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P. Bechtold, S. K. Krueger, W. S. Lewellen, E. van Meijgaard, C.-H. Moeng, D. A. Randall, A. van Ulden, and S. Wang

Several one-dimensional (ID) cloud/turbulence ensemble modeling results of an idealized nighttime marine stratocumulus case are compared to large eddy simulation (LES). This type of model intercomparison was one of the objects of the first Global Energy and Water Cycle Experiment Cloud System Study boundary layer modeling workshop held at the National Center for Atmospheric Research on 16–18 August 1994.

Presented are results obtained with different 1D models, ranging from bulk models (including only one or two vertical layers) to various types (first order to third order) of multilayer turbulence closure models. The ID results fall within the scatter of the LES results. It is shown that ID models can reasonably represent the main features (cloud water content, cloud fraction, and some turbulence statistics) of a well-mixed stratocumulus-topped boundary layer.

Also addressed is the question of what model complexity is necessary and can be afforded for a reasonable representation of stratocumulus clouds in mesoscale or global-scale operational models. Bulk models seem to be more appropriate for climate studies, whereas a multilayer turbulence scheme is best suited in mesoscale models having at least 100- to 200-m vertical resolution inside the boundary layer.

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X. M. Chen, S.-H. Chen, J. S. Haase, B. J. Murphy, K.-N. Wang, J. L. Garrison, S. Y. Chen, C. Y. Huang, L. Adhikari, and F. Xie

Abstract

This study evaluates, for the first time, the impact of airborne global positioning system radio occultation (ARO) observations on a hurricane forecast. A case study was conducted of Hurricane Karl during the Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) field campaign in 2010. The assimilation of ARO data was developed for the three-dimensional variational (3DVAR) analysis system of the Weather Research and Forecasting (WRF) Model version 3.2. The impact of ARO data on Karl forecasts was evaluated through data assimilation (DA) experiments of local refractivity and nonlocal excess phase (EPH), in which the latter accounts for the integrated horizontal sampling along the signal ray path. The tangent point positions (closest point of an RO ray path to Earth’s surface) drift horizontally, and the drifting distance of ARO data is about 2 to 3 times that of spaceborne RO, which was taken into account in these simulations.

Results indicate that in the absence of other satellite observations, the assimilation of ARO EPH resulted in a larger impact on the analysis than local refractivity did. In particular, the assimilation of ARO observations at the actual tangent point locations resulted in more accurate forecasts of the rapid intensification of the storm. Among all experiments, the best forecast was obtained by assimilating ARO data with the most accurate geometric representation, that is, the use of nonlocal EPH operators with tangent point drift, which reduced the error in the storm’s predicted minimum sea level pressure (SLP) by 43% beyond that of the control experiment.

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Jih-Wang A. Wang, Prashant D. Sardeshmukh, Gilbert P. Compo, Jeffrey S. Whitaker, Laura C. Slivinski, Chesley M. McColl, and Philip J. Pegion

Abstract

An important issue in developing a forecast system is its sensitivity to additional observations for improving initial conditions, to the data assimilation (DA) method used, and to improvements in the forecast model. These sensitivities are investigated here for the Global Forecast System (GFS) of the National Centers for Environmental Prediction (NCEP). Four parallel sets of 7-day ensemble forecasts were generated for 100 forecast cases in mid-January to mid-March 2016. The sets differed in their 1) inclusion or exclusion of additional observations collected over the eastern Pacific during the El Niño Rapid Response (ENRR) field campaign, 2) use of a hybrid 4D–EnVar versus a pure EnKF DA method to prepare the initial conditions, and 3) inclusion or exclusion of stochastic parameterizations in the forecast model. The Control forecast set used the ENRR observations, hybrid DA, and stochastic parameterizations. Errors of the ensemble-mean forecasts in this Control set were compared with those in the other sets, with emphasis on the upper-tropospheric geopotential heights and vorticity, midtropospheric vertical velocity, column-integrated precipitable water, near-surface air temperature, and surface precipitation. In general, the forecast errors were found to be only slightly sensitive to the additional ENRR observations, more sensitive to the DA methods, and most sensitive to the inclusion of stochastic parameterizations in the model, which reduced errors globally in all the variables considered except geopotential heights in the tropical upper troposphere. The reduction in precipitation errors, determined with respect to two independent observational datasets, was particularly striking.

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C. A. Luecke, H. W. Wijesekera, E. Jarosz, D. W. Wang, J. C. Wesson, S. U. P. Jinadasa, H. J. S. Fernando, and W. J. Teague

Abstract

Long-term measurements of turbulent kinetic energy dissipation rate (ε), and turbulent temperature variance dissipation rate (χ T) in the thermocline, along with currents, temperature, and salinity were made at two subsurface moorings in the southern Bay of Bengal (BoB). This is a part of a major international program, conducted between July 2018 and June 2019, for investigating the role of the BoB on the monsoon intraseasonal oscillations. One mooring was located on the typical path of the Southwest Monsoon Current (SMC), and the other was in a region where the Sri Lanka dome is typically found during the summer monsoon. Microstructure and finescale estimates of vertical diffusivity revealed the long-term subthermocline mixing patterns in the southern BoB. Enhanced turbulence and large eddy diffusivities were observed within the SMC during the passage of a subsurface-intensified anticyclonic eddy. During this time, background shear and strain appeared to influence high-frequency motions such as near-inertial waves and internal tides, leading to increased mixing. Near the Sri Lanka dome, enhanced dissipation occurred at the margins of the cyclonic feature. Turbulent mixing was enhanced with the passage of Rossby waves and eddies. During these events, values of χ T exceeding 10−4 °C2 s−1 were recorded concurrently with ε values exceeding 10−5 W kg−1. Inferred diffusivity peaked well above background values of 10−6 m2 s−1, leading to an annually averaged diffusivity near 10−4 m2 s−1. Turbulence appeared low throughout much of the deployment period. Most of the mixing occurred in spurts during isolated events.

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H. W. Wijesekera, W. J. Teague, D. W. Wang, E. Jarosz, T. G. Jensen, S. U. P. Jinadasa, H. J. S. Fernando, and Z. R. Hallock

Abstract

High-resolution currents and hydrographic fields were measured at six deep-water moorings in the southern Bay of Bengal (BoB) by the Naval Research Laboratory as part of an international effort focused on the dynamics of the Indian Ocean. Currents, temperature, and salinity were sampled over the upper 500 m for 20 months between December 2013 and August 2015. One of the major goals is to understand the space–time scales of the currents and physical processes that contribute to the exchange of water between the BoB and the Arabian Sea. The observations captured Southwest and Northeast Monsoon Currents, seasonally varying large eddies including a cyclonic eddy, the Sri Lanka dome (SLD), and an anticyclonic eddy southeast of the SLD. The observations further showed intraseasonal oscillations with periods of 30–70 days, near-inertial currents, and tides. Monthly averaged velocities commonly exceeded 50 cm s−1 near the surface, and extreme velocities exceeded 150 cm s−1 during the southwest monsoon. Tides were small and dominated by the M2 component with velocities of about 3 cm s−1. The average transport into the BoB over the measurement period was 2 Sv (1 Sv ≡ 106 m3 s−1) but likely exceeded 15 Sv during summer of 2014. This study suggests the water exchange away from coastal boundaries, in the interior of the BoB, may be largely influenced by the location and strength of the two eddies that modify the path of the Southwest Monsoon Current. In addition, there is a pathway below 200 m for transport of water into the BoB throughout the year.

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Q. Duan, Z. Di, J. Quan, C. Wang, W. Gong, Y. Gan, A. Ye, C. Miao, S. Miao, X. Liang, and S. Fan

Abstract

Weather forecasting skill has been improved over recent years owing to advances in the representation of physical processes by numerical weather prediction (NWP) models, observational systems, data assimilation and postprocessing, new computational capability, and effective communications and training. There is an area that has received less attention so far but can bring significant improvement to weather forecasting—the calibration of NWP models, a process in which model parameters are tuned using certain mathematical methods to minimize the difference between predictions and observations. Model calibration of the NWP models is difficult because 1) there are a formidable number of model parameters and meteorological variables to tune, and 2) a typical NWP model is very expensive to run, and conventional model calibration methods require many model runs (up to tens of thousands) or cannot handle the high dimensionality of NWP models. This study demonstrates that a newly developed automatic model calibration platform can overcome these difficulties and improve weather forecasting through parameter optimization. We illustrate how this is done with a case study involving 5-day weather forecasting during the summer monsoon in the greater Beijing region using the Weather Research and Forecasting Model. The keys to automatic model calibration are to use global sensitivity analysis to screen out the most important parameters influencing model performance and to employ surrogate models to reduce the need for a large number of model runs. Through several optimization and validation studies, we have shown that automatic model calibration can improve precipitation and temperature forecasting significantly according to a number of performance measures.

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Michael D. Hurwitz, Daniel M. Ricciuto, Peter S. Bakwin, Kenneth J. Davis, Weiguo Wang, Chiuxiang Yi, and Martha P. Butler

Abstract

Mixing ratios of CO2 often change abruptly in the presence of inclement weather and low pressure systems. Water vapor mixing ratio, temperature, wind speed, and wind direction data are used to infer that the abrupt changes in CO2 mixing ratios at a site in northern Wisconsin are due to tropospheric mixing, horizontal transport, or a combination of both processes. Four different scenarios are examined: the passage of a summer cold front, a summer convective storm, an early spring frontal passage, and a late autumn low pressure system. Each event caused CO2 mixing ratios to change rapidly when compared to biological processes. In one summer convective event, vertical mixing caused CO2 mixing ratios to rise more than 22 ppm in just 90 s. Synoptic-scale transport was also evident in the presence of storm systems and frontal boundaries. In the cases examined, synoptic-scale transport changed CO2 mixing ratios as much as 15 ppm in a 1-h time period. The events selected here represent extremes in the rate of change of boundary layer CO2 mixing ratios, excluding the commonly observed venting of a shallow, stable boundary layer. The rapid changes in CO2 mixing ratios that were observed imply that large mixing ratio gradients must exist, often over rather small spatial scales, in the troposphere over North America. These rapid changes may be utilized in inverse modeling techniques aimed at identifying sources and sinks of CO2 on regional to continental scales.

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D. Wang, C. Prigent, L. Kilic, S. Fox, C. Harlow, C. Jimenez, F. Aires, C. Grassotti, and F. Karbou

Abstract

The Tool to Estimate Land Surface Emissivity from Microwave to Submillimeter Waves (TELSEM2) is linked to a climatology of monthly emissivity estimates and provides a parameterization of the surface emissivity up to 700 GHz, in the framework of the preparation for the Ice Cloud Imager (ICI) on board the Meteorological Operational Satellite Second Generation (MetOp-SG). It is an updated version of the Tool to Estimate Land Surface Emissivities at Microwave Frequencies (TELSEM; ). This study presents the parameterization of continental snow and ice and sea ice emissivities in TELSEM2. It relies upon satellite-derived emissivities up to 200 GHz, and it is anchored to the Special Sensor Microwave Imager (SSM/I) TELSEM monthly climatology dataset (19–85 GHz). Emissivities from Météo-France and the National Oceanic and Atmospheric Administration (NOAA) at frequencies up to 190 GHz were used, calculated from the Special Sensor Microwave Imager/Sounder (SSMIS) and the Advanced Microwave Sounding Unit-B (AMSU-B) observations. TELSEM2 has been evaluated up to 325 GHz with the observations of the International Submillimeter Airborne Radiometer (ISMAR) and the Microwave Airborne Radiometer Scanning System (MARSS), which were operated on board the Facility for Airborne Atmospheric Measurements (FAAM) aircraft during the Cold-Air Outbreak and Submillimeter Ice Cloud Study (COSMICS) campaign over Greenland. Above continental snow and ice, TELSEM2 is very consistent with the aircraft estimates in spatially homogeneous regions, especially at 89 and 157 GHz. Over sea ice, the aircraft estimates are very variable spatially and temporally, and the comparisons with the TELSEM2 were not conclusive. TELSEM2 will be distributed in the new version of the RTTOV radiative transfer community code, to be available in 2017.

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Song Yang, William S. Olson, Jian-Jian Wang, Thomas L. Bell, Eric A. Smith, and Christian D. Kummerow

Abstract

Rainfall rate estimates from spaceborne microwave radiometers are generally accepted as reliable by a majority of the atmospheric science community. One of the Tropical Rainfall Measuring Mission (TRMM) facility rain-rate algorithms is based upon passive microwave observations from the TRMM Microwave Imager (TMI). In Part I of this series, improvements of the TMI algorithm that are required to introduce latent heating as an additional algorithm product are described. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, 0.5°-resolution estimates of surface rain rate over ocean from the improved TMI algorithm are well correlated with independent radar estimates (r ∼0.88 over the Tropics), but bias reduction is the most significant improvement over earlier algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly 2.5°-resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data is limited, TMI-estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain-rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with (a) additional contextual information brought to the estimation problem and/or (b) physically consistent and representative databases supporting the algorithm. A model of the random error in instantaneous 0.5°-resolution rain-rate estimates appears to be consistent with the levels of error determined from TMI comparisons with collocated radar. Error model modifications for nonraining situations will be required, however. Sampling error represents only a portion of the total error in monthly 2.5°-resolution TMI estimates; the remaining error is attributed to random and systematic algorithm errors arising from the physical inconsistency and/or nonrepresentativeness of cloud-resolving-model-simulated profiles that support the algorithm.

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R. Rasmussen, C. Walcek, H.R. Pruppacher, S.K. Mitra, J. Lew, V. Levizzani, P.K. Wang, and U. Barth

Abstract

Results are presented of a recent wind tunnel experiment in which electrically unchanged water drops of 1000–3000 μm equivalent radius were freely suspended in the vertical air stream of the UCLA Cloud Tunnel. During their suspension, the drops were exposed to external, vertical electric fields of 0–90 volts cm-1. The change in the drop shape with drop size and with electric field strength was noted and is discussed in the light of theoretical work cited in literature which does not take into account the feedback effects between the electric forces of an external electric field and the hydrodynamic forms due to the flow past the drop. In contrast, the present wind tunnel study, documented by photographs from a 16 mm motion picture film, recorded the shape of the water drop in response to both hydrodynamic as well as electric forces.

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