General Circulation Patterns (a) Tropical atmosphere expands, polar atmosphere contracts, causing air to flow poleward at the upper levels (b) Redistribution of mass causes high pressure at poles, low pressure in tropics, causing equatorward flow at the surface (c) Coriolis force imparts a westward component to the equatorward flow and an eastward component to the poleward flow (d) Spontaneous instability imparts a wave-like character to the eastward flow in the midlatitudes Source: Wallace, J. M. and P. V. Hobbs, 2006: Atmospheric Science: An Introductory Survey. Elsevier Inc. , 483 pp.
Angular Momentum When an air parcel moves closer to the axis of rotation (i.e., poleward), the relative eastward velocity must increase to conserve angular momentum When an air parcel moves farther from the axis of rotation (i.e., equatorward), the relative westward velocity must increase to conserve angular momentum
High Surface Pressure Associated with sinking motion and export of water vapor Low Surface Pressure Associated with rising motion and import of water vapor Source: Wallace, J. M. and P. V. Hobbs, 2006: Atmospheric Science: An Introductory Survey. Elsevier Inc. , 483 pp.
September 5, 2008 at 00 UTC Oceanic Deserts Midlatitudes Subtropics Tropics Subtropics Midlatitudes West Pacific Warm Pool SPCZ ITCZ
A warm, moist surface air parcel rises due to its relative buoyancy.
As the parcel rises, it cools, bringing its vapor pressure closer to saturation
Sources: http://asd-www.larc.nasa.gov/edu_act/clouds.html, Wallace, J. M. and P. V. Hobbs, 2006: Atmospheric Science: An Introductory Survey. Elsevier Inc. , 483 pp. Condensation<Evaporation Condensation=Evaporation p=ρRT Vapor pressure: the pressure exerted by water vapor on its environment Cooler air requires less water vapor to reach saturation, by the Clausius-Clapeyron equation.
Visible and infrared radiation cannot penetrate through clouds, so we use longer microwave radiation, which can.
Microwave radiation in this study is in the range:
10.7– 183.3 GHz, or
28.04 – 1.64 mm
Source: Kidder, S. Q., and T. H. Vonder Haar, 1995: Satellite Meteorology: An Introduction. Academic Press , 456 pp. 19 GHz: window region 22 GHz: sensitive to water vapor 37 GHz: attenuated by clouds and rain drops >85 GHz: sensitive to ice
Detecting Total Precipitable Water Ocean ε ~ 0.5 (‘cold’ background) Low, constant emissivity Variable amounts of water vapor are easily detectable Land ε ~ 0.9 (‘warm’ background) High, highly variable emissivity Variable amounts of water vapor are harder to detect
Over the ocean, water vapor increases the brightness temperature above what it would be from a cold ocean background alone.
The bTPW dataset is mostly over the ocean for this reason.
0.5 T B (cold) 1.0 T B (warm) 1.0 T B (warm) 0.9 T B (warm)
Over the ocean, emission from rain drops acts to increase the brightness temperature above the surface emission temperature.
Over land surfaces, the scattering of precipitation-sized ice acts oppositely, lowering the brightness temperature below what would have been observed for a land background alone.
Ocean ε ~ 0.5 (‘cold’ background) Low, constant emissivity Radiation emitted from rain drops and scattered from ice particles is detected Land ε ~ 0.9 (‘warm’ background) High, highly variable emissivity Radiation scattered from ice particles is detected 0.5 T B (cold) 0.9 T B (warm) 1.0 T B (warm) scattering (cools) scattering (cools)
Total Precipitable Water and Rainfall Climatology
Annual Mean TPW The global mean TPW is 24.94 mm, with a maximum of approximately 45 mm just north of the equator.
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.
Annual Mean RR in mm day -1 Source: Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc. , 78 , 2539-2558. Surface Type (CMORPH) RR [mm day -1 ] Ocean 2.68 Land 2.57 All Surfaces 2.63 Surface Type (CMAP) RR [mm day -1 ] Ocean 3.02 Land 1.86 Globe 2.69
Annual Mean RR in mm year -1 The zonal mean RR distribution over land is fairly symmetric, while the oceanic distribution peaks in the tropics and has secondary peaks in the midlatitudes. 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 than land surfaces, but land surfaces receive heavy rain more frequently than ocean surfaces. Latitude (degrees N) Rainfall frequency = 100× 0.07 % 0.03 % 10.0 mm hr -1 0.34 % 0.27 % 5.0 mm hr -1 RR Threshold 8.58 % 11.04 % 0.1 mm hr -1 Land Ocean Surface Type
Seasonal Mean RR in mm month -1 Seasonal mean rainfall estimates from CMORPH are similar to previous findings (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 Rainfall frequency maximizes in the expected areas: the ITCZ, SPCZ, and eastern storm tracks. Rain falls infrequently in desert regions. Using the 0.1 mm hr -1 threshold, quasi-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 %
TPW Threshold for Rainfall? Time series of (a) RR in mm hr -1 , (b) TPW in mm, and (c) global solar radiation at the Koto Tabang GPS station on Sumatra Island during JJA 2001. Rainfall does not tend to occur at times with relatively low TPW. Source: Wu, P., J.-I. Hamada, S. Mori, Y. I. Tauhid, M. D. Yamanaka, and F. Kimura, 2003: Diurnal variation of precipitable water over a mountainous area of Sumatra Island. J. Appl. Meteorol. , 42 , 1107-1115.
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 Higher-intensity rainfall is less likely at lower TPW values. TPW (mm)
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
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.
The ocean receives rainfall in greater quantities and more frequently compared with land surfaces, but land surfaces receive heavier rainfall more frequently.
A RR distribution forms an approximate exponenetial decay, with the slope of the exponential fit related to the frequency of the rainfall, with more negative slopes being associated with lower rainfall frequency
Even at very high TPW values, the probability of rainfall is only about 50 %. Relatively high TPW is only one factor in the production of rain.
In a global mean sense, higher TPW values are associated with more rainfall and higher RRs. But because dynamical patterns are so critical to rainfall production, using TPW to forecast rainfall is only appropriate when done for a particular region since this study does not correct for dynamical variability.