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The Madden–Julian oscillation (MJO) identified by Madden and Julian in the early 1970s has been well recognized as the most prominent intraseasonal signal in the tropics. Its discovery and its relationship with other weather phenomena such as tropical cyclones (TCs) are among the most significant advancements in modern meteorology with broad and far-reaching impacts. The original study by Madden and Julian used radiosonde data on Canton Island, and their spectral analysis revealed the signal of a 40–50-day oscillation.It has come to our attention that an earlier study by Xie et al. published in a Chinese journal documented an oscillatory signal of a 45-day period using radiosonde data from several stations between 70° and 125°E in the tropics. The 40–50-day signal found by Xie et al. is strikingly evident without any filtering. Xie et al. identified that occurrences of TCs are correlated with the 40–50-day variation of low-level westerlies at these stations. The original figures in Xie et al.’s article were hand drawn. Their results are verified using data from a longer period of 1958–70. The 40–50-day oscillation in the monsoon westerlies and its relationship with the occurrence of TCs are confirmed and further expanded upon.This study serves the purpose of bringing recognition to the community of the identification of a 40–50-day signal published in Chinese in 1963 and the discovery of the correlation between MJO phases and TC genesis three decades earlier than studies on this subject published outside China.

Anders K. Angstrom was known primarily for his contributions to the field of atmospheric radiation. However, his scientific interests encompassed many diverse topics. This paper describes the contents of two early, remarkable, and, until recently, largely unknown papers by Angstrom on probability forecasting and the use/value of weather forecasts. These papers, entitled “Sannolikhet och Praktisk Vaderleksprognos” (“Probability and Practical Weather Forecasting”) and “On the Effectivity of Weather Warnings,” were published in 1919 and 1922, respectively. Noteworthy features of these two papers include 1) a discussion of the sources of uncertainty in weather forecasting, 2) discourses on the problems of estimating probabilities by means of empirical relative frequencies and forecasters' subjective judgments, 3) the use of a Gaussian model to describe the accuracy of minimum temperature forecasts, 4) the identification of the ratio of the protection costa to the “risked value” if protective action is not tak...

While conducting a randomized seeding experiment, a storm was selected whose microphysical characteristics were so far from what was expected, given the existing thermodynamic environment, that some explanation was needed to account for the apparent errant behavior of this storm. More than a decade of sampling at −10°C using the project Lear jet has led to a simple classification technique, based on cloud-base temperature and buoyancy, which predicts the absence or presence, and to some extent the degree of coalescence (coalescence-freezing) precipitation growth in local convective storms. The unusual nature of this storm was recognized against this extensive microphysical database. The probable cause is attributed to emissions from a Kraft paper mill 10 km south of the storm's position. The mill had recently undergone an expansion program that had quadrupled its output of paper products. Using the radar characteristics of this unusual storm as a guide, a search of one season of radar data reveal...

Large (128 × 128 cm) pieces of chemically treated blotting paper were exposed to rain and both the size and position of the drops were determined. Analyses were performed indicating that the spatial distribution is fractal. This implies that drops cluster over all the observed scales and, hence, that backscattered microwave radiation from weather radars will have a degree of coherent scattering and a systematic dependence on the measurement resolution not accounted for in the standard theory. This was quantified by two scaling exponents, and a scheme to correct radar measurements for these fractal effects was developed.

Many of the atmospheric anomalies that occur around built-up areas were described qualitatively in the last century. Stimulated no doubt by the 1968 WMO Brussels Symposium on Urban Climates and by the present widespread interest in the environment of “human settlements,” there has been a recent quantum jump in the number of published papers on urban meteorology, including many attempts to model and quantify the anomalies. This short paper, which is not intended to be a survey, contains some thoughts an a few selected topics. The importance of monitoring beyond the suburban limits is stressed, in view of the interactions between the urban and regional fields of motion. Despite the fact that cities are usually located in irregular terrain, the value of searching for universal results is stressed both on the micro- and mesoscales within and near cities. As part of the design of new studies, inventories of existing data should be made. In many cases, the data banks deserve reexamination from time to ...

This article is a major extract from a position paper addressed to the Executive Director, Governor's Task Force on Public Education Policy, State of Minnesota. The author shows a real and significant underrepresentation by public school students as compared with their private and parochial school counterparts, an impression previously voiced by the Twin Cities Chapter.2 Recommendations are made primarily with an eye to the Minnesota scene, but certain of them may be applicable to other areas of the country.

The analyzed wind field at 850 mb during the summer monsoon experiment (MONEX) is subjected to a time series analysis to confirm the existence of a peak in the time range of 30–50 days. Having established that, this study presents a mapping of the motion field for this time scale. In this short paper we illustrate the steady meridional propagation of a train of troughs and ridges that seem to form near the equator and dissipate near the Himalayas. The meridional scale of this mode is around 300 km, and its meridional speed of propagation is ∼0.75° latitude per day. The amplitude of the wind for this mode is around 3–6 m s−1. The salient contributions here are the mapping and the demonstration of a very regular behavior of this mode; its existence is here noted from a period well before the onset of monsoon, i.e., from early May to late July. Three major storms during MONEX were noted to form within the trough line of this system, and the period of major cessation of rains over the Indian subconti...

A hybrid analog-digital computer has been established in the Department of Meteorology and Oceanography of the University of Michigan. It comprises three medium size analog computers, a small, general purpose digital computer, and an analog/digital linkage so that all of the computers can be operated together as a hybrid system. The primary functions of the computer are acquisition and reduction of field data and research in meteorological simulation. It is capable of accepting data acquired on-line from local instruments, or recorded in the field on analog magnetic tape, digital magnetic tape or punched paper tape. These data can then be processed in either analog or digital form or transmitted to a large digital computer via magnetic tape. The analog computers are versatile and of sufficient capacity to be useful for many analog data processing tasks as well as for simulation of atmospheric models such as those used in the study of diffusion and micrometeorology.

An x-ray diffraction study of AgI-NaI aerosols produced from a standard solution generator has revealed the formation of several hydrated phases. The aerosol samples were collected on glass filter paper and analyzed continuously in a controlled atmosphere chamber at 23C, with exploratory runs at 0C, at vapor pressures ranging from 2.5 mb to saturation values. At 4.5 (+1, −1.5) mb and 23C the aerosol transforms from a 3.9:1 weight ratio of dry AgI and NaI to 3.1:1 weight ratio of AgI and NaI·2H2O. At 8.1 (±1) mb there is a 60% loss in free AgI with formation of 3AgI·2NaI·nH2O (4

The climate system responds to changes in the amount of atmospheric greenhouse gases or aerosols through rapid processes, triggered within hours and days, and through slower processes, where the full response may only be seen after centuries. In this paper, we aim to elucidate the mechanisms operating on time scales of hours to years to better understand the response of key climate quantities such as energy fluxes, temperature, and precipitation after a sudden increase in either carbon dioxide (CO2), black carbon (BC), or sulfate (SO4) aerosols. The results are based on idealized simulations from six global climate models. We find that the effect of changing ocean temperatures kicks in after a couple of months. Rapid precipitation reductions start occurring instantly and are established after just a few days. For BC, they constitute most of the equilibrium response. For CO2 and SO4, the magnitude of the precipitation response gradually increases as surface warming/cooling evolves, and for CO2, the sign of the response changes from negative to positive after 2 years. Rapid cloud adjustments are typically established within the first 24 h, and while the magnitude of cloud feedbacks for CO2 and SO4 increases over time, the geographical pattern of the equilibrium cloud change is present already after the first year. While there are model differences, our work underscores the overall similarity of the major time-varying processes and responses simulated by current global models and hence the robustness of key features of simulated responses to historical and future anthropogenic forcing. Significance Statement How does the climate system respond to a change in the amount of atmospheric greenhouse gases or aerosols? Some processes are rapid, responding within hours and days. Others are slow, and the full response to a forcing of the climate may only be seen after centuries. In this paper, we use six global climate models to investigate the time scales of climate responses to carbon dioxide, black carbon, and sulfate, focusing on key climate quantities, such as temperature, precipitation, and clouds. While there are ample model differences, our work underscores the overall similarity of the major time-varying processes and responses simulated by current global models and hence the robustness of key features of simulated responses to historical and future anthropogenic forcing.

Reconstructing the history of polar temperature from ice core water isotope (δ18O) calibration has remained a challenge in paleoclimate research, because of our incomplete understanding of various temperature–δ18O relationships. This paper resolves this classical problem in a new framework called the unified slope equations (USE), which illustrates the general relations among spatial and temporal δ18O–surface temperature slopes. The USE is applied to the Antarctica temperature change during the last deglaciation in model simulations and observations. It is shown that the comparable Antarctica-mean spatial slope with deglacial temporal slope in δ18O–surface temperature reconstruction is caused, accidentally, by the compensation responses between the δ18O–inversion layer temperature relation and the inversion layer temperature itself. Furthermore, in light of the USE, we propose that the present seasonal slope of δ18O–inversion layer temperature is an optimal paleothermometer that is more accurate and robust than the spatial slope. This optimal slope suggests the possibility of reconstructing past Antarctic temperature changes using present and future instrumental observations. Significance Statement This paper develops a new framework called the unified slope equations (USE) to provide, for the first time, a general relation among various spatial and temporal water isotope–temperature slopes. The application of the USE to Antarctic deglacial temperature change shows that the optimal paleothermometer is the seasonal slope of the inversion layer temperature.

High-resolution observations have demonstrated the presence of strong time-mean near-surface wind convergences (NSWC) anchored across oceanic frontal zones, such as the western boundary currents. Initial analyses appeared to show a close association between this time-mean NSWC and time-mean properties of the underlying sea-surface temperature (SST), such as the gradients and second derivatives (e.g., Laplacian of SST), acting through pressure adjustment and vertical mixing mechanisms. However, a series of recent papers have revealed the instantaneous NSWC to be dominated by atmospheric fronts, and suggested the importance of air-sea processes occurring instead on shorter, synoptic timescales. In this paper, using the ERA-5 reanalysis dataset in the Gulf Stream region, we aim to reconcile these viewpoints by investigating the spatial and temporal dependence of NSWC and its relationship to SST. It is revealed that while atmospheric frontal processes govern the day-to-day variability of NSWC, the relatively weak but persistent pressure adjustment and vertical mixing mechanisms provide lower frequency modulations in conditions both with and without atmospheric fronts. In addition to their temporal characteristics, each mechanism is shown through spectral analysis to dominate on specific spatial scales. In light of recent work that has tied remote atmospheric responses to NSWC anomalies in western boundary current regions, these results emphasize the importance of oceanic frontal zones for atmospheric variability on all spatiotemporal scales.

This paper examines the trends in hot summer days for the Pacific Northwest in observations and a regional climate model ensemble. Hot days are identified by the temperature threshold for several percentile values computed over 10-yr intervals (85th, 90th, and 95th percentiles and absolute maximum) to differentiate heat events of different intensities and are compared to the median temperature (50th percentile). For the stations analyzed, the observed rate of warming during hot days is not statistically different from the warming rate of median days since the 1950s. However, for projections to 2100, hot days show a statistically significant increase in the warming rate of the hottest days compared to the warming rate for median days. Depending on location, the 95th-percentile daily maximum temperature shows a warming rate of up to 0.2°C decade−1 above the median warming rate. The divergence in the trends of median and extreme temperature shows substantial regional variation depending on local terrain and coastlines. The warming trend during hot days is related to the unique circulation patterns during heat events, which respond to different feedbacks and amplifying effects in the land–atmosphere system from those that prevail during typical days. The regional climate model simulations are taken from an ensemble of the Weather Research and Forecasting (WRF) Model simulations forced by 12 global climate model simulations from phase 5 of the Climate Model Intercomparison Project (CMIP5) using the RCP8.5 emissions scenario and 12-km grid spacing. Significance Statement The heatwave of June 2021 had substantial societal and ecological impacts, illustrating vulnerability to record-shattering events. This paper addresses whether climate change can cause heat events in the Pacific Northwest to warm at a more rapid rate than typical days. Based on observations, in the recent past, the hottest days warmed at about the same rate as typical days in the recent past. However, results from a high-resolution climate model show a higher rate of warming during the warmest days relative to median days under the most aggressive future emissions scenario. This effect could cause heatwaves to become more intense relative to typical days by 2100, making adaptation to extreme events more difficult.

This paper describes the new Regional Arctic Ocean/sea ice Reanalysis (RARE) with a domain that spans a subpolar/polar cap poleward of 45°N. Sequential data assimilation constrains temperature and salinity using World Ocean Database profiles as well as in situ and satellite SST, and PIOMAS sea ice thickness estimates. The 41-yr (1980–2020) RARE1.15.2 reanalysis with resolution varying between 2 and 5 km horizontally and 1–10 m vertically in the upper 100 m is examined. To explore the impact of resolution RARE1.15.2 is compared to a coarser-resolution SODA3.15.2, which uses the same modeling and data assimilation system. Improving resolution in the reanalysis system improves agreement with observations. It produces stronger more compact currents, enhances eddy kinetic energy, and strengthens along-isopycnal heat and salt transports, but reduces vertical exchanges and thus strengthens upper ocean haline stratification. RARE1.15.2 and SODA3.15.2 are also compared to the Hadley Center EN4.2.2 statistical objective analysis. In regions of reasonable data coverage such as the Nordic seas the three products produce similar time-mean distributions of temperature and salinity. But in regions of poor coverage and in regions where the coverage changes in time EN4.2.2 suffers more from those inhomogeneities. Finally, the impact on the Arctic of interannual temperature fluctuations in the subpolar gyres on the Arctic Ocean is compared. The influence of the subpolar North Pacific is limited to a region surrounding Bering Strait. The influence of the subpolar North Atlantic, in contrast, spreads throughout the Nordic seas and Barents Sea in all three products within two years. Significance Statement The Arctic Ocean/sea ice system plays crucial roles in climate variability and change by controlling the northern end of the oceanic overturning circulation, the equator to pole air pressure gradient, and Earth’s energy balance. Yet the historical ocean observation set is sparse and inhomogeneous, while ocean dynamics has challengingly fine horizontal and vertical scales. This paper introduces a new Regional Arctic Ocean/sea ice Reanalysis (RARE) whose goal is to use the combined constraints of mesoscale ocean dynamics, historical observations, surface meteorology, and continental runoff in a data assimilation framework to reconstruct historical variability. RARE is used to produce a 41-yr ocean/sea ice reanalysis 1980–2020 whose results are described here.

This paper develops the concept of flood problem framing to understand decision-makers’ priorities in flood risk management in the Los Angeles Metropolitan Region in California (LA Metro). Problem frames shape an individual’s preferences for particular management strategies and their future behaviors. While flooding is a complex, multifaceted problem, with multiple causes and multiple impacts, a decision-maker is most likely to manage only those dimensions of flooding about which they are aware or concerned. To evaluate flood decision-makers’ primary concerns related to flood exposure, vulnerability, and management in the LA Metro, we draw on focus groups with flood control districts, city planners, nonprofit organizations, and other flood-related decision-makers. We identify numerous concerns, including concerns about specific types of floods (e.g., fluvial vs pluvial) and impacts to diverse infrastructure and communities. Our analyses demonstrate that flood concerns aggregate into three problem frames: one concerned with large fluvial floods exacerbated by climate change and their housing, economic, and infrastructure impacts; one concerned with pluvial nuisance flooding, pollution, and historic underinvestment in communities; and one concerned with coastal and fluvial flooding’s ecosystem impacts. While each individual typically articulated concerns that overlapped with only one problem frame, each problem frame was discussed by numerous organization types, suggesting low barriers to cross-organizational coordination in flood planning and response. This paper also advances our understanding of flood risk perception in a region that does not face frequent large floods. Significance Statement This paper investigates the primary concerns that planners, flood managers, and other decision-makers have about flooding in Southern California. This is important because the way that decision-makers understand flooding shapes the way that they will plan for and respond to flood events. We find that some decision-makers are primarily concerned with large floods affecting large swaths of infrastructure and housing; others are concerned with frequent, small floods that mobilize pollution in low-income areas; and others are concerned with protecting coastal ecosystems during sea level rise. Our results also highlight key priorities for research and practice, including the need for flexible and accessible flood data and education about how to evacuate.

In this paper, we study the role of climate change as a financial risk for foreign investors. Multinational enterprises seek to internationalize where financial risk is at the minimum level, including the climate change risk on profitability and productivity. Thereby, we conducted an empirical analysis of the effect of climate change on inward foreign direct investment (FDI) net inflows using data from 200 countries and times series from 1970 to 2020 and employing two categories of climate change indicators: Climatology and climate-related natural hazards. Using the estimation methods of fully modified ordinary least squares and robust weighted least squares, we concluded that the rise of climatology indicators (mean annual temperature and precipitations) negatively impacts inward FDI. Second, we conclude that most climate-related natural hazards (coastal/rural/urban floods, landslides, and cyclones) deter FDI while extreme heat and wildfires show no significant effect. In addition, the results show that the negative impact of climate change is more severe when the host economy depends on agricultural activities and there is no significant investment in research and development as compared with countries that depend on service and manufacturing activities and are more innovative and invest in technology infrastructure. Furthermore, we conclude that poorer host countries experience more severe effects of climate change on FDI than rich countries in terms of GDP per capita. Significance Statement The purpose of the paper is to investigate the effect of climate change on inflows of cross-border capital in 200 countries. In other words, we see if rising temperature and natural hazards related to climate change affect the decision of firms to invest in a given country. The results show that global warming and unstable meteorological indicators deter firms from investing abroad. Equally, natural hazards linked to climate change (coastal/rural/urban floods, landslides, and cyclones) constitute an investment risk. The finding suggests that the deterring effects of climate change are less severe when a given country depends less on agriculture and more on industrial sectors and when that country is more developed and technologically advanced.

On 7 February 2020, precipitation within the comma-head region of an extratropical cyclone was sampled remotely and in situ by two research aircraft, providing a vertical cross section of microphysical observations and fine-scale radar measurements. The sampled region was stratified vertically by distinct temperature layers and horizontally into a stratiform region on the west side, and a region of elevated convection on the east side. In the stratiform region, precipitation formed near cloud top as side-plane, polycrystalline, and platelike particles. These habits occurred through cloud depth, implying that the cloud-top region was the primary source of particles. Almost no supercooled water was present. The ice water content within the stratiform region showed an overall increase with depth between the aircraft flight levels, while the total number concentration slightly decreased, consistent with growth by vapor deposition and aggregation. In the convective region, new particle habits were observed within each temperature-defined layer along with detectable amounts of supercooled water, implying that ice particle formation occurred in several layers. Total number concentration decreased from cloud top to the −8°C level, consistent with particle aggregation. At temperatures > −8°C, ice particle concentrations in some regions increased to >100 L−1, suggesting secondary ice production occurred at lower altitudes. WSR-88D reflectivity composites during the sampling period showed a weak, loosely organized banded feature. The band, evident on earlier flight legs, was consistent with enhanced vertical motion associated with frontogenesis, and at least partial melting of ice particles near the surface. A conceptual model of precipitation growth processes within the comma head is presented. Significance Statement Snowstorms over the northeast United States have major impacts on travel, power availability, and commerce. The processes by which snow forms in winter storms over this region are complex and their snowfall totals are hard to forecast accurately because of a poor understanding of the microphysical processes within the clouds composing the storms. This paper presents a case study from the NASA IMPACTS field campaign that involved two aircraft sampling the storm simultaneously with radars, and probes that measure the microphysical properties within the storm. The paper examines how variations in stability and frontal structure influence the microphysical evolution of ice particles as they fall from cloud top to the surface within the storm.

Micropulse differential absorption lidars (MPD) for water vapor, temperature, and aerosol profiling have been developed, demonstrated, and are addressing the needs of the atmospheric science community for low-cost ground-based networkable instruments capable of long-term monitoring of the lower troposphere. The MPD instruments use a diode-laser-based (DLB) architecture that can easily be adapted for a wide range of applications. In this study, a DLB direct-detection Doppler lidar based on the current MPD architecture is modeled to better understand the efficacy of the instrument for vertical wind velocity measurements, with the long-term goal of incorporating these measurements into the current network of MPD instruments. The direct-detection Doppler lidar is based on a double-edge receiver that utilizes two Fabry–Pérot interferometers and a vertical velocity retrieval that requires the ancillary measurement of the backscatter ratio, which is the ratio of the total backscatter coefficient to the molecular backscatter coefficient. The modeling in this paper accounts for the major sources of error. It indicates that the vertical velocity can be retrieved with an error of less than 0.56 m s−1 below 4 km with a 150-m range resolution and an averaging time of 5 min. Significance Statement Monitoring the temperature, relative humidity, and winds in the lower atmosphere is important for improving weather forecasting, particularly for severe weather such as thunderstorms. Cost-effective micropulse differential absorption lidar (MPD) instrumentation for continuous temperature and humidity monitoring has been developed and demonstrated, and its effects on weather forecasting are currently being evaluated. The modeling study described in this paper studies the feasibility of using a similar cost-effective MPD instrument architecture for monitoring vertical wind velocity in the lower atmosphere. Modeling indicates that wind velocities can be measured with less than 0.56 m s−1 accuracy and demonstrates the feasibility of adding vertical wind velocity measurements to the MPD instruments.

Instrumental data from the pre–Industrial Revolution period are important to ­understand climate change. In this paper, the observations made by the French missionary J. Amiot in present-day central Beijing during 1757–62 were processed and analyzed. The observations represent the earliest continuous dataset of meteorological records found in China that have been digitized recently. Comparisons between the Amiot annual temperature range and extreme values with modern observations showed that the observations were read at approximately 0800 and 1500 local solar time (LST) in a well-ventilated outdoor site. The daily maximum, minimum, and mean temperatures (T-max, T-min, and T-mean, respectively) during 1757–62 were determined by examining the relationship between temperature at 0800 and 1500 LST and T-max, T-min, and T-mean in modern reference series. Nearly 260 years ago, Beijing’s climate was typical of an inland temperate monsoon zone with annual T-mean, annual mean T-max, and annual mean T-min being 11.5°, 17.8°, and 6.1°C, respectively; further, the temperatures did not vary considerably from the 1951–1980 temperatures, but differed evidently compared to relatively recent decades (1981–2020). The difference was larger than the magnitudes of global and regional temperature changes. Thus, climate warming since the pre–Industrial Revolution period in the urban areas of Beijing has dominantly occurred over the last four decades. Uncertainties related to the thermometer and observational conditions 260 years ago and the interpolation method used have also been discussed in this paper.

The latest established generation of weather radars provides polarimetric measurements of a wide variety of meteorological and nonmeteorological targets. While the classification of different precipitation types based on polarimetric data has been studied extensively, nonmeteorological targets have garnered relatively less attention beyond an effort to detect them for removal from meteorological products. In this paper we present a supervised learning classification system developed in the Finnish Meteorological Institute (FMI) that uses Bayesian inference with empirical probability density distributions to assign individual range gate samples into 7 meteorological and 12 nonmeteorological classes, belonging to five top-level categories of hydrometeors, terrain, zoogenic, anthropogenic, and immaterial. We demonstrate how the accuracy of the class probability estimates provided by a basic naive Bayes classifier can be further improved by introducing synthetic channels created through limited neighborhood filtering, by properly managing partial moment nonresponse, and by considering spatial correlation of class membership of adjacent range gates. The choice of Bayesian classification provides well-substantiated quality estimates for all meteorological products, a feature that is being increasingly requested by users of weather radar products. The availability of comprehensive, fine-grained classification of nonmeteorological targets also enables a large array of emerging applications, utilizing nonprecipitation echo types and demonstrating the need to move from a single, universal quality metric of radar observations to one that depends on the application, the measured target type, and the specificity of the customers’ requirements. Significance Statement In addition to meteorological echoes, weather radars observe a wide variety of nonmeteorological phenomena including birds, insects, and human-made objects like ships and aircraft. Conventionally, these data have been rejected as undesirable disturbance, but lately their value for applications like aeroecological monitoring of bird and insect migration has been understood. The utilization of these data, however, has been hampered by a lack of comprehensive classification of nonmeteorological echoes. In this paper we present a comprehensive, fine-grained, probabilistic classifier for all common types of nonmeteorological echoes which enables the implementation of a wide range of novel weather radar applications.

Inland flooding and mudslides from tropical cyclone (TC) rainstorms are among the most destructive natural hazards in China, resulting in considerable direct economic losses and large numbers of fatalities. In this paper, a TC precipitation model (TCPM) is improved by incorporating the effects of complex terrain through a set of new parameters (e.g., slope, roughness, and attenuation distance) for a more accurate assessment of TC rainfall hazards in China. Moreover, by introducing parameterized spiral rainbands, the model could more accurately capture the intensity of extreme precipitation. The model comprehensively considers dynamic and thermodynamic precipitation factors and is adept at capturing the climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China. The model is verified by providing two comparisons. One is analysis including detailed results of three typical TC cases, and the other uses empirical cumulative distribution functions for extreme observations and simulations of historical landfalling TCs in China during the period 1960–2018. The comparisons reveal that the TCPM shows impressive performance for strong TCs with heavy precipitation within 200–300 km of the TC center. Moreover, both the modeled extreme hourly and total TC precipitation probability distributions are consistent with the observations. However, the model needs to be further improved for TCs with dispersive or long-distance precipitation. Significance Statement In this paper, an optimized and physics-based model for the simulation of tropical cyclone precipitation is described and used to estimate the risk of TC rainfall hazards in China. The work is innovative in that it considers the effect of complex terrain from three perspectives, including slope, roughness, and attenuation distance. The simulations demonstrated that the model is adept at capturing the main climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China, which is simple to run several hundred thousand times, with bright application prospects in catastrophe risk assessment.

The hydrogen balloon is widely used for wind sensing by tracking it with optical theodolites. The traditional theodolite observation (single- and double-theodolite) methods assume that the balloon is a perfect tracer of the background wind and it rises with a constant speed during the whole observation period, but these assumptions may not hold well in complex wind circumstances. In this paper, an accurate wind field retrieval method based on multi-theodolite measurement is proposed. The extended Kalman filter algorithm is used to filter the angle data observed by the theodolites in order to accurately estimate the trajectory of the balloon, and the motion equation is used to correct the velocity difference between the background wind and the balloon. As a result, not only the horizontal velocity but also the vertical velocity can be accurately retrieved by this method. Numerical simulation and field experiments show that the multi-theodolite observation method excels the traditional single-theodolite method, and the velocity errors can be reduced by even more than 40% in comparison with the single-theodolite method for complex wind cases. Significanace Statement In the meteorological community, hydrogen balloon tracking is a widely used wind retrieval method, but the accuracy is limited, especially under complex wind conditions. In this paper, a new method based on tracking the hydrogen balloon with multi-theodolite is proposed, which uses the extended Kalman filter and the motion equation to get an accurate estimation of the balloon’s velocity and fix the inertia effect of balloon, respectively. Simulation and field experiment show that the new method can reduce the velocity error by more than 40% compared with the traditional method.

In a previous paper a formula was derived for the maximum potential intensity of the tangential wind in a tropical cyclone called PI+. The formula, PI+2 = EPI2 + αrmwmηm, where EPI is the maximum potential intensity of the gradient wind and αrmwmηm represents the supergradient winds. The latter term is the product of the radius rm, the vertical velocity wm, the azimuthal vorticity ηm at the radius and height of the maximum tangential wind (rm, zm), and the (nearly constant) α. Examination of a series of simulations of idealized tropical cyclones indicate an increasing contribution from the supergradient-wind term to PI+ as the radius of maximum wind increases. In the present paper, the physical content of the supergradient-wind term is developed showing how it is directly related to tropical cyclone boundary layer dynamics. It is found that , where −umin is the maximum boundary layer radial inflow velocity and lυ(z) is the vertical mixing length.

Adverse weather such as rain, snow, and fog may significantly reduce visibility or change adhesion properties and, as a consequence, affect drivers’ sense of safety, driving comfort, and their reaction to a changing driving environment (i.e., lower speed and increased headways). The changed behavior of individual drivers affects both traffic flow characteristics, that is, average speed and headways, and parameters related to highway performance such as free-flow speed and capacity. Thus, understanding the impact may be important in the context of predicting and assessing traffic conditions on planned or existing road facilities. The paper discusses the effects of adverse weather conditions and time of day on traffic flow characteristics and the parameters related to highway performance. Using real traffic and weather data from a Polish expressway, the paper aims to identify factors related to weather and time of day that significantly influence traffic flow parameters and traffic conditions and to analyze and quantify this impact. The results of the study may help to develop coefficients of weather-related adjustment factors that will make it possible to estimate, for example, average speed of vehicles in the nighttime or in conditions of rain or limited visibility. The results of the study may contribute to a new Polish method for capacity estimation and traffic conditions assessment for uninterrupted traffic facilities.