Low-level Moisture Research Articles

Local Influence of Surface Relative Humidity on Weather Radar Rainfall Observations over an Agricultural Semi-Arid Area

Agricultural areas in semi-arid regions modify low-level atmospheric conditions through changes in heat and moisture surface fluxes and enhanced evapotranspiration. This study aims to investigate the influence of near-ground-level relative humidity (RH) on local precipitation characteristics in a relatively flat, mid-latitude, semi-arid agricultural region, divided into a rainfed and an irrigated area with high evapotranspiration contrast in summer. The region was selected for the Land Surface Interactions with the Atmosphere over the Iberian Semi-Arid Environment (LIAISE) international field campaign in 2021 and here is studied using Automatic Weather Station observations and C-band weather radar data covering six years. Summer RH records show clear contrasts between irrigated and non-irrigated areas, unlike rain gauge and radar-derived rainfall, which do not exhibit substantial differences. A closer analysis indicates that RH differences between irrigated and non-irrigated areas before rainfall tend to diminish for several hours after the rainfall onset. This suggests that the presence of rainfall is temporally more important than whether the terrain is irrigated or not. Examination of radar reflectivity (Z) profiles considered convective and non-convective cases averaged during the first 30 and 180 min from the precipitation onset. Results indicated a dependence on ground-level RH for convective cases, leading to higher Z values with higher RH, clearer for the first 30 min averaged profiles. Finally, a linear relation was found between the lowest 1 km radar Z value and collocated RH for the first 30 min period of convective precipitation, increasing Z with RH. These results point out that, despite no differences in precipitation amounts found over contiguous irrigated and non-irrigated areas, there is a local impact of low-level moisture on convective rainfall.

Decadal Regime Shifts in Sea Fog Frequency over the Northwestern Pacific: The Influence of the Pacific Decadal Oscillation and Sea Surface Temperature Warming

Sea fog significantly impacts marine activities, ecosystems, and radiation balance. We analyzed the decadal variation characteristics of sea fog frequency (SFF) over the northwestern Pacific and investigated the roles of the Pacific decadal oscillation (PDO) and sea surface temperature (SST) warming in driving these changes. The results show that SFF experienced a significant and sudden decadal increase around 1978 (up by 12.9%) and a prominent decadal decrease around 1999 (down by 7.8%). The sudden increase in SFF around 1978 was closely related to the PDO. A positive PDO phase induced unusual anticyclonic circulation and southerly winds over the northwestern Pacific, enhancing low-level atmospheric stability and moisture supply, thus facilitating sea fog formation. Nevertheless, the decrease in SFF around 1999 was related to SST warming in the north Pacific. The rise in sea temperatures weakened the SST front south of the foggy region, reducing the cooling and condensation of warm air necessary for sea fog formation. This study enhances the understanding of the decadal variability mechanism of SFF over the northwestern Pacific regulated by large-scale circulation systems and provides a reference for future sea fog forecasting work.

Retrieval of Boundary Layer Precipitable Water from GOES ABI Using Machine Learning Techniques

Abstract Low-level moisture is an important ingredient for forecasting severe storms, especially over the Great Plains where severe storms often develop along the dryline. Although ground-based observation systems such as lidar or radiosondes on weather balloons provide accurate information on low-level moisture, data are provided at limited locations, and the low temporal resolution of radiosondes makes it difficult to track a rapidly developing dryline. Geostationary satellites provide high spatial and temporal observation, but the channels of current geostationary satellites are mostly sensitive to water vapor at mid- to upper levels. However, the split window difference (SWD) between the “clean” window channel (10.3 μm) and the “dirty” window channel (12.3 μm) is commonly used for estimating low-level water vapor. However, this estimation is complicated by surface temperature contributions, dependence on the lapse rate, and nonlinear relationships between SWD and moisture. This study applies machine learning techniques to infer boundary layer precipitable water (BLPW) from Geostationary Operational Environmental Satellite (GOES) Advanced Baseline Imager (ABI) data. Since there are few observations that cover wide regions for training convolutional neural networks, especially for the atmosphere above the surface, High-Resolution Rapid Refresh (HRRR) model outputs are used as the truth for training. Statistical results show that using ABI channel 13, 14, and 15 brightness temperatures, skin temperature, solar zenith angle, and GOES total precipitable water product as additional inputs shows the lowest mean-square error (MSE). Case study results show that the model developed in this study is good at capturing strong moisture gradients and depicting a dryline. Significance Statement Knowledge of low-level moisture is important for monitoring drylines and moisture convergence preceding convective initiation. Traditional observations lack the spatial resolution, spatial coverage, or temporal update frequency needed by forecasters. The latest generation of Geostationary Operational Environmental Satellite (GOES), the GOES-R series, provides high spatial resolution and rapid temporal updates. However, the estimation of low-level moisture using the Advanced Baseline Imager (ABI) is complicated by dependencies on other variables and nonlinear relationships. Machine learning is shown to provide good estimates of low-level moisture from ABI observations. This application of machine learning to GOES-R can improve the ability to monitor low-level moisture and forecast convective initiation.

Burn Period: A Use-Inspired Metric to Track Wildfire Risk across Arizona and New Mexico in the Southwest United States

Abstract Numerous tools and indices exist for wildland fire managers to anticipate and track changes in wildfire risk driven by variability in weather and climate conditions at hourly to seasonal scales. However, in working closely with Southwest U.S. managers, we learned of a simple meteorological metric being informally used, but not widely accessible in existing tools or information products, to gauge short-term changes in wildfire risk. This metric, termed “Burn Period” (BP), is the local count of hours per day with relative humidity values equal to or less than 20%. Our collaboration led to the development of an experimental tool called the “Burn Period Tracker” to ease access and promote the use of BP values for planning and response. This study is a climatological analysis of BP values at 124 fire weather stations across Arizona and New Mexico for the period 2000–22 to aid in interpretation and understanding of this use-inspired metric. BP values reflect the strong seasonality in temperature and moisture deficit–driven wildfire risk across the Southwest United States, with risk climbing through the arid spring season, peaking in June, and then falling rapidly with the onset of the summer monsoon in July. Regression analyses show that short-term variability in BP values is driven by variability in low-level atmospheric moisture in all months with strongest relationships during the summer after the onset of the monsoon. This study highlights the utility of BP as a short-term wildfire planning tool as well as an example of collaborative weather and climate services development.

Tropical Cyclone Wind Shear-Relative Asymmetry in Reanalyses

Abstract While tropical cyclones (TCs) are axisymmetric vortices to the first order, they often exhibit noteworthy structural asymmetries. These often result from environmental vertical wind shear, which tilts the vortex and induces a wavenumber 1 pattern in the circulation and precipitation fields. Reanalyses and climate models have improved in representing the TC structure and climatology, but their relatively coarse resolution and dependence on parameterized physics cast doubt on their ability to capture the asymmetric TC structure. We perform the most comprehensive process-oriented assessment of TC asymmetry to date in reanalyses. Specifically, we analyze the composite shear-relative TC structure in ERA5 and Climate Forecast System Reanalysis (CFSR), which vary in their resolutions, physical parameterization suites, and data assimilation techniques. These structures are compared with aircraft reconnaissance radar observations. In agreement with the observations, the strongest tangential winds are usually found left-of-shear, while inner core rainfall, ascent, vortex tilt, and low-level inflow are favored directly downshear or in the downshear-left quadrant. Outer rainband convection generally peaks in the downshear-right quadrant. Thermodynamic asymmetries are also apparent, with anomalous low-level moisture right-of-shear, midlevel warmth in the upshear-right quadrant (uptilt), and cloud properties suggestive of a realistic precipitation life cycle from growth to fallout. We also decompose rainfall contributions from the convective parameterization and large-scale cloud schemes and highlight the roles of vorticity advection, buoyancy advection, and diabatic processes in driving asymmetric vertical motions in the inner core and outer rainband regions. Our results suggest that process-level studies of TC asymmetry and TC–wind shear interaction under future warming are viable using climate models. Significance Statement Asymmetries are common in tropical cyclones (TCs), influencing their intensity, track, and hazards. Vertical wind shear often plays a leading-order role in causing these asymmetries. It is uncertain how well asymmetric structures and processes are captured in reanalyses and global climate models (GCMs) with grid spacings of 0.25° and coarser. In this study, we first evaluate TC asymmetry in reanalyses, which have the benefit of being forced by observations. This helps to assess whether the resolutions associated with GCMs sufficiently capture asymmetric structures and processes and motivates upcoming work with free-running GCMs to study how TC asymmetry may change in a warming climate.

Meteorological factors associated with dry thunderstorms and simultaneous lightning-ignited wildfires: The 15 June 2022 outbreak in Catalonia

Summer heatwaves and extended dry spells create optimal meteorological conditions for occasional dry thunderstorms to produce simultaneous lightning-ignited wildfires (LIW). Concurrent ignitions put a significant burden on the firefighting's initial attack, potentially allowing incipient LIWs to escape and grow into large fires. While we can reasonably forecast lightning activity, predicting dry thunderstorm conditions and potential LIW outbreaks remains challenging. In the present study, we analyze the meteorological factors associated with a LIW outbreak that took place in Catalonia on 15 June 2022, with 22 LIW reported in three consecutive days. The fire hazard was high, but not different from past LIW episodes. ERA5-derived indices related to low-level moisture showed extreme values compared to previous studies. Atmospheric conditions with an elevated lifting condensation level coupled with the synoptic framework were set for the formation of dry thunderstorms. Radar reflectivity profiles revealed sub-cloud evaporation, and rain-gauge records corroborated the occurrence of dry lightning. In the context of global warming, we expect an increase in the frequency of LIW outbreaks in the European Mediterranean region due to an increase in lightning-ignition efficiency, which refers to the average chance of fire per lightning stroke.

Impacts of Large-Scale Offshore Wind Farms on Tropical Cyclones: A Case Study of Typhoon Hato

Abstract With the rising global demand for renewable energy sources, a great number of offshore wind farms are being built worldwide, as well as in the northern South China Sea. There is, however, limited research on the impact of offshore wind farms on the atmospheric and marine environment, particularly tropical cyclones, which frequently occur in summertime in the South China Sea. In this paper, we employ the Weather Research and Forecasting (WRF) Model to investigate the impacts of large-scale offshore wind farms on tropical cyclones, using the case of Typhoon Hato, which caused severe damage in 2017. Model results reveal that maximum wind speeds in coastal areas decrease by 3–5 m s−1 and can reach a maximum of 8 m s−1. Furthermore, the wind farms change low-level moisture convergence, causing a shift in the precipitation center toward the wind farm area and causing a significant overall reduction (up to 16%) in precipitation. Model sensitivity experiments on the area and layout of the wind farm have been carried out. The results show that larger wind farm areas and denser turbine layouts cause a more substantial decrease in the wind speed over the coast and accumulated precipitation reduction, further corroborating our findings. Significance Statement This study holds significant implications for developing offshore wind farms in tropical cyclone-prone regions like the South China Sea. By focusing on Typhoon Hato as a case study, the research sheds light on the previously understudied relationship between large-scale offshore wind farms and tropical cyclones. The observed decrease in coastal wind speeds and altered precipitation patterns due to wind farm presence highlights the potential for mitigating cyclone-related risks in these regions. Additionally, the study’s sensitivity experiments underscore the importance of careful planning and design in optimizing wind farm layouts for maximum impact reduction. This research contributes vital insights into sustainable energy infrastructure development while minimizing environmental and meteorological risks in cyclone-prone areas.

Unraveling the role of the western North Pacific circulation anomaly in modulating Indian summer monsoon rainfall variability beyond ENSO

The Indian summer monsoon (ISM) rainfall interannual variability is known to be strongly linked to the El-Niño–Southern Oscillation (ENSO). This linear relationship is the primary factor in controlling the interannual variation in ISM precipitation. However, there are many outlier cases, and such deviations pose significant challenges in seasonal prediction over this region. Here we show that such challenges can be attributed to anomalous atmospheric pressure patterns in the Western North Pacific (WNP) region. The anticyclonic circulation anomaly over WNP region causes the easterly wind toward the Indian subcontinent, leading to positive precipitation anomalies with stronger low-level moist convergence, while the cyclonic circulation decreases ISM precipitation. The linear baroclinic model simulation results further support that the WNP circulation pattern can serve as an independent factor for forecasting precipitation over India. The WNP circulation anomaly play the crucial role generating ISM precipitation particularly for July and September. Our study suggests that the role of the WNP circulation anomaly should be carefully considered as the secondary prevailing mechanism on the subseasonal timescale during the boreal summer in addition to the ENSO signal.

Phenolic, amino acids, and fatty acids profiles and the nutritional properties in the fresh and dried fruits of black rosehip (Rosa pimpinellifolia L.)

Recently, increased attention has been paid to the raw materials of plants as a source of biologically active substances. Black rosehip (Rosa pimpinellifolia L.) fruits could be a good resource for potential functional components in the food, cosmetic and pharmaceutical industries. Also, drying can influence the composition of heat-sensitive phytochemicals. However, less attention is given to comparing black rosehip bioactive compounds particularly compositions of fatty acid, amino acids, and phenolic content in fresh and dried fruits. So in this study, the amino acid constituents (by amino acid analyzer), fatty acids (by GC–MS), mineral elements (by atomic absorption spectrometer), antioxidant (by DPPH) and phenolic compounds (by HPLC) present in fresh and dried fruits of black rosehip naturally grown in Iran were comprehensively investigated. The results showed that dried fruits had a lower level moisture by 51.55%, and a higher level of total phenolic compounds and total sugar by 786.20 mg GAE/100 g and 15.77 g/100 g, respectively. Chlorogenic acid and gallic acid were the major phenolic compounds (109.3 mg/g). Whilst, linoleic acid, oleic acid, and arachidic acid (85.34%) were the most dominant fatty acids. The most dominant amino acids were glutamic acid, phenylalanine, and arginine (29.41 g/100 g). Also, Fe and Mn as micro-elements were the most dominant elements. In general, the results illustrated the potentials and differences of black rosehip fruits grown in the Arasbaran region as promising resources for food sources, pharmaceutics, cosmetics, and breeding programs. Also, these findings confirm that black rosehip fruits contain significant amounts of secondary metabolites that may positively affect human health.

Diurnal cycles of rain storms over South China during the presummer rainy season

The variation characteristics of rain storms (RSs) are closely related to complex internal physical processes and external dynamic and thermodynamic conditions. Using a 17-year observational rainfall dataset from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), the diurnal cycles of various RS characteristics and their responses to the South China Sea Summer Monsoon (SCSSM) are investigated in South China (SC) during the presummer rainy season (PSRS). Before SCSSM outbreaks, the RSs in the western inland region of SC (WSC) have stronger precipitation intensities and convective features due to orographic lifting, especially at night, while those in the eastern inland region of SC (ESC) have higher RS occurrence frequencies with higher moisture transport, especially in the afternoon. The onset of the SCSSM leads to abundant moisture and sufficient convective available potential energy over the entire SC area, resulting in significant increases in the occurrence frequency, convective fraction, and precipitation top height of RSs. In the WSC, the weakened upward motion and smaller convective inhibition limit RS development, resulting in weaker rainfall intensity. In the ESC, a particularly unstable atmosphere and enhanced low-level moisture transport in the afternoon lead to a larger three-dimensional size, more active convection, and greater precipitation intensity in the RSs. These results offer fresh insight into the diurnal variation in rainfall during the PSRS and can be effectively used to evaluate numerical model simulations.

Enhanced Mid-to-Late Summer Precipitation over Midlatitude East Asia under Global Warming

Abstract East Asian summer monsoon precipitation is projected to increase under greenhouse warming with strong intraseasonal variation. Using a 35-member CESM Large Ensemble and 30 CMIP6 models, this study reveals that in July and August, maximum rainfall changes in East Asia take place in the midlatitudes, influencing regions encompassing North and Northeast China, the Korean Peninsula, and Japan. The intensified precipitation is attributed to the combined effect of the thermodynamic and dynamic components. The former stems from the enriched low-level moisture, which peaks in continental East Asia in July and August, under global warming. The dynamic effect is due to the enhanced upward motion, associated with the enhanced southerlies throughout the troposphere over midlatitude East Asia. The southerlies also act to intensify the low-level monsoonal circulation, strengthening moisture transport from the tropical ocean to the midlatitudes. In addition to the mean-state changes, the precipitation interannual variability in this region also intensifies, partly due to the enhanced low-level moisture and partly associated with enhanced large-scale circulation anomalies, such as the northwestern Pacific anticyclone. The enhanced background precipitation, along with the intensified interannual variability, may lead to more rainy summers in a warmer climate, with instances where historically extreme precipitation events become more frequent, posing challenges for water resource management and agriculture in the region.

Hydrometeorological controls of and social response to the 22 October 2019 catastrophic flash flood in Catalonia, north-eastern Spain

Abstract. On 22 October 2019, the Francolí River basin in Catalonia, north-eastern Spain, experienced a heavy precipitation event that resulted in a catastrophic flash flood, causing six fatalities. Few studies comprehensively address both the physical and human dimensions and their interrelations during extreme flash flooding. This research takes a step forward towards filling this gap in knowledge by examining the alignment among all these factors. The hydrometeorological factors are investigated using the new Triangle-based Regional Atmospheric Model, radar-derived precipitation estimates, post-flood field and gauge observations, and the Kinematic Local Excess Model. The social dimension is assessed by examining the relationship between catchment dynamics and warning response times and by quantifying human behaviour during the course of the flash flood through a post-event citizen science campaign. Results reveal that a persistent south-easterly airflow brought low-level moisture and established convective instability in the region, while local orography was instrumental to triggering deep moist convection. A convective train promoted intense, copious, and prolonged precipitation over the north-western catchment headwaters. Basin response was significantly modulated by the very dry initial soil moisture conditions. After the long-lasting rainfall, an acute burst of precipitation resulted in extreme flash flooding. Fast and abrupt increases in streamflow affect small spatial scales and leave limited time for the effective implementation of protective measures. The institutional organization–protection–prevention cycle unfolded at the spatial and temporal scales typically dominated by the meteorological rather than hydrological scales. Although the citizen science campaign reveals the effectiveness of the warnings in reaching the population living in the most affected areas, a significant proportion of the respondents expressed a lack of adequate information or were unfamiliar with the intended meaning. In addition, a majority of the interviewees did not perceive any significant threat to life or property. In view of these results, this study identifies potential areas for improving social preparedness for similar natural hazards in the future.

Propagation and Maintenance of the Quasi-Biweekly Oscillation over the Western North Pacific in Boreal Winter

Abstract This study investigates the propagation and maintenance mechanisms of the dominant intraseasonal oscillation over the western North Pacific in boreal winter, the quasi-biweekly oscillation (QBWO). The wintertime QBWO over the western North Pacific is characterized by the westward-northwestward movement from the tropical western Pacific to the western North Pacific and resembles the n = 1 equatorial Rossby wave. Its westward migration is primarily driven by the seasonal-mean zonal winds that advect vorticity anomalies in the lower–middle troposphere and moisture anomalies in the lower troposphere. Its northward movement is preconditioned by the vorticity dynamics of the beta effect, the low-level vertical moisture variation, and the local air–sea interaction. The latter involves the atmospheric forcing on the underlying ocean by changing the surface heat flux fluctuations and the sea surface temperature feedback on the low-level atmospheric instability. Its maintenance is primarily through atmospheric external energy sources from diabatic heating, which first generates eddy available potential energy and then converts it to eddy kinetic energy. Significance Statement Atmospheric quasi-biweekly oscillation (QBWO) is an important climate phenomenon over the western North Pacific in boreal winter. It can trigger significant influences both in the tropical and extratropical regions. Given the importance, it is necessary to investigate the propagation and maintenance mechanisms of the QBWO over the western North Pacific in boreal winter. The QBWO usually propagates northwestward from the tropical western Pacific to the western North Pacific. The westward propagation is driven by the seasonal mean zonal winds that advect vorticity anomalies in the lower–middle troposphere and moisture anomalies in the lower troposphere. The northward propagation is caused jointly by several processes, including the atmospheric forcing on the ocean via the surface heat flux fluctuations, the feedback of ocean on the low-level atmospheric instability, the vorticity dynamics of the beta effect, and the vertical variation of low-level moisture. In addition, converting from eddy available potential energy to eddy kinetic energy is essential in maintaining the QBWO’s development. The disclosure of these crucial processes deepens the dynamics of the QBWO over the western North Pacific in boreal winter.

ERA5‐Based Significant Tornado Environments in Canada Between 1980 and 2020

AbstractThis study uses ERA5 close‐proximity soundings and associated convective parameters to characterize significant tornadic storm (F/EF2+) environments between 1980 and 2020 in parts of Canada. It is shown that ERA5 convective parameters are suitable to represent observed parameters, based on radiosonde comparisons. Results indicate that the eastern Canadian Prairies have nearly double the lifted condensation level with higher level of free convection compared to eastern Canada (southern Ontario/Quebec). Eastern Canada has more a humid boundary layer and free troposphere that can lead to warmer cold pools, favoring tornadogenesis. Central Canada (Manitoba) has the largest mixed‐layer (ML) convective available potential energy (CAPE) mainly due to a combination of regional differences in low level moisture and steeper mid‐level lapse rates in western Canada. Central continental U.S. and Canadian regions appear to have the highest (most negative) convective inhibition, leading to more explosive initiation. Mean bulk wind shear and storm relative helicity (SRH) increases from west to east, with eastern regions being significantly larger. The supercell composite and significant tornado parameters are generally less than U.S. magnitudes, particularly in western Canada, and would require recalibration for more practical use in Canada. Overall, western Canada significant tornadic storms are associated with more low‐level looping hodographs and dominated by thermodynamic influences compared to larger wind influences in eastern regions. This is likely due to more spring, late summer, and autumn events that typically have well‐developed synoptic systems (stronger wind shear) with overall less buoyant energy in eastern regions.

Impact of Deforestation in the Maritime Continent on the Madden–Julian Oscillation

Abstract Deforestation is a major issue affecting both regional and global hydroclimates. This study investigated the effect of deforestation in the Maritime Continent (MC) on tropical intraseasonal climate variability. Using a global climate model with credible Madden–Julian oscillation (MJO) simulations, we examined the effect of deforestation over the MC region by replacing the forest canopy with grassland. The results revealed that under constant orographic and land–sea contrast forcing, the modification of the canopy over the MC altered the characteristics of the MJO. We noted the amplification of the MJO and increases in wet–dry fluctuation and the zonal extent. We analyzed more than 100 MJO cases by performing K-means clustering and determined that the continuous propagation of the MJO over the MC increased from 35% in the control experiment to 61% in the deforestation experiment. This phenomenon of less blocked MJO over the MC in the deforestation run was associated with more substantial precipitation, increased soil moisture, and a suppressed diurnal cycle in land convection. Furthermore, when the MJO convection was over the Indian Ocean (IO), we observed the enhancement of low-level moisture over the MC region in the deforestation experiment. Grassland surface forcing provides a thermodynamic source for triggering instability in the atmosphere, resulting in low-level moisture convergence. The MJO exhibited a stronger energy recharge–discharge cycle in the deforestation experiment than in the control experiment, and this difference between the experiments enlarged as the MJO progressed from the IO to MC.

Radar Survey of Hail-Producing Storms and Environments during the 2018–19 Severe-Weather Season in the Córdoba Region of Argentina

Abstract Frequent deep convective thunderstorms and mesoscale convective systems make the Córdoba region, near the Sierras de Córdoba mountain range, one of the most active areas on Earth for hail activity. Analysis of hail observations from trained observers and social media reports cross-referenced with operational radar observations identified the convective characteristics of hail-producing convective systems in central Argentina over a 6-month period divided into early (October–December 2018) and late seasons (January–March 2019). Reflectivity and dual-polarization characteristics from the Córdoba operational radar [Radar Meteorológico Argentina (RMA1)] were used to identify the convective modes of convective cells at time of positive hail indicators. Analysis of ERA5 upper-air and surface data examined convective environments of hail events and identified representative dynamic and thermodynamic environments. A majority of early season hail-producing cells were classified as discrete convection, while discrete and multicell occurrence evened out in the late season. Most hail-producing cells initiated directly adjacent to the Sierras in the late season, while cell initiation and hail production is further spread out in the early season. Dividing convective events into dynamic/thermodynamic regimes based on values of 1000 J kg−1 of CAPE and vertical wind shear of 20 m s−1 results in most early season events reflecting shear-dominant characteristics (low CAPE, high shear) and most late-season events exhibiting CAPE-dominant characteristics (high CAPE, low shear). Strength and placement of low-level temperature and moisture anomalies/advection and upper-level jets largely defined the differences in the dominant regimes. Significance Statement This study used regional radar data alongside hail reports from trained observers and social media to better understand the types and timing of storms identified as producing hail, given the lower resolution of satellite studies. Dividing the hail season (October–December; January–March) showed that within hail season, early season storms tended to be singular storms that formed across the region in environments with strong vertical winds and weak instability. Late-season storms were a mix of singular storms and multicellular storm systems focused on the mountains in weak vertical winds and strong instability. These results show differences from satellite studies and identify key representative hail-producing radar features and environmental regimes for this region, which could guide hail risk analysis within the severe-weather season.

Probabilistic Forecasting of Lightning Strikes over the Continental USA and Alaska: Model Development and Verification

Lightning is responsible for the most area annually burned by wildfires in the extratropical region of the Northern Hemisphere. Hence, predicting the occurrence of wildfires requires reliable forecasting of the chance of cloud-to-ground lightning strikes during storms. Here, we describe the development and verification of a probabilistic lightning-strike algorithm running on a uniform 20 km grid over the continental USA and Alaska. This is the first and only high-resolution lightning forecasting model for North America derived from 29-year-long data records. The algorithm consists of a large set of regional logistic equations parameterized on the long-term data records of observed lightning strikes and meteorological reanalysis fields from NOAA. Principal Component Analysis was employed to extract 13 principal components from a list of 611 potential predictors. Our analysis revealed that the occurrence of cloud-to-ground lightning strikes primarily depends on three factors: the temperature and geopotential heights across vertical pressure levels, the amount of low-level atmospheric moisture, and wind vectors. These physical variables isolate the conditions that are favorable for the development of thunderstorms and impact the vertical separation of electric charges in the lower troposphere during storms, which causes the voltage potential between the ground and the cloud deck to increase to a level that triggers electrical discharges. The results from a forecast verification using independent data showed excellent model performance, thus making this algorithm suitable for incorporation into models designed to forecast the chance of wildfire ignitions.

A study of extreme rainfall events and urban flooding over Hyderabad, October 2020

The present study analyses and describes the evolution of the Mesoscale Convective Complex (MCC) and its atmospheric conditions during Extreme rainfall event in Hyderabad, on 13th October 2020. This extreme weather event was a mesoscale event embedded in a synoptic-scale system. During the second week of October 2020, a depression formed over the west-central Bay of Bengal (BoB) and travelled north-westwards through peninsular India, causing heavy rains in Andhra Pradesh and Telangana states of India on October 13-14. On October 13, many parts of Hyderabad and Cyberabad received more than 300 mm of rain within 24 hrs. Satellite imagery suggests that this mesoscale system constituted a unique set of structured convection those reported in MCC. This MCC has a cloud shield with a continuous low IR temperature of less than - 33 °C over an area of more than 100000 km2 and a cloud shield with a continuous low IR temperature of less than -54 °C over an area of more than 50000 km2 over Hyderabad with a life cycle of about 9 hours. This MCC featured multi cellular characteristics, showing that there was significant low-level moisture in its environment, as well as a mix of vigorous updrafts, implying significant rainfall rates over Hyderabad. The synoptic features suggest that with high precipitable water, the long axis of low-level moisture convergence at 0850 hPa and large horizontal vorticity at 0925 hPa were oriented parallel to the system's mean wind flow. In this case, a clusters of thunderstorms arose in the area of moisture convergence which prolonged the duration of extremely heavy rainfall. The high rain rate, relatively sluggish storm motion, and prolonged back-building over the same locations for several hours are likely to blame for the heavy rainfall accumulations that were observed. The hydrological conditions compounded the effects of the torrential rain, resulting in a natural hazard.

The Impact of High-Density Airborne Observations and Atmospheric Motion Vector Observation Assimilation on the Prediction of Rapid Intensification of Hurricane Matthew (2016)

Tropical cyclone rapid intensification (RI) prediction still remains a big international challenge in numerical weather prediction. Hurricane Matthew (2016) underwent extreme and non-classic RI, intensifying from a Category 1 storm to a Category 5 hurricane within 24 h under a strong vertical shear environment. However, most models failed to capture this RI, and limited or no inner core, and outflow observations were assimilated in the NWS operational HWRF Model before the onset of RI for Matthew (2016). The goals of the study are to (1) explore the best way to assimilate the High-Density Observations (HDOB, including FL and SFMR) and AMV data; (2) study the impact of assimilating these observations on the analysis of both the inner-core and outflow structures; and (3) examine the impact of assimilating these data on the prediction of RI for Matthew. The main results are as follows: (1) With proper pre-processing of the HDOB observations and by using a 4DEnVar method, the inner-core structure analysis was improved. And the RI prediction is more consistent with the best track without spin-down for the first 24 h. Assimilating CIMMS AMV observations on top of the HDOB observations further improves both the track and intensity forecasts. Specifically, both the magnitude and timing of the peak intensity are further improved. (2) Diagnostics are conducted to understand how the assimilation of these different types of observations impacts RI prediction. Without assimilating HODB and AMV data, baseline experimentover-predict the intensification rate during the first 18 h, but under-predict RI after 18 h. However, the assimilation of FL and SFMR and CIMMS AMV correctly weakens the upper-level outflow and improves the shear-relative structure of the inner-core vortex, such as reducing the low-level moisture in the downshear left quadrant. The deep convection on the downshear side is weaker than baseline for the first 18 h but keeps enhancing, later moving cyclonically to the USL quadrant, and then causes more subsidence warming, maximizing in the USL quadrant and the maximum wind increases faster. Moreover, the rapid intensification rate is much more consistent with the best track and the forecast skill of RI is improved. Therefore, 4DEnVar assimilation with proper pre-processing of the high-density observations can indeed correct the shear-relative moisture and structural distributions of both the inner core and environment for TCs imbedded in the stronger shear, which is important for shear-TC RI prediction.

Influences of the South American Low-Level Jet on the Convective Environment in Central Argentina Using a Convection-Permitting Simulation

Abstract This study documents the spatial and temporal distribution of the South American low-level jet (SALLJ) and quantifies its impact on the convective environment using a 6.5-month convection-permitting simulation during the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations and Clouds, Aerosols, and Complex Terrain Interactions (RELAMPAGO-CACTI) campaigns. Overall, the simulation reproduces the observed SALLJ characteristics in central Argentina near the Sierras de Córdoba (SDC), a focal point for terrain-focused upscale growth. SALLJs most frequently occur in the summer with maxima to the northwest and east of the SDC and minima over the higher terrain. The shallower SALLJs (<1750 m) have a strong overnight skew, while the elevated jets are more equally spread throughout the day. SALLJ periods often have higher amounts of low-level moisture and instability compared to non-SALLJ periods, with these impacts increasing over time when the SALLJ is present and decreasing afterward. The SALLJ may enhance low-level wind shear magnitudes (particularly when accounting for the jet height); however, enhancement is somewhat limited due to the presence of speed shear in most situations. SALLJ periods are associated with low-level directional shear favorable for organized convection and an orientation of cloud-layer wind shear parallel to the terrain, which could favor upscale growth. A case study is shown in which the SALLJ influenced both the magnitude and direction of wind shear concurrent with convective upscale growth near the SDC. This study highlights the complex relationship between the SALLJ and its impacts during periods of widespread convection. Significance Statement Areas of enhanced low-level winds, or low-level jets, likely promote favorable conditions for upscale growth, the processes by which storms grow larger. Central Argentina is an ideal place to study the influence of low-level jets on upscale growth as storms often stay connected to the Sierras de Córdoba Mountain range, growing over a relatively small area. This study uses model data to describe the distribution and impact of the South American low-level jet on the storm environment. The South American low-level jet is frequently found near the Sierras de Córdoba, and moisture and convective instability increase when it is present. However, the jet’s impact on other conditions important for upscale growth, such as vertical wind shear, is not as straightforward.