1. Anthropogenic effects on urban and coastal climates R. Bornstein and co-workers San Jose State University pblmodel@hotmail.com Presented at Stanford University 9 April 2007

2. OUTLINE Global warming observations in Calif Global warming observations in Calif –Reverse impacts –Daytime summertime coastal-cooling Urbanized meso-met modeling Urbanized meso-met modeling –uMM5 Houston Houston NYC NYC –uWRF plans

3. (Part 1) Global-warming reverse-impact: observed summer-daytime coastal-cooling in California air-basins R. Bornstein, San Jose State University pblmodel@hotmail.com B. Lebassi, J. E. González, D. Fabris, E. Maurer, Santa Clara University N. Miller, Berkeley National Laboratory

4. OUTLINE Global-warming  reverse impacts Global-warming  reverse impacts Coastal-cooling observations Coastal-cooling observations –Methodology –Results South Coast Air Basin South Coast Air Basin SFBA and Central Valley SFBA and Central Valley Conclusion Conclusion –Summary –Implications FUNDING: Santa Clara University FUNDING: Santa Clara University

5. Global Warming Models: past & future asymmetric-warming Models: past & future asymmetric-warming (i.e., ΔT min > ΔT max ) on (i.e., ΔT min > ΔT max ) on –global scale (1.0-2.5 deg resolution) –regional scale (10 km resolution) Global scale obs Global scale obs –match model results –show accelerated- warming since ‘70s 

6. California Warming: JJA 1900-2000 Δ-T(K) California Warming: JJA 1900-2000 Δ-T aver (K) USC Stat-downscaled global-model results USC Stat-downscaled global-model results –2-m AGL –10-km horiz-grid –warming-rates decrease towards coast Coastal SSTs Coastal SSTs –ICOADS data –2-deg horiz resolution –Warming, but –At slower rate than at inland sites

7. Reverse-Impact Hypothesis INLAND WARMING  INCREASED (COAST TO INLAND) ∂(p,T)/∂n  INCREASED SEA BREEZE FREQ, INTENSITY, PENETRATION, & DURATION  COOLING SUMMER COASTAL T COOLING SUMMER COASTAL T max

8. CALIF TEMP-DATA FROM NCDC FROM NCDC 2-m VALUES 2-m VALUES DAILY T & T DAILY T MAX & T MIN 300 NWS CO-OP SITES 300 NWS CO-OP SITES 1948-2005 1948-2005

9. ANALYSES 1970-2005 data 1970-2005 data Annual & summer warming/ cooling trends (K/decade) for SST, T max, T min Annual & summer warming/ cooling trends (K/decade) for SST, T max, T min Spatial dist of summer Spatial dist of summer T-trends plotted T max -trends plotted (in 2 black boxes) –South Coast Air Basin –SFBA and Central Valley Summer land-sea T-grad (surrogate for p-grad) trend calculated by use of Summer land-sea T aver -grad (surrogate for p-grad) trend calculated by use of –SST: SFBA black-box ocean –2-m land-values: red-box

10. Calif Asymmetric-Warming: 1970-2005 Middle curve (T min )= Middle curve (T min )= 0.27 K/decade Lower curve (T max) = Lower curve (T max) = 0.061 K/decade (small-Δ b/t 2 large nos.) Top curve (SST)= Top curve (SST)= 0.24 K/decade *********** *********** Thus, from T aver & SST: Thus, from T aver & SST: Right curve (T-grad)= 0.16 K/100-km/decade  stronger sea breeze

11. Changes in Diurnal temperature-range (DTR) values: all of Calif daytime-warming (mainly inland) sites: 0.05 K/decade daytime-warming (mainly inland) sites: 0.05 K/decade (as Tincreased a bit faster than did T; why?) (as T max increased a bit faster than did T min ; why?) daytime-cooling (mainly coastal) sites: -0.61 K/decade daytime-cooling (mainly coastal) sites: -0.61 K/decade (as Tcreased & T increased) (as T max decreased & T min increased)

12. Significant South Coast Air Basin Topography

13. SCAB 1970-2005 summer T max warming/cooling trends (K/decade) Arrows = dominant summer flow

14. Significant SFBA and CenValley Topography

15. SFBA & CenV 1970-2005 summer T max warming/cooling trends (K/decade) -

16. Statistical Significance: 1970-2005 Parameter (all Calif) Rate (K/decade)r N e (years) Significance (%) DTR (cooling areas)-0.610.70695 DTR (warming areas)0.050.073132 T min 0.270.521193 T max 0.060.093068 SST0.240.451492 100-km dT/dx0.160.103040 Region-Area Rate (K/decade)r N e (years) Significance (%) Coastal-SFBA-0.160.232272 Inland-SFBA 0.470.581095 Coastal-SoCAB-0.330.371787 Inland-SoCAB 0.210.252274 Coastal-Both-0.220.321983 Inland-Both 0.400.531193

17. SUMMARY MIN-TEMPS IN CALIF WARMED FASTER THAN MAX-TEMPS  ASYMMETRIC WARMING MIN-TEMPS IN CALIF WARMED FASTER THAN MAX-TEMPS  ASYMMETRIC WARMING SUMMER DAYTIME MAX-TEMPS COOLED IN LOW-ELEVATION COASTAL AIR- BASINS SUMMER DAYTIME MAX-TEMPS COOLED IN LOW-ELEVATION COASTAL AIR- BASINS FOLLOWING AREAS COOLED IN CENTRAL CALIFORNIA: FOLLOWING AREAS COOLED IN CENTRAL CALIFORNIA: –MARINE LOWLANDS –MONTEREY –SANTA CLARA VALLEY –LIVERMORE VALLEY –WESTERN-HALF OF SACRAMENTO VALLEY

18. GOOD IMPLICATIONS AGRICULTURAL AREAS MAY NOT SHRINK AGRICULTURAL AREAS MAY NOT SHRINK e.g.: NAPA WINE AREAS MAY NOT GO EXTINCT  ENERGY-NEED FOR COOLING MAY NOT INCREASE AS RAPIDLY AS POPULATION ENERGY-NEED FOR COOLING MAY NOT INCREASE AS RAPIDLY AS POPULATION LOWER HUMAN HEAT-STRESS & MORTALITY RATES LOWER HUMAN HEAT-STRESS & MORTALITY RATES URBAN-OZONE LEVELS WILL CONTINUE TO FALL URBAN-OZONE LEVELS WILL CONTINUE TO FALL

19. IMPLICATIONS FOR CALIF OZONE PAST DECREASES MAY BE IN-PART DUE TO JJA MAX-TEMP COOLING-TREND & NOT ONLY TO EMISSION REDUCTIONS PAST DECREASES MAY BE IN-PART DUE TO JJA MAX-TEMP COOLING-TREND & NOT ONLY TO EMISSION REDUCTIONS WHEN MAX-T DECREASES, THE FOLLOWING ALSO DECREASE: WHEN MAX-T DECREASES, THE FOLLOWING ALSO DECREASE: – BIOGENIC PRECURSOR EMISSIONS – PHOTOCHEM REACTION RATES – ENERGY-USE FOR COOLING AND THUS ANTHROPOGENIC PRECURSOR EMISSIONS

20. REQUIRED FUTURE-EFFORTS: ANALYSIS OF OBS & MESO MET MODELING TO SEPARATE-OUT INFLUENCES (DISCUSSED IN LITERATURE) OF WARMING SSTs  WARMING SSTs  weaker sea breezes INCREASED COASTAL UPWELLING  INCREASED COASTAL UPWELLING  stronger sea breezes LAND-USE CHANGES LAND-USE CHANGES –AGRICULTURAL: INCREASED INLAND IRRIGATION  inland cooling  decreased sea-breezes –URBANIZATION: STRONGER UHIs  increased sea-breezes OTHER SEA-BREEZE INFLUENCES OTHER SEA-BREEZE INFLUENCES INCREASED WIND VELOCITY, STRATUS CLOUD COVER, & SOIL MOISTURE  coastal cooling

21. WHERE TO LOOK FOR COASTAL-COOLING GC winds in same-direction as sea-breeze GC winds in same-direction as sea-breeze Low-elevation air-basins Low-elevation air-basins Cool coastal ocean-currents Cool coastal ocean-currents Upwelling areas Upwelling areas i.e.: mid-lat (what lat range?) west-coast areas What other-types of reverse-impacts might exist, e.g., in mt areas?

22. Part 2: Urbanized Mesoscale Atmospheric Modeling R. Bornstein, R. Balmori, H. Taha San Jose State University San Jose, CA pblmodel@hotmail.com Presented at NRL Monterey, CA 6 October 2006

23. OUTLINE uMM5 uMM5 – Houston ozone – NYC tracer study (Future) uWRF (Future) uWRF Conclusion Conclusion Funded by: TCEQ, NSF, DHS Funded by: TCEQ, NSF, DHS

24. Urbanization History Urbanize momentum, thermoynamic, & TKE Urbanize momentum, thermoynamic, & TKE –surface & SBL: diagnostic eqs –PBL: prognostic eqs From veg-canopy model (Yamada 1982) From veg-canopy model (Yamada 1982) Veg-param replaced with GIS/RS urban-param/data Veg-param replaced with GIS/RS urban-param/data –Brown and Williams (1998) –Masson (2000) –Martilli et al. (2001) in TVM/URBMET –Dupont, Ching, et al. (2003) in EPA/MM5 –Taha et al. (2005), Balmori et al. (2006b) in uMM5 Detailed input urban-parameters as f(x,y) Next: 2 slides

25. From EPA/MM5: Mason + Martilli (by Dupont) Within Gayno-Seaman PBL/TKE scheme

26.  Advanced urbanization scheme from Masson (2000) ______ _________ 3 new terms in each prog equation

27. New GIS/RS inputs for uMM5 as f (x, y, z)  land use (38 categories)  roughness elements  anthropogenic heat as f (t)  vegetation and building heights  paved-surface fractions  drag-force coefficients for buildings & vegetation  building height-to-width, wall-plan, & impervious- area ratios  building frontal, plan, & and rooftop area densities  wall and roof: ε, cρ, α, etc.  vegetation: canopies, root zones, stomatal resistances

28. MM5 input-table urban z MM5 input-table urban z 0 z = 80 cm z 0 = 80 cm –Too low for tall-cities: obs up to 3-4 m –Urban-winds are thus too fast –Must adjust input: via GIS/RS = f(x,y) See next slide See next slide

29. S. Stetson: Houston GIS/RS z o input Values up 3 m Values are too large, as they were f(h) and not f(ơ h )

30. Urbanization  day & nite on same line  stability effects not important Martilli/EPFL q-results Martilli/EPFL q 2 -resultsNon-urban: urbanUrban model values > rooftop max > match obs

31. uMM5 for Houston: Balmori (2006) Goal: Accurate urban/rural temps & winds for Aug 2000 O 3 episode by use of > uMM5 > Taha-modified Houston LU/LC & urban morphology parameters: Additional processing of Burian parameters Additional processing of Burian parameters Modification of uMM5 to accept these data Modification of uMM5 to accept these data > TexAQS2000 field-study: met & 0 data > TexAQS2000 field-study: met & 0 3 data > USFS urban-reforestation scenarios  lower daytime: UHI-intensities & O 3 lower daytime: UHI-intensities & O 3

32.  GC influences: small  Air-mass movement first: along-shore (to east) due to flow along N-edge of cold-core atm-low  Then: from Ship Channel to Houston by Bay Breeze & then to Houston by UHI-con  max O 3 max O 3  Finally: NW of Houston by Gulf Breeze  Contours: 5 ppb (00-16 UTC) & then 10 ppb D-5: UTC episode-day obs of meso O 3 transport-patterns: influences of sea breeze & UHI-convergence

33. L H C Urban min + UHI Conv H Start of N-flow H L H L due to titration H Near-max O 3

34. uMM5 Simulation period: 22-26 August 2000 Model configuration Model configuration –5 domains: 108, 36, 12, 4, 1 km –(x, y) grid points: (43x53, 55x55, 100x100, 136x151, 133x141 –full-  levels: 29 in D 1-4 & 49 in D-5; lowest ½  level=7 m –2-way feedback in D 1-4 Parameterizations/physics options Parameterizations/physics options Grell cumulus (D 1-2)ETA or MRF PBL (D 1-4) Grell cumulus (D 1-2)ETA or MRF PBL (D 1-4) Gayno-Seaman PBL (D-5) Simple ice moisture, Gayno-Seaman PBL (D-5) Simple ice moisture, urbanization module NOAH LSM RRTM radiative cooling urbanization module NOAH LSM RRTM radiative cooling Inputs Inputs NNRP Reanalysis fields, ADP obs data NNRP Reanalysis fields, ADP obs data Burian urban morphology from LIDAR building-data in D-5 Burian urban morphology from LIDAR building-data in D-5 LU/LC modifications (from Byun)

35. Episode-day synoptics: 8/25, 12 UTC (08 DST) H H 700 hPa Surface 700 hPa & sfc GC H’s: at their weakest (no gradient) over Texas  meso-scale forcing (sea breeze & UHI-convergence) will dominate

36. Concurrent NNRP fields at 700 hPa & sfc H H NNRP-input to MM5 (as IC/BC) captured GC/synoptic features, as location & strength of high were similar to NWS charts (previous slide) D p=2 hPa

37. MM5: episode day, 3 PM > D–1: reproduces weak GC p-grad & flow > D-2: coastal (cold-core) L emerges (in weak form) > D-3: well formed L  along-shore V L D-1 D-2 D-3

38. Domain 4 (3 PM) : Note cold-core L off of Houston on O 3 day (25 th ) L L  Episode day day

39. Urbanized Domain 5: near-sfc 3 PM V on 4 successive days  Episode day day H C

40. Along-shore flow, 8/25 (episode day): obs at 1500 UTC vs uMM5 (D-5) at 2000 UTC Tx2000 obs HGA obs D-5 (red box) uMM5 captured HGA obs of along-shore flow (from SST- BC cold-low) HGA Kriege uMM5 C

41. 1 km uMM5 Houston UHI: 8 PM, 21 Aug Upper, L: MM5 UHI (2.0 K) Upper, L: MM5 UHI (2.0 K) Upper, R: uMM5 UHI (3.5 K) Upper, R: uMM5 UHI (3.5 K) Lower L: (uMM5-MM5) UHI Lower L: (uMM5-MM5) UHI LU/LC error

42. 8/23 Daytime 2-m UHI: obs vs uMM5 (D-5) H OBS: 1 PM uMM5: 3 PM Cold UHI

43. Along –shore flow came from Cold-Core L : D-3 MM5 vs Obs Temps MM5: produces coastal cold-core low Obs (18 UTC): > Cold-core L (only 1-ob) > Urban area (blue-dot clump) retards cold-air penetration C H H

44. UHI-Induced Convergence: obs vs. uMM5 OBSERVEDuMM5 C C

45. Obs speeds (m/s) in area of D-5: sfc roughness  speed-decrease over two Houston urban-cores - - - + + + + V

46. Base-case (current) vegetation cover in 0.1’s (urban min) Modeled increases in vegetation cover (urban max); values in 0.01’s

47. Soil moisture increase for: Run 12 (entire area, left) & Run 13 (urban area only, right)

48. Run 12 (urban-max reforestation) minus Run 10 (base case): near-sfc ∆T at 4 PM reforested central urban-area cools & surrounding deforested rural-areas warm

49. D UHI(t) for Base-case minus Runs 15-18 D UHI(t) for Base-case minus Runs 15-18 U1 sea Ru U2 UHI = Temp in urban-box minus Temp in rural-box UHI = Temp in urban-box minus Temp in rural-box Runs 15-18: different urban re-forestation scenarios Runs 15-18: different urban re-forestation scenarios D UHI=Run-17 UHI –Run-13 UHI (max effect, green line) D UHI=Run-17 UHI –Run-13 UHI (max effect, green line) Reduced UHI  lower max-O 3 (not shown)  Reduced UHI  lower max-O 3 (not shown)  EPA emission-reduction credits  $ saved  Max-impact of –0.9 K of a 3.5 K Noon-UHI, of which a 3.5 K Noon-UHI, of which 1.5 K was from uMM5

50. FUTURE WORK: uWRF Urbanize WRF with F. Chen at NCAR for DTRA Urbanize WRF with F. Chen at NCAR for DTRA –Martilli-Dupont-Taha urbanization –Freedman turbulence Possible applications Possible applications –Urban-canyon dispersion for DTRA (awarded) –NYC-ozone for EPA –Calif-ozone for CARB –Urban-thunderstorms for NSF –Urban wx-forecasting for NWS

51. THANKS! Any further questions?