radar reflectivity fields. Once VIL is obtained, pseudo–water vapor observations are derived based on reflectivity thresholds within columns characterized by deep moist convection. Areas of spurious convection also are identified by the algorithm to help reduce their detrimental impact on the forecast. The third step is to assimilate the derived pseudo–water vapor observations into a convection-resolving-scale NWP model along with radar radial velocity and reflectivity fields in a 3DVAR framework during 4-h data assimilation cycles. Finally, 3-h forecasts are launched every hour during that period. The performance of this method is examined for two selected high-impact severe thunderstorm events: namely, the 24 May 2011 Oklahoma and 16 May 2017 Texas and Oklahoma tornado outbreaks. Relative to a control simulation that only assimilated radar data, the analyses and forecasts of these supercells (reflectivity patterns, tracks, and updraft helicity tracks) are qualitatively and quantitatively improved in both cases when the water vapor information is added into the analysis.
Abstract
To improve severe thunderstorm prediction, a novel pseudo-observation and assimilation approach involving water vapor mass mixing ratio is proposed to better initialize NWP forecasts at convection-resolving scales. The first step of the algorithm identifies areas of deep moist convection by utilizing the vertically integrated liquid water (VIL) derived from three-dimensional radar reflectivity fields. Once VIL is obtained, pseudo–water vapor observations are derived based on reflectivity thresholds within columns characterized by deep moist convection. Areas of spurious convection also are identified by the algorithm to help reduce their detrimental impact on the forecast. The third step is to assimilate the derived pseudo–water vapor observations into a convection-resolving-scale NWP model along with radar radial velocity and reflectivity fields in a 3DVAR framework during 4-h data assimilation cycles. Finally, 3-h forecasts are launched every hour during that period. The performance of this method is examined for two selected high-impact severe thunderstorm events: namely, the 24 May 2011 Oklahoma and 16 May 2017 Texas and Oklahoma tornado outbreaks. Relative to a control simulation that only assimilated radar data, the analyses and forecasts of these supercells (reflectivity patterns, tracks, and updraft helicity tracks) are qualitatively and quantitatively improved in both cases when the water vapor information is added into the analysis.
Abstract
High-resolution dropwindsonde and in-flight measurements collected by a research aircraft during the Severe Clear-Air Turbulence Colliding with Aircraft Traffic (S
Turbulence occurred in association with a wide spectrum of upward propagating gravity waves above the jet core. Inertia–gravity waves were generated within a region of unbalanced frontogenesis in the vicinity of a complex tropopause fold. Turbulent kinetic energy fields forecast by the RUC and CH models displayed a strongly banded appearance associated with these mesoscale gravity waves (horizontal wavelengths of ∼120–216 km). Smaller-scale gravity wave packets (horizontal wavelengths of 1–20 km) within the mesoscale wave field perturbed the background wind shear and stability, promoting the development of bands of reduced Richardson number conducive to the generation of turbulence. The wavelet analysis revealed that brief episodes of high turbulent energy were closely associated with gravity wave occurrences. Structure function analysis provided evidence that turbulence was most strongly forced at a horizontal scale of 700 m.
Fluctuations in ozone measured by the aircraft correlated highly with potential temperature fluctuations and the occurrence of turbulent patches at altitudes just above the jet core, but not at higher flight levels, even though the ozone fluctuations were much larger aloft. These results suggest the existence of remnant “fossil turbulence” from earlier events at higher levels, and that ozone cannot be used as a substitute for more direct measures of turbulence. The findings here do suggest that automated turbulence forecasting algorithms should include some reliable measure of gravity wave activity.
Abstract
High-resolution dropwindsonde and in-flight measurements collected by a research aircraft during the Severe Clear-Air Turbulence Colliding with Aircraft Traffic (S
Turbulence occurred in association with a wide spectrum of upward propagating gravity waves above the jet core. Inertia–gravity waves were generated within a region of unbalanced frontogenesis in the vicinity of a complex tropopause fold. Turbulent kinetic energy fields forecast by the RUC and CH models displayed a strongly banded appearance associated with these mesoscale gravity waves (horizontal wavelengths of ∼120–216 km). Smaller-scale gravity wave packets (horizontal wavelengths of 1–20 km) within the mesoscale wave field perturbed the background wind shear and stability, promoting the development of bands of reduced Richardson number conducive to the generation of turbulence. The wavelet analysis revealed that brief episodes of high turbulent energy were closely associated with gravity wave occurrences. Structure function analysis provided evidence that turbulence was most strongly forced at a horizontal scale of 700 m.
Fluctuations in ozone measured by the aircraft correlated highly with potential temperature fluctuations and the occurrence of turbulent patches at altitudes just above the jet core, but not at higher flight levels, even though the ozone fluctuations were much larger aloft. These results suggest the existence of remnant “fossil turbulence” from earlier events at higher levels, and that ozone cannot be used as a substitute for more direct measures of turbulence. The findings here do suggest that automated turbulence forecasting algorithms should include some reliable measure of gravity wave activity.
The International H2O Project (IHOP_2002) is one of the largest North American meteorological field experiments in history. From 13 May to 25 June 2002, over 250 researchers and technical staff from the United States, Germany, France, and Canada converged on the Southern Great Plains to measure water vapor and other atmospheric variables. The principal objective of IHOP_2002 is to obtain an improved characterization of the time-varying three-dimensional water vapor field and evaluate its utility in improving the understanding and prediction of convective processes. The motivation for this objective is the combination of extremely low forecast skill for warm-season rainfall and the relatively large loss of life and property from flash floods and other warm-season weather hazards. Many prior studies on convective storm forecasting have shown that water vapor is a key atmospheric variable that is insufficiently measured. Toward this goal, IHOP_2002 brought together many of the existing operational and new state-of-the-art research water vapor sensors and numerical models.
The IHOP_2002 experiment comprised numerous unique aspects. These included several instruments fielded for the first time (e.g., reference radiosonde); numerous upgraded instruments (e.g., Wyoming Cloud Radar); the first ever horizontal-pointing water vapor differential absorption lidar (DIAL; i.e., Leandre II on the Naval Research Laboratory P-3), which required the first onboard aircraft avoidance radar; several unique combinations of sensors (e.g., multiple profiling instruments at one field site and the German water vapor DIAL and NOAA/Environmental Technology Laboratory Doppler lidar on board the German Falcon aircraft); and many logistical challenges. This article presents a summary of the motivation, goals, and experimental design of the project, illustrates some preliminary data collected, and includes discussion on some potential operational and research implications of the experiment.
The International H2O Project (IHOP_2002) is one of the largest North American meteorological field experiments in history. From 13 May to 25 June 2002, over 250 researchers and technical staff from the United States, Germany, France, and Canada converged on the Southern Great Plains to measure water vapor and other atmospheric variables. The principal objective of IHOP_2002 is to obtain an improved characterization of the time-varying three-dimensional water vapor field and evaluate its utility in improving the understanding and prediction of convective processes. The motivation for this objective is the combination of extremely low forecast skill for warm-season rainfall and the relatively large loss of life and property from flash floods and other warm-season weather hazards. Many prior studies on convective storm forecasting have shown that water vapor is a key atmospheric variable that is insufficiently measured. Toward this goal, IHOP_2002 brought together many of the existing operational and new state-of-the-art research water vapor sensors and numerical models.
The IHOP_2002 experiment comprised numerous unique aspects. These included several instruments fielded for the first time (e.g., reference radiosonde); numerous upgraded instruments (e.g., Wyoming Cloud Radar); the first ever horizontal-pointing water vapor differential absorption lidar (DIAL; i.e., Leandre II on the Naval Research Laboratory P-3), which required the first onboard aircraft avoidance radar; several unique combinations of sensors (e.g., multiple profiling instruments at one field site and the German water vapor DIAL and NOAA/Environmental Technology Laboratory Doppler lidar on board the German Falcon aircraft); and many logistical challenges. This article presents a summary of the motivation, goals, and experimental design of the project, illustrates some preliminary data collected, and includes discussion on some potential operational and research implications of the experiment.
Abstract
Previous studies of the low-level jet (LLJ) over the central Great Plains of the United States have been unable to determine the role that mesoscale and smaller circulations play in the transport of moisture. To address this issue, two aircraft missions during the International H2O Project (IHOP_2002) were designed to observe closely a well-developed LLJ over the Great Plains (primarily Oklahoma and Kansas) with multiple observation platforms. In addition to standard operational platforms (most important, radiosondes and profilers) to provide the large-scale setting, dropsondes released from the aircraft at 55-km intervals and a pair of onboard lidar instruments—High Resolution Doppler Lidar (HRDL) for wind and differential absorption lidar (DIAL) for moisture—observed the moisture transport in the LLJ at greater resolution. Using these observations, the authors describe the multiscalar structure of the LLJ and then focus attention on the bulk properties and effects of scales of motion by computing moisture fluxes through cross sections that bracket the LLJ. From these computations, the Reynolds averages within the cross sections can be computed. This allow an estimate to be made of the bulk effect of integrated estimates of the contribution of small-scale (mesoscale to convective scale) circulations to the overall transport. The performance of the Weather Research and Forecasting (WRF) Model in forecasting the intensity and evolution of the LLJ for this case is briefly examined.
Abstract
Previous studies of the low-level jet (LLJ) over the central Great Plains of the United States have been unable to determine the role that mesoscale and smaller circulations play in the transport of moisture. To address this issue, two aircraft missions during the International H2O Project (IHOP_2002) were designed to observe closely a well-developed LLJ over the Great Plains (primarily Oklahoma and Kansas) with multiple observation platforms. In addition to standard operational platforms (most important, radiosondes and profilers) to provide the large-scale setting, dropsondes released from the aircraft at 55-km intervals and a pair of onboard lidar instruments—High Resolution Doppler Lidar (HRDL) for wind and differential absorption lidar (DIAL) for moisture—observed the moisture transport in the LLJ at greater resolution. Using these observations, the authors describe the multiscalar structure of the LLJ and then focus attention on the bulk properties and effects of scales of motion by computing moisture fluxes through cross sections that bracket the LLJ. From these computations, the Reynolds averages within the cross sections can be computed. This allow an estimate to be made of the bulk effect of integrated estimates of the contribution of small-scale (mesoscale to convective scale) circulations to the overall transport. The performance of the Weather Research and Forecasting (WRF) Model in forecasting the intensity and evolution of the LLJ for this case is briefly examined.
