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Peter N. Blossey, Christopher S. Bretherton, and Johannes Mohrmann

Abstract

The goal of this study is to challenge a large-eddy simulation model with a range of observations from a modern field campaign and to develop case studies useful to other modelers. The 2015 Cloud System Evolution in the Trades (CSET) field campaign provided a wealth of in situ and remote sensing observations of subtropical cloud transitions in the summertime northeast Pacific. Two Lagrangian case studies based on these observations are used to validate the thermodynamic, radiative, and microphysical properties of large-eddy simulations (LES) of the stratocumulus to cumulus transition. The two cases contrast a relatively fast cloud transition in a clean, initially well-mixed boundary layer versus a slower transition in an initially decoupled boundary layer with higher aerosol concentrations and stronger mean subsidence. For each case, simulations of two neighboring trajectories sample mesoscale variability and the coherence of the transition in adjacent air masses. In both cases, LES broadly reproduce satellite and aircraft observations of the transition. Simulations of the first case match observations more closely than for the second case, where simulations underestimate cloud cover early in the simulations and overestimate cloud top height later. For the first case, simulated cloud fraction and liquid water path increase if a larger cloud droplet number concentration is prescribed. In the second case, precipitation onset and inversion cloud breakup occur earlier when the LES domain is chosen to be large enough to support strong mesoscale organization.

Open access
Mampi Sarkar, Paquita Zuidema, Bruce Albrecht, Virendra Ghate, Jorgen Jensen, Johannes Mohrmann, and Robert Wood

Abstract

Three genuine stratocumulus-to-cumulus transitions sampled during the Cloud System Evolution over the Trades (CSET) campaign are documented. The focus is on Lagrangian evolution of in situ precipitation, thought to exceed radar/lidar retrieved values because of Mie scattering. Two of the three initial stratocumulus cases are pristine [cloud droplet number concentrations (N d) of ~22 cm−3] but occupied boundary layers of different depths, while the third is polluted (N d ~ 225 cm−3). Hourly satellite-derived cloud fraction along Lagrangian trajectories indicate that more quickly deepening boundary layers tend to transition faster, into more intense but more occasional precipitation. These transitions begin either in the morning or late afternoon, suggesting that preceding night processes can precondition or delay the inevitable transition. The precipitation shifts toward larger drop sizes throughout the transition as the boundary layers deepen, with aerosol concentrations only diminishing in two of the three cases. Ultraclean (N d < 1 cm−3) cumulus clouds evolved from pristine stratocumulus cloud with unusually high precipitation rates occupying a shallow, well-mixed boundary layer. Results from a simple one-dimensional evaporation model and from radar/lidar retrievals suggest subcloud evaporation likely increases throughout the transition. This, coupled with larger drop sizes capable of lowering the latent cooling profile, facilitates the transition to more surface-driven convection. The coassociation between boundary layer depth and precipitation does not provide definitive conclusions on the isolated effect of precipitation on the pace of the transition. Differences between the initial conditions of the three examples provide opportunities for further modeling studies.

Free access
Johannes Mohrmann, Christopher S. Bretherton, Isabel L. McCoy, Jeremy McGibbon, Robert Wood, Virendra Ghate, Bruce Albrecht, Mampi Sarkar, Paquita Zuidema, and Rabindra Palikonda

Abstract

Flight data from the Cloud System Evolution over the Trades (CSET) campaign over the Pacific stratocumulus-to-cumulus transition are organized into 18 Lagrangian cases suitable for study and future modeling, made possible by the use of a track-and-resample flight strategy. Analysis of these cases shows that 2-day Lagrangian coherence of long-lived species (CO and O3) is high (r = 0.93 and 0.73, respectively), but that of subcloud aerosol, MBL depth, and cloud properties is limited. Although they span a wide range in meteorological conditions, most sampled air masses show a clear transition when considering 2-day changes in cloudiness (−31% averaged over all cases), MBL depth (+560 m), estimated inversion strength (EIS; −2.2 K), and decoupling, agreeing with previous satellite studies and theory. Changes in precipitation and droplet number were less consistent. The aircraft-based analysis is augmented by geostationary satellite retrievals and reanalysis data along Lagrangian trajectories between aircraft sampling times, documenting the evolution of cloud fraction, cloud droplet number concentration, EIS, and MBL depth. An expanded trajectory set spanning the summer of 2015 is used to show that the CSET-sampled air masses were representative of the season, with respect to EIS and cloud fraction. Two Lagrangian case studies attractive for future modeling are presented with aircraft and satellite data. The first features a clear Sc–Cu transition involving MBL deepening and decoupling with decreasing cloud fraction, and the second undergoes a much slower cloud evolution despite a greater initial depth and decoupling state. Potential causes for the differences in evolution are explored, including free-tropospheric humidity, subsidence, surface fluxes, and microphysics.

Free access
Patrik Benáček and Máté Mile

Abstract

The bias correction of satellite radiances is an essential component of data assimilation system in numerical weather prediction (NWP). The variational bias correction (VarBC) scheme is widely used by global NWP centers, but there are still open questions regarding its use in limited-area models (LAMs). We present a study of key VarBC aspects in the limited-area 3D-Var system using the state-of-the-art NWP system ALADIN. Two basic VarBC applications are tested, specifically adopting bias coefficients from the global model ARPEGE and cycling bias coefficients independently in the LAM ALADIN (VarBC-LAM). The latter application is studied using daily update of bias coefficients with regards to static and dynamic settings of the VarBC stiffness. Extensive testing shows that the VarBC-LAM methods outperform the use of global coefficients from ARPEGE providing the better quality of the model first guess (3-h forecast), in the assimilation cycle with the largest normalized impact of 2%–3% for temperature and wind components in the midtroposphere. Compared to the global coefficients, there was little forecast impact between 24 and 48 h from using the VarBC-LAM coefficients. The various VarBC-LAM methods were comparable, but the CAM method may be most useful when an unexpected bias shows up.

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Christopher S. Bretherton, Isabel L. McCoy, Johannes Mohrmann, Robert Wood, Virendra Ghate, Andrew Gettelman, Charles G. Bardeen, Bruce A. Albrecht, and Paquita Zuidema

Abstract

During the Cloud System Evolution in the Trades (CSET) field study, 14 research flights of the National Science Foundation G-V sampled the stratocumulus–cumulus transition between Northern California and Hawaii and its synoptic variability. The G-V made vertically resolved measurements of turbulence, cloud microphysics, aerosol characteristics, and trace gases. It also carried dropsondes and a vertically pointing W-band radar and lidar. This paper summarizes these observations with the goals of fostering novel comparisons with theory, models and reanalyses, and satellite-derived products. A longitude–height binning and compositing strategy mitigates limitations of sparse sampling and spatiotemporal variability. Typically, a 1-km-deep decoupled stratocumulus-capped boundary layer near California evolved into 2-km-deep precipitating cumulus clusters surrounded by patches of thin stratus that dissipated toward Hawaii. Low cloud cover was correlated with estimated inversion strength more than with cloud droplet number, even though the thickest clouds were generally precipitating and ultraclean layers indicative of aerosol–cloud–precipitation interaction were common west of 140°W. Accumulation-mode aerosol concentration correlated well with collocated cloud droplet number concentration and was typically largest near the surface. Aitken mode aerosol concentration was typically larger in the free troposphere. Wildfire smoke produced spikes of aerosol and trace gases on some flights. CSET data are compared with space–time collocated output from MERRA-2 reanalysis and from the CAM6 climate model run with winds and temperature nudged toward this reanalysis. The reanalysis compares better with the observed relative humidity than does nudged CAM6. Both vertically diffuse the stratocumulus cloud layer versus observations. MERRA-2 slightly underestimates in situ carbon monoxide measurements and underestimates ozone depletion within the boundary layer.

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Jenny V. Turton, Thomas Mölg, and Dirk Van As

Abstract

The Nioghalvfjerdsfjorden glacier (the 79 fjord, henceforth referred to as 79N) has been thinning and accelerating since the early 2000s, as a result of calving episodes at the front of the glacier. As 8% of the Greenland Ice Sheet area drains into 79N, changes in the stability of 79N could propagate into the interior of Greenland. Despite this concern, relatively little is known about the atmospheric conditions over 79N. We present the surface atmospheric processes and climatology of the 79N region from analyses of data from four automatic weather stations (AWS) and reanalysis data from ERA-Interim. Over the floating section of the glacier, the annual average air temperature is −16.7°C, decreasing to −28.5°C during winter. Winds over the glacier are predominantly westerly and are of katabatic origin. Over the last 39 years the near-surface air temperature has increased at a rate of +0.08°C yr−1. In addition, we find that large, rapid (48 h) temperature increases (>10°C) occur during the five-month dark period (November–March). Eight (±4) warm-air events occur annually from 1979 to 2017. We use the Weather Research and Forecasting (WRF) Model to simulate a particular warm-air event with above-freezing air temperatures between 30 November and 2 December 2014. The warm event was caused by warm-air advection from the southeast and a subsequent increase in the longwave radiation toward the surface due to low-level cloud formation. The frequent nature of the temperature jumps and the magnitude of the temperature increases are likely to have an impact on the surface mass balance of the glacier by bringing the skin temperatures to the melting point.

Open access
Vasubandhu Misra and Amit Bhardwaj

Abstract

This study introduces an objective definition for onset and demise of the northeast Indian monsoon (NEM). The definition is based on the land surface temperature analysis over the Indian subcontinent. It is diagnosed from the inflection points in the daily anomaly cumulative curve of the area-averaged surface temperature over the provinces of Andhra Pradesh, Rayalseema, and Tamil Nadu located in the southeastern part of India. Per this definition, the climatological onset and demise dates of the NEM season are 6 November and 13 March, respectively. The composite evolution of the seasonal cycle of 850-hPa winds, surface wind stress, surface ocean currents, and upper-ocean heat content suggest a seasonal shift around the time of the diagnosed onset and demise dates of the NEM season. The interannual variations indicate onset date variations have a larger impact than demise date variations on the seasonal length, seasonal anomalies of rainfall, and surface temperature of the NEM. Furthermore, it is shown that warm El Niño–Southern Oscillation (ENSO) episodes are associated with excess seasonal rainfall, warm seasonal land surface temperature anomalies, and reduced lengths of the NEM season. Likewise, cold ENSO episodes are likely to be related to seasonal deficit rainfall anomalies, cold land surface temperature anomalies, and increased lengths of the NEM season.

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Johna E. Rudzin, Lynn K. Shay, and Benjamin Jaimes de la Cruz

Abstract

The influence of the Amazon–Orinoco River plume in the Caribbean Sea on latent and sensible heat flux (enthalpy flux) and tropical cyclone (TC) intensity is investigated for Hurricanes Ivan (2004), Emily (2005), Dean (2007), and Felix (2007) using dropwindsonde data, satellite sea surface temperature (SST), and the SMARTS climatology. Relationships among enthalpy fluxes, ocean heat content relative to the 26°C isotherm depth (OHC), and SST during storm passage are diagnosed. Results indicate that sea surface cooling in the river plume, a low-OHC region, is comparable to that in the warm eddy region, which has high OHC. An isothermal layer heat budget shows that upper-ocean cooling in the river plume can be explained predominantly by sea-to-air heat flux, rather than by entrainment flux from the thermocline. The latter two findings suggest that relatively large upper-ocean stratification in the plume regime limited entrainment cooling, sustaining SST and enthalpy flux. Inspection of atmospheric variables indicates that deep moderate wind shear is prevalent, and equivalent potential temperature is enhanced over the river plume region for most of these storms. Thus, sustained surface fluxes in this region may have provided warm, moist boundary layer conditions, which may have helped these storms to rapidly intensify even over relatively low-OHC waters and moderate shear. These findings are important because several Caribbean Sea TCs, including these cases, have been underforecast with respect to intensity and/or rapid intensifications, yet minimal upper-ocean observations exist to understand air–sea interaction during TCs in the salinity-stratified Amazon–Orinoco plume regime.

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Bradley W. Klotz and David S. Nolan

Abstract

Surface wind speeds in tropical cyclones are important for defining current intensity and intensification. Traditionally, airborne observations provide the best information about the surface wind speeds, with the Stepped Frequency Microwave Radiometer (SFMR) providing a key role in obtaining such data. However, the flight patterns conducted by hurricane hunter aircraft are limited in their azimuthal coverage of the surface wind field, resulting in an undersampling of the wind field and consequent underestimation of the peak 10-m wind speed. A previous study provided quantitative estimates of the average underestimate for a very strong hurricane. However, no broader guidance on applying a correction based on undersampling has been presented in detail. To accomplish this task, a modified observing system simulation experiment with five hurricane simulations is used to perform a statistical evaluation of the peak wind speed underestimate over different stages of the tropical cyclone life cycle. Analysis of numerous simulated flights highlights prominent relationships between wind speed undersampling and storm size, where size is defined by the radius of maximum wind speed (RMW). For example, an intense hurricane with small RMW needs negligible correction, while a large-RMW tropical storm requires a 16%–19% change. A lookup table of undersampling correction factors as a function of peak SFMR wind speed and RMW is provided to assist the tropical cyclone operations community. Implications for hurricane best track intensity estimates are also discussed using real data from past Atlantic hurricane seasons.

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