ALBERT

Description: A unique automated planetary boundary layer (PBL) retrieval algorithm is proposed as a common cross-platform method for use with commercially available ceilometers for implementation under the redesigned U.S. Environmental Protection Agency Photochemical Assessment Monitoring Stations program. This algorithm addresses instrument signal quality and screens for precipitation and cloud layers before the implementation of the retrieval methodology using the Haar wavelet covariance transform method. Layer attribution for the PBL height is supported with the use of continuation and time-tracking parameters, and uncertainties are calculated for individual PBL height retrievals. Commercial ceilometer retrievals are tested against radiosonde PBL height and cloud-base height during morning and late afternoon transition times, critical to air quality model prediction and when retrieval algorithms struggle to identify PBL heights. A total of 58 radiosonde profiles were used and retrievals for nocturnal stable layers, residual layers and mixing layers were assessed. Overall good agreement was found for all comparisons with one system showing limitations for the cases of nighttime surface stable layers and daytime mixing layer. It is recommended that nighttime shallow stable layer retrievals be performed with a recommended minimum height or with additional verification. Retrievals of residual layer heights and mixing layer comparisons revealed overall good correlations to radiosonde heights (correlation coefficients, r2, ranging from 0.89 – 0.96 and bias ranging from ~ -131 to +63 m, and r2 from 0.88 – 0.97 and bias from -119 to +101 m, respectively).

Description: No Abstract available.

Description: Advances in computer power, new forecasting challenges, and new diagnostic techniques have brought about changes in the way atmospheric development and vertical motion are diagnosed in an operational setting. Many of these changes, such as improved model skill, model resolution, and ensemble forecasting, have arguably been detrimental to the ability of forecasters to understand and respond to the evolving atmosphere. The use of nondivergent wind in place of geostrophic wind would be a step in the right direction, but the advantages of potential vorticity suggest that its widespread adoption as a diagnostic tool on the west side of the Atlantic is overdue. Ertel potential vorticity (PV), when scaled to be compatible with pseudopotential vorticity, is generally similar to pseudopotential vorticity, so forecasters accustomed to quasigeostrophic reasoning through the height tendency equation can transfer some of their intuition into the Ertel-PV framework. Indeed, many of the differences between pseudopotential vorticity and Ertel potential vorticity are consequences of the choice of definition of quasigeostrophic PV and are not fundamental to the quasigeostrophic system. Thus, at its core, PV thinking is consistent with commonly used quasigeostrophic diagnostic techniques.

Description: Synoptic and mesoscale meteorology underwent a revolution in the 1940s and 1950s with the widespread deployment of novel weather observations, such as the radiosonde network and the advent of weather radar. These observations provoked a rapid increase in our understanding of the structure and dynamics of the atmosphere by pioneering analysts such as Fred Sanders. The authors argue that we may be approaching an analogous revolution in our ability to study the structure and dynamics of atmospheric phenomena with the advent of probabilistic objective analyses. These probabilistic analyses provide not only best estimates of the state of the atmosphere (e.g., the expected value) and the uncertainty about this state (e.g., the variance), but also the relationships between all locations and all variables at that instant in time. Up until now, these relationships have been determined by sampling in time by, for example, case studies, composites, and time-series analysis. Here the authors propose a new approach, ensemble synoptic analysis, which exploits the information contained in probabilistic samples of analyses at one or more instants in time. One source of probabilistic analyses is ensemble-based state-estimation methods, such as ensemble-based Kalman filters. Analyses from such a filter may be used to study atmospheric phenomena and the relationships between fields and locations at one or more instants in time. After a brief overview of a research-based ensemble Kalman filter, illustrative examples of ensemble synoptic analysis are given for an extratropical cyclone, including relationships between the cyclone minimum sea level pressure and other synoptic features, statistically determined operators for potential-vorticity inversion, and ensemble-based sensitivity analysis.

Description: The pioneering large-scale studies of cyclone frequency, location, and intensity conducted by Fred Sanders prompt similar questions about lesser-studied anticyclone development. The results of a climatology of closed anticyclones (CAs) at 200, 500, and 850 hPa, with an emphasis on the subtropics and midlatitudes, is presented to assess the seasonally varying distribution and hemispheric differences of these features. To construct the CA climatology, a counting program was applied to twice-daily 2.5° NCEP–NCAR reanalysis 200-, 500-, and 850-hPa geopotential height fields for the period 1950–2003. Stationary CAs, defined as those CAs that were located at a particular location for consecutive time periods, were counted only once. The climatology results show that 200-hPa CAs occur preferentially during summer over subtropical continental regions, while 500-hPa CAs occur preferentially over subtropical oceans in all seasons and over subtropical continents in summer. Conversely, 850-hPa CAs occur preferentially over oceanic regions beneath upper-level midocean troughs, and are most prominent in the Northern Hemisphere, and over midlatitude continents in winter. Three case studies of objectively identified CAs that produced heal waves over the United States, Europe, and Australia in 1995, 2003, and 2004, respectively, are presented to supplement the climatological results. The case studies, examining the subset of CAs than can produce heat waves, illustrate how climatologically hot continental tropical air masses produced over arid and semiarid regions of the subtropics and lower midlatitudes can become abnormally hot in conjunction with dynamically driven upper-level ridge amplification. Subsequently, these abnormally hot air masses are advected downstream away from their source regions in conjunction with transient disturbances embedded in anomalously strong westerly jets.

Description: Oklahoma Mesonetwork data are used to illustrate important atmospheric features that are not well shown by the usual synoptic data. For example, some shifts of wind from south to north that are shown as cold fronts on synoptic charts are not cold fronts by any plausible definition. As previously discussed by Fred Sanders and others, such errors in analysis can be reduced by knowledge of the wide variety of weather phenomena that actually exists, and by more attention to temperatures at the earth's surface as revealed by conventional synoptic data. Mesoscale data for four cases reinforce previous discussions of the ephemeral nature of fronts and deficiencies in the usual analyses of cold fronts. One type of misanalyzed case involves post-cold-frontal boundary layer air that is warmer than the prefrontal air. A second type is usually nocturnal, with a rise of local temperature during disruption of an inversion and a wind shift with later cooling that accompanies advection of a climatological gradient of temperature.

Description: The advent of the polar front theory of cyclones in Norway early in the last century held that the development of fronts and air masses is central to understanding midlatitude weather phenomena. While work on fronts continues to this day, the concept of air masses has been largely forgotten, superseded by the idea of a continuum. The Norwegians placed equal emphasis on the thermodynamics of airmass formation and on the dynamical processes that moved air masses around; today, almost all the emphasis is on dynamics, with little published literature on diabatic processes acting on a large scale. In this essay, the author argues that a lack of understanding of large-scale diabatic processes leads to an incomplete picture of the atmosphere and contributes to systematic errors in medium- and long-range weather forecasts. At the same time, modern concepts centered around potential vorticity conservation and inversion lead one to a redefinition of the term "air mass" that may have some utility in conceptualizing atmospheric physics and in weather forecasting.

Description: Historically, the atmospheric sciences have tended to treat problems of weather and climate separately. The real physical system, however, is a continuum, with short-term (minutes to days) “weather” fluctuations influencing climate variations and change, and, conversely, more slowly varying aspects of the system (typical time scales of a season or longer) affecting the weather that is experienced. While this past approach has served important purposes, it is becoming increasingly apparent that in order to make progress in addressing many socially important problems, an improved understanding of the connections between weather and climate is required. This overview summarizes the progress over the last few decades in the understanding of the phenomena and mechanisms linking weather and climate variations. The principal emphasis is on developments in understanding key phenomena and processes that bridge the time scales between synoptic-scale weather variability (periods of approximately 1 week) and climate variations of a season or longer. Advances in the ability to identify synoptic features, improve physical understanding, and develop forecast skill within this time range are reviewed, focusing on a subset of major, recurrent phenomena that impact extratropical wintertime weather and climate variations over the Pacific–North American region. While progress has been impressive, research has also illuminated areas where future gains are possible. This article concludes with suggestions on near-term directions for advancing the understanding and capabilities to predict the connections between weather and climate variations.

Description: Fred Sanders' career extended over 55 yr, touching upon many of the revolutionary transformations in the field of meteorology during that period. In this paper, his contributions to the transformation of synoptic meteorology, his research into the nature of explosive cyclogenesis, and related advances in the ability to predict these storms are reviewed. In addition to this review, the current status of forecasting oceanic cyclones 4.5 days in advance is presented, illustrating the progress that has been made and the challenges that persist, especially for forecasting those extreme extratropical cyclones that are marked by surface wind speeds exceeding hurricane force. Last, Fred Sanders' participation in a forecast for the historic 1947 snowstorm (that produced snowfall amounts in the New York City area that set records at that time) is reviewed along with an attempt to use today's operational global model to simulate this storm using data that were available at the time. The study reveals the predictive limitations involved with this case based on the scarcity of upper-air data in 1947, while confirming Fred Sanders' forecasting skills when dealing with these types of major storm events, even as a young aviation forecaster at New York's LaGuardia Airport.

Description: A case study of a double dryline on 22 May 2002 is presented. Mobile, 3-mm-wavelength Doppler radars from the University of Massachusetts and the University of Wyoming (Wyoming cloud radar) were used to collect very fine resolution vertical-velocity data in the vicinity of each of the moisture gradients associated with the drylines. Very narrow (50–100 m wide) channels of strong upward vertical velocity (up to 8 m s–1) were measured in the convergence zone of the easternmost dryline, larger in magnitude than reported with previous drylines. Distinct areas of descending motion were evident to the east and west of both drylines. Radar data are interpreted in the context of other observational platforms available during the International H2O Project (IHOP-2002). a variational ground-based mobile radar data processing technique was developed and applied to pseudo-dual-Doppler data collected during a rolling range-height indicator deployment. It was found that there was a secondary (vertical) circulation normal to the easternmost moisture gradient; the circulation comprised an easterly component near-surface flow to the east, a strong upward vertical component in the convergence zone, a westerly return, flow above the convective boundary layer, and numerous regions of descending motion, the most prominent approximately 3–5 km to the east of the surface convergence zone.

Description: Fred Sanders' teaching and research contributions in the area of quasigeostrophic theory are highlighted in this paper. The application of these contributions is made to the topic of extreme cold-season precipitation events in the Saint Lawrence valley in the northeastern United States and southern Quebec. This research focuses on analyses of Saint Lawrence valley heavy precipitation events. Synoptic- and planetary-scale circulation anomaly precursors are typically identified several days prior to these events. These precursors include transient upper-level troughs, strong moisture transports into the region, and anomalously large precipitable water amounts. The physical insight of Fred Sanders' work is used in the analysis of these composite results. Further details of this insight are provided in analyses of one case of heavy precipitation.

Description: Sanders designed a barotropic tropical cyclone (TC) track prediction model for the North Atlantic TC basin that became known as the Sanders barotropic (SANBAR) model. It predicted the streamfunction of the deeplayer mean winds (tropical circulation vertically averaged from 1000 to 100 hPa) that represents the vertically averaged tropical circulations. Originally, the wind input for the operational objective analysis (OA) consisted of winds measured by radiosondes and 44 bogus winds provided by analysis at the National Hurricane Center (NHC), which corresponded to the vertically averaged flow over sparsely observed tropical, subtropical, and midlatitude oceanic regions. The model covered a fixed regional area and had a grid size of ~ 154 km. It estimated the initial storm motion solely on the basis of the large-scale flow from the OA, not taking into account the observed storm motion. During 1970, the SANBAR model became the first dynamical TC track model to be run operationally at NHC. Track forecasts of SANBAR were verified from the 1971 TC season when track model verifications began at NHC until its retirement after the 1989 Atlantic TC season. The average annual SANBAR forecast track errors were verified relative to Climatology and Persistence (CLIPER), the standard no-skill track forecast. Comparison with CLIPER determines the skill of track forecast methods. Verifications are presented for two different versions of the SANBAR model system used operationally during 1973–84 and 1985–89. In homogeneous comparisons (i.e., includes only forecasts for the same initial times) for the former period, SANBAR's track forecasts were slightly better than CLIPER at 24–48-h forecast intervals; however, from 1985 to 1989 the average SANBAR track forecast errors from 24–72 h were ~10% more skillful than homogeneous CLIPER track forecasts.

Description: In the last decade, Fred Sanders was often critical of current surface analysis techniques. This led to his promoting the use of surface potential temperatures to distinguish between fronts, baroclinic troughs, and non-frontal baroclinic zones, and to the development of a climatology of surface baroclinic zones. In this paper, criticisms of current surface analysis techniques and the usefulness of surface potential temperature analyses are discussed. Case examples are used to compare potential temperature analyses and current National Centers for Environmental Prediction analyses. The 1-yr climatology of Sanders and Hoffman is reconstructed using a composite technique. Annual and seasonal mean potential temperature analyses over the continental United States, southern Canada, northern Mexico, and adjacent coastal waters are presented. In addition, gridpoint frequencies of moderate and strong potential temperature gradients are calculated. The results of the mean potential temperature analyses show that moderate and strong surface baroclinic zones are favored along the coastlines and the slopes of the North American cordillera. Additional subsynoptic details, not found in Sanders and Hoffman, are identified. The availability of the composite results allows for the calculation of potential temperature gradient anomalies. It is shown that these anomalies can be used to identify significant frontal baroclinic zones that are associated with weak potential temperature gradients. Together the results and reviews in this paper show that surface potential temperature analyses are a valuable forecasting and analysis tool allowing analysts to distinguish and identify fronts, baroclinic troughs, and nonfrontal baroclinic zones.

Description: The nature of the different types of surface boundaries that appear in the southern plains of the United States during the convectively active season is reviewed. The following boundaries are discussed: fronts, the dryline, troughs, and outflow boundaries, The boundaries are related to their environment and to local topography. The role these boundaries might play in the initiation of convective storms is emphasized. The various types of boundary-related vertical circulations and their dynamics are discussed. In particular, quasigeostrophic and semigeostrophic dynamics, and the dynamics of solenoidal circulations, density currents, boundary layers, and gravity waves are considered. Miscellaneous topics pertinent to convective storms and their relationship to surface boundaries such as along-the-boundary variability, boundary collisions, and the role of vertical shear are also discussed. Although some cases of storm initiation along surface boundaries have been well documented using research datasets collected during comprehensive field experiments, much of what we know is based only on empirical forecasting and nowcasting experience. It is suggested that many problems relating to convective-storm formation need to be explored in detail using real datasets with new observing systems and techniques, in conjunction with numerical simulation studies, and through climatological studies.

Description: This paper begins with a review of basic surface frontogenesis concepts with an emphasis on fronts located over sloping terrain adjacent to mountain barriers and fronts located in large-scale baroclinic zones close to coastlines. The impact of cold-air damming and differential diabatic heating and cooling on frontogenesis is considered through two detailed case studies of intense surface fronts. The first case, from 17 to 18 April 2002, featured the westward passage of a cold (side-door) front across coastal eastern New England in which 15°–20°C temperature decreases were observed in less than one hour. The second case, from 28 February to 4 March 1972, featured a long-lived front that affected most of the United States from the Rockies to the Atlantic coast and was noteworthy for a 50°C temperature contrast between Kansas and southern Manitoba, Canada. In the April 2002 case most of New England was initially covered by an unusually warm, dry air mass. Dynamical anticyclogenesis over eastern Canada set the stage for a favorable pressure gradient to allow chilly marine air to approach coastal New England from the east. Diabatic cooling over the chilly (5°–8°C) waters of the Gulf of Maine allowed surface pressures to remain relatively high offshore while diabatic heating over the land (31°–33°C temperatures) enabled surface pressures to fall relative to over the ocean. The resulting higher pressures offshore resulted in an onshore cold push. Frontal intensity was likely enhanced prior to leaf out and grass green-up as virtually all of the available insolation went into sensible heating. The large-scale environment in the February–March 1972 case favored the accumulation of bitterly cold arctic air in Canada. Frontal formation occurred over northern Montana and North Dakota as the arctic air moved slowly southward in conjunction with surface pressure rises east of the Canadian Rockies. The arctic air accelerated southward subsequent to lee cyclogenesis–induced pressure falls ahead of an upstream trough that crossed the Rockies. The southward acceleration of the arctic air was also facilitated by dynamic anticyclogenesis in southern Canada beneath a poleward jet-entrance region. Frontal intensity varied diurnally in response to differential diabatic heating. Three types of cyclogenesis events were observed over the lifetime of the event: 1) low-amplitude frontal waves with no upper-level support, 2) low-amplitude frontal waves that formed in a jet-entrance region, and 3) cyclones that formed ahead of advancing upper-level troughs. All cyclones were either nondeveloping or weak developments despite extreme baroclinicity, likely the result of large atmospheric static stability in the arctic frontal zone and unfavorable alongfront stretching deformation. Significant frontal–mountain interactions were observed over the Rockies and the Appalachians.

Description: Over 50 yr have passed since the publication of Sanders' 1955 study, the first quantitative study of the structure and dynamics of a surface cold front. The purpose of this chapter is to reexamine some of the results of that study in light of modern methods of numerical weather prediction and diagnosis. A simulation with a resolution as high as 6-km horizontal grid spacing was performed with the fifth-generation-Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) Mesoscale Model (MM5), given initial and lateral boundary conditions from the National Centers for Environmental Precipitation-National Center for Atmospheric Research (NCEP-NCAR) reanalysis project data from 17 to 18 April 1953. The MM5 produced a reasonable simulation af the front, albeit its strength was not as intense and its movement was not as fast as was analyzed by Sanders. The vertical structure of the front differed from that analyzed by Sanders in several significant ways. First, the strongest horizontal temperature gradient associated with the cold front in the simulation occurred above a surface-based inversion, not at the earth's surface. Second, the ascent plume at the leading edge of the front was deeper and more intense than that analyzed by Sanders. The reason was an elevated mixed layer that had moved over the surface cold front in the simulation, allowing a much deeper vertical circulation than was analyzed by Sanders. This structure is similar to that of Australian cold fronts with their deep, well-mixed, prefrontal surface layer. These two differences between the model simulation and the analysis by Sanders may be because upper-air data from Fort Worth, Texas, was unavailable to Sanders. Third, the elevated mixed layer also meant that isentropes along the leading edge of the front extended vertically. Fourth, the field of frontogenesis of the horizontal temperature gradient calculated from the three-dimensional wind differed in that the magnitude of the maximum of the deformation term was larger than the magnitude of the maximum of the tilting term in the simulation, in contrast to Sanders' analysis and other previously published cases. These two discrepancies may be attributable to the limited horizontal resolution of the data that Sanders used in constructing his cross section. Last, a deficiency of the model simulation was that the postfrontal surface superadiabatic layer in the model did not match the observed well-mixed boundary layer. This result raises the question of the origin of the well-mixed postfrontal boundary layer behind cold fronts. To address this question, an additional model simulation without surface fluxes was performed, producing a well-mixed, not superadiabatic, layer. This result suggests that surface fluxes were not necessary for the development of the well-mixed layer, in agreement with previous research. Analysis of this event also amplifies two research themes that Sanders returned to later in his career, First, a prefrontal wind shift occurred in both the observations and model simulation at stations in western Oklahoma. This prefrontal wind shift was caused by a lee cyclone departing the leeward slopes of the Rockies slightly equatorward of the cold front, rather than along the front as was the case farther eastward. Sanders' later research showed how the occurrence of these prefrontal wind shifts leads to the weakening of fronts. Second, this study shows the advantage of using surface potential temperature, rather than surface temperature, for determining the locations of the surface fronts on sloping terrain.

Description: Today, even with state-of-the-art observational, data assimilation, and modeling systems run routinely on supercomputers, there are often surprises in the prediction of snowstorms, especially the “big ones,” affecting coastal regions of the mid-Atlantic and northeastern United States. Little did the author know that lessons from Fred Sanders' synoptic meteorology class at the Massachusetts Institute of Technology (1967) would later (late 1980s) inspire him to pursue practical issues of predictability in the context of the development of ensemble prediction systems, strategies, and applications for providing information on the inevitable case-dependent uncertainties in forecasts. This paper is a brief qualitative and somewhat colloquial overview, based upon this author's personal involvement and experiences, intended to highlight some basic aspects of the source and nature of uncertainties in forecasts and to illustrate the sort of value added information ensembles can provide in dealing with uncertainties in predictions of East Coast snowstorms.

Description: One characteristic of Fred Sanders' research is his ability to take a topic that is believed to be well understood by the research community and show that interesting research problems still exist. Among Sanders' considerable contributions to synoptic meteorology, those concerned with surface cold fronts have been especially influential. After a brief historical review of fronts and frontal analysis, this chapter presents three stages in Sanders' career when he performed research on the structure, dynamics, and analysis of surface cold fronts. First, his 1955 paper, "An investigation of the structure and dynamics of an intense surface frontal zone," was the first study to discuss quantitatively the dynamics of a surface cold front. In the 1960s, Sanders and his students further examined the structure of cold fronts, resulting in the unpublished 1967 report to the National Science Foundation, "Frontal structure and the dynamics of frontogenesis." For a third lime in his career, Sanders published several papers (1995–2005) revisiting the structure and dynamics of cold fronts. His 1967 and 1995–2005 work raises the question of the origin and dynamics of the surface pressure trough and/or wind shift that sometimes precedes the temperature gradient (hereafter called a prefrontal trough or prefrontal wind shift, respectively). Sanders showed that the relationship between this prefrontal feature and the temperature gradient is fundamental to the strength of the front. When the wind shift is coincident with the temperature gradient, frontogenesis (strengthening of the front) results; when the wind shift lies ahead of the temperature gradient, frontolysis (weakening of the front) results. a number of proposed mechanisms for the formation of prefrontal troughs and prefrontal wind shifts exist. Consequently, much research remains to be performed on these topics.

Description: No Abstract available.

Description: The dynamic origin of the interannual variability of West China autumn rainfall (WCAR), a special weather/climate phenomenon over western-central China in September and October, was investigated via observational diagnosis and numerical simulations. Here we found that the interannual variability of WCAR is closely related to the local horizontal trough, which is passively induced by two lower-level anticyclonic (high pressure) anomalies over East Asia. The anticyclonic anomaly over the south is a Gill-type response to the central and eastern Pacific diabatic cooling, while that over the north is part of the mid- to high-latitude barotropic Rossby wave train, which could be induced by either the thermal forcing of the central and eastern Pacific Ocean sea surface temperature (SST) cooling or that of the subtropical northern Atlantic Ocean SST warming. The quasi-barotropic high pressure anomaly over East Asia acts as an “invisible mountain” that steers the low-level anomalous southwesterly into a southeasterly and hinders the water vapor going farther to the north, leading to enhanced WCAR. However, the real mountain ranges in the region (the Qinglin and Ba Mountains) have no essential impact on the formation and interannual variability of WCAR.

Description: Capsule Edward Kidson was a New Zealand scientist who spearheaded the modernisation of Australasian meteorology by introducing Bergen School methods of synoptic analysis to the Southern Hemisphere in the 1930s.

Description: Accurate simulation of planetary boundary layer height (PBLH) is key to greenhouse gas emission estimation, air quality prediction, and weather forecasting. This paper describes an extensive performance assessment of several Weather Research and Forecasting (WRF) Model configurations in which novel observations from ceilometers, surface stations, and a flux tower were used to study their ability to reproduce the PBLH and the impact that the urban heat island (UHI) has on the modeled PBLHs in the greater Washington, D.C., area. In addition, CO2 measurements at two urban towers were compared with tracer transport simulations. The ensemble of models used four PBL parameterizations, two sources of initial and boundary conditions, and one configuration including the building energy parameterization urban canopy model. Results have shown low biases over the whole domain and period for wind speed, wind direction, and temperature, with no drastic differences between meteorological drivers. We find that PBLH errors are mostly positively correlated with sensible heat flux errors and that modeled positive UHI intensities are associated with deeper modeled PBLs over the urban areas. In addition, we find that modeled PBLHs are typically biased low during nighttime for most of the configurations with the exception of those using the MYNN parameterization, and these biases directly translate to tracer biases. Overall, the configurations using the MYNN scheme performed the best, reproducing the PBLH and CO2 molar fractions reasonably well during all hours and thus opening the door to future nighttime inverse modeling.

Description: Summer monsoon rainfall supplies over 55% of annual precipitation to global monsoon regions. As shown by more than 70% of models, including 30 models from CMIP5 and 30 models from CMIP6 under high-emission scenarios, North American (NAM) monsoon rainfall decreases in a warmer climate, in sharp contrast to the robust increase in Asian-African monsoon rainfall. A hierarchy of model experiments are analyzed to understand the mechanism for the reduced NAM monsoon rainfall in this study. Modeling evidence shows that the reduction of NAM monsoon rainfall is related to both direct radiative forcing of increased CO2 concentration and SST warming, manifested as fast and slow responses to abrupt CO2 quadrupling in CGCMs. A cyclone anomaly forms over the Eurasian-African continent due to enhanced land-sea thermal contrast under increased CO2 concentration, and this leads to a subsidence anomaly on its western flank, suppressing the NAM monsoon rainfall. The SST warming acts to further reduce the rainfall over the NAM monsoon region, and the El Niño-like SST warming pattern with enhanced SST warming over the equatorial Pacific plays a key role in suppressing NAM rainfall, whereas relative cooling over the subtropical North Atlantic has no contribution. A positive feedback between monsoon precipitation and atmospheric circulation helps to amplify the responses of monsoon rainfall.

Description: The assimilation of L-band surface brightness temperature (Tb) into the land surface model (LSM) component of a numerical weather prediction (NWP) system is generally expected to improve the quality of summertime 2-m air temperature (T2m) forecasts during water-limited surface conditions. However, recent retrospective results from the European Centre for Medium-Range Weather Forecasts (ECMWF) suggest that the assimilation of L-band Tb from the European Space Agency’s (ESA) Soil Moisture Ocean Salinity (SMOS) mission may, under certain circumstances, degrade the accuracy of growing-season 24-h T2m forecasts within the central United States. To diagnose the source of this degradation, we evaluate ECMWF soil moisture (SM) and evapotranspiration (ET) forecasts using both in situ and remote sensing resources. Results demonstrate that the assimilation of SMOS Tb broadly improves the ECMWF SM analysis in the central United States while simultaneously degrading the quality of 24-h ET forecasts. Based on a recently derived map of true global SM–ET coupling and a synthetic fraternal twin data assimilation experiment, we argue that the spatial and temporal characteristics of ECMWF SM analyses and ET forecast errors are consistent with the hypothesis that the ECMWF LSM overcouples SM and ET and, as a result, is unable to effectively convert an improved SM analysis into enhanced ET and T2m forecasts. We demonstrate that this overcoupling is likely linked to the systematic underestimation of root-zone soil water storage capacity by LSMs within the U.S. Corn Belt region.

Description: Recent advances in global ocean prediction systems are fostered by the needs of accurate representation of mesoscale processes. The day-by-day realistic representation of its variability is hampered by the scarcity of observations as well as the capability of assimilation systems to correct the ocean states at the same scale. This work extends a 3dvar system designed for oceanic applications, to cope with global eddy-resolving grid and dense observational datasets in a hybridly parallelized environment. The efficiency of the parallelization is assessed in term of both scalability and accuracy. The scalability is favoured by a weak-constrained formulation of the continuity requirement among the artificial boundaries implied by the domain decomposition. The formulation forces possible boundary discontinuities to be less than a prescribed error, and minimizes the parallel communication compared to standard methods. Theoretically, the exact solution is recovered by decreasing the boundary error towards zero. Practically, it is shown that the accuracy increases until a lower bound arises, due to the presence of the mesh and the finite accuracy of the minimizer. A twin experiment has been set up to estimate the benefit of employing an eddy-resolving grid within the assimilation step compared to an eddy-permitting one, while keeping the eddy-resolving grid within the forecast step. It is shown that the use of coarser grid for data assimilation does not allow an optimal exploitation of the present remote sensing observation network. A global decrease of about 15% in the error statistics is found when assimilating dense surface observations, while no significant improvement is seen for sparser observations (insitu profilers).

Description: 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 0.03°–0.05°C 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.

Description: Buoy observations from a 1999 Gulf of Mexico field program (GOM99) are used to investigate the relationships among friction velocity u*, wind speed U, and amount of swell present. A U–u*sea parameterization is developed for the case of pure wind sea (denoted by u*sea), which is linear in U over the range of available winds (2–16 m s−1). The curve shows no sign of an inflection point near 7–8 m s−1 as suggested in a 2012 paper by Andreas et al. on the basis of a transition from smooth to rough flow. When observations containing more than minimal swell energy are included, a different U–u* equation for U 〈 8 m s−1 is found, which would intersect the pure wind-sea curve about 7–8 m s−1. These two relationships yield a bilinear curve similar to Andreas et al. with an apparent inflection near 7–8 m s−1. The absence of the inflection in the GOM99 experiment pure wind-sea curve and the similarity of the GOM99 swell-dominated low wind speed to Andreas et al.’s low wind speed relationship suggest that the inflection may be due to the effect of swell and not a flow transition. Swell heights in the range of only 25–50 cm may be sufficient to impact stress at low wind speeds.

Description: Concentrated poleward flows near the eastern boundaries between 2- and 4-km depth have been observed repeatedly, particularly in the Southern Hemisphere. These deep eastern boundary currents (DEBCs) play an important role in setting the large-scale tracer distribution and have nonnegligible contribution to global transports of mass, heat, and tracers, but their dynamics are not well understood. In this paper, we first demonstrate the significant role of DEBCs in the southeastern Atlantic, Indian, and Pacific Oceans, using the Southern Ocean State Estimate (SOSE) data assimilating product, and using high-resolution regional general circulation model configurations. The vorticity balances of these DEBCs reveal that, over most of the width of such currents, they are in an interior-like vorticity budget, with the meridional advection of planetary vorticity βυ and vortex stretching fwz being the largest two terms, and with contributions of nonlinearity and friction that are of smaller spatial scale. The stretching is shown, using a temperature budget, to be largely forced by resolved or parameterized eddy temperature transport. Strongly decaying signals from the eastern boundary in friction and stretching form the dominant balance in a sublayer close to the eastern boundary. The temporal variability of DEBCs is then examined, to help to interpret observations that tend to be sporadic in both time and space. The probability distribution functions of northward velocity in DEBC regions are broad, implying that flow reversals are common. Although the regions of the simulated DEBCs are generally local minima of eddy kinetic energy, they are still constantly releasing westward-propagating Rossby waves.

Description: The intensity of the tropical cyclone has been introduced into the Dynamical-Statistical-Analog Ensemble Forecast (DSAEF) for Landfalling Typhoon (or tropical cyclone) Precipitation (DSAEF_LTP) model. Moreover the accumulated precipitation prediction experiments have been conducted on 21 target tropical cyclones with daily precipitation ≥100 mm in South China from 2012 to 2016. The best forecasting scheme for the DSAEF_LTP model is identified, and the performance of the prediction is compared with three numerical weather prediction models (the European Centre for Medium-Range Weather Forecasts, the Global Forecast System and T639). The forecasting ability of the DSAEF_LTP model for heavy rainfall (accumulated precipitation ≥250 mm and ≥100 mm) improves when the intensity of the tropical cyclone is introduced, giving some advantages over the three numerical weather prediction models. The selection of analog tropical cyclones with a maximum intensity (during precipitation over land) equaling to or higher than the initial intensity of the target tropical cyclone gives better forecasts. The prediction accuracy for accumulated precipitation is higher for tropical cyclones with higher intensity and higher observed precipitation, with in both cases positive linear correlations with the threat score.

Description: Global numerical weather prediction (NWP) models have begun to resolve the mesoscale k−5/3 range of the energy spectrum, which is known to impose an inherently finite range of deterministic predictability per se as errors develop more rapidly on these scales than on the larger scales. However, the dynamics of these errors under the influence of the synoptic-scale k−3 range is little studied. Within a perfect-model context, the present work examines the error growth behavior under such a hybrid spectrum in Lorenz’s original model of 1969, and in a series of identical-twin perturbation experiments using an idealized two-dimensional barotropic turbulence model at a range of resolutions. With the typical resolution of today’s global NWP ensembles, error growth remains largely uniform across scales. The theoretically expected fast error growth characteristic of a k−5/3 spectrum is seen to be largely suppressed in the first decade of the mesoscale range by the synoptic-scale k−3 range. However, it emerges once models become fully able to resolve features on something like a 20-km scale, which corresponds to a grid resolution on the order of a few kilometers.

Description: Dust is the major aerosol type over the Tibetan Plateau (TP), and the TP plays an important role in forming the spring dust belt across the Northern Hemisphere in the upper troposphere. Estimated spring dust mass flux (DMF) showed a significant declining trend over the TP during 2007–19. The total spring DMF across the TP (TDMFTP) was mainly affected by DMFs over the Tarim Basin, while the spring DMF across the TP in the midtroposphere was also connected with DMFs over the northwest Indian Peninsula and central Asia. Interannual variability of spring TDMFTP was strongly correlated with the North Atlantic winter sea surface temperature (SST) tripole. A cold preceding winter induced by the North Atlantic winter SST tripole over midlatitude Eurasia promotes dust activities in the subsequent spring. The North Atlantic winter SST tripole anomalies persist into the subsequent spring and induce a corresponding atmosphere response. Enhanced atmospheric baroclinicity develops over northwest China and the northern Indian Peninsula during spring, which is attributed to surface thermal forcing induced by the positive winter SST tripole phase. A strong positive North Atlantic winter SST tripole anomaly strengthens the upper-level westerly jets, enhancing airflow toward the TP midtroposphere; together, these circulation patterns cause anomalous cyclonic conditions in the lower troposphere, especially over the Tarim Basin, via the eastward propagation of a Rossby wave train. These atmospheric circulation conditions are likely to increase the frequency of dust occurrence and promote the transport of dust onto the TP.

Description: The Kiremt rainy season is the foundation of agriculture in the Ethiopian Highlands and a key driver of economic development as well as the instigator of famines that have plagued the country’s history. Despite the importance of these rains, relatively little research exists on predicting the season’s onset; even less research evaluates statistical modeling approaches, in spite of their demonstrated utility for decision-making at local scales. To explore these methods, predictions are generated conditioned on three definitions of onset, at three lead times, using partial least squares (PLS) regression and random forest classification. Results illustrate moderate prediction skill and an ability to avoid false onsets, which may guide planting decisions; however, they are highly sensitive to how onset is defined, suggesting that future prediction approaches should additionally consider local agricultural definitions of onset.

Description: We formulate a new second-order closure turbulence model by employing a recent closure for the pressure–temperature correlation at the equation level. As a result, we obtain new heat flux equations that avoid the long-standing issue of a finite critical Richardson number. The new, structurally simpler model improves on the Mellor–Yamada and Galperin et al. models; a key feature includes enhanced mixing under stable conditions facilitating agreement with observational, experimental, and high-resolution numerical datasets. The model predicts a planetary boundary layer height deeper than predicted by models with low critical Richardson numbers, as demonstrated in single-column model runs of the GISS ModelE general circulation model.

Description: A novel approach to compare airborne observations of solar spectral irradiances measured above clouds with along-track radiative transfer simulations (RTS) is presented. The irradiance measurements were obtained with the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the High Altitude and Long Range Research Aircraft (HALO). The RTS were conducted using the operational ecRad radiation scheme of the Integrated Forecast System (IFS), operated by the European Centre for Medium-Range Weather Forecasts (ECMWF), and a stand-alone radiative transfer solver, the library for Radiative transfer (libRadtran). Profiles of observed and simulated radar reflectivity were provided by the HALO Microwave Package (HAMP) and the Passive and Active Microwave Transfer Model (PAMTRA), respectively. The comparison aims to investigate the capability of the two models to reproduce the observed radiation field. By analyzing spectral irradiances above clouds, different ice cloud optical parameterizations in the models were evaluated. Simulated and observed radar reflectivity fields allowed the vertical representation of the clouds modeled by the IFS to be evaluated, and enabled errors in the IFS analysis data (IFS AD) and the observations to be separated. The investigation of a North Atlantic low pressure system showed that the RTS, in combination with the IFS AD, generally reproduced the observed radiation field. For heterogeneously distributed liquid water clouds, an underestimation of upward irradiance by up to 27% was found. Simulations of ice-topped clouds, using a specific ice optics parameterization, indicated a systematic underestimation of broadband cloud-top albedo, suggesting major deficiencies in the ice optics parameterization between 1242 and 1941 nm wavelength.

Description: Based on a priori analysis of large-eddy simulations (LESs) of the convective atmospheric boundary layer, improved turbulent mixing and dissipation length scales are proposed for a turbulence kinetic energy (TKE)-based planetary boundary layer (PBL) scheme. The turbulent mixing length incorporates surface similarity and TKE constraints in the surface layer, and makes adjustments for lateral entrainment effects in the mixed layer. The dissipation length is constructed based on balanced TKE budgets accounting for shear, buoyancy, and turbulent mixing. A nongradient term is added to the TKE flux to correct for nonlocal turbulent mixing of TKE. The improved length scales are implemented into a PBL scheme, and are tested with idealized single-column convective boundary layer (CBL) cases. Results exhibit robust applicability across a broad CBL stability range, and are in good agreement with LES benchmark simulations. It is then implemented into a community atmospheric model and further evaluated with 3D real-case simulations. Results of the new scheme are of comparable quality to three other well-established PBL schemes. Comparisons between simulated and radiosonde-observed profiles show favorable performance of the new scheme on a clear day.

Description: During spring 2016 the Probabilistic Hazard Information (PHI) prototype experiment was run in the National Oceanic and Atmospheric Administration (NOAA) Hazardous Weather Testbed (HWT) as part of the Forecasting a Continuum of Environmental Threats (FACETS) program. Nine National Weather Service forecasters were trained to use the web-based PHI prototype tool to produce dynamic PHI for severe weather threats. Archived and real-time weather scenarios were used to test this new paradigm of issuing probabilistic information, rather than deterministic information. The forecasters’ mental workload was evaluated after each scenario using the NASA-Task Load Index (TLX) questionnaire. This study summarizes the analysis results of mental workload experienced by forecasters while using the PHI prototype. Six subdimensions of mental workload: mental demand, physical demand, temporal demand, performance, effort, and frustration were analyzed to derive top contributing factors to workload. Average mental workload was 46.6 (out of 100, standard deviation: 19, range 70.8). Top contributing factors to workload included using automated guidance, PHI object quantity, multiple displays, and formulating probabilities in the new paradigm. Automated guidance provided support to forecasters in maintaining situational awareness and managing increased quantities of threats. The results of this study provided understanding of forecasters’ mental workload and task strategies and developed insights to improve usability of the PHI prototype tool.

Description: This study investigates the northward-propagating quasi-biweekly oscillation (QBWO) in the western North Pacific by examining the composite meridional structures. Using newly released reanalysis and remote sensing data, the northward propagation is understood in terms of the meridional contrasts in the planetary boundary layer (PBL) moisture and the column-integrated moist static energy (MSE). The meridional contrast in the PBL moisture, with larger values north of the convection center, is predominantly attributed to the moisture convergence associated with barotropic vorticity anomalies. A secondary contribution comes from the meridional moisture advection, for which advections by mean and perturbation winds are almost equally important. The meridional contrast in the MSE tendency, due to the recharge in the front of convection and discharge in the rear of convection, is jointly contributed by the meridional and vertical MSE advections. The meridional MSE advection mainly depends on the moisture processes particularly in the PBL, and the vertical MSE advection largely results from the advection of the mean MSE by vertical velocity anomalies, wherein the upper-troposphere ascending motion related to the stratiform heating in the rear of the convection plays the major role. In addition, partial feedback from sea surface temperature (SST) anomalies is evaluated on the basis of MSE budget analysis. SST anomalies tend to enhance the surface turbulent heat fluxes ahead of the convention center and suppress them behind the convention center, thus positively contributing approximately 20% of the meridional contrast in the MSE tendency.

Description: Although the development of supergradient winds is well understood, the importance of supergradient winds in tropical cyclone (TC) intensification is still under debate. One view is that the spinup of the eyewall occurs by the upward advection of high tangential momentum associated with supergradient winds from the boundary layer. The other view argues that the upward advection of supergradient winds by eyewall updrafts results in an outward agradient force, leading to the formation of a shallow outflow layer immediately above the inflow boundary layer. As a result, the spinup of tangential wind in the eyewall by the upward advection of supergradient wind from the boundary layer is largely offset by the spindown of tangential wind due to the outflow resulting from the agradient force. In this study, the net contribution by the upward advection of the supergradient wind component from the boundary layer to the intensification rate and final intensity of a TC are quantified through ensemble sensitivity numerical experiments using an axisymmetric TC model. Results show that consistent with the second view above, the positive upward advection of the supergradient wind component from the boundary layer by eyewall updrafts is largely offset by the negative radial advection due to the outflow resulting from the outward agradient force. As a result, the upward advection of the supergradient wind component contributes little (often less than 4%) to the intensification rate and but it contributes about 10%–15% to the final intensity of the simulated TC due to the enhanced inner-core air–sea thermodynamic disequilibrium.

Description: This study is the first to reach a global view of the precipitation process partitioning, using a combination of satellite and global climate modeling data. The pathways investigated are 1) precipitating ice (ice/snow/graupel) that forms above the freezing level and melts to produce rain (S) followed by additional condensation and collection as the melted precipitating ice falls to the surface (R); 2) growth completely through condensation and collection (coalescence), warm rain (W); and 3) precipitating ice (primarily snow) that falls to the surface (SS). To quantify the amounts, data from satellite-based radar measurements—CloudSat, GPM, and TRMM—are used, as well as climate model simulations from the Community Atmosphere Model (CAM) and the Met Office Unified Model (UM). Total precipitation amounts and the fraction of the total precipitation amount for each of the pathways is examined latitudinally, regionally, and globally. Carefully examining the contributions from the satellite-based products leads to the conclusion that about 57% of Earth’s precipitation follows pathway S, 15% R, 23% W, and 5% SS, each with an uncertainty of ±5%. The percentages differ significantly from the global climate model results, with the UM indicating smaller fractional S, more R, and more SS; and CAM showing appreciably greater S, negative R (indicating net evaporation below the melting layer), a much larger percentage of W and much less SS. Possible reasons for the wide differences between the satellite- and model-based results are discussed.

Description: The emergence of a spatial pattern in the externally forced response (FR) of dynamic sea level (DSL) during the altimeter era has recently been demonstrated using climate models but our understanding of its initial emergence, drivers, and implications for the future is poor. Here the anthropogenic forcings of the DSL pattern are explored using the Community Earth System Model Large Ensemble (CESM-LE) and Single-Forcing Large Ensemble, a newly available set of simulations where values of individual forcing agents remain fixed at 1920 levels, allowing for an estimation of their effects. Statistically significant contributions to the DSL FR are identified for greenhouse gases (GHGs) and industrial aerosols (AERs), with particularly strong contributions resulting from AERs in the mid-twentieth century and GHGs in the late twentieth and twenty-first century. Secondary, but important, contributions are identified for biomass burning aerosols in the equatorial Atlantic Ocean in the mid-twentieth century, and for stratospheric ozone in the Southern Ocean during the late twentieth century. Key to understanding regional DSL patterns are ocean heat content and salinity anomalies, which are driven by surface heat and freshwater fluxes, ocean dynamics, and the spatial structure of seawater thermal expansivity. Potential implications for the interpretation of DSL during the satellite era and the longer records from tide gauges are suggested as a topic for future research.

Description: Capsule Developing and providing interdisciplinary formal climate change training and education for current and future decision-makers.

Description: The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program User Facility produces ground-based long-term continuous unique measurements for atmospheric state, precipitation, turbulent fluxes, radiation, aerosol, cloud, and the land surface, which are collected at multiple sites. These comprehensive datasets have been widely used to calibrate climate models and are proven to be invaluable for climate model development and improvement. This article introduces an evaluation package to facilitate the use of ground-based ARM measurements in climate model evaluation. The ARM data-oriented metrics and diagnostics package (ARM-DIAGS) includes both ARM observational datasets and a Python-based analysis toolkit for computation and visualization. The observational datasets are compiled from multiple ARM data products and specifically tailored for use in climate model evaluation. In addition, ARM-DIAGS also includes simulation data from models participating the Coupled Model Intercomparison Project (CMIP), which will allow climate-modeling groups to compare a new, candidate version of their model to existing CMIP models. The analysis toolkit is designed to make the metrics and diagnostics quickly available to the model developers.

Description: A sensitivity analysis methodology recently developed by the authors is applied to COAMPS and WRF. The method involves varying model parameters according to Latin Hypercube Sampling, and developing multivariate multiple regression models that map the model parameters to forecasts over a spatial domain. The regression coefficients and p values testing whether the coefficients are zero serve as measures of sensitivity of forecasts with respect to model parameters. Nine model parameters are selected from COAMPS and WRF, and their impact is examined on nine forecast quantities (water vapor, convective and gridscale precipitation, and air temperature and wind speed at three altitudes). Although the conclusions depend on the model parameters and specific forecast quantities, it is shown that sensitivity to model parameters is often accompanied by nontrivial spatial structure, which itself depends on the underlying forecast model (i.e., COAMPS vs WRF). One specific difference between these models is in their sensitivity with respect to a parameter that controls temperature increments in the Kain–Fritsch trigger function; whereas this parameter has a distinct spatial structure in COAMPS, that structure is completely absent in WRF. The differences between COAMPS and WRF also extend to the quality of the statistical models used to assess sensitivity; specifically, the differences are largest over the waters off the southeastern coast of the United States. The implication of these findings is twofold: not only is the spatial structure of sensitivities different between COAMPS and WRF, the underlying relationship between the model parameters and the forecasts is also different between the two models.

Description: An increase in the severity of extreme weather is arguably one of the most important consequences of climate change with immediate and potentially devastating impacts. Recent events, like Hurricane Harvey, stimulated public discourse surrounding the role of climate change in amplifying, or otherwise modifying, the patterns of such events. Within the scientific community, recent years have witnessed considerable progress on “climate attribution”—the use of statistical techniques to assess the probability that climate change is influencing the character of some extreme weather events. Using a novel application of signal detection theory, this article assesses when, and to what extent, laypeople attribute changes in hurricanes to climate change and whether and how certain characteristics predict this decision. The results show that people attribute hurricanes to climate change based on their preexisting climate beliefs and numeracy. Respondents who were more dubious about the existence of climate change (and more numerate) required a greater degree of evidence (i.e., a more extreme world) before they were willing to suggest that an unusual hurricane season might be influenced by climate change. However, those who have doubts were still willing to make these attributions when hurricane behavior becomes sufficiently extreme. In general, members of the public who hold different prior views about climate change are not in complete disagreement about the evidence they perceive, which leaves the possibility for future work to explore ways to bring such judgments back into alignment.

Description: Aircraft cruising near the tropopause currently benefit from the highest thermal efficiency and the least viscous (sticky) air, within the lowest 50 km of Earth’s atmosphere. Both advantages wane in a warming climate, because atmospheric dynamic viscosity increases with temperature, in synergy with the simultaneous engine efficiency reduction. Here, skin friction drag, the dominant term for extra aviation fuel consumption in a future warming climate, is quantified by 34 climate models under a strong emissions scenario. Since 1950, the viscosity increase at cruising altitudes (∼200 hPa) reaches ∼1.5% century‒1, corresponding to a total drag increment of ∼0.22% century‒1 for commercial aircraft. Meridional gradients and regional disparities exist, with low to midlatitudes experiencing greater increases in skin friction drag. The North Atlantic corridor (NAC) is moderately affected, but its high traffic volume generates additional fuel cost of ∼3.8 × 107 gallons annually by 2100, compared to 2010. Globally, a normal year after 2100 would consume an extra ∼4 × 106 barrels per year. Intermodel spread is

Description: The Facility for Weather and Climate Assessments (FACTS) developed at the NOAA Physical Sciences Laboratory is a freely available resource that provides the science community with analysis tools; multimodel, multiforcing climate model ensembles; and observational/reanalysis datasets for addressing a wide class of problems on weather and climate variability and its causes. In this paper, an overview of the datasets, the visualization capabilities, and data dissemination techniques of FACTS is presented. In addition, two examples are given that show the use of the interactive analysis and visualization feature of FACTS to explore questions related to climate variability and trends. Furthermore, we provide examples from published studies that have used data downloaded from FACTS to illustrate the types of research that can be pursued with its unique collection of datasets.

Description: The current atmospheric observing systems fail to provide a satisfactory amount of spatially and temporally resolved observations of temperature and humidity in the planetary boundary layer (PBL) despite their potential positive impact on numerical weather prediction (NWP). This is particularly critical for humidity, which exhibits a very high variability in space and time or for the vertical distribution of temperature, determining the atmosphere’s stability. Novel ground-based lidar remote sensing technologies and in situ measurements from unmanned aerial vehicles can fill this observational gap, but operational maturity was so far lacking. Only recently, commercial lidar systems for temperature and humidity profiling in the lower troposphere and automated observations on board of drones have become available. Raman lidar can provide profiles of temperature and humidity with high temporal and vertical resolution in the troposphere. Drones can provide high-quality in situ observations of various meteorological variables with high temporal and vertical resolution, but flights are complicated in high-wind situations, icing conditions, and can be restricted by aviation activity. Both observation systems have shown to considerably improve analyses and forecasts of high-impact weather, such as thunderstorms and fog in an operational, convective-scale NWP framework. The results of this study demonstrate the necessity for and the value of additional, high-frequency PBL observations for NWP and how lidar and drone observations can fill the gap in the current operational observing system.

Description: When drought hits water-scarce regions, there are significant repercussions for food and water security, as well as serious issues for the stability of broader social and environmental systems. To mitigate these effects, environmental monitoring and early warning systems aimed at detecting the onset of drought conditions can facilitate timely and effective responses from government and private sector stakeholders. This study uses multistage, participatory research methods across more than 135 interviews, focus groups, and workshops to assess extant climatic, agricultural, hydrological, and drought monitoring systems; key cross-sector drought impacts; and drought monitoring needs in four countries in the Middle East and North Africa (MENA) region: Morocco, Tunisia, Lebanon, and Jordan. This extensive study of user needs for drought monitoring across the MENA region is informing and shaping the ongoing development of drought early warning systems, a composite drought indicator (CDI), and wider drought management systems in each country. Overarching themes of drought monitoring needs include technical definitions of drought for policy purposes; information-sharing regimes and data-sharing platforms; ground-truthing of remotely sensed and modeled data; improved data quality in observation networks; and two-way engagement with farmers, organizations, and end-users of drought monitoring products. This research establishes a basis for informing enhanced drought monitoring and management in the countries, and the broad stakeholder engagement can help foster the emergence of effective environmental monitoring coalitions.

Description: Many regions in Africa and the Middle East are vulnerable to drought and to water and food insecurity, motivating agency efforts such as the U.S. Agency for International Development’s (USAID) Famine Early Warning Systems Network (FEWS NET) to provide early warning of drought events in the region. Each year these warnings guide life-saving assistance that reaches millions of people. A new NASA multimodel, remote sensing–based hydrological forecasting and analysis system, NHyFAS, has been developed to support such efforts by improving the FEWS NET’s current early warning capabilities. NHyFAS derives its skill from two sources: (i) accurate initial conditions, as produced by an offline land modeling system through the application and/or assimilation of various satellite data (precipitation, soil moisture, and terrestrial water storage), and (ii) meteorological forcing data during the forecast period as produced by a state-of-the-art ocean–land–atmosphere forecast system. The land modeling framework used is the Land Information System (LIS), which employs a suite of land surface models, allowing multimodel ensembles and multiple data assimilation strategies to better estimate land surface conditions. An evaluation of NHyFAS shows that its 1–5-month hindcasts successfully capture known historic drought events, and it has improved skill over benchmark-type hindcasts. The system also benefits from strong collaboration with end-user partners in Africa and the Middle East, who provide insights on strategies to formulate and communicate early warning indicators to water and food security communities. The additional lead time provided by this system will increase the speed, accuracy, and efficacy of humanitarian disaster relief, helping to save lives and livelihoods.

Description: The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) performed comprehensive meteorological and aerosol measurements and ground-based atmospheric remote sensing at two Antarctic stations using the most advanced instrumentation available. A suite of cloud research radars, lidars, spectral and broadband radiometers, aerosol chemical and microphysical sampling equipment, and meteorological instrumentation was deployed at McMurdo Station on Ross Island from December 2015 through December 2016. A smaller suite of radiometers and meteorological equipment, including radiosondes optimized for surface energy budget measurement, was deployed on the West Antarctic Ice Sheet between 4 December 2015 and 17 January 2016. AWARE provided Antarctic atmospheric data comparable to several well-instrumented high Arctic sites that have operated for many years and that reveal numerous contrasts with the Arctic in aerosol and cloud microphysical properties. These include persistent differences in liquid cloud occurrence, cloud height, and cloud thickness. Antarctic aerosol properties are also quite different from the Arctic in both seasonal cycle and composition, due to the continent’s isolation from lower latitudes by Southern Ocean storm tracks. Antarctic aerosol number and mass concentrations are not only non-negligible but perhaps play a more important role than previously recognized because of the higher sensitivities of clouds at the very low concentrations caused by the large-scale dynamical isolation. Antarctic aerosol chemical composition, particularly organic components, has implications for local cloud microphysics. The AWARE dataset, fully available online in the ARM Program data archive, offers numerous case studies for unique and rigorous evaluation of mixed-phase cloud parameterization in climate models.

Description: A rapidly growing number of TV weathercasters are reporting on the local implications of climate change, although little is known about the effectiveness of such communication. To test the impact of localized climate reporting, we conducted an internet-based randomized controlled experiment in which local TV news viewers (n = 1,200) from two American cities (Chicago and Miami) watched either three localized climate reports or three standard weather reports featuring a prominent TV weathercaster from their city; each of the videos was between 1 and 2 min in duration. Participants’ understanding of climate change as real, human-caused, and locally relevant was assessed with a battery of questions after watching the set of three videos. Compared to participants who watched weather reports, participants who watched climate reports became significantly more likely to 1) understand that climate change is happening, is human-caused, and is causing harm in their community; 2) feel that climate change is personally relevant and express greater concern about it; and 3) feel that they understand how climate change works and express greater interest in learning more about it. In short, our findings demonstrate that watching even a brief amount of localized climate reporting (less than 6 min) delivered by TV weathercasters helps viewers develop a more accurate understanding of global climate change as a locally and personally relevant problem, and offer strong support for this promising approach to promoting enhanced public understanding of climate change through public media.

Description: Recent social science research has provided a better understanding of risk communication and decision-making. However, less is understood about the public’s actual weather knowledge, how they assess their weather knowledge, and how knowledge may relate to weather forecast information use. The objective of this study was to gain a better understanding of self-perceived and assessed weather knowledge of participants. Psychology literature indicates some people are prone to overestimating their knowledge, which is known as the Dunning–Kruger effect (DKE), but this has yet to be studied in a meteorological context. This study compared participants’ assessed weather knowledge with their self-perceived weather knowledge, and results indicate participants with the lowest assessed weather knowledge do overestimate their weather knowledge, a result consistent with previous psychological studies. Participants who obtained a weather forecast more frequently exhibited higher perceived and assessed weather knowledge. Higher perceived and assessed weather knowledge was also observed among users of a specialty weather website compared to a more general audience. The study raises interesting questions about how users of different weather sources acquire or (add to) their weather knowledge and is the first study to explore DKE in the context of weather communication.

Description: As we celebrate the fiftieth anniversary of NASA’s Apollo missions, images of Earth simulated with the ECMWF Integrated Forecasting System (IFS) are visually compared with pictures collected during space missions of the past five decades, in particular from the Apollo missions (1968–72). The numerical weather reforecasts use the latest version of the IFS and are initialized from (re)analysis data, which provide our current best representation of the atmospheric state for any given date back to the 1950s. Visible images of our planet are produced from the IFS with a simple simulator whose main inputs are the solar fluxes at the top of the atmosphere. First, a comparison to recent imagery from deep space illustrates the high level of performance of the IFS on recent dates. Then, the validation of the IFS against photographs taken by Apollo 11 and 17 both in-flight and from the lunar surface exhibits a significant level of agreement, despite the absence or very limited number of satellite observations available. This short study confirms that the combination of high-quality initial conditions with a modern numerical weather prediction model can yield reasonably accurate reforecasts of global meteorological conditions, especially cloud systems, for dates as far back as the late 1960s.

Description: It might be impossible to truly fathom the magnitude of the threat that global-mean sea level rise poses. However, conceptualizing the scale of the solutions required to protect ourselves against global-mean sea level rise aids in our ability to acknowledge and understand that threat. On these grounds, we here discuss a means to protect over 25 million people and important economical regions in northern Europe against sea level rise. We propose the construction of a Northern European Enclosure Dam (NEED) that stretches between France, the United Kingdom, and Norway. NEED may seem an overwhelming and unrealistic solution at first. However, our preliminary study suggests that NEED is potentially favorable financially, but also in scale, impacts, and challenges compared to that of alternative solutions, such as (managed) migrations and that of country-by-country protection efforts. The mere realization that a solution as considerable as NEED might be a viable and cost-effective protection measure is illustrative of the extraordinary global threat of global-mean sea level rise that we are facing. As such, the concept of constructing NEED showcases the extent of protection efforts that are required if mitigation efforts fail to limit sea level rise.

Description: The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of observations from high-altitude unmanned aircraft to improve forecasts of high-impact weather events like tropical cyclones or mitigate potential degradation of forecasts in the event of a future gap in satellite coverage. During three field campaigns conducted in 2015 and 2016, the National Aeronautics and Space Administration (NASA) Global Hawk, instrumented with GPS dropwindsondes and remote sensors, flew 15 missions sampling 6 tropical cyclones and 3 winter storms. Missions were designed using novel techniques to target sampling regions where high model forecast uncertainty and a high sensitivity to additional observations existed. Data from the flights were examined in real time by operational forecasters, assimilated in operational weather forecast models, and applied postmission to a broad suite of data impact studies. Results from the analyses spanning different models and assimilation schemes, though limited in number, consistently demonstrate the potential for a positive forecast impact from the observations, both with and without a gap in satellite coverage. The analyses with the then-operational modeling system demonstrated large forecast improvements near 15% for tropical cyclone track at a 72-h lead time when the observations were added to the otherwise complete observing system. While future decisions regarding use of the Global Hawk platform will include budgetary considerations, and more observations are required to enhance statistical significance, the scientific results support the potential merit of the observations. This article provides an overview of the missions flown, observational approach, and highlights from the completed and ongoing data impact studies.

Description: When a forecast is assessed, a single value for a verification measure is often quoted. This is of limited use, as it needs to be complemented by some idea of the uncertainty associated with the value. If this uncertainty can be quantified, it is then possible to make statistical inferences based on the value observed. There are two main types of inference: confidence intervals can be constructed for an underlying “population” value of the measure, or hypotheses can be tested regarding the underlying value. This paper will review the main ideas of confidence intervals and hypothesis tests, together with the less well known “prediction intervals,” concentrating on aspects that are often poorly understood. Comparisons will be made between different methods of constructing confidence intervals—exact, asymptotic, bootstrap, and Bayesian—and the difference between prediction intervals and confidence intervals will be explained. For hypothesis testing, multiple testing will be briefly discussed, together with connections between hypothesis testing, prediction intervals, and confidence intervals.

Description: Studies using International Satellite Cloud Climatology Project (ISCCP) data have reported decreases in cloud optical depth with increasing temperature, thereby suggesting a positive feedback in cloud optical depth as climate warms. The negative cloud optical depth and temperature relationships are questioned because ISCCP employs threshold assumptions to identify cloudy pixels that have included partly cloudy pixels. This study applies the spatial coherence technique to one month of Advanced Very High Resolution Radiometer (AVHRR) data over the Pacific Ocean to differentiate overcast pixels from the partly cloudy pixels and to reexamine the cloud optical depth–temperature relationships. For low-level marine stratus clouds studied here, retrievals from partly cloudy pixels showed 30%–50% smaller optical depths, 1°–4°C higher cloud temperatures, and slightly larger droplet effective radii, when they were compared to retrievals from the overcast pixels. Despite these biases, retrievals for the overcast and partly cloudy pixels show similar negative cloud optical depth–temperature relationships and their magnitudes agree with the ISCCP results for the midlatitude and subtropical regions. There were slightly negative droplet effective radius–temperature relationships, and considerable positive cloud liquid water content–temperature relationships indicated by aircraft measurements. However, cloud thickness decreases appear to be the main reason why cloud optical depth decreases with increasing temperature. Overall, cloud thickness thinning may explain why similar negative cloud optical depth–temperature relationships are found in both overcast and partly cloudy pixels. In addition, comparing the cloud-top temperature to the air temperature at 740 hPa indicates that cloud-top height generally rises with warming. This suggests that the cloud thinning is mainly due to the ascending of cloud base. The results presented in this study are confined to the midlatitude and subtropical Pacific and may not be applicable to the Tropics or other regions.

Description: A statistical model to analyze different time scales of the variability of extreme high sea levels is presented. This model uses a time-dependent generalized extreme value (GEV) distribution to fit monthly maxima series and is applied to a large historical tidal gauge record (San Francisco, California). The model allows the identification and estimation of the effects of several time scales—such as seasonality, interdecadal variability, and secular trends—in the location, scale, and shape parameters of the probability distribution of extreme sea levels. The inclusion of seasonal effects explains a large amount of data variability, thereby allowing a more efficient estimation of the processes involved. Significant correlation with the Southern Oscillation index and the nodal cycle, as well as an increase of about 20% for the secular variability of the scale parameter have been detected for the particular dataset analyzed. Results show that the model is adequate for a complete analysis of seasonal-to-interannual sea level extremes providing time-dependent quantiles and confidence intervals.

Description: The interannual and intraseasonal variability of West African vegetation over the period 1982–2002 is studied using the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR).The novel independent component analysis (ICA) technique is applied to extract the main modes of the interannual variability of the vegetation, among which two modes are worth describing. The first component (IC1) describes NDVI variability over the Sahel from August to October. A strong photosynthetic activity over the Sahel is related to above-normal convection and rainfall within the intertropical convergence zone (ITCZ) in summertime and is partly associated with colder (warmer) SST in the eastern tropical Pacific (the Mediterranean). The second component (IC2) depicts a dipole pattern between the Sahelian and Guinean regions during the northern summer followed by a southward-propagating signal from October to December. It is associated with a north–south dipole in convection and rainfall induced by variations in the latitudinal location of the ITCZ as a response to the occurrence of the tropical Atlantic dipole.The analysis of the intraseasonal variability of the Sahelian vegetation relies on the analysis of the seasonal marches and their main phenological stages. Green-up usually starts in early July and shows a very low year-to-year variability, while senescence ends by mid-November and is prone to larger interannual variability. Six types of vegetative seasonal marches are discriminated according to variations in the timing of phenological stages as well as in the greening intensity. These types appear to be strongly dependent on rainfall distribution and amount, particularly those recorded in late August. Finally, year-to-year memory effects are highlighted: NDVI recorded during the green-up phase in year j appears to be strongly related to the maximum NDVI value recorded at year j − 1.

Description: Based on the data of optimum interpolation sea surface temperature (OISST), the temporal correlations of the sea surface temperature anomaly (SSTA) in the South China Sea (SCS) are studied by using the rescaled range analysis (R/S) and detrended fluctuation analysis (DFA). The results show that the scaling exponents of SSTAs are larger than 0.8. This finding indicates that the SSTAs in the SCS exhibit persistent long-range time correlation of the fluctuations and the interval spreads over a wide period, from about 1 month to 4.5 yr (4∼235 weeks). In addition, the “degree” of the correlations depends very much on the geographic locations: near to the coastal regions, the value is small, while far from the coastline, the value is relatively larger. This means that SSTAs in the central SCS are smoother than those of the coastal regions. The persistence of SST in the SCS may be used as a “minimum skill” to assess the ocean models and to evaluate their performance.

Description: Winds at the Salt Lake City International Airport (SLC) during the April–October period from 1948 to 2003 have been observed to shift to the north (up-valley direction) between late morning and afternoon on over 70% of the days without precipitation. Lake-breeze fronts that develop as a result of the differential heating between the air over the nearby Great Salt Lake and that over the lake’s surroundings are observed at SLC only a few times each month. Fewer lake-breeze fronts are observed during late July–early September than before or after that period. Interannual fluctuations in the areal extent of the shallow Great Salt Lake contribute to year-to-year variations in the number of lake-breeze frontal passages at SLC. Data collected during the Vertical Transport and Mixing Experiment (VTMX) of October 2000 are used to examine the structure and evolution of a lake-breeze front that moved through the Salt Lake Valley on 17 October. The onset of upslope and up-valley winds occurred within the valley prior to the passage of the lake-breeze front. The lake-breeze front moved at roughly 3 m s−1 up the valley and was characterized near the surface by an abrupt increase in wind speed and dewpoint temperature over a distance of 3–4 km. Rapid vertical mixing of aerosols at the top of the 600–800-m-deep boundary layer was evident as the front passed.

Description: This study combines the experimental measurements with large-eddy simulation (LES) data of a neutral planetary boundary layer (PBL) documented by a 60-m tower instrumented with eight sonic anemometers, and a high-resolution Doppler lidar during the 1999 Cooperative Atmospheric and Surface Exchange Study (CASES-99) experiment. The target of the paper is (i) to investigate the multiscale nature of the turbulent eddies in the surface layer (SL), (ii) to explain the existence of a −1 power law in the velocity fluctuation spectra, and (iii) to investigate the different nature of turbulence in the two sublayers within the SL, which are the eddy surface layer (ESL; lower sublayer of the SL lying between the surface and about 20-m height) and the shear surface layer (SSL; lying between the ESL top and the SL top). The sonic anemometers and Doppler lidar prove to be proper instruments for LES validation, and in particular, the Doppler lidar because of its ability to map near-surface eddies.This study shows the different nature of turbulence in the ESL and the SSL in terms of organized eddies, velocity fluctuation spectra, and second-order moment statistics. If quantitative agreement is found in the SSL between the LES and the measurements, only qualitative similarity is found in the ESL due to the subgrid-scale model, indicating that the LES captures part of the physics of the ESL. The LES helps explain the origin of the −1 power-law spectral subrange evidence in the velocity fluctuation spectra computed in the SL using the CASES-99 dataset: strong interaction between the mean flow and the fluctuating vorticities is found in the SL, and turbulent production is found to be larger than turbulent energy transfer for k1z 〉 1 (k1 being the longitudinal wavenumber and z the height), which is the condition of the −1 power-law existence.

Description: Citizen science is often recognized for its potential to directly engage the public in science, and is uniquely positioned to support and extend participants’ learning in science. In March 2018, the Global Learning and Observations to Benefit the Environment (GLOBE) Program, NASA’s largest and longest-lasting citizen science program about Earth, organized a month-long event that asked people around the world to contribute daily cloud observations and photographs of the sky (15 March–15 April 2018). What was considered a simple engagement activity turned into an unprecedented worldwide event that garnered major public interest and media recognition, collecting over 55,000 observations from 99 different countries, in more than 15,000 locations, on every continent including Antarctica. The event was called the “Spring Cloud Challenge” and was created to 1) engage the general public in the scientific process and promote the use of the GLOBE Observer app, 2) collect ground-based visual observations of varying cloud types during boreal spring, and 3) increase the number and locations of ground-based visual cloud observations collocated with cloud-observing satellites. The event resulted in roughly 3 times more observations than during the historic and highly publicized 2017 North American total solar eclipse. The dataset also includes observations over the Drake Passage in Antarctica and reports from intense Saharan dust events. This article describes how the challenge was crafted, outreach to volunteer scientists around the world, details of the data collected, and impact of the data.

Description: There are at least three popular perceptions surrounding the weather forecast for the D-day landing in Normandy, 6 June 1994: 1) that the Allied weather forecasters predicted a crucial break or “window of opportunity” in the unsettled weather prevailing at the time; 2) that the German meteorologists, lacking observations from the North Atlantic, failed to see this break coming and thus the invasion took the Wehrmacht by surprise; and 3) that the American forecasters, guided by a skillful analog system, predicted the favorable conditions several days ahead but got no support from their pessimistic British colleagues. This article will present evidence taken mostly from hitherto rather neglected sources of information, transcripts of the telephone discussions between the Allied forecasters and archived German weather analyses. They show that 1) the synoptic development for the invasion was not particularly well predicted and, if there was a break in the weather, it occurred for reasons other than those predicted; 2) the German forecasters were fairly well informed about the large-scale synoptic situation over most of the North Atlantic, probably thanks to decoded American analyses; and 3) from the viewpoint of a “neutral Swede,” the impression is that the American analog method might not have performed as splendidly as its adherents have claimed, but also not as badly as its critics have alleged. Finally, the D-day forecast, the discussions among the forecasters, and their briefings with the Allied command are interesting not only from a historical perspective, but also as an early and well-documented example of decision-making under meteorological uncertainty.

Description: Climate change and air pollution have important societal consequences, especially in emerging economies, wherein transitions from polluting technologies to cleaner alternatives coincide with high population vulnerability to environmental threats. India is home to a fifth of the world’s population and a gamut of human activities, employing a far ranging spectrum of technologies and fuels, with consequent emissions. Atmospheric fine particles or aerosols in the region predominate in carbonaceous constituents and dust. Multi-institutional studies in the region have earlier focused on natural and anthropogenic climate forcing by aerosols and feedbacks on regional and global climate. Important gaps remain in understanding human activities influencing emissions, emission aerosol properties, and regional atmospheric processes, specifically those related to carbonaceous aerosol impacts on climate and air quality. With an aim to address these gaps, the COALESCE (Carbonaceous Aerosol Emissions, Source Apportionment and Climate Impacts) project was launched on 7 July 2017. The project adopts integration of scientific methods developed by both the climate and air quality research communities. New fundamental knowledge from the project and strong links to India’s policy framework would enable climate and clean-air action in the region. The article describes the scientific rationale, objectives, and planned activities under COALESCE to explore engagement with the international climate and air quality research communities and to enable eventual dissemination of research findings, knowledge products, and decision-support tools.

Description: The effects of natural and anthropogenic heterogeneity on a hydrological simulation are evaluated using a distributed biosphere hydrological model (DBHM) system. The DBHM embeds a biosphere model into a distributed hydrological scheme, representing both topography and vegetation in a mesoscale hydrological simulation, and the model system includes an irrigation scheme. The authors investigated the effects of two kinds of variability, precipitation variability and the variability of irrigation redistributing runoff, representing natural and anthropogenic heterogeneity, respectively, on hydrological processes. Runoff was underestimated if rainfall was placed spatially uniformly over large grid cells. Accounting for precipitation heterogeneity improved the runoff simulation. However, the negative runoff contribution, namely, the situation that mean annual precipitation is less than evapotranspiration, cannot be simulated by only considering the natural heterogeneity. This constructive model shortcoming can be eliminated by accounting for anthropogenic heterogeneity caused by irrigation water withdrawals. Irrigation leads to increased evapotranspiration and decreased runoff, and surface soil moisture in irrigated areas increases because of irrigation. Simulations performed for the Yellow River basin of China indicated streamflow decreases of 41% due to irrigation effects. The latent heat flux in the peak irrigation season [June–August (JJA)] increased 3.3 W m−2 with a decrease in the ground surface temperature of 0.1 K for the river basin. The maximum simulated increase in the latent heat flux was 43 W m−2, and the ground temperature decrease was 1.6 K in the peak irrigation season.

Description: A method for routinely verifying numerical weather prediction surface marine winds with satellite scatterometer winds is introduced. The marine surface winds from the Australian Bureau of Meteorology’s operational global and regional numerical weather prediction systems are evaluated. The model marine surface layer is described. Marine surface winds from the global and limited-area models are compared with observations, both in situ (anemometer) and remote (scatterometer). A 2-yr verification shows that wind speeds from the regional model are typically underestimated by approximately 5%, with a greater bias in the meridional direction than the zonal direction. The global model also underestimates the surface winds by around 5%–10%. A case study of a significant marine storm shows that where larger errors occur, they are due to an underestimation of the storm intensity, rather than to biases in the boundary layer parameterizations.

Description: The applicability of axisymmetric theory of angular momentum conserving circulations to the large-scale steady monsoon is studied in a general circulation model with idealized representations of continental geometry and simple physics. Results from an aquaplanet setup with localized subtropical forcing are compared with a continental case. It is found that the meridional circulation that develops is close to angular momentum conserving for cross-equatorial circulation cells, both in the aquaplanet and in the continental cases. The equator proves to be a substantial barrier to boundary layer meridional flow; flow into the summer hemisphere from the winter hemisphere tends to occur in the free troposphere rather than in the boundary layer. A theory is proposed to explain the location of the monsoon; assuming quasiequilibrium, the poleward boundary of the monsoon circulation is collocated with the maximum in subcloud moist static energy, with the monsoon rains occurring near and slightly equatorward of this maximum. The model results support this theory of monsoon location, and it is found that the subcloud moist static energy distribution is determined by a balance between surface forcing and advection by the large-scale flow.

Description: This paper concerns the calculation of the probability of exceedance of wave crest elevation. The statistics have been calculated for broadbanded, unidirectional, deep-water sea states by incorporating a fully nonlinear wave model into a spectral response surface method. This is a novel approach to the calculation of statistics and, as all of the calculations are performed in the probability domain, avoids the need for long time-domain simulations. Furthermore, in contrast to theoretical distributions, the broadbanded, fully nonlinear nature of the sea state can be considered. The results have been compared with those of fully nonlinear time-domain simulations and are shown to be in good agreement. The results indicate that in unidirectional seas the crest elevations of the largest waves can be much higher than would be predicted by linear or second-order theory. Hence, the occurrence of locally long crested sea states offers a possible explanation for the formation of freak or rogue waves.

Description: Nearly one-half of the earth’s terrestrial surface is susceptible to drought, which can have significant social, economic, and environmental impacts. Therefore, it is important to develop better descriptions and models of the processes linking the land surface and atmosphere during drought. Using data collected during the International H2O Project, the study presented here investigates the effects of variations in the environmental factors driving the latent heat flux (λE) during drought conditions at a rangeland site located in the panhandle of Oklahoma. Specifically, this study focuses on the relationships of λE with vapor pressure deficit, wind speed, net radiation, soil moisture content, and greenness fraction. While each of these environmental factors has an influence, soil moisture content is the key control on λE. The role of soil moisture in regulating λE is explained in terms of the surface resistance to water vapor transfer. The results show that λE transitioned between being water or energy limited during the course of the drought. The implications of this on the ability to understand and model drought conditions and transitions into or out of droughts are discussed.

Description: Common Land Model (CLM) and Land Surface Process (LSP) model simulations are compared to measured values for a 13-day dry-down period with a rapidly decreasing near-surface water table for a marsh wetland community in Florida. LSP was able to provide reasonable estimates without any modifications to the model physics. To obtain reasonable simulations using CLM, the baseline TOPMODEL baseflow generation and the bottom drainage mechanisms were not employed and the lower layers were allowed to remain saturated. In addition, several of CLM’s default wetland vegetation parameters were replaced with grassland parameters. Even after these modifications, CLM underestimated soil water storage. However, both model-simulated soil temperatures showed very good agreement as compared to measured temperatures, capturing both the soil warming during the study period and the diurnal fluctuations. Modeled surface energy fluxes also agreed well with measured values. LSP’s inability to consistently capture latent heat fluxes appears to be linked to its canopy resistance scaling functions. Other minor issues were that CLM’s rooting depth greatly exceeded observed depths and that CLM did not move water in the vadose zone from lower to upper layers during the nighttime as observed in the measurements. Overall, these results suggest that LSP can be applied to characterize a marsh dry down, but that minor modifications could greatly improve results. CLM demonstrated considerable potential, but requires some changes to model physics and default parameters prior to application to wetlands at a subgrid scale.

Description: In March 2003 several autonomous underwater vehicle (AUV) missions were carried out under sea ice in the western Bellingshausen Sea. Data from the upward-looking acoustic Doppler current profiler (ADCP) on the “Autosub” AUV indicate a strongly oscillating horizontal velocity of the ice due to ocean swell. Swell period, height, direction, and directional spread have been computed every 800 m from the ice edge to 10 km inward for three missions. Exponential, period-dependent attenuation of waves propagating through sea ice was observed. Mean period increased with distance from the ice edge. The wave field refracted during propagation. The directional wave spread does not seem to relate to distance from the ice edge, although higher frequencies tended to be more spread. If suitably deployed, an ordinary ADCP may be used with this technique to study both scalar and directional properties of waves in open or ice-covered water.

Description: Wind-sea generation was observed during two experiments off the coast of North Carolina. One event with offshore winds of 9–11 m s−1 directed 20° from shore normal was observed with eight directional stations recording simultaneously and spanning a fetch from 4 to 83 km. An opposing swell of 1-m height and 10-s period was also present. The wind-sea part of the wave spectrum conforms to established growth curves for significant wave height and peak period, except at inner-shelf stations where a large alongshore wind-sea component was observed. At these short fetches, the mean wave direction θm was observed to change abruptly across the wind-sea spectral peak, from alongshore at lower frequencies to downwind at higher frequencies. Waves from another event with offshore winds of 6–14 m s−1 directed 20°–30° from shore normal were observed with two instrument arrays. A significant amount of low-frequency wave energy was observed to propagate alongshore from the region where the wind was strongest. These measurements are used to assess the performance of some widely used parameterizations in wave models. The modeled transition of θm across the wind-sea spectrum is smoother than that in the observations and is reproduced very differently by different parameterizations, giving insights into the appropriate level of dissipation. Calculations with the full Boltzmann integral of quartet wave–wave interactions reveal that the discrete interaction approximation parameterization for these interactions is reasonably accurate at the peak of the wind sea but overpredicts the directional spread at high frequencies. This error is well compensated by parameterizations of the wind input source term that have a narrow directional distribution. Observations also highlight deficiencies in some parameterizations of wave dissipation processes in mixed swell–wind-sea conditions.

Description: Seven sets of 2D particle image velocimetry data obtained in the bottom boundary layer of the coastal ocean along the South Carolina and Georgia coast [at the South Atlantic Bight Synoptic Offshore Observational Network (SABSOON) site] are examined, covering the accelerating and decelerating phases of a single tidal cycle at several heights above the seabed. Additional datasets from a previous deployment are also included in the analysis. The mean velocity profiles are logarithmic, and the vertical distribution of Reynolds stresses normalized by the square of the free stream velocity collapse well for data obtained at the same elevation but at different phases of the tidal cycle. The magnitudes of 〈u′u′〉, 〈w′w′〉, and −〈u′w′〉 decrease with height above bottom in the 25–160-cm elevation range and are consistent with the magnitudes and trends observed in laboratory turbulent boundary layers. If a constant stress layer exists, it is located below 25-cm elevation. Two methods for estimating dissipation rate are compared. The first, a direct estimate, is based on the measured in-plane instantaneous velocity gradients. The second method is based on fitting the resolved part of the dissipation spectrum to the universal dissipation spectrum available in Gargett et al. Being undervalued, the direct estimates are a factor of 2–2.5 smaller than the spectrum-based estimates. Taylor microscale Reynolds numbers for the present analysis range from 24 to 665. Anisotropy is present at all resolved scales. At the transition between inertial and dissipation range the longitudinal spectra exhibit a flatter than −5/3 slope and form spectral bumps. Second-order statistics of the velocity gradients show a tendency toward isotropy with increasing Reynolds number. Dissipation exceeds production at all measurement heights, but the difference varies with elevation. Close to the bottom, the production is 40%–70% of the dissipation, but it decreases to 10%–30% for elevations greater than 80 cm.

Description: Scalar exchange between San Francisco Bay and the coastal ocean is examined using shipboard observations made across the Golden Gate Channel. The study consists of experiments during each of the following three “seasons”: winter/spring runoff (March 2002), summer upwelling (July 2003), and autumn relaxation (October 2002). Within each experiment, transects across the channel were repeated approximately every 12 min for 25 h during both spring and neap tides. Velocity was measured from a boat-mounted ADCP. Scalar concentrations were measured at the surface and from a tow-yoed SeaSciences Acrobat. Net salinity exchange rates for each season are quantified with harmonic analysis. Accuracy of the net fluxes is confirmed by comparison with independently measured values. Harmonic results are then decomposed into flux mechanisms using temporal and spatial correlations. In this study, the temporal correlation of cross-sectionally averaged salinity and velocity (tidal pumping flux) is the largest part of the dispersive flux of salinity into the bay. From the tidal pumping flux portion of the dispersive flux, it is shown that there is less exchange than was found in earlier studies. Furthermore, tidal pumping flux scales strongly with freshwater flow resulting from the density-driven movement of a tidally trapped eddy and stratification-induced increases in ebb–flood frictional phasing. Complex bathymetry makes salinity exchange scale differently with flow than would be expected from simple tidal asymmetry and gravitational circulation models.

Description: As part of a program aimed at developing a long-duration, subsurface mooring, known as Ultramoor, several modern acoustic current meters were tested. The instruments with which the authors have the most experience are the Aanderaa RCM11 and the Nortek Aquadopp, which measure currents using the Doppler shift of backscattered acoustic signals, and the Falmouth Scientific ACM, which measures changes in travel time of acoustic signals between pairs of transducers. Some results from the Doppler-based Sontek Argonaut and the travel-time-based Nobska MAVS are also reported. This paper concentrates on the fidelity of the speed measurement but also presents some results related to the accuracy of the direction measurement. Two procedures were used to compare the instruments. In one, different instruments were placed close to one another on three different deep-ocean moorings. These tests showed that the RCM11 measures consistently lower speeds than either a vector averaging current meter or a vector measuring current meter, both more traditional instruments with mechanical velocity sensors. The Aquadopp in use at the time, but since updated to address accuracy problems in low scattering environments, was biased high. A second means of testing involved comparing the appropriate velocity component of each instrument with the rate of change of pressure when they were lowered from a ship. Results from this procedure revealed no depth dependence or measurable bias in the RCM11 data, but did show biases in both the Aquadopp and Argonaut Doppler-based instruments that resulted from low signal-to-noise ratios in the clear, low scattering conditions beneath the thermocline. Improvements in the design of the latest Aquadopp have reduced this bias to a level that is not significant.

Description: The energy pathways in geostrophic turbulence are explored using a two-layer, flat-bottom, f-plane, quasigeostrophic model forced by an imposed, horizontally homogenous, baroclinically unstable mean flow and damped by bottom Ekman friction. A systematic presentation of the spectral energy fluxes, the mean flow forcing, and dissipation terms allows for a comprehensive understanding of the sources and sinks for baroclinic and barotropic energy as a function of length scale. The key new result is a robust inverse cascade of kinetic energy for both the baroclinic mode and the upper layer. This is consistent with recent observations of satellite altimeter data over the South Pacific Ocean. The well-known forward cascade of baroclinic potential and total energy was found to be very robust. Decomposing the spectral fluxes into contributions from different terms provided further insight. The inverse baroclinic kinetic energy cascade is driven mostly by an efficient interaction between the baroclinic velocity and the barotropic vorticity, the latter playing a crucial catalytic role. This cascade can be further enhanced by the baroclinic mode self-interaction, which is only present with nonuniform stratification (unequal layer depths). When model parameters are set such that modeled eddies compare favorably with observations, the inverse baroclinic kinetic energy cascade is actually much stronger than the well-known inverse cascade in the barotropic mode. The upper-layer kinetic energy cascade was found to dominate the lower-layer cascade over a wide range of parameters, suggesting that the surface cascade and time mean density stratification may be sufficient for estimating the depth-integrated cascade from ocean observations. This may find useful application in inferring the kinetic to gravitational potential energy conversion rate from satellite measurements.

Description: A high-resolution global atmospheric model, the nonhydrostatic icosahedral atmospheric model (NICAM), exhibited underestimation biases in low-level mixed-phase clouds in the midlatitudes and polar regions. The ice-cloud microphysics used in a single-moment bulk cloud microphysics scheme (NSW6) was evaluated and improved using a single-column model by reference to a double-moment bulk cloud microphysics scheme (NDW6). Budget analysis indicated that excessive action of the Bergeron–Findeisen and riming processes crucially reduced supercooled liquid water. In addition, the rapid production of rain directly reduced cloud water and indirectly reduced cloud water through the production of snow and graupel by riming. These biases in growth rates were found to originate from the number concentration diagnosis used in NSW6. The diagnosis based on the midlatitude cloud systems assumption was completely different from the one for low-level mixed-phase clouds. To alleviate underestimation biases, rain production, heterogeneous ice nucleation, vapor deposition by snow and graupel, and riming processes were revised. The sequential revisions of cloud microphysics alleviated the underestimation biases step by step without parameter tuning. The lifetime of cloud layers simulated by NSW6 was reasonably prolonged.

Description: Warm-season rainfall associated with mesoscale convective systems (MCSs) in the central United States is characterized by higher intensity and nocturnal timing compared to rainfall from non-MCS systems, suggesting their potentially different footprints on the land surface. To differentiate the impacts of MCS and non-MCS rainfall on the surface water balance, a water tracer tool embedded in the Noah land surface model with multiparameterization options (WT-Noah-MP) is used to numerically “tag” water from MCS and non-MCS rainfall separately during April–August (1997–2018) and track their transit in the terrestrial system. From the water-tagging results, over 50% of warm-season rainfall leaves the surface–subsurface system through evapotranspiration by the end of August, but non-MCS rainfall contributes a larger fraction. However, MCS rainfall plays a more important role in generating surface runoff. These differences are mostly attributed to the rainfall intensity differences. The higher-intensity MCS rainfall tends to produce more surface runoff through infiltration excess flow and drives a deeper penetration of the rainwater into the soil. Over 70% of the top 10th percentile runoff is contributed by MCS rainfall, demonstrating its important contribution to local flooding. In contrast, lower-intensity non-MCS rainfall resides mostly in the top layer and contributes more to evapotranspiration through soil evaporation. Diurnal timing of rainfall has negligible effects on the flux partitioning for both MCS and non-MCS rainfall. Differences in soil moisture profiles for MCS and non-MCS rainfall and the resultant evapotranspiration suggest differences in their roles in soil moisture–precipitation feedbacks and ecohydrology.

Description: Capsule summary. Helicopter-borne observations with unprecedented high resolution provide new insights in the fine-scale structure of marine boundary layer clouds and aerosol stratification over the Eastern North Atlantic.

Description: Tropical cyclones (TCs) rank among the most costly natural disasters in the United States, and accurate forecasts of track and intensity are critical for emergency response. Intensity guidance has improved steadily but slowly, as processes which drive intensity change are not fully understood. Because most TCs develop far from land-based observing networks, geostationary satellite imagery is critical to monitor these storms. However, these complex data can be challenging to analyze in real time, and off-the-shelf machine learning algorithms have limited applicability on this front due to their “black box” structure. This study presents analytic tools that quantify convective structure patterns in infrared satellite imagery for over-ocean TCs, yielding lower-dimensional but rich representations that support analysis and visualization of how these patterns evolve during rapid intensity change. The proposed ORB feature suite targets the global Organization, Radial structure, and Bulk morphology of TCs. By combining ORB and empirical orthogonal functions, we arrive at an interpretable and rich representation of convective structure patterns that serve as inputs to machine learning methods. This study uses the logistic lasso, a penalized generalized linear model, to relate predictors to rapid intensity change. Using ORB alone, binary classifiers identifying the presence (versus absence) of such intensity change events can achieve accuracy comparable to classifiers using environmental predictors alone, with a combined predictor set improving classification accuracy in some settings. More complex nonlinear machine learning methods did not perform better than the linear logistic lasso model for current data.

Description: Using 4-yr mooring observations and ocean circulation model experiments, this study characterizes the spatial and temporal variability of the Equatorial Intermediate Current (EIC; 200–1200 m) in the Indian Ocean and investigates the causes. The EIC is dominated by seasonal and intraseasonal variability, with interannual variability being weak. The seasonal component dominates the midbasin with a predominant semiannual period of ~166 days but weakens toward east and west where the EIC generally exhibits large intraseasonal variations. The resonant second and fourth baroclinic modes at the semiannual period make the largest contribution to the EIC, determining the overall EIC structures. The higher baroclinic modes, however, modify the EIC’s vertical structures, forming multiple cores during some time periods. The EIC intensity has an abrupt change near 73°E, which is strong to the east and weak to the west. Model simulation suggests that the abrupt change is caused primarily by the Maldives, which block the propagation of equatorial waves. The Maldives impede the equatorial Rossby waves, reducing the EIC’s standard deviation associated with reflected Rossby waves by ~48% and directly forced waves by 20%. Mode decomposition further demonstrates that the semiannual resonance amplitude of the second baroclinic mode reduces by 39% because of the Maldives. However, resonance amplitude of the four baroclinic mode is less affected, because the Maldives fall in the node region of mode 4’s resonance. The research reveals the spatiotemporal variability of the poorly understood EIC, contributing to our understanding of equatorial wave–current dynamics.

Description: The Early Twentieth Century Warming (ETCW) defined as the period 1921–50 saw a clear increase in actinometrical observations in the Arctic. Nevertheless, information on radiation balance and its components at that time is still very limited in availability, and therefore large discrepancies exist among estimates of total solar irradiance forcing. To eliminate these uncertainties, all available solar radiation data for the Arctic needs to be collected and processed. Better knowledge about incoming solar radiation (direct, diffuse and global) should allow for more reliable estimation of the magnitude of total solar irradiance forcing, which can help in turn, to more precisely and correctly explain the reasons for the ETCW in the Arctic. The paper summarises our research into the availability of solar radiation data for the Arctic. An important part of this work is its detailed inventory of data series (including metadata) for the period before the mid-20th century. Based on the most reliable data series, general solar conditions in the Arctic during the ETCW are described. The character of solar radiation changes between the ETCW and present times, in particular after 2000, is also analyzed. Average annual global solar radiation in the Russian Arctic during the ETCW were slightly greater than in the period 1964–90 (by about 1–2 W·m˗2), and markedly greater than in the period 2001–19 (by about 16 W·m˗2). Our results also reveal that in the period 1920–2019 three phases of solar radiation changes can be distinguished: a brightening phase (1921–50), a stabilisation phase (1951–93) and a dimming phase (after 2000).

Description: Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifth-generation reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979–2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments.

Description: Data assimilation combines forecasts from a numerical model with observations. Most of the current data assimilation algorithms consider the model and observation error terms as additive Gaussian noise, specified by their covariance matrices Q and R, respectively. These error covariances, and specifically their respective amplitudes, determine the weights given to the background (i.e., the model forecasts) and to the observations in the solution of data assimilation algorithms (i.e., the analysis). Consequently, Q and R matrices significantly impact the accuracy of the analysis. This review aims to present and to discuss, with a unified framework, different methods to jointly estimate the Q and R matrices using ensemble-based data assimilation techniques. Most of the methods developed to date use the innovations, defined as differences between the observations and the projection of the forecasts onto the observation space. These methods are based on two main statistical criteria: 1) the method of moments, in which the theoretical and empirical moments of the innovations are assumed to be equal, and 2) methods that use the likelihood of the observations, themselves contained in the innovations. The reviewed methods assume that innovations are Gaussian random variables, although extension to other distributions is possible for likelihood-based methods. The methods also show some differences in terms of levels of complexity and applicability to high-dimensional systems. The conclusion of the review discusses the key challenges to further develop estimation methods for Q and R. These challenges include taking into account time-varying error covariances, using limited observational coverage, estimating additional deterministic error terms, or accounting for correlated noise.

Description: A large midlatitude cyclone occurred over the central United States from 0000 to 1800 UTC 30 April 2017. During this period, there were more than 1100 reports of moderate-or-greater turbulence at commercial aviation cruising altitudes east of the Rocky Mountains. Much of this turbulence was located above or, otherwise, outside the synoptic-scale cloud shield of the cyclone, thus complicating its avoidance. In this study we use two-way nesting in a numerical model with finest horizontal spacing of 370 m to investigate possible mechanisms producing turbulence in two distinct regions of the cyclone. In both regions, model-parameterized turbulence kinetic energy compares well to observed turbulence reports. Despite being outside of hazardous large radar reflectivity locations in deep convection, both regions experienced strong modification of the turbulence environment as a result of upper-tropospheric/lower-stratospheric (UTLS) convective outflow. For one region, where turbulence was isolated and short lived, simulations revealed breaking of ~100-km horizontal-wavelength lower-stratospheric gravity waves in the exit region of a UTLS jet streak as the most likely mechanism for the observed turbulence. Although similar waves occurred in a simulation without convection, the altitude at which wave breaking occurred in the control simulation was strongly affected by UTLS outflow from distant deep convection. In the other analyzed region, turbulence was more persistent and widespread. There, overturning waves of much shorter 5–10-km horizontal wavelengths occurred within layers of gradient Richardson number 〈 0.25, which promoted Kelvin–Helmholtz instability associated with strong vertical shear in different horizontal locations both above and beneath the convectively enhanced UTLS jet.

Description: In this study, we investigate the technical application of the regularized regression method Lasso for identifying systematic biases in decadal precipitation predictions from a high-resolution regional climate model (CCLM) for Europe. The Lasso approach is quite novel in climatological research. We apply Lasso to observed precipitation and a large number of predictors related to precipitation derived from a training simulation, and transfer the trained Lasso regression model to a virtual forecast simulation for testing. Derived predictors from the model include local predictors at a given grid box and EOF predictors that describe large-scale patterns of variability for the same simulated variables. A major added value of the Lasso function is the variation of the so-called shrinkage factor and its ability in eliminating irrelevant predictors and avoiding overfitting. Among 18 different settings, an optimal shrinkage factor is identified that indicates a robust relationship between predictand and predictors. It turned out that large-scale patterns as represented by the EOF predictors outperform local predictors. The bias adjustment using the Lasso approach mainly improves the seasonal cycle of the precipitation prediction and, hence, improves the phase relationship and reduces the root-mean-square error between model prediction and observations. Another goal of the study pertains to the comparison of the Lasso performance with classical model output statistics and with a bivariate bias correction approach. In fact, Lasso is characterized by a similar and regionally higher skill than classical approaches of model bias correction. In addition, it is computationally less expensive. Therefore, we see a large potential for the application of the Lasso algorithm in a wider range of climatological applications when it comes to regression-based statistical transfer functions in statistical downscaling and model bias adjustment.

Description: Using a Lagrangian trajectory model, contributions of moisture from the Indian Ocean (IO), the South China Sea (SCS), the adjacent land region (LD), and the Pacific Ocean (PO) to interannual summer precipitation variations in southwestern China (SWC) are investigated. Results show that, on average, the IO, SCS, LD, and PO contribute 48.8%, 21.1%, 23.6%, and 3.7% of the total moisture release in SWC, respectively. In summers with the above-normal precipitation, moisture release from the IO and SCS increases significantly by 41.4% and 15.1%, respectively. In summers with below-normal precipitation, moisture release from the IO and SCS decreases significantly by 44.2% and 24.6%, respectively. In addition, the moisture anomalies from the four source regions together explain 86.5% of the total interannual variances of SWC summer precipitation, and the IO and SCS only can explain 75.7%. Variations in moisture transport from the IO, SCS, and LD to SWC are not independent of one another and are commonly influenced by the anomalous anticyclone in the western North Pacific Ocean, which enhances the moisture transport from the IO and SCS by the anomalous southwesterlies over its northwestern quadrant but reduces that from the LD east of SWC by the anomalous westerlies along its northern edge. Anomalous warming in the tropical Atlantic Ocean can modify the Walker circulation, induce anomalous descending motion over the central tropical Pacific, and excite the anomalous anticyclone in the western North Pacific as the classic Matsuno–Gill response. The observed impacts of the tropical Atlantic warming on the anomalous anticyclone and summer precipitation in SWC can be well reproduced in an atmospheric general circulation model.

Description: The NOAA Warn-on-Forecast System (WoFS) is an experimental rapidly updating convection-allowing ensemble designed to provide probabilistic operational guidance on high-impact thunderstorm hazards. The current WoFS uses physics diversity to help maintain ensemble spread. We assess the systematic impacts of the three WoFS PBL schemes—YSU, MYJ, and MYNN—using novel, object-based methods tailored to thunderstorms. Very short forecast lead times of 0–3 h are examined, which limits phase errors and thereby facilitates comparisons of observed and model storms that occurred in the same area at the same time. This evaluation framework facilitates assessment of systematic PBL scheme impacts on storms and storm environments. Forecasts using all three PBL schemes exhibit overly narrow ranges of surface temperature, dewpoint, and wind speed. The surface biases do not generally decrease at later forecast initialization times, indicating that systematic PBL scheme errors are not well mitigated by data assimilation. The YSU scheme exhibits the least bias of the three in surface temperature and moisture and in many sounding-derived convective variables. Interscheme environmental differences are similar both near and far from storms and qualitatively resemble the differences analyzed in previous studies. The YSU environments exhibit stronger mixing, as expected of nonlocal PBL schemes; are slightly less favorable for storm intensification; and produce correspondingly weaker storms than the MYJ and MYNN environments. On the other hand, systematic interscheme differences in storm morphology and storm location forecast skill are negligible. Overall, the results suggest that calibrating forecasts to correct for systematic differences between PBL schemes may modestly improve WoFS and other convection-allowing ensemble guidance at short lead times.