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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. [ABSTRACT FROM AUTHOR]

A major challenge encountered in the development of systems exposed to weather stressors, such as autonomous vehicles and unstaffed aerial vehicles, is to ensure their proper functioning under adverse rain or snow conditions. Since the sensing of the surroundings by these vehicles relies on optical sensors such as lidars and cameras, it is essential to ensure the robustness of these systems from the early stages of the project. In this respect, experiments in climatic wind tunnels provide a solution for simulating the operating conditions that the autonomous vehicles will confront. This work proposes a method based on field measurements and unsupervised machine learning to faithfully reproduce in controlled environments real weather conditions captured during wintertime in Ontario, Canada. The purpose of this paper is not to investigate correlations between observed weather conditions and the characteristics of the precipitation encountered, but rather to establish a consistent method based on outdoor disdrometer data to identify critical parameters to be simulated in climatic wind tunnels. To achieve this goal, weather data such as temperature, relative humidity, and droplet size distribution were recorded at General Motors’s McLaughlin Advanced Technology Track (MATT) using an FD70 disdrometer andWXT530 weather transmitter, both manufactured by Vaisala, installed on a car provided by the Automotive Center of Excellent (ACE) team of the University of Ontario Institute of Technology. The implementation of the proposed method allowed the identification of precipitation clusters characterized by parameters of a theoretical model for particle size distributions fitted to the collected data. [ABSTRACT FROM AUTHOR]

Syukoro (Suki) Manabe's Nobel Prize in Physics was awarded largely for his early work on one-dimensional models of "radiative–convective equilibrium" (RCE), which produced the first credible estimates of Earth's climate sensitivity. This article reviews that work and tries to identify those aspects that make it so distinctive. We argue that Manabe's model of RCE contained three crucial ingredients. These are (i) a tight convective coupling of the surface to the troposphere, (ii) an assumption of fixed relative humidity rather than fixed absolute humidity, and (iii) a sufficiently realistic representation of greenhouse gas radiative transfer. Previous studies had separately identified these key ingredients, but none had properly combined them. We then discuss each of these ingredients in turn, highlighting how subsequent research in the intervening decades has only cemented their importance for understanding global climate change. We close by reflecting on the elegance of Manabe's approach and its lasting value. [ABSTRACT FROM AUTHOR]

Ice habit diagrams published prior to 2009—and many since—do not accurately describe in situ observations of ice shapes as a function of temperature and moisture. Laboratory studies and analysis of field observations by Bailey and Hallett in a series of papers in 2002, 2004, and 2009 corrected several errors from earlier studies, but their work has not been widely disseminated. We present a new, simplified diagram based on Bailey and Hallett's work that focuses on several ice growth forms arising from the underlying surface processes by which mass is added to a crystal: tabular, columnar, branched, side branched, two types of polycrystalline forms, and a multiple growth regime at low ice supersaturations. To aid interpretation for a variety of applications, versions of the ice growth diagram are presented in terms of relative humidity with respect to water as well as the traditional formats of relative humidity with respect to ice and vapor density excess. These diagrams are intended to be understandable and useful in classroom settings at the sophomore undergraduate level and above. The myriad shapes of pristine snow crystals can be described as the result of either a single growth form or a sequence of growth forms. Overlays of data from upper-air soundings on the ice growth diagrams aid interpretation of expected physical properties and processes in conditions of ice growth. [ABSTRACT FROM AUTHOR]

This work examines the diurnal and seasonal variability of near-surface temperature and humidity at several large areas with high population density within the Maritime Continent using the Bureau of Meteorology Atmospheric Regional Reanalysis (BARRA) 12-km-resolution dataset that covers the period 1990–2019. The diurnal cycle is examined in detail, with a key feature being the relatively small diurnal variation of the wet-bulb temperature TWB when compared with the temperature and dewpoint temperature TD. The diurnal variability is strongly modulated by the monsoons with their increased rainfall and cloud cover. The near-surface signals associated with the Madden–Julian oscillation across the domains are relatively weak. Dry and humid temperature extremes are examined for regional and seasonal variability. The dry and moist variable extremes occur at different times of year, but each have spatially coherent structure. Significance Statement: This paper examines the climatological variations of near-surface temperature and humidity and their extremes in four locations in the "Maritime Continent." This is important because there are significant variations potentially affecting human and ecosystem health and its resilience to climate change. [ABSTRACT FROM AUTHOR]

Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs). This paper presents and compares different statistical downscaling models that use multiple linear regression (MLR), positive coefficient regression (PCR), stepwise regression (SR), and support vector machine (SVM) techniques for estimating monthly rainfall amounts in the state of Florida. Mean sea level pressure, air temperature, geopotential height, specific humidity, U wind, and V wind are used as the explanatory variables/predictors in the downscaling models. Data for these variables are obtained from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis dataset and the Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model, version 3 (CGCM3) GCM simulations. The principal component analysis (PCA) and fuzzy c-means clustering method (FCM) are used as part of downscaling model to reduce the dimensionality of the dataset and identify the clusters in the data, respectively. Evaluation of the performances of the models using different error and statistical measures indicates that the SVM-based model performed better than all the other models in reproducing most monthly rainfall statistics at 18 sites. Output from the third-generation CGCM3 GCM for the A1B scenario was used for future projections. For the projection period 2001-10, MLR was used to relate variables at the GCM and NCEP grid scales. Use of MLR in linking the predictor variables at the GCM and NCEP grid scales yielded better reproduction of monthly rainfall statistics at most of the stations (12 out of 18) compared to those by spatial interpolation technique used in earlier studies. [ABSTRACT FROM AUTHOR]

Better understanding of how moisture, clouds, and precipitation covary under climate warming lacks a comprehensive observational view. This paper analyzes the tropical atmospheric water cycle's evolution with sea surface temperature (SST), using for the first time, the synergistic dataset of instantaneous observations of the relative humidity profile from the Megha-Tropiques satellite, clouds from the CALIPSO satellite, and near-surface precipitation from the CloudSat satellite, and quantifies their rates of change with SST warming. The dataset is partitioned into three vertical velocity regimes, with cloudy grid boxes categorized by phase (ice or liquid), opacity (opaque or thin), and the presence of near-surface precipitation. Opaque cloud cover is always larger in the presence of near-surface precipitation (high ice clouds especially). Low liquid water clouds in the descending regime dominate for SSTs < 299.25 K, where the free troposphere is dry (~20%), and opaque liquid water cloud cover decreases with SST warming (−8% K−1) and thin liquid water cloud cover stays constant (~20%). High ice clouds dominate the ascending regime in which, for 299.25 < SST < 301.75 K, humidity increases with SST in the lower free troposphere and peaks around 302 K. Over the warm SST range (>301.75 K), in the ascending regime, opaque high ice cloud cover decreases with SST (−13% K−1), while thin ice cloud cover increases (+6% K−1). Over the warm SST range, total cloudiness decreases with warming in all regimes. This paper characterizes fundamental relationships between aspects of the tropical atmospheric water cycle and SST. [ABSTRACT FROM AUTHOR]

Globally, extreme rainfall has intense impacts on ecosystems and human livelihoods. However, no effort has yet been made to forecast the extreme rainfall indices through machine learning techniques. In this paper, a new extreme rainfall indices forecasting model is proposed using a random forest (RF) model to provide effective forecasts of monthly extreme rainfall indices. In addition, RF feature importance is proposed in this study to identify the most and least important features for the proposed model. This study forecasts only statistically significant extreme rainfall indices over Bangladesh including consecutive dry days (CDD), the number of heavy rain days (R10mm; rainfall ≥ 10 mm), and the number of heavy rain days (R20mm; rainfall ≥ 20 mm) within 1–3 months of lead time. The proposed model uses monthly antecedent CDD, R10mm, and R20mm including atmospheric parameters and ocean–atmospheric teleconnections, namely, convective available potential energy (CAPE), relative humidity (RH), air temperature (TEM), El Niño–Southern Oscillation (ENSO), Indian Ocean dipole (IOD), and North Atlantic Oscillation (NAO), as the inputs to the model. Results show that the proposed model yields the best performance to forecast CDD, R10mm, and R20mm with only the antecedent of these indices as input. Ocean–atmospheric teleconnections (IOD, ENSO, and NAO) are useful for CDD forecasting, and local atmospheric parameters (CAPE, RH, and TEM) are useful for R10mm and R20mm forecasting. The results suggest that adding atmospheric parameters and ocean–atmospheric teleconnections is useful to forecast extreme rainfall indices. [ABSTRACT FROM AUTHOR]

The impact of two different coupled cirrus microphysics-radiation parameterizations on the zonally averaged temperature and humidity biases in the tropical tropopause layer (TTL) of a Met Office climate model configuration is assessed. One parameterization is based on a linear coupling between a model prognostic variable, the ice mass mixing ratio q i, and the integral optical properties. The second is based on the integral optical properties being parameterized as functions of q i and temperature, T c, where the mass coefficients (i.e., scattering and extinction) are parameterized as nonlinear functions of the ratio between q i and T c. The cirrus microphysics parameterization is based on a moment estimation parameterization of the particle size distribution (PSD), which relates the mass moment (i.e., second moment if mass is proportional to size raised to the power of 2) of the PSD to all other PSD moments through the magnitude of the second moment and T c. This same microphysics PSD parameterization is applied to calculate the integral optical properties used in both radiation parameterizations and, thus, ensures PSD and mass consistency between the cirrus microphysics and radiation schemes. In this paper, the temperature-non-dependent and temperature-dependent parameterizations are shown to increase and decrease the zonally averaged temperature biases in the TTL by about 1 K, respectively. The temperature-dependent radiation parameterization is further demonstrated to have a positive impact on the specific humidity biases in the TTL, as well as decreasing the shortwave and longwave biases in the cloudy radiative effect. The temperature-dependent radiation parameterization is shown to be more consistent with TTL and global radiation observations. [ABSTRACT FROM AUTHOR]

Extensive expansion in irrigated agriculture has taken place over the last half century. Due to increased irrigation and resultant land-use–land-cover change, the central United States has seen a decrease in temperature and changes in precipitation during the second half of the twentieth century. To investigate the impacts of widespread commencement of irrigation at the beginning of the growing season and continued irrigation throughout the summer on local and regional weather, the Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 in southeastern Nebraska. GRAINEX consisted of two 15-day intensive observation periods. Observational platforms from multiple agencies and universities were deployed to investigate the role of irrigation in surface moisture content, heat fluxes, diurnal boundary layer evolution, and local precipitation. This article provides an overview of the data collected and an analysis of the role of irrigation in land–atmosphere interactions on time scales from the seasonal to the diurnal. The analysis shows that a clear irrigation signal was apparent during the peak growing season in mid-July. This paper shows the strong impact of irrigation on surface fluxes, near-surface temperature and humidity, and boundary layer growth and decay. [ABSTRACT FROM AUTHOR]

Cascade reservoirs were designed for the Yalong River basin, which ranks as the third-largest hydropower base in China. Reservoir impoundment has certain impacts on local climate, but few researches focus on this field. This paper integrates spatiotemporal analysis techniques and geostatistical methods to identify the reservoir projected meteorological indices (MIs) variations as well as the impact scope under different circumstances. Results show that the reservoir projected variations of moisture indexes were much more significant than temperatures. Anthropogenic disturbance has led to a dramatic decrease of relative humidity in the past decade, far beyond its periodic amplitude range. Moreover, dry valleys faced more serious drought risk, but reservoir impoundment of this region alleviated the local drought risk. The daily minimum temperature, relative to the maximum temperature, was more sensitive to catchment changes with an earlier appearance of temperature zone variation. Since impounding, the MIs' internal relationships in nondry valleys varied significantly more than that in dry valleys, with a positive correlation of 0.7 between the relative humidity and precipitation weakening greatly. The severe warming hotspots are distributed in the upper reach and have a probability of 0.95-1 to exceed the 1.5°C IPCC control target. This study provides references for the disturbance of reservoir impoundment to local climate at multiple temporal--spatial scales under different circumstances and contributes to the MIs variation pattern identification and quantitative risk assessment. [ABSTRACT FROM AUTHOR]

Future projections of precipitation at regional scales are vital to inform climate change adaptation activities. Therefore, is it important to quantify projected changes and associated uncertainty, and understand model processes responsible. This paper addresses these challenges for southern Africa and the adjacent Indian Ocean focusing on the local wet season. Precipitation projections for the end of the twenty-first century indicate a pronounced dipole pattern in the CMIP5 multimodel mean. The dipole indicates future wetting (drying) to the north (south) of the climatological axis of maximum rainfall, implying a northward shift of the ITCZ and south Indian Ocean convergence zone that is not consistent with a simple "wet get wetter" pattern. This pattern is most pronounced in early austral summer, suggesting a later and shorter wet season over much of southern Africa. Using a decomposition method we determine physical mechanisms underlying this dipole pattern of projected change, and the associated intermodel uncertainty. The projected dipole pattern is largely associated with the dynamical component of change indicative of shifts in the location of convection. Over the Indian Ocean, this apparent northward shift in the ITCZ may reflect the response to changes in the north-south SST gradient over the Indian Ocean, consistent with a "warmest get wetter" mechanism. Over land subtropical drying is relatively robust, particularly in the early wet season. This has contributions from dynamical shifts in the location of convection, which may be related to regional SST structures in the southern Indian Ocean, and the thermodynamic decline in relative humidity. Implications for understanding and potentially constraining uncertainty in projections are discussed. [ABSTRACT FROM AUTHOR]

In this paper, the reliability of the wind speed, temperature, humidity, pressure, and precipitation values of three surface meteorological forcing products [China Meteorological Administration Land Data Assimilation System, version 2 (CLDAS-2); China Meteorological Forcing Dataset (CMFD); and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)] in the Tibetan Plateau (TP) region was investigated from 2008 to 2014. Compared with the China Meteorological Administration (CMA) observations, CLDAS-2 exhibited the highest correlation coefficient for wind speed, CMFD displayed the best coefficients for temperature and specific humidity, and MERRA-2 best reflected pressure variations. Based on the biases, CLDAS-2 exhibited the best overall performance for temperature, specific humidity, and pressure, while CMFD displayed the best performance for wind speed. The high overall accuracy and false alarm ratio of precipitation based on MERRA-2 both stem from its continuous overestimation of the precipitation frequency. Both CLDAS-2 and CMFD overestimated the nonprecipitation frequency in comparisons with CMA observations, and a significant positive bias exists in MERRA-2 based on the analysis of daily precipitation. The results obtained from the comparisons with field observations over the TP and CMA observations are similar, except for the temperature and humidity biases of CLDAS-2. The meteorological effects on the coupled land-blowing snow modeling discussed in this paper suggest that the occurrence of blowing snow and snowdrift sublimation are projected to be reduced by CLDAS-2 due to the underestimation of wind speed, continual lack of snowfall events, and the positive biases in low temperatures and humidity, while simulations of blowing processes by MERRA-2 are likely to be much more severe than they actually are. These results may contribute to identifying deficiencies associated with the development of land surface models coupled with a blowing snow model. [ABSTRACT FROM AUTHOR]

This paper examines the structure and variability of the moisture field in the tropical marine boundary layer (TMBL) as defined by Bragg scattering layers (BSLs) observed with S-band radar. Typically, four to five BSLs were present in the TMBL, including the transition layer at the top of the surface-based mixed layer. The transition-layer depth (~350 m) exhibited a weak diurnal cycle because of changes in the mixed-layer depth. BSLs and the 'clear' layers between them each had a median thickness of about 350 m and a lifetime over the radar of 8.4 h, with about 25% having lifetimes longer than 20 h. More (fewer) BSLs were present when surface winds had a more southerly (northerly) component. Both BSLs and clear layers increased in depth with increasing rain rates, with the rainiest days producing layers that were about 100 m thicker than those on the driest days. The analyses imply that the relative humidity (RH) field in the TMBL exhibits layering on scales observable by radar. Satellite and wind profiler measurements show that the layered RH structure is related, at least in part, to detraining cloudy air. Based on analyses in this series of papers, a revised conceptual model of the TMBL is presented that emphasizes moisture variability and incorporates multiple moist and dry layers and a higher TMBL top. The model is supported by comparing BSL tops with satellite-derived cloud tops. This comparison suggests that the layered RH structure is related, in part, to cloud detrainment at preferred altitudes within the TMBL. The potential ramifications of this change in TMBL conceptualization on modeling of the TMBL are discussed. [ABSTRACT FROM AUTHOR]

Recent studies have shown that cumulus updrafts often consist of a succession of discrete rising thermals with spherical vortex-like circulations. In this paper, a theory is developed for why this ''thermal chain'' structure occurs. Theoretical expressions are obtained for a passive tracer, buoyancy, and vertical velocity in axisymmetric moist updrafts. Analysis of these expressions suggests that the thermal chain structure arises from enhanced lateral mixing associated with intrusions of dry environmental air below an updraft's vertical velocity maximum. This dry-air entrainment reduces buoyancy locally. Consequently, the updraft flow above levels of locally reduced buoyancy separates from below, leading to a breakdown of the updraft into successive discrete thermals. The range of conditions in which thermal chains exist is also analyzed from the theoretical expressions. Atransition in updraft structure from isolated rising thermal, to thermal chain, to starting plume occurs with increases in updraft width, environmental relative humidity, and/or convective available potential energy. Corresponding expressions for the bulk fractional entrainment rate «are also obtained. These expressions indicate rather complicated entrainment behavior of ascending updrafts, with local enhancement of «up to a factor of ;2 associated with the aforementioned environmental-air intrusions, consistent with recent large-eddy simulation (LES) studies. These locally large entrainment rates contribute significantly to overall updraft dilution in thermal chain-like updrafts, while other regions within the updraft can remain relatively undilute. Part II of this study compares results from the theoretical expressions to idealized numerical simulations and LES. [ABSTRACT FROM AUTHOR]

Heat stress caused by high air temperature and high humidity is a serious health concern for urban residents. Mobile measurement of these two parameters can complement weather station observations because of its ability to capture data at fine spatial scales and in places where people live and work. In this paper, we describe a smart temperature and humidity sensor (Smart-T) for use on bicycles to characterize intracity variations in human thermal conditions. The sensor has several key characteristics of internet of things (IoT) technology, including lightweight, low cost, low power consumption, ability to communicate and geolocate the data (via the cyclist's smartphone), and the potential to be deployed in large quantities. The sensor has a reproducibility of 0.038-0.058C for temperature and of 0.18%-0.33% for relative humidity (one standard deviation of variation among multiple units). The time constant with a complete radiation shelter and moving at a normal cycling speed is 9.7 and 18.5 s for temperature and humidity, respectively, corresponding to a spatial resolution of 40 and 70 m. Measurements were made with the sensor on street transects in Nanjing, China. Results show that increasing vegetation fraction causes reduction in both air temperature and absolute humidity and that increasing impervious surface fraction has the opposite effect. [ABSTRACT FROM AUTHOR]

This paper discusses the application of principal component analysis and stepwise regression in the retrieval of vertical profiles of temperature and humidity based on the measurements of a 35-channel microwave radiometer. It uses the radiosonde data of 6 yr from Hong Kong, China, and the monochromatic radiative transfer model (MonoRTM) to calculate the brightness temperatures of the 35 channels of the radiometer. The retrieval of the atmospheric profile is then established based on principal component analysis and stepwise regression. The accuracy of the retrieval method is also analyzed. Using an independent sample, the root-mean-square error of the retrieved temperature is less than 1.5 K, on average, with better retrieval results in summer than in winter. Likewise, the root-mean-square error of the retrieved water vapor density reaches a maximum value of 1.4 g m−−3 between 0.5 and 2 km, and is less than 1 g m−−3 for all other heights. The retrieval method is then applied to the actual measured brightness temperatures by the 35-channel microwave radiometer at a station in Nansha, China. It is shown that the statistical model as developed in this paper has better retrieval results than the profiles obtained from the neural network as supplied with the radiometer. From numerical analysis, the error with the water vapor density retrieval is found to arise from the treatment of cloud liquid water. Finally, the retrieved profiles from the radiometer are studied for two typical weather phenomena during the observation period, and the retrieved profiles using the method discussed in the present paper is found to capture the evolution of the atmospheric condition very well. [ABSTRACT FROM AUTHOR]

The aim of the present series of papers is to develop a density current parameterization for global circulation models. This first paper is devoted to the presentation of this new wake parameterization coupled with Emanuel’s convective scheme. The model represents a population of identical circular cold pools (the wakes) with vertical frontiers. The wakes are cooled by the precipitating downdrafts while the outside area is warmed by the subsidence induced by the saturated drafts. The budget equations for mass, energy, and water yield evolution equations for the prognostic variables (the vertical profiles of the temperature and humidity differences between the wakes and their exterior). They also provide additional terms for the equations of the mean variables. The driving terms of the wake equations are the differential heating and drying due to convective drafts. The action of the convection on the wakes is implemented by splitting the convective tendency and attributing the effect of the precipitating downdrafts to the wake region and the effect of the saturated drafts to their exterior. Conversely, the action of the wakes on convection is implemented by introducing two new variables representing the convergence at the leading edge of the wakes. The available lifting energy (ALE) determines the triggers of deep convection: convection occurs when ALE exceeds the convective inhibition. The available lifting power (ALP) determines the intensity of convection; it is equal to the power input into the system by the collapse of the wakes. The ALE/ALP closure, together with the splitting of the convective heating and drying, implements the full coupling between wake and convection. The coupled wake–convection scheme thus created makes it possible to represent the moist convective processes more realistically, to prepare the coupling of convection with boundary layer and orographic processes, and to consider simulating the propagation of convective systems. [ABSTRACT FROM AUTHOR]

The Korea Institute of Atmospheric Prediction Systems (KIAPS) has developed a new global numerical weather prediction model, named the Korean Integrated Model (KIM). This paper presents the cumulus parameterization scheme (CPS) used in KIM, which originates from the simplified Arakawa–Schubert (SAS) convection scheme in the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and has undergone numerous modifications in an effort to improve the medium-range forecast skill for precipitation and large-scale fields. The modifications include the following: 1) the threshold of the trigger condition is updated to consider the dependency on the environmental relative humidity (RH) averaged over the subcloud layer in order to suppress the trigger of convection in dry low-level environments; 2) the entrainment rate is modified to increase the sensitivity to environmental humidity, so that enhanced entrainment under lower RH conditions leads to a greater decrease in the strength of the convection that develops in drier environments; 3) the autoconversion parameter from cloud condensate to convective precipitation is changed to have a temperature dependency above the freezing level; 4) the closure is modified to consider rapidly varying boundary layer forcing; 5) the effect of the convection-induced pressure gradient force in convective momentum transport is enhanced in the upper part of the convective updrafts; and 6) scale awareness that enables a mass-flux CPS to work seamlessly at various grid sizes across gray-zone resolutions is addressed. The evaluation of medium-range forecasts with the KIM CPS reveals higher forecast skill, especially over the tropics, in comparison with its original version. [ABSTRACT FROM AUTHOR]

We present in this paper the results of the Russian Academy of Sciences North Atlantic Atmospheric Downscaling (RAS-NAAD) project, which provides a 40-yr 3D hindcast of the North Atlantic (10°–80°N) atmosphere at 14-km spatial resolution with 50 levels in the vertical direction (up to 50 hPa), performed with a regional setting of the WRF-ARW 3.8.1 model for the period 1979–2018 and forced by ERA-Interim as a lateral boundary condition. The dataset provides a variety of surface and free-atmosphere parameters at sigma model levels and meets many demands of meteorologists, climate scientists, and oceanographers working in both research and operational domains. Three-dimensional model output at 3-hourly time resolution is freely available to the users. Our evaluation demonstrates a realistic representation of most characteristics in both datasets and also identifies biases mostly in the ice-covered regions. High-resolution and nonhydrostatic model settings in NAAD resolve mesoscale dynamics first of all in the subpolar latitudes. NAAD also provides a new view of the North Atlantic extratropical cyclone activity with a much larger number of cyclones as compared with most reanalyses. It also effectively captures highly localized mechanisms of atmospheric moisture transports. Applications of NAAD to ocean circulation and wave modeling are demonstrated. [ABSTRACT FROM AUTHOR]

A Winter Fog Experiment (WiFEX) was conducted to study the genesis of fog formation between winters 2016–17 and 2017–18 at Indira Gandhi International Airport (IGIA), Delhi, India. To support the WiFEX field campaign, the Weather Research and Forecasting (WRF) Model was used to produce real-time forecasts at 2-km horizontal grid spacing. This paper summarizes the performance of the model forecasts for 43 very dense fog episodes (visibility < 200 m) and preliminary evaluation of the model against the observations. Similarly, near-surface liquid water content (LWC) from models and continuous visibility observations are used as a metric for model evaluation. Results show that the skill score is relatively promising for the hit rate with a value of 0.78, whereas the false alarm rate (0.19) and missing rate (0.32) are quite low. This indicates that the model has reasonable predictive accuracy, and the performance of the real-time forecast is better for both dense fog events and no-fog events. For success cases, the model accurately captured the near-surface meteorological conditions, particularly the low-level moisture, wind fields, and temperature inversion. In contrast, for failed cases, the WRF Model shows large error in near-surface relative humidity and temperature compared to the observations, although it captures temperature inversions reasonably well. Our results also suggest that the model is able to capture the variability in fog onset for consecutive fog events. Errors in near-surface variables during failed cases are found to be affected by the errors in the initial conditions taken from the Indian Institute of Tropical Meteorology Global Forecasting System (IITM-GFS) spectral model forecast. Further evaluation of the operational forecasts for dense fog cases indicates that the error in predicting fog onset stage is relatively large (mean error of 4 h) compared to the dissipation stage. [ABSTRACT FROM AUTHOR]

Climate classification aims to divide a given region into distinct groups on the basis of meteorological variables, and it has important applications in fields such as agriculture and buildings. In this paper, we propose a novel spectral clustering–based method to partition 661 meteorological stations in China into several zones. First, the correlations are analyzed among five meteorological variables: daily average temperature, average relative humidity, sunshine hours, diurnal temperature range, and atmospheric pressure. The resulting weak linear correlation supports the classification under multiple views. Next, a similarity matrix/graph is constructed by combining the advantages of k-nearest-neighbor and sparse subspace representation. The blocking effect of the similarity matrix confirms the rationality of the classification. Then, we consider respectively the climate classification under a single view and multiple views. For the single view, atmospheric pressure has the highest imbalance degree, and sunshine hours and diurnal temperature range have the strongest classification consistency. The consistency rates are improved evidently in a multiple-view situation. Afterward, we propose a determining method for the number of clusters and make a sensitivity analysis on various parameters. Finally, we provide a further statistical analysis on the classification results and compare the consistency with another climate dataset. All experimental results show that the proposed classification method is feasible and effective in the climate zoning of China. [ABSTRACT FROM AUTHOR]

This paper presents a straightforward approach to mitigate the problem of spurious cloud-edge supersaturation in high-spatial-resolution cloud models (e.g., moist large-eddy simulation models). The central idea, following a 1989 J. Atmos. Sci. paper by Grabowski, is that supersaturation predicted by the supersaturation equation should be used to adjust the temperature and moisture solutions, rather than the other way around as in the standard approach in cloud modeling, where the temperature and moisture solutions are used to diagnose the supersaturation. Details of the adjustment scheme are discussed and illustrated through simple one-dimensional tests applying a two-moment warm-rain microphysics scheme that predicts the in-cloud supersaturation. Extension of this approach to bin microphysics models is also outlined. [ABSTRACT FROM AUTHOR]

The North China Plain (NCP) is becoming one of the most polluted areas characterized by a high frequency of haze pollution. However, the spatial and temporal evolutions of aerosol chemical compositions in such a highly polluted region are not well understood due to the lack of a long-term and comprehensive observation-based network. China's National Aerosol Composition Monitoring Network (NACMON) has conducted comprehensive offline and online measurements of compositions and optical properties of airborne aerosols in order to systematically investigate the formation process, source apportionments of haze, and interactions between haze pollution and climate change. The objective of the observations is to provide information for policy makers to make strategies for the alleviation of haze occurrence. In this paper, we present instrumentations and methodologies as well as the preliminary results of the offline observations in NACMON stations over the NCP region. The implications and future perspectives of the network are also summarized. Benefiting from simultaneous observations from this network, we found that secondary aerosols were the dominant component in haze pollution. High anthropogenic emissions, low wind speed, and high relative humidity (RH) facilitated gas-to-particle transformation and resulted in high PM2.5 formation (PM2.5 is particulate matter that is smaller than 2.5 μm in diameter). Sulfate-dominant or nitrate-dominant aerosols during the haze period were driven by ambient RH. Moreover, the contributions of coal combustion and biomass burning to PM2.5 revealed downward trends, whereas secondary aerosols showed upward trends over the last decade. Thus, we highlighted that strict control of anthropogenic emissions of precursor gases, such as NOx, NH3, and volatile organic compounds (VOCs), will be an important way to decrease PM2.5 pollution in the NCP region. [ABSTRACT FROM AUTHOR]

This study investigates how multifrequency cloud radar observations can be used to evaluate the representation of rain microphysics in the WRF Model using two bulk microphysics schemes. A squall line observed over Oklahoma on 12 June 2011 is used as a case study. A recently developed retrieval technique combining observations of two vertically pointing cloud radars provides quantitative description of the drop size distribution (DSD) properties of the transition and stratiform regions of the squall-line system. For the first time, the results of this multifrequency cloud radar retrieval are compared to more conventional retrievals from a nearby polarimetric radar, and a supplementary result of this work is that this new methodology provides a much more detailed description of the DSD vertical and temporal variations. While the extent and evolution of the squall line is well reproduced by the model, the 1-h low-reflectivity transition region is not. In the stratiform region, simulations with both schemes are able to reproduce the observed downdraft and the associated significative subsaturation below the melting level, but with a slight overestimation of the relative humidity. Under this subsaturated air, the simulated rain mixing ratio continuously decreases toward the ground, in agreement with the observations. Conversely, the profiles of the mean volume diameter and the concentration parameter of the DSDs are not well reproduced. These discrepancies pinpoint at an issue in the representation of rain microphysics. The companion paper, investigates the sources of the biases in the microphysics processes in the rain layer by performing numerical sensitivity studies. [ABSTRACT FROM AUTHOR]

Extreme precipitation associated with extratropical cyclones can lead to flooding if cyclones track over land. However, the dynamical mechanisms by which moist air is transported into cyclones is poorly understood. In this paper we analyze airflows within a climatology of cyclones in order to understand how cyclones redistribute moisture stored in the atmosphere. This analysis shows that within a cyclone's warm sector the cyclone-relative airflow is rearwards relative to the cyclone propagation direction. This low-level airflow (termed the feeder airstream) slows down when it reaches the cold front, resulting in moisture flux convergence and the formation of a band of high moisture content. One branch of the feeder airstream turns toward the cyclone center, supplying moisture to the base of the warm conveyor belt where it ascends and precipitation forms. The other branch turns away from the cyclone center exporting moisture from the cyclone. As the cyclone travels, this export results in a filament of high moisture content marking the track of the cyclone (often used to identify atmospheric rivers). We find that both cyclone precipitation and water vapor transport increase when moisture in the feeder airstream increases, thus explaining the link between atmospheric rivers and the precipitation associated with warm conveyor belt ascent. Atmospheric moisture budgets calculated as cyclones pass over fixed domains relative to the cyclone tracks show that continuous evaporation of moisture in the precyclone environment moistens the feeder airstream. Evaporation behind the cold front acts to moisten the atmosphere in the wake of the cyclone passage, potentially preconditioning the environment for subsequent cyclone development. [ABSTRACT FROM AUTHOR]

Precipitation changes in a warming climate have been examined with a focus on either mean precipitation or precipitation extremes, but changes in the full probability distribution of precipitation have not been well studied. This paper develops a methodology for the quantile-conditional column moisture budget of the atmosphere for the full probability distribution of precipitation. Analysis is performed on idealized aquaplanet model simulations under 3-K uniform SST warming across different horizontal resolutions. Because the covariance of specific humidity and horizontal mass convergence is much reduced when conditioned onto a given precipitation percentile range, their conditional averages yield a clear separation between the moisture (thermodynamic) and circulation (dynamic) effects of vertical moisture transport on precipitation. The thermodynamic response to idealized climate warming can be understood as a generalized "wet get wetter" mechanism, in which the heaviest precipitation of the probability distribution is enhanced most from increased gross moisture stratification, at a rate controlled by the change in lower-tropospheric moisture rather than column moisture. The dynamic effect, in contrast, can be interpreted by shifts in large-scale atmospheric circulations such as the Hadley cell circulation or midlatitude storm tracks. Furthermore, horizontal moisture advection, albeit of secondary role, is important for regional precipitation change. Although similar mechanisms are at play for changes in both mean precipitation and precipitation extremes, the thermodynamic contributions of moisture transport to increases in high percentiles of precipitation tend to be more widespread across a wide range of latitudes than increases in the mean, especially in the subtropics. [ABSTRACT FROM AUTHOR]

The local environment during the joint Atmospheric Radiation Measurement Program (ARM) Madden-Julian oscillation (MJO) Investigation Experiment (AMIE)-Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011 (CINDY2011)-Dynamics of the MJO (DYNAMO) field experiments caused frequent occurrences of sidelobe artifacts in the NCAR S-Pol radar dataset. Although generally low in radar reflectivity factor value (less than 5 dB Z), this contamination still proved problematic for Bragg scattering layer (BSL) analysis, generating numerous false BSL edge detections. In this paper, a statistical filtering technique is developed that effectively removes these false BSL edge detections, utilizing a new version of BSL analysis based on range-height indicator (RHI) data instead of plan position indicator data. [ABSTRACT FROM AUTHOR]

The design of reclamation soil covers at oil sands mines in northern Alberta, Canada, has been conventionally based on the calibration of soil–vegetation–atmosphere transfer (SVAT) models against field monitoring observations collected over several years, followed by simulations of long-term performance using historical climate data. This paper evaluates the long-term water balances for reclamation covers on two oil sands landforms and three natural coarse-textured forest soil profiles using both historical climate data and future climate projections. Twenty-first century daily precipitation and temperature data from CanESM2 were downscaled based on three representative concentration pathways (RCPs) employing a stochastic weather generator [Long Ashton Research Station Weather Generator (LARS-WG)]. Relative humidity, wind speed, and net radiation were downscaled using the delta change method. Downscaled precipitation and estimated potential evapotranspiration were used as inputs to simulate soil water dynamics using physically based models. Probability distributions of growing season (April–October) actual evapotranspiration (AET) and net percolation (NP) for the baseline and future periods show that AET and NP at all sites are expected to increase throughout the twenty-first century regardless of RCP, time period, and soil profile. Greater increases in AET and NP are projected toward the end of the twenty-first century. The increases in future NP at the two reclamation covers are larger (as a percentage increase) than at most of the natural sites. Increases in NP will result in greater water yield to surface water and may accelerate the rate at which chemical constituents contained within mine waste are released to downstream receptors, suggesting these potential changes need to be considered in mine closure designs. [ABSTRACT FROM AUTHOR]

The moist-air entropy can be used to analyze and better understand the general circulation of the atmosphere or convective motions. Isentropic analyses are commonly based on studies of different equivalent potential temperatures, all of which are assumed to fully represent the entropy of moist air. It is, however, possible to rely either on statistical physics or the third law of thermodynamics when defining and computing the absolute entropy of moist air and to study the corresponding third-law potential temperature, which is different from the previous ones. The third law assumes that the entropy for the most stable crystalline state of all substances is zero when approaching absolute zero temperature. This paper shows that the way all these moist-air potential temperatures are defined has a large impact on (i) the plotting of the isentropes for a simulation of Hurricane Dumile, (ii) the changes in moist-air entropy computed for a steam cycle defined for this hurricane, (iii) the analyses of isentropic streamfunctions computed for this hurricane, and (iv) the computations of the heat input, the work function, and the efficiency defined for this steam cycle. The moist-air entropy is a state function and the isentropic analyses must be completely determined by the local moist-air conditions. The large differences observed between the different formulations of moist-air entropy are interpreted as proof that the isentropic analyses of moist-air atmospheric motions must be achieved by using the third-law potential temperature defined from general thermodynamics. [ABSTRACT FROM AUTHOR]

Advances in computer power have made it possible to increase the spatial resolution of regional numerical models to a scale encompassing larger convective elements of less than 5 km in size. One goal of high resolution is to begin to resolve convective processes, and therefore it is necessary to evaluate the realism of convective clouds resolved explicitly at this resolution. This paper presents a method that is based on satellite comparisons to examine the simulation of continental tropical convection over Africa, in a high-resolution integration of the Met Office Unified Model (UK UM), developed under the Cascade project. The spatial resolution of these simulations is 1.5 km, the temporal resolution is 15 min, and the convection is resolved explicitly. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer measurements were simulated by the Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (RTTOV) model, and then a comparison between the simulations and real SEVIRI measurements was performed. The analysis using the presented method shows that the UK UM can represent tropical convection dynamics realistically. However, an error has been found in the high-level humidity distribution, which is characterized by strong humidity gradients. A key point of this paper is to present a method for establishing the credibility of a convection-permitting model by direct comparison with satellite data. [ABSTRACT FROM AUTHOR]

This paper investigates wintertime tropical marine boundary layer (TMBL) statistical characteristics over the western North Atlantic using the complete set of island-launched soundings from the Rain in Cumulus over the Ocean (RICO) experiment. The soundings are subdivided into undisturbed and disturbed classifications using two discriminators: 1) dates chosen by Global Energy and Water Cycle Experiment (GEWEX) Cloud System Studies (GCSS) investigators to construct the mean RICO sounding and 2) daily average rain rates. A wide range of relative humidity (RH) values was observed between the surface and 8.0 km. At 2.0 km, half the RH values were within 56%-89%; at 4.0 km, half were within 13%-61%. The rain-rate method of separating disturbed and undisturbed soundings appears more meaningful than the GCSS method. The median RH for disturbed conditions using the rain-rate method showed moister conditions from the surface to 8.0 km, with maximum RH differences of 30%-40%. Moist air generally extended higher on disturbed than undisturbed days. Based on equivalent potential temperature, wind direction, and RH analyses, the most common altitude marking the TMBL top was about 4.0 km. Temperature inversions (over both 50- and 350-m intervals) were observed at every altitude above 1.2 km; there were no dominant inversion heights and most of the inversions were weak. Wind direction analyses indicated that winds within the TMBL originated from more tropical latitudes on disturbed days. The analyses herein suggest that the RICO profile used to initialize many model simulations of this environment represents only a small subset of the broad range of possible conditions characterizing the wintertime trades. [ABSTRACT FROM AUTHOR]

This paper presents an object-based, global climatology (1979-2014) of strong large-scale ocean evaporation (SLOE) and its associated climatic properties. SLOE is diagnosed using an ''atmospheric moisture uptake efficiency'' criterion related to the ratio of surface evaporation and integrated water vapor content in the near-surface atmosphere. The chosen Eulerian identification procedure focuses on events that strongly contribute to the available near-surface atmospheric humidity. SLOE is particularly frequent along the warm ocean western boundary currents, downstream of large continental areas, and at the sea ice edge in polar regions with frequent cold-air outbreaks. Furthermore, wind-driven SLOE occurs in regions with topographically enforced winds. On a global annual average, SLOE occurs only 6% of the time but explains 22% of total ocean evaporation. An analysis of the past history and fate of air parcels involved in cold season SLOE in the North Atlantic and south Indian Oceans shows that cold-air advection is the main mechanism that induces these events. Extratropical cyclones thereby play an important role in setting the necessary equatorward synoptic flow. Consequently, the interannual variability of SLOE associated with the North Atlantic Oscillation and the southern annular mode reveals a very high sensitivity of SLOE with respect to the location of the storm tracks. This study highlights the strong link between transient synoptic events and the spatiotemporal variability in ocean evaporation patterns, which cannot be deduced from thermodynamic steadystate and climate mean state considerations alone. [ABSTRACT FROM AUTHOR]

This paper discusses the relevance of transient events of strong large-scale ocean evaporation (SLOE) for the deuteriumexcess of marine boundary layer vapor d using a theoretical framework that invokes the closure assumption. We argue that during SLOE events, d is essentially determined by the evaporation flux signature. Distinct high d during SLOE with global-mean values in the range of 12%-23% depending on the nonequilibrium fractionation factor ak result from the large air--sea humidity gradients reflected in low relative humidity with respect to sea surface temperature (hs 5 53% 6 9%) that characterize these events. Extratropical cyclones are highlighted as an important driver for the variability of d. On the one hand, they are themselves associated with high hs and low d, especially in areas of cloud formation and precipitation in the warm sector. On the other hand, cyclones are the main driver inducing SLOE events with high d in regions of cold-air advection upstream of their path. The sensitivity of d to its direct climate controls (hs and SST) is analyzed during SLOE for different ak formulations and found to be coherent with d--hs and d--SST slopes determined from available observations. The d--hs relationship exhibits a robust negative correlation as opposed to the d--SST relationship, which shows regional and time-scale-dependent variations in strength and sign that are induced by indirect hs--SST cross-correlation effects. The dynamical features involved in SLOE generation appear to exert a key control on the moisture source properties relevant for d in the extratropics. [ABSTRACT FROM AUTHOR]

As a follow-up of our recent paper on the practical and intrinsic predictability of multiscale tropical weather and equatorial waves, this study explores the potentials in improving the analysis and prediction of these weather systems through assimilating simulated satellite-based observations with a regional ensemble Kalman filter (EnKF). The observing networks investigated include the retrieved temperature and humidity profiles from the Advanced TIROS Operational Vertical Sounder (ATOVS) and global positioning system radio occultation (GPSRO), the atmospheric motion vectors (AMVs), infrared brightness temperature from Meteosat-7 (Met7-Tb), and retrieved surface wind speed from the Cyclone Global Navigation Satellite System (CYGNSS). It is found that assimilating simulated ATOVS thermodynamic profiles and AMV winds improves the accuracy of wind, temperature, humidity, and hydrometeors for scales larger than 200 km. The skillful forecast lead times can be extended by as much as 4 days for scales larger than 1000 km. Assimilation of Met7-Tb further improves the analysis of cloud hydrometeors even at scales smaller than 200 km. Assimilating CYGNSS surface winds further improves the low-level wind and temperature. Meanwhile, the impact from assimilating the current-generation GPSRO data with better vertical resolution and accuracy is comparable to assimilating half of the current ATOVS profiles, while a hypothetical 25-times increase in the number of GPSRO profiles can potentially exceed the impact from assimilating the current network of retrieved ATOVS profiles. Our study not only shows great promises in further improving practical predictability of multiscale equatorial systems but also provides guidance in the evaluation and design of current and future spaceborne observations for tropical weather. [ABSTRACT FROM AUTHOR]

Exposure to weather extremes, such as heatwaves, can cause discomfort, harm, or death in grazing cattle in pastures. While the Australian Bureau of Meteorology issues sheep graziers alerts when there is an exposure risk to chill for livestock, there is no equivalent alert for heat stress for Australian cattle. Before any such alert system can be developed, a robust assessment and comparison of relevant cattle thermal stress indices is required. This study evaluates and compares the multiyear climatology of three cattle thermal heat stress indices across Australia in the warm season months (October–March). The same indices are then used to assess historical Australian heat events where cattle died from heat exposure. These events are based off official records and survey responses from northern Australian graziers. In the seven historical heat events studied, high relative humidity combined with low wind speeds, or high solar exposure combined with high surface temperatures, exacerbated the impact of heat stress on cattle. In the two historic events where multiple compounding weather factors combined (e.g., high humidity, low winds, and high solar exposure), the cattle mortality levels were significantly high. These events were characterized by rainy conditions followed by a rapid warming, meaning cattle were likely unable to acclimatize to such dramatic temperature changes. This study highlights the need for using more than one thermal stress index when verifying cattle heat stress events and, importantly, calls for further research on standardizing the risk classifications of these thermal indices for cattle in Australia's variable climate. Significance Statement: Cattle across Australia's northern tropical and semiarid regions often experience extreme hot and humid conditions in the summer months, which increases the risk of heat stress. This is the first study of its kind to evaluate observations of cattle heat stress across Australia using indices that describe the combined effects of solar exposure, wind speed, relative humidity, and surface temperatures. These cattle heat stress indices can be used to evaluate historical cattle mortality events in feedlots and in grazed pastures. This study lays the groundwork for the development of Australian-wide cattle heat stress forecast products on the 7-day to multiweek time scales. [ABSTRACT FROM AUTHOR]

A nonhydrostatic, fully compressible spectral element (SE) model is evaluated in a series of two-dimensional idealized simulations. A dry formulation of the model is evaluated for a linear hydrostatic mountain-wave case, and a version with moisture is tested for a squall line. In the SE method, two setup parameters control the spatial resolution: the number of elements (h) and the polynomial order Co) of the basis functions. In this paper, the h--p parameter space is systematically explored, with the average horizontal resolution (Δx) varying from 0.2 to 10 km in 91 simulations. The dry experiments are evaluated using an analytic solution. The ratio of Δx/a < 0.2, where a is the mountain half-width, is sufficient to accurately resolve the mountain wave. Accuracy, computational cost, and convergence to the analytic solution are evaluated and compared to a second-order finite-difference (FD) model. The increase in computational cost by refining the spatial resolution yields a significant accuracy gain for the SE, with only a marginal improvement for the FD model. The squall line is evaluated across the control parameter space by assessing three integrated quantities: total precipitation accumulation, maximum vertical velocity, and maximum precipitation rate. The squall line is adequately resolved with Δx < 2 km and p > 5. There is little variation in metrics due to the varying nodal spacing within an element at the same average &r. When the spatial resolution is refined, the analyzed metrics no longer converge. The nonlinear nature of moist convection is responsible for this resolution dependence as a result of localized buoyancy sources, evident in the vertical velocity spectrum. [ABSTRACT FROM AUTHOR]

Aerodynamic contrails have been recognized for a long time although they appear sporadically. Usually one observes them under humid conditions near the ground, where they are short-lived phenomena. Aerodynamic contrails appear also at cruise levels where they may persist when the ambient atmosphere is ice-supersaturated. The present paper presents a theoretical investigation of aerodynamic contrails in the upper troposphere. The required flow physics are explained and applied to a case study. Results show that the flow over aircraft wings leads to large variations of pressure and temperature. Average pressure differences between the upper and lower sides of a wing are on the order of 50 hPa, which is a quite substantial fraction of cruise-level atmospheric pressures. Adiabatic cooling exceeds 20 K about 2 m above the wing in a case study shown here. Accordingly, extremely high supersaturations (exceeding 1000%) occur for a fraction of a second. The potential consequences for the ice microphysics are discussed. Because aerodynamic contrails are independent of the formation conditions of jet contrails, they form an additional class of contrails that might be complementary because they form predominantly in layers that are too warm for jet contrail formation. [ABSTRACT FROM AUTHOR]

This paper examines the extent to which an empirical correction method can improve forecasts of the National Centers for Environmental Prediction (NCEP) operational Global Forecast System. The empirical correction is based on adding a forcing term to the prognostic equations equal to the negative of the climatological tendency errors. The tendency errors are estimated by a least squares method using 6-, 12-, 18-, and 24-h forecast errors. Tests on independent verification data show that the empirical correction significantly reduces temperature biases nearly everywhere at all lead times up to at least 5 days but does not significantly reduce biases in forecast winds and humidity. Decomposing mean-square error into bias and random components reveals that the reduction in total mean-square error arises solely from reduction in bias. Interestingly, the empirical correction increases the random error slightly, but this increase is argued to be an artifact of the change in variance in the forecasts. The empirical correction also is found to reduce the bias more than traditional “after the fact” corrections. The latter result might be a consequence of the very different sample sizes available for estimation, but this difference in sample size is unavoidable in operational situations in which limited calibration data are available for a given forecast model. [ABSTRACT FROM AUTHOR]

This paper presents the results from the Observing System Experiments (OSEs) with the current ECMWF data assimilation and modeling system for quantifying the impact on both analysis and forecast quality of Special Sensor Microwave Imager (SSM/I) observations sensitive to moisture and clouds as well as precipitation. SSM/I radiances have been assimilated operationally in clear-sky areas for 8 yr and in cloud- and rain-affected areas since June 2005. This paper examines experiments set up such that clear-sky and rain-affected observations were either added to a baseline with a restricted observing system configuration or withdrawn from the full system. The experiment duration was 10 weeks of which the first 14 days were excluded from the evaluation to allow the system to lose the memory of the initial conditions at day -1. It is shown that both clear-sky and rain-affected observations account for the bulk correction of moisture in the ECMWF analysis. SSM/I data adds 1 day of forecast skill over the first 48 h when evaluated in addition to a baseline-observing system. In the tropics, the rain-affected data contributes more skill to the moisture forecast than the clear-sky data at 700 hPa and above. In the Northern and Southern Hemispheres, the effect is generally weaker and slightly in favor of clear-sky observations. A similar performance can be seen with respect to the wind vector forecast skill, which reflects the connection between the analysis of moisture and dynamics. [ABSTRACT FROM AUTHOR]

This paper discusses the representation of subgrid-scale turbulent mixing in bulk models of warm (ice free) clouds, which assume instantaneous adjustment to grid-scale saturation. This is a reasonable assumption for condensation of water vapor because supersaturations inside clouds are typically small (∼0.1% or smaller), except near cloud bases where about an order of magnitude larger supersaturations are anticipated. For the cloud evaporation, however, instantaneous adjustment to grid-scale saturation is questionable, especially when evaporation occurs as a result of turbulent mixing between a cloud and its unsaturated environment. This is because turbulent mixing between initially separated volumes of cloudy and cloud-free environmental air proceeds through a gradual filamentation of these volumes, with progressively increasing evaporation of cloud water during the approach to final homogenization. A relatively simple model of this chain of events is included in a bulk model of moist nonprecipitating thermodynamics. The model delays adjustment to saturation for cloud evaporation following the turbulent mixing until the volume can be assumed homogeneous. An additional prognostic variable, the width of a cloudy filament, is added to represent the progress of turbulent mixing and the approach to homogenization. Theoretical developments are illustrated by idealized 2D simulations of moist thermals rising from rest and realistic large-eddy simulations of a cloud field. [ABSTRACT FROM AUTHOR]

In the first part of the paper, a high space–time resolution (1° latitude/longitude and daily) dataset of the turbulent fluxes at the ocean surface is used to estimate and study the seasonal to annual near-global maps of the decorrelation scales of the latent and sensible heat fluxes. The decorrelation scales describe the temporal and spatial patterns that dominate the flux fields (within a bandpass window) and hence reveal the dominant variability in the air–sea interaction. Regional comparison to the decorrelation scales of the flux-related variables such as the wind stress, the humidity difference, and the SST identifies the main mechanism responsible for the variability in each flux field. In the second part of the paper, the decorrelation scales are used to develop a method for filling missing values in the dataset that result from the incomplete satellite coverage. Weight coefficients in a linear regression function are determined from the spatial and temporal decorrelations and are functions of zonal and meridional distance and time. Therefore they account for all spatial and temporal patterns on scales greater than 1 day and 1° latitude/longitude and less than 1 yr and the ocean basin scale. The method is evaluated by simulating the missing-value distribution of the Goddard Satellite-Based Surface Turbulent Fluxes, version 2 (GSSTF2) dataset in the NCEP SST, the International Satellite Climatology Project (ISCCP)-FD (fluxes calculated using D1 series) surface radiation, and the Global Precipitation Climatology Project (GPCP) datasets and by comparing the filled datasets to the original ones. Main advantages of the method are that the decorrelation scales are unrestricted functions of space and time; only information internal to the flux field is used in the interpolation scheme, and the computation cost of the method is low enough to facilitate its use in similar large datasets. [ABSTRACT FROM AUTHOR]

The relative contributions of locally evapotranspired (i.e., recycled) moisture versus externally advected water vapor for the growing-season precipitation of the U.S. Corn Belt and surrounding areas (1.23 × 106 km2) are estimated in this paper. Four May–August seasons with highly contrasting precipitation and crop yields (1975, 1976, 1979, and 1988) are investigated. A simple recycling equation—developed from the traditional atmospheric moisture budget and involving regional evapotranspiration and atmospheric water vapor inflow—is applied on daily, monthly, and seasonal time scales. Several atmospheric moisture budget components {moisture flux divergence [MFD], storage change [or change in precipitable water (dPW)], and inflow [IF]} are evaluated for 24-h periods using standard finite difference and line integral methods applied to objectively analyzed U.S. and Canadian rawinsonde data (50-hPa vertical resolution, surface to 300 hPa) for 0000 and 1200 UTC. Daily area-averaged precipitation (P) totals are derived from approximately 600 evenly distributed (but ungridded) recording rain gauges. Evapotranspiration (E) is estimated as the residual of the moisture budget equation for 24-h periods; values compare favorably with the few existing observations. Traditional budget results show the following: E is weakly related to P on monthly and seasonal time scales; there is surprising interannual constancy of seasonal E cycles and averages given the large variation in resulting crop yields; and monthly and seasonal variability of the export of the E - P surplus is determined largely by the horizontal velocity divergence component of MFD. New recycling analyses suggest that the contribution of local E to P (i.e., PE/P) is relatively small and remarkably consistent (largely 0.19–0.24) for monthly and seasonal periods, despite large P and crop yield variations. However, the monthly/seasonal averaging process is found to completely mask a striking decrease of daily PE/P (from approximately 0.30 to 0.15) with increasing P from 0 to 8 mm day-1. Unique and detailed analyses of P-stratified daily moisture budget results provide key insights into apparent contradictions between daily and monthly/seasonal recycling and related results and concomitant interannual variability, especially for the very dry 1988 season. Interpretation is facilitated by the use of modeled daily global radiation values, measured (instantaneous) and modeled (monthly) soil moisture, United States Department of Agriculture (USDA) crop yield estimates, and satellite normalized difference vegetation index (NDVI) imagery. This paper shows that land–atmosphere interactions are intimately involved in pronounced seasonal climate anomalies for the world's richest agricultural region, but apparently with considerable complexity that includes plant behavior, solar radiation forcing, and challenging time-scale interrelations. [ABSTRACT FROM AUTHOR]

Recently, three distinct archetypes for midlatitude linear mesoscale convective systems (MCSs) have been identified. This article focuses on the fundamentals of two of these archetypes: convective lines with trailing stratiform (TS) precipitation and convective lines with leading stratiform (LS) precipitation. Both the TS and LS modes typically exhibit quasi-2D reflectivity patterns and quasi-2D environmental storm-relative wind fields. Ongoing work has revealed that there are three common flow structures for these quasi-2D MCSs: front-fed TS systems (which are sustained by front-to-rear storm-relative inflow), as well as front-fed LS and rear-fed LS systems (which are sustained by rear-to-front storm-relative inflow). This paper summarizes the observed structures of the front-fed TS, front-fed LS, and rear-fed LS modes, and then outlines an idealized numerical experiment in which these modes were simulated. The authors analyze the basic simulated kinematic and microphysical structures and provide a framework in which to analyze the dynamics of the modeled systems. To a large degree, the organizational modes of developing quasi-2D MCSs may be anticipated by considering the magnitudes and preferred directions of the horizontal pressure gradient accelerations associated with a surface cold pool [whose strength is largely related to the environmental humidity and convective available potential energy (CAPE)] and an updraft in the mean environmental wind shear profile. In this regard, the lower-tropospheric shear is of prime importance, although the middle- and upper-tropospheric shear provide for additional, nontrivial accelerations. [ABSTRACT FROM AUTHOR]

This paper compares upper-tropospheric humidity from the Microwave Limb Sounder (MLS) on the Upper Atmosphere Research Satellite with European Centre for Medium-Range Weather Forecasts (ECMWF) data. MLS measurements are not included in the ECMWF analyses, and so a comparison of two independent datasets is possible. The focus of this paper is on the tropical region from 1991 to 1997 when MLS measurements are available and, to be more specific, from 1991 to 1994 during the ECMWF 15-yr reanalysis period (ERA-15). It is found that the contrast between moist and dry areas, or areas of convection and subsidence, is less pronounced in ECMWF data than in MLS measurements. This result applies on the scale of both global and regional circulations and results in a semiannual cycle of high and low correlations between the two datasets that is particularly pronounced over South America. Time series show that the impact of model changes to the absolute values of humidity make long-term comparison with MLS difficult. [ABSTRACT FROM AUTHOR]

This paper describes the formulation and the application of the nonhydrostatic anelastic vorticity model (TVM). This model is constructed using a method involving two horizontal streamfunctions and two horizontal vorticity components. The evaluation of this formulation is performed by simulating various bidimensional hydrostatic and nonhydrostatic mountain wave cases. Results are compared with analytical solutions and in particular with those developed by Laprise and Peltier for nonlinear forcings. The anelastic formulation is also validated with respect to the highly nonlinear 1972 Boulder windstorm. TVM is shown to accurately reproduce these mountain wave test cases in both its incompressible and anelastic formulations. In the second part of this paper, the adequacy of the hydrostatic and anelastic assumptions in simulating thermally induced circulations is investigated and compared to previous works. For a moderate surface thermal forcing, typical geographical setups are used and show slight differences between hydrostatic and nonhydrostatic horizontal wind speeds. For vertical wind speeds, differences are shown to be much larger and more sensitive to changes in grid resolution. For more stringent thermal surface forcing, differences remain low for horizontal wind speeds but increase considerably for the vertical wind component. The comparison between anelastic and incompressible solutions for the same cases shows the adequacy of the incompressible assumption when circulations are forced by the surface and are characterized by a relatively shallow vertical extent. In such conditions, virtually no differences are observed between the two formulations. [ABSTRACT FROM AUTHOR]

Accurately predicting moisture and stability in the Antarctic planetary boundary layer (PBL) is essential for low-cloud forecasts, especially when Antarctic forecasters often use relative humidity as a proxy for cloud cover. These forecasters typically rely on the Antarctic Mesoscale Prediction System (AMPS) Polar Weather Research and Forecasting (Polar WRF) Model for high-resolution forecasts. To complement the PBL observations from the 30-m Alexander Tall Tower! (ATT) on the Ross Ice Shelf as discussed in a recent paper by Wille and coworkers, a field campaign was conducted at the ATT site from 13 to 26 January 2014 using Small Unmanned Meteorological Observer (SUMO) aerial systems to collect PBL data. The 3-km-resolution AMPS forecast output is combined with the global European Centre for Medium-Range Weather Forecasts interim reanalysis (ERAI), SUMO flights, and ATT data to describe atmospheric conditions on the Ross Ice Shelf. The SUMO comparison showed that AMPS had an average 2-3 m s−1 high wind speed bias from the near surface to 600 m, which led to excessive mechanical mixing and reduced stability in the PBL. As discussed in previous Polar WRF studies, the Mellor-Yamada-Janjić PBL scheme is likely responsible for the high wind speed bias. The SUMO comparison also showed a near-surface 10-15-percentage-point dry relative humidity bias in AMPS that increased to a 25-30-percentage-point deficit from 200 to 400 m above the surface. A large dry bias at these critical heights for aircraft operations implies poor AMPS low-cloud forecasts. The ERAI showed that the katabatic flow from the Transantarctic Mountains is unrealistically dry in AMPS. [ABSTRACT FROM AUTHOR]

Santa Ana winds, common to Southern California from the fall through early spring, are a type of downslope windstorm originating from a direction generally ranging from 360°/0° to 100° and are usually accompanied by very low humidity. Since fuel conditions tend to be driest from late September through the middle of November, Santa Ana winds occurring during this time have the greatest potential to produce large, devastating fires upon ignition. Such catastrophic fires occurred in 1993, 2003, 2007, and 2008. Because of the destructive nature of such fires, there has been a growing desire to categorize Santa Ana wind events in much the same way that tropical cyclones have been categorized. The Santa Ana wildfire threat index (SAWTI) is a tool for categorizing Santa Ana wind events with respect to anticipated fire potential. The latest version of the index has been a result of a three-and-a-half-year collaboration effort between the USDA Forest Service, the San Diego Gas and Electric utility (SDG&E), and the University of California, Los Angeles (UCLA). The SAWTI uses several meteorological and fuel moisture variables at 3-km resolution as input to the Weather Research and Forecasting (WRF) Model to generate the index out to 6 days. In addition to the index, a 30-yr climatology of weather, fuels, and the SAWTI has been developed to help put current and future events into perspective. This paper outlines the methodology for developing the SAWTI, including a discussion on the various datasets employed and its operational implementation. [ABSTRACT FROM AUTHOR]

This study evaluates the methods of identifying the height zi of the top of the convective boundary layer (CBL) during winter (December and January) over the Great Lakes and nearby land areas using observations taken by the University of Wyoming King Air research aircraft during the Lake-Induced Convection Experiment (1997/98) and Ontario Winter Lake-effect Systems (2013/14) field campaigns. Since CBLs facilitate vertical mixing near the surface, the most direct measurement of zi is that above which the vertical velocity turbulent fluctuations are weak or absent. Thus, we use zi from the turbulence method as the "reference value" to which zi from other methods, based on bulk Richardson number (Rib), liquid water content, and vertical gradients of potential temperature, relative humidity, and water vapor mixing ratio, are compared. The potential temperature gradient method using a threshold value of 0.015 K m−1 for soundings over land and 0.011 K m−1 for soundings over lake provided the estimates of zi that are most consistent with the turbulence method. The Rib threshold-based method, commonly used in numerical simulation studies, underestimated zi. Analyzing the methods' performance on the averaging window zavg we recommend using zavg = 20 or 50 m for zi estimations for lake-effect boundary layers. The present dataset consists of both cloudy and cloud-free boundary layers, some having decoupled boundary layers above the inversion top. Because cases of decoupled boundary layers appear to be formed by nearby synoptic storms, we recommend use of the more general term, elevated mixed layers. Significance Statement: The depth zi of the convective atmospheric boundary layer (CBL) strongly influences precipitation rates during lake-effect snowstorms (LES). However, various zi approximation methods produce significantly different results. This study utilizes extensive concurrently collected observations by project aircraft during two LES field studies [Lake-Induced Convection Experiment (Lake-ICE) and OWLeS] to assess how zi from common estimation methods compare with "reference" zi derived from turbulent fluctuations, a direct measure of CBL mixing. For soundings taken both over land and lake; with cloudy or cloud-free conditions, potential temperature gradient (PTG) methods provided the best agreement with the reference zi. A method commonly employed in numerical simulations performed relatively poorly. Interestingly, the PTG method worked equally well for "coupled" and elevated decoupled CBLs, commonly associated with nearby cyclones. [ABSTRACT FROM AUTHOR]

This paper investigates the potential of reanalyses as proxies of observed surface precipitation and temperature to force hydrological models. Three global atmospheric reanalyses (ERA-Interim, CFSR, and MERRA), one regional reanalysis (NARR), and one global meteorological forcing dataset obtained by bias-correcting ERA-Interim [Water and Global Change (WATCH) Forcing Data ERA-Interim (WFDEI)] were compared to one gridded observation database over the contiguous United States. Results showed that all temperature datasets were similar to the gridded observation over most of the United States. On the other hand, precipitation from all three global reanalyses was biased, especially in summer and winter in the southeastern United States. The regional reanalysis precipitation was closer to observations since it indirectly assimilates surface precipitation. The WFDEI dataset was generally less biased than the reanalysis datasets. All datasets were then used to force a global conceptual hydrological model on 370 watersheds of the Model Parameter Estimation Experiment (MOPEX) database. River flows were computed for each watershed, and results showed that the flows simulated using NARR and gridded observations forcings were very similar to the observed flows. The simulated flows forced by the global reanalysis datasets were also similar to the observations, except in the humid continental and subtropical climatic regions, where precipitation seasonality biases degraded river flow simulations. The WFDEI dataset led to better river flows than reanalysis in the humid continental and subtropical climatic regions but was no better than reanalysis-and sometimes worse-in other climatic zones. Overall, the results indicate that global reanalyses have good potential to be used as proxies to observations to force hydrological models, especially in regions with few weather stations. [ABSTRACT FROM AUTHOR]