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Hong Ye and Riyu Lu

Abstract

The findings of the study reported in this paper show that, during ENSO decaying summers, rainfall and circulation anomalies exhibit clear subseasonal variation. Corresponding to a positive (negative) December–February (DJF) Niño-3.4 index, a positive (negative) subtropical rainfall anomaly, with a southwest–northeast tilt, appears in South China and the western North Pacific (WNP) in the subsequent early summer (from June to middle July) but advances northward into the Huai River Basin in China as well as Korea and central Japan in late summer (from late July to August). Concurrently, a lower-tropospheric anticyclonic anomaly over the WNP extends northward from early to late summer. The seasonal change in the basic flows, characterized by the northward shift of the upper-tropospheric westerly jet and the WNP subtropical high, is suggested to be responsible for the differences in the above rainfall and circulation anomalies between early and late summer by inducing distinct extratropical responses even under the almost identical tropical forcing of a precipitation anomaly in the Philippine Sea.

A particular focus of the study is to investigate, using station rainfall data, the subseasonal variations in ENSO-related rainfall anomalies in eastern China since the 1950s, to attempt to examine their role in weakening the relationship between the ENSO and summer mean rainfall in eastern China since the late 1970s. It is found that the ENSO-related rainfall anomalies tend to be similar between early and late summer before the late 1970s, that is, the period characterized by a stronger ENSO–summer mean rainfall relationship. After the late 1970s, however, the anomalous rainfall pattern in eastern China is almost reversed between early and late summer, resulting accordingly in a weakened relationship between the ENSO and total summer rainfall in eastern China.

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Ye Hong and Hyo-Suk Lim

Abstract

Evidence for the 30–60-day oscillation was found in the rainfall data that were retrieved from Special Sensor Microwave/Imager brightness temperatures from January to December 1989. Spectral analysis of daily rainfall showed that the strongest rainfall oscillations were located from 5°S to 5°N and extend from about 60°E to 180°. The oscillation propagated eastward at a speed of approximately 4 m s−1 along the equatorial Indian–western Pacific Ocean area. Northward propagation at a speed of about 1.5 m s−1 was also detected from 15°S to 30°N over the Indian Ocean between early May and late July.

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Nicolas Viltard, Christian Kummerow, William S. Olson, and Ye Hong

Abstract

A combination of passive microwave and radar observations from the Tropical Rainfall Measuring Mission (TRMM) satellite is used to investigate the consistency between the two sensors. Rather than relying on some absolute “truth” to verify retrievals, this paper focuses on one assumption—namely, the drop size distribution (DSD)—and how different DSDs lead to improved or reduced consistency. Results from a case in the central Pacific suggest that a crude consistency may be achieved if a different drop size is used for the radiometer and the radar. In this particular case, a Marshall–Palmer or a gamma distribution with the shape parameters properly set leads to similar results. Although this study offers no independent validation of its conclusions, it does demonstrate that rainfall validation need not be confined to surface rainfall measurements, which are only loosely related to the volumetric observations made by most sensors. As mean size distributions of raindrops are measured in the TRMM field experiments by disdrometers, profilers, multiparameter radars, and direct aircraft observations, the technique presented in this paper can be applied on a storm-by-storm basis, and conclusions can be verified directly.

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Ye Hong, Christian D. Kummerow, and William S. Olson

Abstract

This paper presents a new scheme that classifies convective and stratiform (C/S) precipitation areas over oceans using microwave brightness temperature. In this scheme, data are first screened to eliminate nonraining pixels. For raining pixels, C/S indices are computed from brightness temperatures and their variability for emission (19 and 37 GHz) and scattering (85 GHz). Since lower-resolution satellite data generally contain mixtures of convective and stratiform precipitation, a probability matching method is employed to relate the C/S index to a convective fraction of precipitation area.

The scheme has been applied on synthetic data generated from a dynamical cloud model and radiative transfer computations to simulate the frequencies and resolutions of the Tropical Rainfall Measuring Mission (TRMM) Microwave (TMI) Imager as well as the Special Sensor Microwave/Imager (SSM/I). The results from simulated TMI data during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment agree very well with the ground-based radar classification maps. The classification accuracy degrades when SSM/I data is used, due largely to the lower spatial resolution of the SSM/I.

The successful launch of TRMM satellite in November 1997 has made it possible to test this scheme on actual TMI data. Preliminary results of TMI derived C/S classification compared with that from the first spaceborne precipitation radar has shown a very good agreement. Further verification and improvement of this scheme are under way.

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Ye Hong, Thomas T. Wilheit, and William R. Russell

Abstract

A physical–statistical monthly rainfall retrieval algorithm has been developed using multichannel brightness temperatures from the Special Sensor Microwave/Imager (SSM/I). Since an emission-based retrieval algorithm gives the most physically direct estimation of rainfall over oceans, instantaneous rain rates are retrieved using brightness temperature–rain rate (TR) relationships derived from a radiative transfer model. The retrieved rain rates, however, are only reliable and useful over a portion of a whole dynamic range of rain rate due to limitations of the emission-based algorithm. When monthly rainfall in a 5° × 5° box is estimated, the instantaneous rain-rate samples are actually truncated. The method used in this study assumes that monthly rainfall intensity in a 5° × 5° box has a mixed lognormal distribution. Thus, the contribution of the rain rates outside of the dynamic range can be estimated by extrapolation. Coefficients of the mixed lognormal distribution are determined by fitting the truncated rain-rate samples to the lognormal form using a maximum likelihood estimate method. The beamfilling error is corrected by a multiplicative factor generated from simulation studies. Comparison between the monthly rainfall estimated from the SSM/I and Pacific atoll data indicates that the algorithm works very well in tropical areas. Although this algorithm is tested on SSM/I data, it is also suited for the Tropical Rainfall Measuring Mission data, which should have a larger dynamic range with 10.7-GHz channels added.

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Kai Wang, Hong Ye, Feng Chen, Yongzhu Xiong, and Cuiping Wang

Abstract

Based on the 1960–2009 meteorological data from 559 stations across China, the urbanization effect on the diurnal temperature range (DTR) was evaluated in this study. Different roles of urbanization were specially detected under solar dimming and solar brightening. During the solar dimming time, both urban and rural stations showed decreasing trends in maximum temperature (T max) because of decreased radiation, suggesting that the dimming effects are not only evident in urban areas but also in rural areas. However, minimum temperature (T min) increased more substantially in urban areas than in rural areas during the dimming period, resulting in a greater decrease in the DTR in the urban areas. When the radiation reversed from dimming to brightening, the change in the DTR became different. The T max increased faster in rural areas, suggesting that the brightening could be much stronger in rural areas than in urban areas. Similar trends of T min between urban and rural areas appeared during the brightening period. The urban DTR continued to show a decreasing trend because of the urbanization effect, while the rural DTR presented an increasing trend. The remarkable DTR difference in the urban and rural areas showed a significant urbanization effect in the solar brightening time.

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William S. Olson, Ye Hong, Christian D. Kummerow, and Joseph Turk

Abstract

Observational and modeling studies have revealed the relationships between convective–stratiform rain proportion and the vertical distributions of vertical motion, latent heating, and moistening in mesoscale convective systems. Therefore, remote sensing techniques that can be used to quantify the area coverage of convective or stratiform rainfall could provide useful information regarding the dynamic and thermodynamic processes in these systems. In the current study, two methods for deducing the area coverage of convective precipitation from satellite passive microwave radiometer measurements are combined to yield an improved method. If sufficient microwave scattering by ice-phase precipitation is detected, the method relies mainly on the degree of polarization in oblique-view, 85.5-GHz radiances to estimate the fraction of the radiometer footprint covered by convection. In situations where ice scattering is minimal, the method draws mostly on texture information in radiometer imagery at lower microwave frequencies to estimate the convective area fraction.

Based upon observations of 10 organized convective systems over ocean and nine systems over land, instantaneous, 0.5°-resolution estimates of convective area fraction from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are compared with nearly coincident estimates from the TRMM precipitation radar (PR). TMI convective area fraction estimates are low-biased relative to PR estimates, with TMI–PR correlation coefficients of 0.78 and 0.84 over ocean and land surfaces, respectively. TMI monthly average convective area percentages in the Tropics and subtropics from February 1998 are greatest along the intertropical convergence zone and in the continental regions of the Southern (summer) Hemisphere. Although convective area percentages from the TMI are systematically lower than those derived from the PR, the monthly patterns of convective coverage are similar. Systematic differences in TMI and PR convective area percentages do not show any clear correlation or anticorrelation with differences in retrieved rain depths, and so discrepancies between TRMM version-5 TMI- and PR-retrieved rain depths are likely due to other sensor or algorithmic differences.

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Jian-Sheng Ye, Yan-Hong Gong, Feng Zhang, Jiao Ren, Xiao-Ke Bai, and Yang Zheng

Abstract

Intensifying climate extremes are one of the major concerns with climate change. Using 100-yr (1911–2010) daily temperature and precipitation records worldwide, 28 indices of extreme temperature and precipitation are calculated. A similarity percentage analysis is used to identify the key indices for distinguishing how extreme warm and cold years (annual temperature above the 90th and below the 10th percentile of the 100-yr distribution, respectively) differ from one another and from average years, and how extreme wet and dry years (annual precipitation above the 90th and below the 10th percentile of the 100-yr distribution, respectively) differ from each other and from average years. The analysis suggests that extreme warm years are primarily distinguished from average and extreme cold years by higher occurrence of warm nights (annual counts when night temperature >90th percentile), which occur about six more counts in extreme warm years compared with average years. Extreme wet years are mainly distinguished from average and extreme dry years by more occurrences of heavy precipitation events (events with ≥10 mm and ≥20 mm precipitation). Compared with average years, heavy events occur 60% more in extreme wet years and 50% less in extreme dry years. These indices consistently differ between extreme and average years across terrestrial ecoregions globally. These key indices need to be considered when analyzing climate model projections and designing climate change experiments that focus on ecosystem response to climate extremes.

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William S. Olson, Peter Bauer, Christian D. Kummerow, Ye Hong, and Wei-Kuo Tao

Abstract

The one-dimensional, steady-state melting-layer model developed in Part I of this study is used to calculate both the microphysical and radiative properties of melting precipitation, based upon the computed concentrations of snow and graupel just above the freezing level at applicable horizontal grid points of three-dimensional cloud-resolving model simulations. The modified 3D distributions of precipitation properties serve as input to radiative transfer calculations of upwelling radiances and radar extinction/reflectivities at the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) frequencies, respectively. At the resolution of the cloud-resolving model grids (∼1 km), upwelling radiances generally increase if mixed-phase precipitation is included in the model atmosphere. The magnitude of the increase depends upon the optical thickness of the cloud and precipitation, as well as the scattering characteristics of the mixed-phase particles and ice-phase precipitation aloft. Over the set of cloud-resolving model simulations utilized in this study, maximum radiance increases of 43, 28, 18, and 10 K are simulated at 10.65, 19.35, 37.0, and 85.5 GHz, respectively. The impact of melting on TMI-measured radiances is determined not only by the physics of the melting particles but also by the horizontal extent of the melting precipitation, given that the lower-frequency channels have footprints that extend over tens of kilometers. At TMI resolution, the maximum radiance increases are 16, 15, 12, and 9 K at the same frequencies. Simulated PR extinction and reflectivities in the melting layer can increase dramatically if mixed-phase precipitation is included, a result consistent with previous studies. Maximum increases of 0.46 (−2 dB) in extinction optical depth and 5 dB in reflectivity are simulated based upon the set of cloud-resolving model simulations.

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William S. Olson, Christian D. Kummerow, Ye Hong, and Wei-Kuo Tao

Abstract

A method for the remote sensing of three-dimensional latent heating distributions in precipitating tropical weather systems from satellite passive microwave observations is presented. In this method, cloud model simulated hydrometeor/latent heating vertical profiles that have radiative characteristics consistent with a given set of multispectral microwave radiometric observations are composited to create a best estimate of the observed profile. An estimate of the areal coverage of convective precipitation within the radiometer footprint is used as an additional constraint on the contributing model profiles. This constraint leads to more definitive retrieved profiles of precipitation and latent heating in synthetic data tests.

The remote sensing method is applied to Special Sensor Microwave/Imager (SSM/I) observations of tropical systems that occurred during the TOGA COARE Intensive Observing Period, and to observations of Hurricane Andrew (1992). Although instantaneous estimates of rain rates are high-biased with respect to coincident radar rain estimates, precipitation patterns are reasonably correlated with radar patterns, and composite rain rate and latent heating profiles show respectable agreement with estimates from forecast models and heat and moisture budget calculations. Uncertainties in the remote sensing estimates of precipitation/latent heating may be partly attributed to the relatively low spatial resolution of the SSM/I and a lack of microwave sensitivity to tenuous anvil cloud, for which upper-tropospheric latent heating rates may be significant. Estimated latent heating distributions in Hurricane Andrew exhibit an upper-level heating maximum that strengthens as the storm undergoes a period of intensification.

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