SURF Progresses Contents 1 5th Workshop: June 21-23, 2017 2 SURF-2016 Summer Experiment 3 Preliminary results 4 Future plan
(1) 5 th Workshop: June 21-23, 2017
SURF WS-5: Structure I. New Science Reports 3 talks II. Panel Discussion: SURF Obs, Data, QA/QC, Archive, & Analyses 4 talks III. Panel Discussion: SURF Urban Modeling 5 talks IV. Summary & recommendations Open discussion on: Future SURF projects, new observing platforms, research to operational strategies, collaborations etc.
(2) Instruments for SURF-2016 Summer Experiment King Air HUL YAN CHP SHA TAN SHU HUA MIY SHA PIN Mobile lidar Wind profiler (S) Wind profiler (O) Wind profiler (R) Wind profiler (I) Flux tower (O) Flux tower (I) Radiometer (O) Aerosol lidar (I) Total Wind profiler 14 Radiometer 3 Aerosol lidar 2 Doppler lidar 1 XIA GUC FAN FEN IAP NAN TON WUQ XIQ JIN TMS BAO TAN Doppler lidar (I) Radiosonde (O) GPS Radiosonde (IOP only) S/C Band radar (O) X-band radar (O) Ceilometer (O) Boundary Layer Radiosonde (Aug 28 -- Sept 2) Flux tower 6 Ceilometer 10 Weather radar 4 X-band radar 6 GPS sounding (IOP) Green: new in 2016 4 S: data Sharing site O: Operational site R: Rental instruments I: IUM s instruments
(3) Preliminary results Urban turbulence: Averaged HOST relations between wind speed V and friction velocity u * (each dot represents a 30-min averaged value) (a) at 47 m for three surface roughness ranges, where rough, medium, and smooth refer to wind direction ranges of 160-240, 300-360, and 360-160 o, respectively; and (b) at 47 m and 140 m on nights following sunny days, with CASES- 99 HOST over grass and neutral MOST prediction slopes. Effects of urban canopy on turbulent mixing: similar to plant canopies, but more complicated. HOST (HOckey Stick Transition) hypothesis can be used to explain the observed turbulent momentum and heat transfers in urban areas Two unique features: -Direction-dependent z 0 - Fog/haze effects turbulence
Estimate of PBL depth using Doppler LiDAR data Fractional Methodology for SURF NBL-depths (+ s) Definitions: Near-surface max Assumed constants at PBL top Background f = 0.1 = 0.01 m 2 s -2 is min possible value in model s scheme Here, is averaged nighttime value above 1 km Results: NBL depths now look reasonable (details follow) Lidar measures u/v/w σ 2 is the variance of w indicating the turbulence strength
Improvement of urban model with SURF data Cooling Tower (CT) scheme was incorporated to BEP+BEM to improve the modeling of LE. (with J. E. Gonzalez s CCNY Team) AMS-2017: Improving the Representation of Latent Heat Fluxes on Operational Forecast Models for Beijing, China, M. Yu 7
Urban impacts on rainfall: Climatic analysis Weak-UHI cases: two western-max ( > 15%), Old Town-min ( < - 15 %) and urban rain-shadow (<-35%) are intensified Strong-UHI cases: UHI-induced two urban-max (75% & 60 %) over urban centers. Weak-UHI cases(< 1.5 C) Strong-UHI cases(> 1.5 C) Summer total rainfall anormaly
The distribution of aerosol number concentration based on 53 flights observation The concentration in PBL during both winter and summer show consistent number loadings at 3000-4000#/cc and effective diameter ~0.4um, suggesting generally consistent emission and uniform mixing of pollutants. The strong subsidence inversion on top of PBL in winter sometimes lead to substantially increased concentration (0.12-0.5um) >6000#/cc. After being removed by dynamic air conditions, the background aerosol number concentrations (0.12-0.5um) are consistent in summer and winter at 1000-2000 #/cc.
Haze impacts on albedo: Observed (a) PM2.5 mass concentration at HAI, and albedo from 325 m tower at the height of (b) 47 m, (c) 140 m, and (d) 280m on 1 Dec. 2015 and 4 Dec. 2015 The albedo on haze day is largely greater than that on clear day The albedo increases with height no matter on clear or haze day. The difference of albedo between clear and haze day also increases with height. Haze could affect the radiation process and then stabilize the stratification.
SURF Publications Project intro: 1. All, SURF: Understanding and predicting urban convection and haze, BAMS (in revision) Observations: 2. Meng Huang, et al., 2016: Estimate of BL depth over Beijing, BLM, 162(3), 503-522 3. Jielun Sun, et al., Understanding urban HOST hypothesis with SURF, JAS (in revision) 4. Zhaobin Sun, et al., 2017: Oscillation of surface PM2.5 in Beijing, JMR (in revision) 5. Junxia Dou, et al. Urban surface energy balance observations.(in preparation) 6. Zuofang Zheng, et al. Relationship between Fine Particle Pollution and UHI (in preparation) Numerical simulation: 7. M. Barlage, et al., 2016: Impact of physics on NWP, JGR Atmospheres, 121, 4487 4498 8. Yuhuan Li, et al., 2016: Introducing and evaluating a new building-height, IJC (in press) 9. Jingjing Dou and Shiguang Miao, 2017: Impact of mass human migration on UHI, IJC (in press) 10.Miao Yu, et al., 2017: Urban signatures of a heavy rainfall, JGR Atmospheres (in press) 11.Yizhou Zhang, et al., 2017: Urban effects under different UHII, JGR Atmospheres (in press) 12.Bob Bornstein, et al. Suggested guidelines for urban impact analyses, UC (in revision) 13.Jingjing Dou, et al. Bifurcation over Beijing, Part 1. MWR (in preparation) 14.Bob Bornstein, et al. Bifurcation over Beijing, Part 2. MWR (in preparation) 15.Miao Yu, et al. Improving the representation of latent heat fluxes, TAC (in preparation) 16.Miao Yu, et al. Uncertainty of urban-impacts on rainfall. JGR Atmospheres (in preparation) 17.Xiaoyu Xu, et al. Assessment of UHI Effect on Building Energy Consumption (in preparation) 18.Xiaoyu Xu, et al. Assess summertime air conditioning electric loads (in preparation) 19.Yizhou Zhang, et al. Noah-MP coupled with urban canopy model in Beijing. (in preparation) Published in Chinese: 8 others
(4) Future Plan 1. SURF data: QC and sharing 2. New equipment and new data The new network of ceilometers Soil moisture network Urban and weather satellite remote sensing In-situ thermal remote sensing 3. New sciences Interaction between urban and heat/cold wave Interaction between fog/haze and weather Interaction between urban and terrain (Phase II) 4. R2O: Research to Operation 5. Outreach, and Education 6. Phase II: SURF-MT( Mountain Terrain)
Phase II: SURF-MT (preliminary discussion) In order to answer the following questions: How can we combine radar, lidar, wind profilers, and other sensors to fill the gap between the city and the mountains? How does precipitation evolve once it is initiated in elevated terrains and moves to the city? What is the interaction between urban and terrain? Science Objectives Promote cooperative international-research to improve understanding of 4-D boundary-layer structure in mountain terrain via workshops & field studies Evaluate & improve high-resolution (~10-100 m grids) numerical models Enhance forecast-utility for urban and mountain terrain, and for Winter Olympics applications
Thanks for your attention! 14