1. Mesoscale Observing Challenges: One Perspective with Emphasis on the Urban Zone presentation to the: NSF Observing Facilities Users Workshop 24-26 September 2007 NCAR Boulder, CO presentation to the: NSF Observing Facilities Users Workshop 24-26 September 2007 NCAR Boulder, CO Walt Dabberdt Director, Strategic Research Vaisala - Boulder, Colorado

2. ©Vaisala | date | Ref. code | Page 2 Presentation Outline Urban Demographics & Challenges Importance of the PBL Measurement Systems Mesoscale Networks and Testbeds

3. ©Vaisala | date | Ref. code | Page 3 Presentation Outline Urban Demographics & Challenges Importance of the PBL Measurement Systems Mesoscale Networks and Testbeds

4. ©Vaisala | date | Ref. code | Page 4 Ten(10) Largest Cities in 1000A.D. (M-Inhabitants) CordovaSpain0.450 KaifengChina0.400 ConstantinopleTurkey0.300 AngkorCambodia0.200 KyotoJapan0.175 CairoEgypt0.135 BaghdadIraq0.125 (1.25???) NishapurIran0.125 Al-HasaSaudi Arabia0.110 PatanIndia0.100 Source: Tertius Chandler: “4,000 Years of Urban Growth” (1987)

5. ©Vaisala | date | Ref. code | Page 5 1950 2000 2015

6. ©Vaisala | date | Ref. code | Page 6 Growth of Mega-Cities City-2015Population Tokyo Mumbai Lagos Dhaka Sao Paulo Karachi Mexico City Shanghai New York Jakarta Kolkata Delhi Metro Manila Los Angeles Buenos Aires Cairo Istanbul Beijing Rio de Janeiro Osaka Tianjin Hyderabad Bangkok 26.4 26.1 23.2 21.1 20.4 19.2 19.1 17.4 17.3 16.8 14.8 14.1 13.8 12.5 12.3 11.9 11.0 10.7 10.5 10.1 379.3 (23) Source: UN Population Division, March 2000 most mega-cities are in the less developed regions (16) blue = coastal city green = inland city

7. ©Vaisala | date | Ref. code | Page 7 The March of Urbanization in the World (% global population) WorldMDRLDR 195029.854.917.8 197537.970.026.8 200047.275.440.4 203060.282.656.4 MDR = more developed regions LDR = less developed regions source: UNPD, 2001 Today, 1.3 million people are moving to the cities every week!

8. ©Vaisala | date | Ref. code | Page 8 Growth by City Size Contrary to popular belief, the bulk of urban population growth is likely to occur in smaller cities and towns of less than 500,000.

9. ©Vaisala | date | Ref. code | Page 9 Some Relevant City Factoids (source: Arnulf Gruber, 2004) ~50% world population (~2007) > 80(?)% world GDP (few data) > 80(?)% world electricity [wfd: ~ CO2 eq. emissions?; no good data] ~ 95% world internet sites and internet traffic (good data) 78% mega-cities are coastal [wfd] 70% mega-cities are in less-developed regions [wfd]

10. ©Vaisala | date | Ref. code | Page 10 Warm Season Events Tornadoes Mesoscale boundaries Mesoscale systems Convection (localized) Hurricanes/Tropical storms Flash floods and main-stem flooding Fire weather events Air quality episodes (O3) Heat waves Toxic plumes Winter Season Events Fronts/short-waves Liquid/freezing/frozen boundaries Ice storms Orographic (e.g., lake effect storms) Blizzards/Wind chill Coastal Gales Air quality episodes (PM) Cold air outbreaks Toxic plumes Examples of Mesoscale Events That Impact Human Well- Being and/or Have Major Economic Impacts

11. ©Vaisala | date | Ref. code | Page 11 Tornado – Ft. Worth, TX Source: North Central Texas Council of Governments simulation March 28, 2000 Path Length: Approximately 3 miles Path Width: 1/4 mile F-Scale: F1 (73-112mph) to F2 (113-157mph)

12. ©Vaisala | date | Ref. code | Page 12 MODIS Imagery: France Heat Wave -- August 13-28, 2003 Source: Zaitchik et al., 2006 Vegetation index anomaly Surface temperature anomaly Solid lines demarcate conventional climate zones.

13. ©Vaisala | date | Ref. code | Page 13 Three Recent Heat Waves EventYearLocationFatalities Heat wave1987Athens~900 deaths Heat wave1995Chicago~700 deaths Heat wave2003 France~15,000 deaths Source: Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond (2007)

14. ©Vaisala | date | Ref. code | Page 14 Hurricane Katrina (2005) Tracks: Forecasts and Actual Courtesy of James Franklin, NHC

15. ©Vaisala | date | Ref. code | Page 15 Mega-City Smog -- Beijing

16. ©Vaisala | date | Ref. code | Page 16 Presentation Outline Urban Demographics & Challenges Importance of the PBL Measurement Systems Mesoscale Networks and Testbeds

17. ©Vaisala | date | Ref. code | Page 17 Bi-directional physical problem with feedbacks: Weather and Climate Impacts on the City Quality of life Economy Human health and mortality Urban effects on the atmosphere Direct:Indirect: sensible heat urban heat island runoff and latent heat human heat stress thermal conductivity and heat capacity PBL & ML structure aerodynamic roughness cloud cover & precip. zero-plane displacement insolation and radiation gaseous and particulate loadingbalance sun shading local circulations City-Atmosphere Interactions

18. ©Vaisala | date | Ref. code | Page 18 Why the Planetary Boundary Layer? PBL contains the Depth of cold air in winter to tops of stratocumulus Low-level jet for weather Courtesy of Fed Carr, NAOS Layer of air containing the roots of summertime convection Fog and low clouds under nocturnal inversion Convective events in well mixed layer during daytime heating

19. ©Vaisala | date | Ref. code | Page 19 The Need for Mesoscale Observations -- as Reported by the North American Observing System (NAOS) Study * Need to measure mesoscale phenomena at resolution that is high enough to accurately represent these mesoscale features in the initial conditions of a mesoscale model If using 6-8 grid points per wavelength criterion, then the needed resolution can be estimated as follows: –20-30 km resolution for jet streams, IPV details, etc. –But 0.1 – 1 km resolution to observe thunderstorm updrafts and downdrafts * Courtesy of: Fred Carr, Univ. Oklahoma

20. ©Vaisala | date | Ref. code | Page 20 Tropopause (8~13 km) Jet Stream Mid Troposphere (2~8 km) Location/intensity of short waves PBL (Sfc~2 km) Ageostrophic Orographic Temp, Moisture, Wind, Precipitation Surface/sub-surface conditions PBL has largest unmet need for improved observations (assuming that next-generation satellite sensors measure V, T and q at needed resolutions and precision above the PBL) Critical to get forcing correct in PBL, and short waves in troposphere Courtesy of: Fred Carr, Univ. Oklahoma What Additional Observations Are Needed? (source: NAOS) Satellite imagery & soundings

21. ©Vaisala | date | Ref. code | Page 21 The greatest need in future mesoscale observing capability is high vertical resolution of T, q and wind in the PBL. Slight variations in these values will have a major impact on: thunderstorm vs. severe thunderstorm vs. squall line vs. MCC, and subsequent forecasts of flooding, winds, temperatures, etc., and consequent impacts on health, safety, agriculture, transportation, energy, etc. ~2km Need 100-200m resolution! Courtesy of: Fred Carr, Univ. Oklahoma Why the PBL? (source: NAOS)

22. ©Vaisala | date | Ref. code | Page 22 Diurnal Boundary-Layer Evolution (after Stull)

23. ©Vaisala | date | Ref. code | Page 23 Source: J. Voogt (http://www.actionbioscience.org/environment/figures/voogt1.jpg) Main Components of the Urban Atmosphere

24. ©Vaisala | date | Ref. code | Page 24 Urban Boundary Layer: Scales & Layers

25. ©Vaisala | date | Ref. code | Page 25 Near-Surface Layer: Scales & Layers

26. ©Vaisala | date | Ref. code | Page 26 Urban Boundary Layer Structure

27. ©Vaisala | date | Ref. code | Page 27 Urban Multi-scales

28. ©Vaisala | date | Ref. code | Page 28 1 mm 1 cm 1 m 10 m 100 m 1 km 10 km 100 km 1000 km Horizontal grid spacing CFD Mesoscale GW&CM DNSLES Building Urban Storm Fronts Synoptic Physical Modeling GAP Modeling Capabilities and Model Grid Sizes Slide courtesy Walter Bach, ARO

29. ©Vaisala | date | Ref. code | Page 29 1 mm 1 cm 1 m 10 m 100 m 1 km 10 km 100 km 1000 km Horizontal grid spacing Modeling Gap Rawinsondes ACARS RADAR Daytime Boundary Layer Sfc Obs Building Urban Storm Fronts Synoptic Surface Layer Measurement Capabilities: Transport & Diffusion Scales Slide courtesy Walter Bach, ARO

30. ©Vaisala | date | Ref. code | Page 30 1 mm 1 cm 1 m 10 m 100 m 1 km 10 km 100 km 1000 km Horizontal grid spacing Modeling Gap Rawinsondes ACARSRADAR Nocturnal Boundary Layer Sfc Obs Building Urban Storm Fronts Synoptic Surface Layer Measurement Capabilities: Transport & Diffusion Scales Slide modified after Walter Bach, ARO

31. ©Vaisala | date | Ref. code | Page 31 (MacDonald et al., 2001) SCOS-97 mixing depths, September 4, 1997 Mixing Depth – Spatial and Temporal Variability 0300LST 1400LST L.A. Basin (Plate, 2004)

32. ©Vaisala | date | Ref. code | Page 32 Emergence of Urban-Based Mesoscale Initiatives U.S. Weather Research Program PDT-10 on Urban Forecasting (1998) U.S. Weather Research Program PDT-11 on Air Quality Forecasting (2001) and subsequent AQF Workshop (2003) U.S. Weather Research Program Community Workshop on Multifunctional Mesoscale Observing Systems (2003) U.S. Environmental Protection Agency Recommendations on Air Quality Forecasting and the Role of Urban Testbeds (2004) Helsinki Mesoscale Testbed (in operation since 2005) U.S. National Academies’ Panel on Multi-Functional Mesoscale Networks (midway through an 18-month study; completion 1Q 2008) U.S. Multi-Agency New Study of Urban Meteorological Testbeds (ongoing; completion 1Q 2008) American Meteorological Society’s New Panel on Partnerships and Mesoscale Networks (midway through an 18-month study; no completion target as yet) Canadian Research on Improved Urban Weather and Air Quality Forecasting (started in 2006 a 3-Year Study) U.S. National Science Foundation Study on Urban Meteorology (started a 5-year study in 2006) Beijing Mesoscale Network (in advanced implementation stage) London Mesoscale Network (in early planning stage)

33. ©Vaisala | date | Ref. code | Page 33 Common Themes from Four USWRP Workshops & PDTs

34. ©Vaisala | date | Ref. code | Page 34 One Very Relevant Study of the US Weather Research Program BAMS 86(7), 2005

35. ©Vaisala | date | Ref. code | Page 35 Broad Issues as Defined by the Modeling & Data Assimilation Community (from the Mesoscale Workshop)  What is the optimal mix of observations?  Regional testbeds provide a basis for answering this question.  Modelers – together with observationalists -- should be involved in the observing network decision process by designing observing systems and experiments to determine:  the most important variables to measure;  the minimum spacing and resolution requirements (network design);  adaptive and targeted sampling strategies; and  data assimilation techniques to effectively use these new measurements.

36. ©Vaisala | date | Ref. code | Page 36 Recommendations re: Modeling & Data Assimilation  Current observations are not sufficient for mesoscale applications. The following observations are needed to most effectively address deficiencies in current observing networks:  More accurate precipitation rates with good quality control;  Three-dimensional hydrometeor fields;  Three-dimensional mass, wind, and moisture fields  10-km horizontal resolution in the lower troposphere  10-100 km in the upper troposphere;  Three-dimensional cloud fields and cloud diabatic heating rate profiles;  Daily land (sea) surface features  Soil moisture and temperature profiles,  Snow cover and depth,  Land and sea-surface temperature (SST),  Emissivity  Vegetation type and state;  Turbulent flow, fluxes, and stability measured from Earth’s surface to 2 km  15 min. intervals and 100-200m vertical resolution;  PBL height and characteristics of convective rolls;  Tropopause topology with 10 km horizontal resolution;  O 3, CO 2, water vapor, & cloud distributions req’d for radiative transfer models;  Aerosols and chemical tracer concentrations Observational Recommendations from the Modeling & Data Assimilation Community (mesoscale workshop) Observational Recommendations from the Modeling & Data Assimilation Community 3D high-resolution fields Precipitation, hyrdometeors and clouds Surface characterization PBL structure Chemical species and PM Testbeds are crucial

37. ©Vaisala | date | Ref. code | Page 37 Recommendations re: Nowcasting Top mesonet recommendation: Establish a national mesonetwork of surface stations. NOAA should take the lead to establish this network, and set standards for data quality. Resolution needed: <10-25km and 5-15min. Remote sensing recommendations:  Addition of dual polarization capability to the WSR-88D network.  Pursue integration of other radars into the national radar network.  Investigate improving boundary-layer coverage through the use of closely spaced X-band radars.  Vigorously pursue national expansion of the NOAA Profiler Network with emphasis on boundary-layer observations.  Test the utility of radar refractivity measurements to improve nowcasting. Observational Recommendations from the Nowcasting Community (mesoscale workshop) Observational Recommendations from the Nowcasting Community (from the Mesoscale Workshop)

38. ©Vaisala | date | Ref. code | Page 38 Recommendations re: Nowcasting Other priority recommendations:  Conduct research aimed at using total lightning data to improve severe weather warnings and nowcasts.  Demonstrate added value of high-resolution water vapor fields for improve nowcasting.  Establish testbeds for very short period forecasting (0-6 hr, nowcasting) of high-impact weather. Tasks should include:  siting recommendations;  identification of leveraged funding sources;  identification of public/private partners;  specification of nowcasting systems and products;  involvement of potential clients and users; and  conducting impact and benefits studies. Observational Recommendations from the Nowcasting Community (mesoscale workshop) Observational Recommendations from the Nowcasting Community (from the Mesoscale Workshop)

39. ©Vaisala | date | Ref. code | Page 39 Recent Supporting Studies of the USWRPTwo Other Relevant USWRP Studies on AQF BAMS 87(2), 2006

40. ©Vaisala | date | Ref. code | Page 40 Organization of Recommendations Scope of AQF Workshop Recommendations BLD = Boundary-layer Dynamics WG C&A = Clouds and Aerosols WG M&M = Measurements and Modeling WG OAQF = Operational Air Quality Forecasting WG S&SI = Stakeholders and Societal Impacts WG Recommendations focus equally on measurement & modeling

41. ©Vaisala | date | Ref. code | Page 41 U+ extremely urgent U urgent I important Some Specific Recommendations from the USWRP AQF Workshop (29 April - 1 May 2003)

42. ©Vaisala | date | Ref. code | Page 42 U+ extremely urgent U urgent I important Some Specific Recommendations from the USWRP AQF Workshop (29 April - 1 May 2003)

43. ©Vaisala | date | Ref. code | Page 43 U+ extremely urgent U urgent I important Some Specific Recommendations from the USWRP AQF Workshop (29 April - 1 May 2003)

44. ©Vaisala | date | Ref. code | Page 44 U+ extremely urgent U urgent I important Some Specific Recommendations from the USWRP AQF Workshop (29 April - 1 May 2003)

45. ©Vaisala | date | Ref. code | Page 45 Presentation Outline Urban Demographics & Challenges Importance of the PBL Measurement Systems Mesoscale Networks and Testbeds

46. ©Vaisala | date | Ref. code | Page 46 Science Measurement Technology & Environmental Prediction Modeling Computing Observations Improved atmospheric measurements are central to improved environmental analyses and forecasts

47. ©Vaisala | date | Ref. code | Page 47 Weather radar: reflectivity; velocity, polarization; refractivity Wind profilers: radar, sodar; lidar; tethersondes; aircraft Thermodynamic soundings: RAOBS, aircraft; tethersondes; lidar Lightning detection:CG; total Radiometers:microwave -- scanning; multi-wavelength GPS receivers:precipitable water vapor -- column integrated; maybe slant path and 3D Surface mesonets:PTU; V; LW, SW, net radiation; energy & momentum fluxes Satellites:geostationary; POES; LEO Candidate Measurement Systems

48. ©Vaisala | date | Ref. code | Page 48 Elevation angles between 0.5 and 20 degrees Earth surface curvature effect “Cone of silence” & “pyramid of silence” Much less coverage at the low levels/in PBL where features such as thunderstorm outflows, convergence boundaries are crucially important Resolution degrades further away from radar ~75-85% of PBL is not observed Courtesy of: Fred Carr, Univ. Oklahoma WSR-88D Radar Network Coverage – PBL Limitations CONE OF SILENCE PYRAMID OF SILENCE 0.5deg 20deg

49. ©Vaisala | date | Ref. code | Page 49 CASA Price target equivalent to a mid-to-high-end automobile

50. ©Vaisala | date | Ref. code | Page 50

51. ©Vaisala | date | Ref. code | Page 51 Estimating Mixing Depth Cn2Cn2 Vertical Velocity Spectral Width Mixing Depth – Data and MethodsMixing Depth – Radar Wind Profiler 0 local time 24

52. ©Vaisala | date | Ref. code | Page 52 Mixing Depth – Ceilometer vs. RAOB Sounding (2000) CT25K Backscatter 28-29-Mar-2000 Local Time (h) Altitude (m) 10121416182022 0 2 4 6 810121416182022 0 0 500 1000 1500 2000 2500 3000 0 510 0 200 400 600 800 1000 1200 1400 1600 1800 2000 Radiosonde Sounding 29-Mar-2000 @ 11:44 Potential Temperature (°C) Altitude (m) 10 2 3 4 0 200 400 600 800 1000 1200 1400 1600 1800 2000 CT25K Backscatter 29-Mar-2000 @ 11:44 Backscatter (a.u.) Altitude (m) 1m CT25K BSL

53. ©Vaisala | date | Ref. code | Page 53 Boundary Layer Structure by CL31 Ceilometer

54. ©Vaisala | date | Ref. code | Page 54 Mixing Depth – Ceilometer vs. RAOB Sounding (2006)

55. ©Vaisala | date | Ref. code | Page 55 N/A BENEFICIAL ESSENTIAL APPLICATION Mesoscale Applications & Measurements -- Synergies Multiple applications

56. ©Vaisala | date | Ref. code | Page 56 N/A BENEFICIAL ESSENTIAL APPLICATION Mesoscale Applications & Measurements -- Synergies

57. ©Vaisala | date | Ref. code | Page 57 N/A BENEFICIAL ESSENTIAL Mesoscale Applications & Measurements -- Synergies

58. ©Vaisala | date | Ref. code | Page 58 N/A (16) BENEFICIAL (39) ESSENTIAL (62) Mesoscale Measurements and Applications -- Synergies

59. ©Vaisala | date | Ref. code | Page 59 Summary of Selected Mesoscale/Urban Challenges  PBL observations with high vertical and temporal resolution  radar wind profilers  lidars & laser ceilometers  x-band radars  aircraft  Dynamic characterization of land surface  Acquire & assimilate 4D meteorological and chemical data  High-resolution surface networks: <10km and 5min resolution  Augmentation of weather radar network  dual polarization  radars of opportunity  high-density, low-power radar networks  total lightning observations – merge with radar data  adaptive radar calibration  Testbeds -- a vehicle to evaluate alternative measurement, modeling and implementation strategies  Optimal network design

60. ©Vaisala | date | Ref. code | Page 60 Presentation Outline Urban Demographics & Challenges Importance of the PBL Measurement Systems Mesoscale Networks and Testbeds

61. ©Vaisala | date | Ref. code | Page 61 Some Definitions APPLICATION Mesoscale networks measure the three-dimensional, time-dependent structure of the lower atmosphere using an integrated observing system that incorporates in situ and remote sensing systems, deployed on/from the ground and aloft. “Mesonets” are a subset of mesoscale networks that consist of high-density surface stations. Mesoscale networks measure the three-dimensional, time-dependent structure of the lower atmosphere using an integrated observing system that incorporates in situ and remote sensing systems, deployed on/from the ground and aloft. “Mesonets” are a subset of mesoscale networks that consist of high-density surface stations.

62. ©Vaisala | date | Ref. code | Page 62 General applications Analysis/description of current atmospheric state – research or ops Nowcasting/very short-range forecasting (0+ to ~2 hrs) Short-range mesoscale prediction (~3 to 48 hrs) Site of interest Area (rel.) analysis mesoscale prediction nowcasting Schematic illustration Time (rel.) As the timescale of the prediction increases, so does the commonality of the observing systems needed to make the prediction (i.e. they become less application-specific). As the timescale of the prediction decreases -- toward analysis and short- term nowcasting – the observing requirements become more application- specific As the timescale of the prediction increases, so does the commonality of the observing systems needed to make the prediction (i.e. they become less application-specific). As the timescale of the prediction decreases -- toward analysis and short- term nowcasting – the observing requirements become more application- specific

63. ©Vaisala | date | Ref. code | Page 63 Mesoscale Weather Forecasting -- Testbeds Testbed Definition: “A working relationship in quasi-operational framework among forecasters, researchers, private-sector, and government agencies aimed at solving operational and practical regional problems with a strong connection to end-users.”

64. ©Vaisala | date | Ref. code | Page 64 Testbed Recommendations Testbed considerations and attributes:  Yield improved services, products, and economic/public safety benefits.  Accelerate transition of R&D to better operations, services, and decision making.  Testbeds require a long-term (multi-year) commitment, probably at multiple locations  With a view toward improving operational weather services, the observing systems deployed within testbeds should be reliable, cost- effective, commercial off-the-shelf (COTS) where possible, and capable of sustained, continuous operation.  Some redundancy in the observational capability of testbeds is needed to inform decisions about which sites and instruments are needed for long-term operational purposes.

65. ©Vaisala | date | Ref. code | Page 65 Testbed Criteria A successful testbed must satisfy the following criteria:  Address the detection, monitoring, and prediction of regional phenomena of particular interest  Define expected outcomes  Provide special observing networks needed for pilot studies and research  Define strategies for achieving the expected outcomes  Engage experts in the phenomena of interest  Involve stakeholders in planning, operation, and evaluation of the testbeds  Expedite R2O: transitioning research to operations

66. ©Vaisala | date | Ref. code | Page 66 Testbed Concept Testbeds provide the infrastructure for transitioning from R&D to operations. Testbeds need the flexibility to test many new ideas, the expertise to judge which of them are viable, and the infrastructure to harden the sensors, algorithms and models that will generate new products for operations.

67. ©Vaisala | date | Ref. code | Page 67 Status of some Mesoscale Testbeds Helsinki Testbed Phase I (observations) started August 2005; Phase II (applications) started August 2007 Beijing Olympics 2008 enhanced mesoscale observing-and- forecasting underway Shanghai 2010 World Expo enhanced meso- and micro-scale multi- functional observing-and-forecasting system in advanced planning U.S. preparations/planning underway DHS – Homeland Security limited urban nets in New York and WDC OFCM urban testbeds under consideration Multi-agency planning in early stage – NRC/BASC study (completion early 2008)

68. ©Vaisala | date | Ref. code | Page 68 Two Approaches to Designing Networks Designing Mesoscale Meteorological Observing Networks Empirical Methods (current state-of-the-art) Analytical Methods (in development) Team of experts (Wx & AQ): Forecasters Modelers Observationalists Other ‘stakeholders’ Numerical tools: OSSEs OSEs Data denial experiments Observational testbeds

69. ©Vaisala | date | Ref. code | Page 69