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Stephen Jewson

Abstract

Knutson et al. recently published a metastudy that gives multimodel projections for changes in various properties of tropical cyclones under climate change. They considered frequency of tropical cyclones, frequency of very intense tropical cyclones, intensity of tropical cyclones, and total rainfall rate of tropical cyclones. For each of these properties, they reported changes globally and by basin for the six major tropical cyclone basins. The changes were presented as the change that would occur with 2°C warming of global mean surface temperature. These projections are potentially of great use to the tropical cyclone risk modeling community. However, most risk models use temporal baselines, such as the period from 1950 to 2019, and the Knutson et al. results can only be applied to risk models after some steps of adjustment involving past and future global mean surface temperature values. We derive the necessary adjustments and present and discuss some of the resulting projections, for different properties, basins, RCPs, and baselines. We find that the results are sensitive to the baseline being used, which implies that users of tropical cyclone risk models need to make sure they clearly understand what baseline their model represents before they adjust the model for climate change. One part of our analysis derives estimates of the implied impact of climate change so far on TC properties, relative to a representative baseline. The computer code we use to calculate the adjustments is available online.

Open access
Ioannis Cheliotis, Elsa Dieudonné, Hervé Delbarre, Anton Sokolov, Egor Dmitriev, Patrick Augustin, Marc Fourmentin, François Ravetta, and Jacques Pelon

Abstract

The studies related to the coherent structures in the atmosphere, using Doppler wind lidar observations, so far have relied on the manual detection and classification of the structures in the lidar images, making this process time-consuming. We developed an automated classification that is based on texture analysis parameters and the quadratic discriminant analysis algorithm for the detection of medium-to-large fluctuations and coherent structures recorded by single Doppler wind lidar quasi-horizontal scans. The algorithm classified a training dataset of 150 cases into four types of patterns, namely, streaks (narrow stripes), rolls (wide stripes), thermals (enclosed areas), and “others” (impossible to classify), with 91% accuracy. Subsequently, we applied the trained algorithm to a dataset of 4577 lidar scans recorded in Paris, atop a 75-m tower for a 2-month period (September–October 2014). The current study assesses the quality of the classification by examining the physical properties of the classified cases. The results show a realistic classification of the data: with rolls and thermals cases mostly classified concurrently with a well-developed atmospheric boundary layer and the streaks cases associated with nocturnal low-level jets events. Furthermore, rolls and streaks cases were mostly observed under moderate or high wind conditions. The detailed analysis of a 4-day period reveals the transition between the types. The analysis of the space spectra in the direction transverse to the mean wind, during these four days, revealed streak spacing of 200–400 m and roll sizes, as observed in the lower level of the mixed layer, of approximately 1 km.

Open access
James F. Booth, Veeshan Narinesingh, Katherine L. Towey, and Jeyavinoth Jeyaratnam

Abstract

Storm surge is a weather hazard that can generate dangerous flooding and is not fully understood in terms of timing and atmospheric forcing. Using observations along the northeastern United States, surge is sorted on the basis of duration and intensity to reveal distinct time-evolving behavior. Long-duration surge events slowly recede, whereas strong, short-duration events often involve negative surge in quick succession after the maximum. Using Lagrangian track information, the tropical and extratropical cyclones and atmospheric blocks that generate the surge events are identified. There is a linear correlation between surge duration and surge maximum, and the relationship is stronger for surge caused by extratropical cyclones as compared with those events caused by tropical cyclones. For the extremes based on duration, the shortest-duration strong surge events are caused by tropical cyclones, whereas the longest-duration events are most often caused by extratropical cyclones. At least one-half of long-duration surge events involve anomalously strong atmospheric blocking poleward of the cyclone, whereas strong, short-duration events are most often caused by cyclones in the absence of blocking. The dynamical influence of the blocks leads to slow-moving cyclones that take meandering paths. In contrast, for strong, short-duration events, cyclones travel faster and take a more meridional path. These unique dynamical scenarios provide better insight for interpreting the threat of surge in medium-range forecasts.

Open access
Hilde Haakenstad, Øyvind Breivik, Birgitte R. Furevik, Magnar Reistad, Patrik Bohlinger, and Ole Johan Aarnes

Abstract

The 3-km Norwegian Reanalysis (NORA3) is a 15-yr mesoscale-permitting atmospheric hindcast of the North Sea, the Norwegian Sea, and the Barents Sea. With a horizontal resolution of 3 km, the nonhydrostatic numerical weather prediction model HARMONIE–AROME runs explicitly resolved deep convection and yields hindcast fields that realistically downscale the ERA5 reanalysis. The wind field is much improved relative to its host analysis, in particular in mountainous areas and along the improved grid-resolving coastlines. NORA3 also performs much better than the earlier hydrostatic 10-km Norwegian Hindcast Archive (NORA10) in complex terrain. NORA3 recreates the detailed structures of mesoscale cyclones with sharp gradients in wind and with clear frontal structures, which are particularly important when modeling polar lows. In extratropical windstorms, NORA3 exhibits significantly higher maximum wind speeds and compares much better to observed maximum wind than do NORA10 and ERA5. The activity of the model is much more realistic than that of NORA10 and ERA5, both over the ocean and in complex terrain.

Open access
Domingo Muñoz-Esparza, Hyeyum Hailey Shin, Teddie L. Keller, Kyoko Ikeda, Robert D. Sharman, Matthias Steiner, Jeff Rawdon, and Gary Pokodner

Abstract

Takeoff and landing maneuvers can be particularly hazardous at airports surrounded by complex terrain. To address this situation, the Federal Aviation Administration has developed a precipitous terrain classification as a way to impose more restrictive terrain clearances in the vicinity of complex terrain and to mitigate possible altimeter errors and pilot control problems experienced while executing instrument approach procedures. The current precipitous point value (PPV) algorithm relies on the terrain characteristics within a local area of 2 n mi (3.7 km) in radius and is therefore static in time. In this work, we investigate the role of meteorological effects leading to potential aviation hazards over complex terrain, namely, turbulence, altimeter-setting errors, and density-altitude deviations. To that end, we combine observations with high-resolution numerical weather forecasts within a 2° × 2° region over the Rocky Mountains in Colorado containing three airports that are surrounded by precipitous terrain. Both available turbulence reports and model’s turbulence forecasts show little correlation with the PPV algorithm for the region analyzed, indicating that the static terrain characteristics cannot generally be used to reliably capture hazardous low-level turbulence events. Altimeter-setting errors and density-altitude effects are also found to be only very weakly correlated with the PPV algorithm. Altimeter-setting errors contribute to hazardous conditions mainly during cold seasons, driven by synoptic weather systems, whereas density-altitude effects are on the contrary predominantly present during the spring and summer months and follow a very well-marked diurnal evolution modulated by surface radiative effects. These findings demonstrate the effectiveness of high-resolution weather forecast information in determining aviation-relevant hazardous conditions over complex terrain.

Open access
Virendra P. Ghate, Maria P. Cadeddu, Xue Zheng, and Ewan O’Connor

Abstract

Marine stratocumulus clouds are intimately coupled to the turbulence in the boundary layer and drizzle is known to be ubiquitous within them. Six years of data collected at the Atmospheric Radiation Measurement’s (ARM) Eastern North Atlantic (ENA) site are utilized to characterize turbulence in the marine boundary layer and air motions below stratocumulus clouds. Profiles of variance of vertical velocity binned by wind direction (wdir) yielded that the boundary layer measurements are affected by the island when the wdir is between 90° and 310° (measured clockwise from the north from where air is coming). Data collected during the marine conditions (wdir < 90° or wdir > 310°) showed that the variance of vertical velocity was higher during the winter months than during the summer months because of higher cloudiness, wind speeds, and surface fluxes. During marine conditions the variance of vertical velocity and cloud fraction exhibited a distinct diurnal cycle with higher values during the nighttime than during the daytime. Detailed analysis of 32 cases of drizzling marine stratocumulus clouds showed that, for a similar amount of radiative cooling at the cloud top, within the subcloud layer 1) drizzle increasingly falls within downdrafts with increasing rain rates, 2) the strength of the downdrafts increases with increasing rain rates, and 3) the correlation between vertical air motion and rain rate is highest in the middle of the subcloud layer. The results presented herein have implications for climatological and model evaluation studies conducted at the ENA site, along with efforts to accurately represent drizzle–turbulence interactions in a range of atmospheric models.

Open access
L. Mahrt, H. J. S Fernando, and O. Acevedo

Abstract

Our study examines the horizontal variation of the nocturnal surface air temperature by analyzing measurements from four contrasting networks of stations with generally modest topography. The horizontal extent of the networks ranges from 1 to 23 km. For each network, we investigate the general relationship of the horizontal variation of temperature to the wind speed, wind direction, near-surface stratification, and turbulence. As an example, the horizontal variation of temperature generally increases with increasing stratification and decreases with increasing wind speed. However, quantitative details vary significantly between the networks. Needed changes of the observational strategy are discussed.

Open access
Xiaoxiong Lu, Qinglan Li, Wei Zhao, Aiguo Xiao, Guangxin Li, and Zifeng Yu

Abstract

Based on daily meteorological observation data in South China (SC) from 1967 to 2018, the spatiotemporal characteristics of the precipitation in SC over the past 52 years were studied. Only 8% of the stations showed a significant increase in annual rainfall, and there was no significant negative trend at any weather stations at a confidence level of 90%. Monthly rainfall showed the most significant decreasing and increasing trends in April and November, respectively. During the entire flooding season from April to September, the monthly rainfall at the weather stations in the coastal areas showed almost no significant change. The annual rainfall gradually decreased toward the inland area with the central and coastal areas of Guangdong Province as the high-value rainfall center. By using the empirical orthogonal function decomposition method, it was found that the two main monthly rainfall modes had strong annual signals. The first modal spatial distribution was basically consistent with the average annual rainfall distribution. Based on the environmental background analysis, it was found that during the flooding season the main water vapor to SC was transported by the East Asian summer monsoon and the Indian summer monsoon. In late autumn and winter, the prevailing wind from northeastern China could not bring much water vapor to SC and led to little precipitation in these two seasons. The spatial distribution of precipitation in SC during summer was more consistent with the moisture flux divergence distribution of the bottom layer from 925 to 1000 hPa rather than that of the layer from 700 to 1000 hPa.

Open access
Natalia Odnoletkova and Tadeusz W. Patzek

Abstract

We have analyzed the long-term temperature trends and extreme temperature events in Saudi Arabia between 1979 and 2019. Our study relies on high-resolution, consistent, and complete ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). We evaluated linear trends in several climate descriptors, including temperature, dewpoint temperature, thermal comfort, and extreme event indices. Previous works on this topic used data from weather station observations over limited time intervals and did not include temperature data for recent years. The years 2010–19 have been the warmest decade ever observed by instrumental temperature monitoring and are the eight warmest years on record. Therefore, the earlier results may be incomplete, and their results may no longer be relevant. Our findings indicate that, over the past four decades, Saudi Arabia has warmed up at a rate that is 50% higher than the rest of the landmass in the Northern Hemisphere. Moreover, moisture content of the air has significantly increased in the region. The increases of temperature and humidity have resulted in the soaring of dewpoint temperature and thermal discomfort across the country. These increases are more substantial during summers, which are already very hot relative to winters. Such changes may be dangerous to people over vast areas of the country. If the current trend persists into the future, human survival in the region will be impossible without continuous access to air conditioning.

Open access
Baojuan Huai, Michiel R. van den Broeke, Carleen H. Reijmer, and John Cappellen

Abstract

This paper estimates rainfall totals at 17 Greenland meteorological stations, subjecting data from in situ precipitation gauge measurements to seven different precipitation phase schemes to separate rainfall and snowfall amounts. To correct the resulting snow/rain fractions for undercatch, we subsequently use a dynamic correction model (DCM) for automatic weather stations (AWS, Pluvio gauges) and a regression analysis correction method for staffed stations (Hellmann gauges). With observations ranging from 5% to 57% for cumulative totals, rainfall accounts for a considerable fraction of total annual precipitation over Greenland’s coastal regions, with the highest rain fraction in the south (Narsarsuaq). Monthly precipitation and rainfall totals are used to evaluate the regional climate model RACMO2.3. The model realistically captures monthly rainfall and total precipitation (R = 0.3–0.9), with generally higher correlations for rainfall for which the undercatch correction factors (1.02–1.40) are smaller than those for snowfall (1.27–2.80), and hence the observations are more robust. With a horizontal resolution of 5.5 km and simulation period from 1958 to the present, RACMO2.3 therefore is a useful tool to study spatial and temporal variability of rainfall in Greenland, although further statistical downscaling may be required to resolve the steep rainfall gradients.

Open access