The Relationship Between Total Precipitable Water and Precipitation The Relationship Between Total Precipitable Water and Precipitation RatesRates

Kelly HowellKelly Howell11, Stanley Q. Kidder, Stanley Q. Kidder22, and Thomas H. Vonder Haar, and Thomas H. Vonder Haar1,21,2

Howell@cira.colostate.edu1-Colorado State University Department of Atmospheric Science, Fort Collins, CO 80523-1371

2-DoD Center for Geosciences/Atmospheric Research; Cooperative Institute for Research in the Atmosphere, Fort Collins, CO 80523-1375

No Annual Cycle

With Annual Cycle

Introduction Mean TPW given Rain Rate

References

Study time: Feb. 2006 – Dec. 2008; 3924 casesStudy area: 60o N to 60o S6 hour time resolution0.25o spatial resolutionTotal Precipitable Water from CIRA bTPW product

Uses passive microwave sensorsAMSU, SSM/I instruments on 6 satellites

Precipitation Rate from CMORPH product

Uses passive microwave sensorsAMSU, SSM/I, TMI instruments on 7 satellites

Data

Joyce, R.J., J.E. Janowiak, P.A. Arkin, and P. Xie, 2004: CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution. J. Hydrometeor., 5,487-503.Kidder, S.Q. and A.S. Jones, 2007: A Blended Satellite Total Precipitable Water Product for Operational Forecasting. J. Atmos. Oceanic Technol., 24, 74-81.

AcknowledgementsThis research is supported by the DoD Center for

Geosciences/Atmospheric Research at Colorado State University under Cooperative Agreement

W911NF-06-2-0015 with the Army Research Laboratory.

Higher rain rates tend to correspond with higher TPW values:

Atmospheric water vapor is a necessary condition for precipitation. This poster displays distributions of precipitable water and precipitation rate. Blended Total Precipitable Water (bTPW) from the Cooperative Institute for Research in the Atmosphere (CIRA) is used for the water vapor data, and the Climate Prediction Center morphing method (CMORPH) is used for the precipitation rate. The relationship between these two quantities is potentially useful for several purposes, including predicting the probability of rain, analyzing the performance of models, and comparing satellite retrieval algorithms.

0< RR <0.1 mm/hr

Future Work

0.1< RR <0.5 mm/hr

0.5< RR <1.0 mm/hr

1.0< RR <2.0 mm/hr

RR > 2.0 mm/hr

Complete a more detailed analysis of TPW values in the different rain rate regimesQuantify seasonal differencesEstimate annual global precipitationCalculate distributions of rain rates in different TPW regimesIdentify climate regimes; these may affect how TPW relates to rain rate values in different regionsThis master’s thesis project is scheduled to conclude in summer 2010.

For higher rain rate values, the distribution of TPW is skewed toward higher values. For instance, for RR > 2.0 mm/hr, there are relatively few cases of TPW < 12.5 mm, whereas for 0.1< RR <0.5 mm/hr, those lower TPW values are more prevalent. The same pattern is present when mean

TPW given RR is plotted seasonally. All available cases were used to create the plots above.

Seasonal Variations in Mean Daily Rain

Rate

DJF:

MAM:

JJA:

SON:

Since the spatial distribution of rain rates varies with season, these plots demonstrate the importance of

investigating the seasonal differences of TPW and RR values. The relationship between the two quantities may

change with the season.