Howell Defense
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Howell Defense



Thesis defense presentation, successfully defended July 2010.

Thesis defense presentation, successfully defended July 2010.



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Howell Defense Howell Defense Presentation Transcript

  • Quasi-Global and Regional Water Vapor and Rainfall Rate Climatologies for a 35 Month Period Kelly Howell MS Thesis Defense July 9, 2010
  • Acknowledgements
    • Tom Vonder Haar and Stan Kidder, advisor and co-advisor, for their many suggestions on the direction of this project and confidence in my success
    • Chris Kummerow and Jorge Ramírez, committee members, for their time in reviewing this work
    • Eric Guillot and Jessica Ram, officemates, for their continual encouragement, suggestions, and distractions
    • Family and friends for their support and readiness to listen
    • DoD Center for Geosciences/Atmospheric Research at CSU under Cooperative Agreement W911NF-06-2-0015 with the Army Research Laboratory for funding this research
  • Introduction
  • Motivation
    • Use new datasets to create total precipitable water (TPW) and rainfall rate (RR) climatologies
    • Further investigate the relationship between TPW and RR with the hopes of improving rain forecasting techniques:
      • In areas lacking adequate forecasting capabilities
      • In areas that may experience flood-inducing rainfall
  • September 5, 2008 at 00 UTC Areas with elevated TPW are often associated with instances of rainfall. Hurricane Ike
  • Domain
    • Spatially, the data cover 60 o S to 60 o N at all longitudes at 0.25 o ×0.25 o resolution.
    • CMORPH covers the entire domain; bTPW covers the oceans. Over the continental US, bTPW is supplemented by GPS TPW estimates.
    • Temporally, both datasets were sampled 6-hourly from February 2006 to December 2008 and used at 00, 06, 12, and 18 UTC.
    • In all, 3928 time periods were used in this analysis, or approximately 92% of the temporal domain.
  • Data
    • Total precipitable water (TPW) is the total atmospheric water vapor in a vertical column, measured in mm. Data in this study come from the CIRA blended TPW product (bTPW), which combines TPW measurements from 6 instruments (Kidder and Jones 2007).
    • Rainfall rate (RR) is the amount of rain that falls during a given amount of time. The data in this study come from the CPC morphing method product (CMORPH), which combines RR measurements from 7 instruments and uses an IR-based advection technique to fill in missing data (Joyce et al. 2004).
    • In this project, ‘rainfall’ implies a RR≥0.1 mm hr -1 .
  • Satellite Instruments Conical Cross-track Conical Cross-track Conical Scan Type Kummerow et al. 1996 10, 19, 21, 37, 85 GHz TMI TRMM Ferraro et al. 2005 89, 150, 183 GHz AMSU-B NOAA-15, -16, -17 Ferraro 1997 19, 22, 37, 85.5 GHz SSM/I DMSP F-13, -14, -15 RR Ferraro et al. 2005 23.8, 31.4 GHz AMSU-A2 NOAA-15, -16, -17 Ferraro et al. 1996 19, 22, 37 GHz SSM/I DMSP F-13, -14, -15 TPW Source Channels Used Sensor Satellites Data type
  • Total Precipitable Water Climatology
  • Annual Mean TPW (Trenberth 1998) Mean global TPW is 24.52 mm (Trenberth et al. 2003). TPW maximizes north of the equator around 45 mm.
  • Annual Mean TPW The global mean TPW is 24.94 mm, with a maximum of approximately 45 mm north of the equator. West Pacific Warm Pool SPCZ ITCZ Oceanic Deserts
  • Seasonal Mean TPW (Ferraro et al. 1996) The seasonal changes in TPW are evident, particularly in the west Pacific warm pool during the JJA monsoon period and in the eastward advancement of the SPCZ during DJF. In addition, the northernmost latitudes display their highest TPW values during JJA and the southernmost latitudes display their highest TPW values during DJF, following the seasonal changes in solar insolation.
  • Seasonal Mean TPW The seasonal TPW distributions are similar to previous findings, with the SPCZ extending its farthest eastward during DJF and TPW highs around southeast Asia during the JJA monsoon period. The presence of a double ITCZ can be detected in the eastern tropical Pacific during MAM. However, TPW values in the ITCZ are lower than the findings by Ferraro et al. (1996).
  • Rainfall Climatology
  • Global Mean RR in mm day -1 (Legates and Willmott 1990) Over land, rainfall maximizes over the Amazon Basin and the African rainforests. Over the ocean, the most rainfall occurs in the ITCZ, the west Pacific warm pool, and the SPCZ. This plot was constructed based on rain gauge measurements. On average, ocean surfaces receive the most rainfall while land surfaces receive the least. Source: Xie and Arkin (1997). Source Surface Type RR [mm day -1 ] CMAP Ocean 3.02 Land 1.86 Globe 2.69 Jaeger (1976) Ocean 2.91 Land 2.01 Globe 2.66 LW (1990) Ocean 3.15 Land 1.97 Globe 2.82
  • Annual Mean RR in mm day -1 The oceans receive more rainfall than land surfaces. The ITCZ receives the most rainfall; the oceanic deserts receive the least. Surface Type RR [mm day -1 ] Ocean 2.68 Land 2.57 All Surfaces 2.63
  • Annual Mean RR in mm year -1 (Ferraro et al. 1996) Over land, rainfall maximizes just south of the equator. Over the oceans, there is a double peak in the tropics, maximizing north of the equator. The solid lines indicate Ferraro et al.’s (1996) findings; the dashed lines indicate findings from Legates and Willmott (1990).
  • Annual Mean RR in mm year -1 The zonal mean RR distributions over ocean and land display similar trends to the findings by Ferraro et al. (1996), although these estimations are slightly higher. Latitude (degrees N)
  • Annual Mean Rainfall Frequency The zonal distributions of rainfall frequency are analogous to the zonal distributions of rainfall. Overall, the oceans receive rain more frequently (11.04 %) than land surfaces (8.58 %). Latitude (degrees N) Rainfall frequency = 100× Latitude Zone Ocean Frequency Land Frequency 60-45 o N 10.99 % 4.68 % 45-30 o N 12.72 % 5.65 % 30-15 o N 7.56 % 5.15 % 15-0 o N 16.48 % 13.91 % 0-15 o S 11.02 % 16.41 % 15-30 o S 7.63 % 6.90 % 30-45 o S 11.32 % 5.91 % 45-60 o S 10.23 % 5.19 %
  • Seasonal Mean RR in mm month -1 (Ferraro et al. 1996) Seasonal mean rainfall tends to follow the patterns of seasonal mean TPW, with the SPCZ extending its farthest eastward in DJF and monsoonal rains occurring over southeast Asia during JJA. Also notable is the presence of a southern branch of the ITCZ during MAM.
  • Seasonal Mean RR in mm month -1 Seasonal mean rainfall estimates from CMORPH are similar to the findings by Ferraro et al. (1996). The NH and SH land areas show large changes between DJF and JJA: the winter hemisphere’s land areas receive very little rainfall.
  • Seasonal Mean Rainfall Frequency (Ferraro et al. 1996) Seasonal rainfall frequency patterns mimic rainfall patterns, with more frequent rain occurring over the areas that typically receive more rainfall.
  • Seasonal Mean Rainfall Frequency The global frequency distribution estimates are much higher than those found by Ferraro et al. (1996), although the same patterns are present. Using the 0.1 mm hr -1 threshold, global frequencies hover around 10%. Season 0.1 mm hr -1 0.5 mm hr -1 1.0 mm hr -1 DJF 10.31 % 4.88 % 2.76 % MAM 10.30 % 4.79 % 2.76 % JJA 10.17 % 5.00 % 2.92 % SON 10.09 % 4.95 % 2.88 %
  • Regional Studies
  • TPW Threshold for Rainfall? Average rainfall rate versus column water vapor for the eastern Pacific at various tropospheric temperatures. 25% of the rainfall occurs for TPW values above a ‘critical value.’ Time series of (a) RR in mm hr -1 , (b) TPW in mm, and (c) global solar radiation at the Koto Tabang GPS station during JJA 2001. Rainfall does not tend to occur at times with relatively low TPW. Source: Wu et al. (2003) Source: Neelin et al. (2009)
  • Regional Studies The following plots were constructed using the data at each of these grid points analyzed over all 35 months. Location Longitude Latitude East of Florida 70 o W 30 o N Indian Ocean 75 o E 8 o S East of Japan 142 o E 35 o N South of Panama 83 o W 4 o N South Atlantic Ocean 22 o W 45 o S North Atlantic Ocean 30 o W 50 o N West Pacific 155 o E 6 o N Southeastern Pacific 120 o W 8 o S SPCZ 170 o E 10 o S
  • TPW Distributions Annual mean TPW is highly variable in the midlatitude location, relatively high in the tropical location, and relatively low in the oceanic desert location. TPW (mm) Location Mean TPW East of Florida 30.66 mm West Pacific 54.28 mm Southeastern Pacific 29.62 mm
  • RR Distributions Equation of exponential decay. A more negative slope indicates a faster rate of decay (i.e., there are relatively few heavy rain events). More negative slopes tend to be associated with lower rainfall frequencies. RR [mm hr -1 ] Location Slope of Fit Rainfall Frequency East of Florida -0.58 11.11 % West Pacific -0.516 31.20 % Southeastern Pacific -1.556 2.29 %
  • RR vs TPW The shapes of these distributions approximate the TPW distributions. In general, the higher RRs occur at the more frequently occurring TPW values. However, this is not the case in the southeastern Pacific, where the highest RRs occur at higher TPW values. TPW (mm)
  • Probability of Rainfall RR ≥ 0.1 mm hr -1 RR ≥ 3.0 mm hr -1 As rain intensity increases, rainfall becomes less likely at lower TPW values. TPW (mm)
  • RR Distributions by TPW Range
  • RR Distribution by TPW Range At higher TPW values, rainfall is more probable and there is a higher proportion of heavier rainfall. RR [mm hr -1 ] TPW Range Probability of Rainfall 0-15 mm 2.34 % 15-30 mm 7.64 % 30-45 mm 16.59 % 45-60 mm 29.89 % 60-75 mm 45.89 %
  • RR Distribution by TPW Range The RR distributions are not strictly exponential, but an exponential fit is a consistent representation of the distribution. Steeper slopes are associated with drier environments. RR [mm hr -1 ] TPW Range Slope of RR Distribution 0-15 mm -1.01 15-30 mm -0.90 30-45 mm -0.70 45-60 mm -0.59 60-75 mm -0.49
  • Conclusions
    • The bTPW and CMORPH datasets result in climatologies that are comparable to those from previous studies. TPW, rainfall, and rainfall frequency are the highest in the ITCZ, SPCZ, and west Pacific warm pool, and the lowest in oceanic desert regions.
    • Quasi-global mean TPW is 24.94 mm.
    • Quasi-global mean RR is 2.63 mm day -1 .
    • The ocean receives rainfall in greater quantities and more frequently compared with land surfaces.
    • In a global mean sense, rainfall is more probable and higher RRs are more frequent at higher TPW values.
  • Future Work
    • Extend this study over land areas when an accurate TPW dataset over land becomes available.
    • Incorporate CloudSat estimates into the RR results in order to better measure lighter rainfall events.
    • Because TPW may not be detected when rain is present, estimate missing the TPW values in order to create more robust statistics.
    • Use TPW anomaly data to compare with occurrences of rainfall.
    • Incorporate regional TPW and RR characteristics into forecast and climate models.
  • Questions?