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Hawbecker, Patrick; Knievel, Jason C.
2022 Journal of Applied Meteorology and Climatology
AbstractSimulations of Chesapeake Bay breezes are performed with varying water surface temperature (WST) datasets and formulations for the diurnal cycle of WST to determine whether more accurate depictions of water surface temperature improve prediction of bay breezes. The accuracy of simulations is measured against observed WST, inland wind speed and temperature, and in simulations’ ability to detect bay breezes via a detection algorithm developed for numerical model output. Missing WST data are found to be problematic within the Weather Research and Forecasting (WRF) Model framework, especially when activating the prognostic equation for skin temperature, sst_skin. This is alleviated when filling all missing WST values with skin temperature values within the initial and boundary conditions. Performance of bay-breeze prediction is shown to be somewhat associated with the resolution of the WST dataset. Further, model performance in simulating WST as well as in simulating the Chesapeake Bay breeze is improved when diurnal fluctuations of WST are considered via the sst skin option. Prior to running simulations, model performance in simulating the bay breeze can be accurately predicted through the use of a simple formulation.
, Nischal; Attada, Raju; Hunt, Kieran M. R.
2022 Journal of Applied Meteorology and Climatology
AbstractConsiderable uncertainties are associated with precipitation characteristics over the western Himalayan region (WHR). These are due to typically small-scale but high-intensity storms caused by the complex topography that are under-resolved by a sparse gauge network. Additionally, both satellite and gauge precipitation measurements remain subject to systematic errors, typically resulting in underestimation over mountainous terrains. Reanalysis datasets provide prospective alternative but are limited by their resolution, which has so far been too coarse to properly resolve orographic precipitation. In this study, we evaluate and cross compare Indian Monsoon Data Assimilation and Analysis (IMDAA), the first high-resolution (12 km) regional reanalysis over India, with various precipitation products during winter season over WHR. We demonstrate IMDAA’s efficiency in representing winter precipitation characteristics at seasonal, diurnal, interannual scales, as well as heavy precipitation associated with western disturbances (WDs). IMDAA shows closer agreement to other reanalyses than to gauge-based and satellite products in error and bias analysis. Although depicting higher magnitudes, its fine resolution allows a much closer insight into localized spatial patterns and the diurnal cycle, a key advantage over other datasets. Mean winter precipitation over WHR shows a significant decreasing trend in IMDAA, despite no significant trend in the frequency of WDs tracked in either IMDAA or ERA5. The study also exhibits the potential use of IMDAA for characterizing winter atmospheric dynamics, both for climatological studies and during WD activity such as localized valley winds. Overall, these findings highlight the potential utility for IMDAA in conducting monitoring and climate change impact assessment studies over the fragile western Himalayan ecosystem.
Carney, Meagan; Kantz, Holger; Nicol, Matthew
2022 Journal of Applied Meteorology and Climatology
AbstractParticularly important to hurricane risk assessment for coastal regions is finding accurate approximations of return probabilities of maximum wind speeds. Since extremes in maximum wind speed have a direct relationship with minima in the central pressure, accurate wind speed return estimates rely heavily on proper modeling of the central pressure minima. Using the HURDAT2 database, we show that the central pressure minima of hurricane events can be appropriately modeled by a nonstationary extreme value distribution. We also provide and validate a Poisson distribution with a nonstationary rate parameter to model returns of hurricane events. Using our nonstationary models and numerical simulation techniques from established literature, we perform a simulation study to model returns of maximum wind speeds of hurricane events along the North Atlantic coast. We show that our revised model agrees with current data and results in an expectation of higher maximum wind speeds for all regions along the coast, with the highest maximum wind speeds occurring along the northeast seaboard.
Nazarian, Robert H.; Vizzard, James V.; Agostino, Carissa P.; Lutsko, Nicholas J.
2022 Journal of Applied Meteorology and Climatology
AbstractThe northeastern United States (NEUS) is a densely populated region with a number of major cities along the climatological storm track. Despite its economic and social importance, as well as the area’s vulnerability to flooding, there is significant uncertainty around future trends in extreme precipitation over the region. Here, we undertake a regional study of the projected changes in extreme precipitation over the NEUS through the end of the twenty-first century using an ensemble of high-resolution, dynamically downscaled simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) project. We find that extreme precipitation increases throughout the region, with the largest changes in coastal regions and smaller changes inland. These increases are seen throughout the year, although the smallest changes in extreme precipitation are seen in the summer, in contrast to earlier studies. The frequency of heavy precipitation also increases such that there are relatively fewer days with moderate precipitation and relatively more days with either no or strong precipitation. Averaged over the region, extreme precipitation increases by +3%–5% °C−1 of local warming, with the largest fractional increases in southern and inland regions and occurring during the winter and spring seasons. This is lower than the +7% °C−1 rate expected from thermodynamic considerations alone and suggests that dynamical changes damp the increases in extreme precipitation. These changes are qualitatively robust across ensemble members, although there is notable intermodel spread associated with models’ climate sensitivity and with changes in mean precipitation. Together, the NA-CORDEX simulations suggest that this densely populated region may require significant adaptation strategies to cope with the increase in extreme precipitation expected at the end of the next century.Significance StatementObservations show that the northeastern United States has already experienced increases in extreme precipitation, and prior modeling studies suggest that this trend is expected to continue through the end of the century. Using high-resolution climate model simulations, we find that coastal regions will experience large increases in extreme precipitation (+6.0–7.5 mm day−1), although there is significant intermodel spread in the trends’ spatial distribution and in their seasonality. Regionally averaged, extreme precipitation will increase at a rate of ∼2% decade−1. Our results also suggest that the frequency of extreme precipitation will increase, with the strongest storms doubling in frequency per degree of warming. These results, taken with earlier studies, provide guidance to aid in resiliency preparation and planning by regional stakeholders.
Zhang, Zhixuan; Lou, Yidong; Zhang, Weixing; Liang, Hong; Bai, Jingna; Song, Weiwei
2022 Journal of Applied Meteorology and Climatology
AbstractCorrelation analysis between precipitable water vapor (PWV) and precipitation over China was conducted by combining high-quality PWV data based on 1999–2015 ground-based global positioning system (GPS) observations with the measurements at matched meteorological stations in the same period. The mean correlation coefficient at all the stations is approximately 0.73, indicating that there is a significant positive correlation between PWV content and precipitation measurements, and the comparison of correlation among different climate types suggests that the distribution characteristics of the correlation coefficients are distinctively related to different climate types. There is also some positive correlation between PWV and precipitation long-term trends, with the correlation coefficients of monthly anomalies ranging generally from 0.2 to 0.6. Furthermore, the intensity of both PWV and precipitation extremes shows a long-term upward trend overall, with the most-intense events showing more significant increases. The extreme precipitation–temperature scaling rate of changes can reach above Clausius–Clapeyron (CC) scaling, whereas that of the extreme PWV-temperature is sub-CC overall, with regional differences in the specific scaling values. The correlation analysis in this work is of great significance for long-term climate analysis and extreme weather understanding, which provides a valuable reference for better utilizing the advantages of PWV data to carry out the studies above.Significance StatementAtmospheric water vapor is crucial to the climate system, especially in the context of global warming, and accurate knowledge of the correlation between precipitable water vapor (PWV) and precipitation is of great significance for long-term climate analysis and extreme precipitation weather forecasting. We take full advantage of the long-term homogeneity of ground-based GPS to conduct long-term correlation analysis between GPS-derived PWV and precipitation over China. Results show a significant positive correlation between them, and the degree of correlation is related to different climate types. The correlation of monthly anomalies is also positive, and, over the long-term, both water vapor and precipitation extremes have been increasing in intensity, with more significant increases occurring in the most-intense events. Extreme precipitation might increase beyond thermodynamic expectations, whereas PWV increases below expectations.
Dunnavan, Edwin L.; Carlin, Jacob T.; Hu, Jiaxi; Bukovčić, Petar; Ryzhkov, Alexander V.; McFarquhar, Greg M.; Finlon, Joseph A.; Matrosov, Sergey Y.; Delene, David J.
2022 Journal of Applied Meteorology and Climatology
AbstractThis study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed Kdp and ZDR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using ZDR and Kdp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals.significance statementDeveloping snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting.
Zaremba, Troy J.; Rauber, Robert M.; Haimov, Samuel; Geerts, Bart; French, Jeffrey R.; Grasmick, Coltin; Heimes, Kaylee; Tessendorf, Sarah A.; Friedrich, Katja; Xue, Lulin; Rasmussen, Roy M.; Kunkel, Melvin L.; Blestrud, Derek R.
2022 Journal of Applied Meteorology and Climatology
AbstractVertical motions over the complex terrain of Idaho’s Payette River basin were observed by the Wyoming Cloud Radar (WCR) during 23 flights of the Wyoming King Air during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) field campaign. The WCR measured radial velocity Vr, which includes the reflectivity-weighted terminal velocity of hydrometeors Vt, vertical air velocity w, horizontal wind contributions as a result of aircraft attitude deviations, and aircraft motion. Aircraft motion was removed through standard processing. To retrieve vertical radial velocity W, Vr was corrected using rawinsonde data and aircraft attitude measurements; w was then calculated by subtracting the mean W (W¯) at a given height along a flight leg long enough for W¯ to equal the mean reflectivity-weighted terminal velocity Vt¯ at that height. The accuracy of the w and Vt¯ retrievals were dependent on satisfying assumptions along a given flight leg that the winds at a given altitude above/below the aircraft did not vary, the vertical air motions at a given altitude sum to 0 m s−1, and Vt¯ at a given altitude did not vary. The uncertainty in the w retrieval associated with each assumption is evaluated. Case studies and a projectwide summary show that this methodology can provide estimates of w that closely match gust probe measurements of w at the aircraft level. Flight legs with little variation in equivalent reflectivity factor at a given height and large horizontal echo extent were associated with the least retrieval uncertainty. The greatest uncertainty occurred in regions with isolated convective turrets or at altitudes where split cloud layers were present.
Zaremba, Troy J.; Heimes, Kaylee; Rauber, Robert M.; Geerts, Bart; French, Jeffrey R.; Grasmick, Coltin; Tessendorf, Sarah A.; Xue, Lulin; Friedrich, Katja; Rasmussen, Roy M.; Kunkel, Melvin L.; Blestrud, Derek R.
2022 Journal of Applied Meteorology and Climatology
AbstractUpdrafts in wintertime cloud systems over mountainous regions can be described as fixed, mechanically driven by the terrain under a given ambient wind and stability profile (i.e., vertically propagating gravity waves tied to flow over topography), and transient, associated primarily with vertical wind shear and conditional instability within passing weather systems. This analysis quantifies the magnitude of fixed and transient updraft structures over the Payette River basin sampled during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). Vertical motions were retrieved from Wyoming Cloud Radar measurements of radial velocity using the algorithm presented in Part I. Transient circulations were removed, and fixed orographic circulations were quantified by averaging vertical circulations along repeated cross sections over the same terrain during the campaign. Fixed orographic vertical circulations had magnitudes of 0.3–0.5 m s−1. These fixed vertical circulations were composed of a background circulation in which transient circulations were embedded. Transient vertical circulations are shown to be associated with transient wave motions, cloud-top generating cells, convection, and turbulence. Representative transient vertical circulations are illustrated, and data from rawinsondes over the Payette River basin are used to infer the relationship of the vertical circulations to shear and instability. Maximum updrafts are shown to exceed 5 m s−1 within Kelvin–Helmholtz waves, 4 m s−1 associated with transient gravity waves, 3 m s−1 in generating cells, 6 m s−1 in elevated convection, 4 m s−1 in surface-based deep convection, 5 m s−1 in boundary layer turbulence, and 9 m s−1 in shear-induced turbulence.
Heimes, Kaylee; Zaremba, Troy J.; Rauber, Robert M.; Tessendorf, Sarah A.; Xue, Lulin; Ikeda, Kyoko; Geerts, Bart; French, Jeffrey; Friedrich, Katja; Rasmussen, Roy M.; Kunkel, Melvin L.; Blestrud, Derek R.
2022 Journal of Applied Meteorology and Climatology
AbstractIn Part II, two classes of vertical motions, fixed (associated with vertically propagating gravity waves tied to flow over topography) and transient (associated primarily with vertical wind shear and conditional instability within passing weather systems), were diagnosed over the Payette River basin of Idaho during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). This paper compares vertical motions retrieved from airborne Doppler radial velocity measurements with those from a 900-m-resolution model simulation to determine the impact of transient vertical motions on trajectories of ice particles initiated by airborne cloud seeding. An orographic forcing index, developed to compare vertical motion fields retrieved from the radar with the model, showed that fixed vertical motions were well resolved by the model while transient vertical motions were not. Particle trajectories were calculated for 75 cross-sectional pairs, each differing only by the observed and modeled vertical motion field. Wind fields and particle terminal velocities were otherwise identical in both trajectories so that the impact of transient vertical circulations on particle trajectories could be isolated. In 66.7% of flight-leg pairs, the distance traveled by particles in the model and observations differed by less than 5 km with transient features having minimal impact. In 9.3% of the pairs, model and observation trajectories landed within the ideal target seeding elevation range (>2000 m), whereas, in 77.3% of the pairs, both trajectories landed below the ideal target elevation. Particles in the observations and model descended into valleys on the mountains’ lee sides in 94.2% of cases in which particles traveled less than 37 km.
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