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Zhang, Fuqing

Publications and source records attributed to Zhang, Fuqing.

At least 19 records

Ensemble‐Based Assimilation of Satellite All‐Sky Microwave Radiances Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017)

Abstract Ensemble‐based data assimilation of radar observations across inner‐core regions of tropical cyclones (TCs) in tandem with satellite all‐sky infrared (IR) radiances across the TC domain improves TC track and intensity forecasts. This study further investigates potential enhancements in TC track, intensity, and rainfall forecasts via assimilation of all‐sky microwave (MW) radiances using Hurricane Harvey (2017) as an example. Assimilating Global Precipitation Measurement constellation all‐sky MW radiances in addition to GOES‐16 all‐sky IR radiances reduces the forecast errors in the TC track, rapid intensification (RI), and peak intensity compared to assimilating all‐sky IR radiances alone, including a 24‐hr increase in forecast lead‐time for RI. Assimilating all‐sky MW radiances also improves Harvey's hydrometeor fields, which leads to improved forecasts of rainfall after Harvey's landfall. This study indicates that avenues exist for producing more accurate forecasts for TCs using available yet underutilized data, leading to better warnings of and preparedness for TC‐associated hazards in the future.

54 ENVIRONMENTAL SCIENCES↗

Notable Contributions of Aerosols to the Predictability of Hail Precipitation

There is an increasing concern of the uncertainty produced by aerosols in forecasting precipitation including hail precipitation. This study provides an assessment of the uncertainties in hail and total precipitation by varying initial cloud condensation nuclei (CCN) number concentration (CCNC) and meteorological conditions based on 1200 cloud-resolving simulations of an idealized hailstorm. Although the meteorological perturbations produce large uncertainties in hail precipitation (including rate and maximum hail size) as well as total precipitation, varying CCNC by an order of magnitude can cause even larger uncertainties, especially pairing with the thermodynamics perturbation (i.e., potential temperature and water vapor). Changing CCNC modifies the predictability of hail precipitation, with a higher predictability in moderate polluted environments compared with the very clean and polluted environments. Increasing CCNC consistently leads a non-monotonic response of ensemble mean with an optimal CCNC for hail precipitation but a monotonic decreasing response of total precipitation with the various meteorological perturbations, meaning the initial meteorological perturbations does not qualitatively change the aerosol effects. Investigation with 10-fold reduced initial perturbation further supports the large CCN effects are not dependent of metrological perturbations. The findings suggest the importance of considering CCN effects in severe weather simulations and forecasting.

54 ENVIRONMENTAL SCIENCES↗

Potential Impacts of Assimilating All-sky Satellite Infrared Radiances on Convection-Permitting Analysis and Prediction of Tropical Convection

Geostationary infrared satellite observations are spatially dense [< 1/(20 km)2] and temporally frequent (< 1/hour). These suggest the possibility of using these observations to constrain sub-synoptic features over data sparse regions, such as tropical oceans. In this study, the potential impacts of assimilating water vapor channel brightness temperature (WV-BT) observations from the geostationary Meteorological Satellite 7 (Meteosat-7) on tropical convection analysis and prediction were systematically examined through a series of ensemble data assimilation experiments. WV-BT observations were assimilated hourly into convection-permitting ensembles using Penn State’s ensemble square root filter (EnSRF). Comparisons against independently observed Meteosat-7 window channel brightness temperature (Window-BT) show that the assimilation of WV-BT generally improved the intensities and locations of large-scale cloud patterns at spatial scales larger than 100 km. However, comparisons against independent soundings indicate that the EnSRF analysis produced a much stronger dry bias than the no data assimilation experiment. This strong dry bias is associated with the use of the simulated WV-BT from the prior mean during the EnSRF analysis step. A stochastic variant of the ensemble Kalman filter (NoMeanSF) is proposed. The NoMeanSF algorithm was able to assimilate the WV-BT without causing such a strong dry bias and the quality of the analyses’ horizontal cloud pattern is similar to EnSRF’s analyses. Finally, deterministic forecasts initiated from the NoMeanSF analyses possess better horizontal cloud patterns above 500 km than those of the EnSRF. These results suggest that it might be better to assimilate all-sky WV-BT through the NoMeanSF algorithm than EnSRF algorithm.

Chan, Man-Yau↗

Observations of Greenhouse Gas Changes across Summer Frontal Boundaries in the Eastern United States

Our knowledge about synoptic-scale variations of atmospheric CO2 produced by interactions between mid-latitude cyclones and regional-scale surface fluxes remains limited by scarcity of observations. We synthesize observations of greenhouse gases (GHG) with respect to frontal passages to understand how GHG distributions change vertically and horizontally during a synoptic event. We use the airborne in-situ measurements of GHGs collected during the first Atmospheric Carbon and Transport–America (ACT) summer field campaign across three regions of the eastern US. We find that frontal structures are consistently and clearly associated with spatially coherent, significant changes in GHG composition. Warm sector CO2 mole fractions (henceforth, [CO2]) are significantly higher than those in the cold sector. The CO2 frontal differences (5-30 ppm) are largest in the atmospheric boundary layer (ABL) with smaller differences (3-5 ppm) in the free troposphere (FT). Bands of elevated CO2 (5-20 ppm enhancement compared to warm-sector mean [CO2]) repeatedly occurred in the ABL adjacent to the frontal boundary. Analyses of 84 vertical profiles reveal higher [CO2] in the FT than in the ABL in the cold-sector, the opposite pattern in the warm-sector. Average ABL-to-FT [CO2] differences are 12 ppm and -6 ppm in the warm and cold sectors, respectively. The same analysis for CH4 shows higher [CH4] in the ABL than in the FT in both warm and cold sectors with at least 30-ppb higher ABL-to-FT [CH4] differences in the warm-sector than in the cold-sector. The observational analyses presented here define new metrics for model evaluation of GHG transport.

Pal, Sandip↗

Convectively Forced Diurnal Gravity Waves in the Maritime Continent

Long-lived, zonally propagating diurnal rainfall disturbances are a highly pronounced and common feature in the Maritime Continent (MC). A recent study argues that these disturbances can be explained as diurnally phase-locked gravity waves. Here we explore the origins of these waves through regional cloud-permitting numerical model experiments. The gravity waves are reproduced and isolated in the model framework through the combined use of realistic geography and diurnally cyclic lateral boundary conditions representative of both characteristic easterly and westerly background zonal flow regimes. These flow regimes are characteristic of the Madden–Julian oscillation (MJO) suppressed and active phase in the MC, respectively. Tests are conducted wherein Borneo, Sumatra, or both islands and/or their orography are removed. These tests imply that the diurnal gravity waves are excited and maintained directly by latent heating from the vigorous mesoscale convective systems (MCSs) that form nocturnally in both Borneo and Sumatra. Removing orography has only a secondary impact on both the MCSs and the gravity waves, implying that it is not critical to these waves. We therefore hypothesize that diurnal gravity waves are fundamentally driven by mesoscale organized deep convection, and are only sensitive to orography to the measure that the convection is affected by the orography and its mesoscale flows. Factor separation further reveals that the nonlinear interaction of synchronized diurnal cycles in Sumatra and Borneo slightly amplifies this gravity wave mode compared to if either island existed in isolation. This nonlinear feedback appears most prominently at longitudes directly between the two islands.

Ruppert, Jr., James H.↗

Modeling Arctic boundary layer cloud streets at grey-zone resolutions

To better understand how model resolution affects the formation of Arctic boundary layer clouds, we investigated the influence of grid spacing on simulating cloud streets that occurred near Utqiagvik (formerly Barrow), Alaska on 2 May 2013 and were observed by the Moderate Resolution Imaging Spectroradiometer (MODIS). The Weather Research and Forecasting model was used to simulate the clouds using nested domains with increasingly fine resolution ranging from a horizontal grid spacing of 27 km in the boundary-layer-parameterized mesoscale domain to a grid spacing of 0.111 km in the large-eddy-permitting domain. We investigated the model-simulated mesoscale environment, horizontal and vertical cloud structures, boundary layer stability, and cloud properties, all of which were subsequently used to interpret the observed roll-cloud case. Increasing model resolution led to a transition from a more buoyant boundary layer to a more shear-driven turbulent boundary layer. The clouds were stratiform-like in the mesoscale domain, but as the model resolution increased, roll-like structures, aligned along the wind field, appeared with ever smaller wavelengths. A stronger vertical water vapor gradient occurred above the cloud layers with decreasing grid spacing. With fixed model grid spacing at 0.333 km, changing the model configuration from a boundary layer parameterization to a large-eddy-permitting scheme produced a more shear-driven and less unstable environment, a stronger vertical water vapor gradient below the cloud layers, and the wavelengths of the rolls decreased slightly. In this study, only the large-eddy-permitting simulation with gird spacing of 0.111 km was sufficient to model the observed roll clouds.

Lai, Hui-Wen↗

Validation of Regional CO2 Concentrations in the ECMWF Real-Time Analysis and Carbon-Tracker Reanalysis with Airborne Observations from ACT-A Field Campaign

Through verifying against hundreds of hours of airborne in-situ measurements from the NASA-sponsored Atmospheric Carbon and Transport – America (ACT-A) field campaign, this study systematically examines the regional uncertainties and biases of the carbon dioxide (CO2) concentrations from two of the state-of-the-art global analysis products, namely the real-time analysis from the European Center (EC) for Medium Range Forecasting and NOAA’s near real-time Carbon Tracker (CT) reanalysis. It is found that both the EC and CT-NRT analyses agree reasonably well with the independent ACT-A flight-level CO2 measurements in the free troposphere but the uncertainties are considerably larger in the boundary layer during both the summer months of 2016 and the winter months of 2017. There are also strong variabilities in accuracy and bias between seasons, and across three different subregions in the United States (Mid-Atlantic, Midwest and South). Overall, the analysis uncertainties of the EC and CT-NRT analyses in terms of root-mean square deviations against airborne data are comparable to each other, both of which are between 1-2 ppm in the free troposphere but can be as large as 10 ppm near the surface, which are grossly consistent with the difference between the two analyses. The current study not only provides systematic uncertainty estimates for both analysis products over North America but also demonstrated that these two independent estimates can be used to approximate the overall regional CO2 analysis uncertainties. Both statistics are important in future studies in quantifying the uncertainties of regional carbon concentration and flux estimates, as well as in assessing the impact of regional transport through more refined regional modeling and analysis systems.

Chen, Hans W.↗

Applications of SMAP Data to Retrieval of Ocean Surface Wind and Salinity

We have examined the L-band radiometer and radar data from NASA’s Soil Moisture Active Passive (SMAP) mission for ocean research and applications. We find that the SMAP data are in excellent agreement with the geophysical model function (GMF) derived from the Aquarius data up to a wind speed of 20 ms-1. For severe wind conditions, the higher resolution data from SMAP allowed us to assess the sensitivity of L-band radiometer signals to hurricane force winds. We applied the L-band GMF to the retrieval of ocean surface wind and SSS from the SMAP data. Comparison with the European Center for Medium-Range Weather Forecasting, WindSat and RapidSCAT wind speeds suggests that SMAP’s radiometer wind speed reaches an excellent accuracy of about 1.1-1.7 ms-1 below a wind speed of 20 ms-1. We have also found that the maximum wind speed derived from the SMAP radiometer data can reach 140 knots for severe storms and are generally in good agreement with the hurricane track analysis and operational aircraft Stepped Frequency Microwave Radiometer wind speeds. The spatial patterns of the SMAP SSS agree well with climatological distributions, but exhibit several unique spatial and temporal features.

ocean surface wind↗

Isentropic Analysis of a Simulated Hurricane

Hurricanes, like many other atmospheric flows, are associated with turbulent motions over a wide range of scales. Here the authors adapt a new technique based on the isentropic analysis of convective motions to study the thermodynamic structure of the overturning circulation in hurricane simulations. This approach separates the vertical mass transport in terms of the equivalent potential temperature of air parcels. In doing so, one separates the rising air parcels at high entropy from the subsiding air at low entropy. This technique filters out oscillatory motions associated with gravity waves and separates convective overturning from the secondary circulation. This approach is applied here to study the flow of an idealized hurricane simulation with the Weather Research and Forecasting (WRF) Model. The isentropic circulation for a hurricane exhibits similar characteristics to that of moist convection, with a maximum mass transport near the surface associated with a shallow convection and entrainment. There are also important differences. For instance, ascent in the eyewall can be readily identified in the isentropic analysis as an upward mass flux of air with unusually high equivalent potential temperature. The isentropic circulation is further compared here to the Eulerian secondary circulation of the simulated hurricane to show that the mass transport in the isentropic circulation is much larger than the one in secondary circulation. This difference can be directly attributed to the mass transport by convection in the outer rainband and confirms that, even for a strongly organized flow like a hurricane, most of the atmospheric overturning is tied to the smaller scales.

convection↗

Dynamics and Predictability of Hurricane Humberto (2007) Revealed from Ensemble Analysis and Forecasting

This study uses short-range ensemble forecasts initialized with an Ensemble-Kalman filter to study the dynamics and predictability of Hurricane Humberto, which made landfall along the Texas coast in 2007. Statistical correlation is used to determine why some ensemble members strengthen the incipient low into a hurricane and others do not. It is found that deep moisture and high convective available potential energy (CAPE) are two of the most important factors for the genesis of Humberto. Variations in CAPE result in as much difference (ensemble spread) in the final hurricane intensity as do variations in deep moisture. CAPE differences here are related to the interaction between the cyclone and a nearby front, which tends to stabilize the lower troposphere in the vicinity of the circulation center. This subsequently weakens convection and slows genesis. Eventually the wind-induced surface heat exchange mechanism and differences in landfall time result in even larger ensemble spread. 1

Sippel, Jason A.↗

Effects of Moist Convection on Hurricane Predictability

This study exemplifies inherent uncertainties in deterministic prediction of hurricane formation and intensity. Such uncertainties could ultimately limit the predictability of hurricanes at all time scales. In particular, this study highlights the predictability limit due to the effects on moist convection of initial-condition errors with amplitudes far smaller than those of any observation or analysis system. Not only can small and arguably unobservable differences in the initial conditions result in different routes to tropical cyclogenesis, but they can also determine whether or not a tropical disturbance will significantly develop. The details of how the initial vortex is built can depend on chaotic interactions of mesoscale features, such as cold pools from moist convection, whose timing and placement may significantly vary with minute initial differences. Inherent uncertainties in hurricane forecasts illustrate the need for developing advanced ensemble prediction systems to provide event-dependent probabilistic forecasts and risk assessment.

Zhang, Fuqing↗