Abstract
Abstract. This paper describes a new multi-sensor approach for convective rain cell continuous monitoring based on rainfall derived from Passive Microwave (PM) remote sensing from the Low Earth Orbit (LEO) satellite coupled with Infrared (IR) remote sensing Brightness Temperature (TB) from the Geosynchronous (GEO) orbit satellite. The proposed technique, which we call Precipitation Evolving Technique (PET), propagates forward in time and space the last available rain-rate (RR) maps derived from Advanced Microwave Sounding Units (AMSU) and Microwave Humidity Sounder (MHS) observations by using IR TB maps of water vapor (6.2 μm) and thermal-IR (10.8 μm) channels from a Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer. PET is based on two different modules, the first for morphing and tracking rain cells and the second for dynamic calibration IR-RR. The Morphing module uses two consecutive IR data to identify the motion vector to be applied to the rain field so as to propagate it in time and space, whilst the Calibration module computes the dynamic relationship between IR and RR in order to take into account genesis, extinction or size variation of rain cells. Finally, a combination of the Morphing and Calibration output provides a rainfall map at IR space and time scale, and the whole procedure is reiterated by using the last RR map output until a new MW-based rainfall is available. The PET results have been analyzed with respect to two different PM-RR retrieval algorithms for seven case studies referring to different rainfall convective events. The qualitative, dichotomous and continuous assessments show an overall ability of this technique to propagate rain field at least for 2–3 h propagation time.
Highlights
The ability to estimate convective precipitation with a high level of accuracy, by using Passive Microwave (PM) from radiometers onboard satellites, has been well known for several years (Ebert et al, 1996; Smith et al, 1998; Kummerow et al, 2001), since the launch of the first Special Sensor Microwave/Imager (SSM/I) radiometer in 1987 – and especially after the launch of the Tropical Rainfall Measuring Mission (TRMM) space observatory in 1997
This paper focuses on the evaluation of the Precipitation Evolving Technique (PET) algorithm in reproducing the Advanced Microwave Sounding Units (AMSU)/Microwave Humidity Sounder (MHS)-based rain-rate estimates when these instruments are not passing over the region
To exclude the uncertainties related to the performance of the AMSU/MHS-based retrieval algorithm from the evaluation of PET results, it is more interesting to compare the PET performance versus the first available AMSU/MHS-based retrieved rain field successive to that used for initializing PET algorithm
Summary
The ability to estimate convective precipitation with a high level of accuracy, by using Passive Microwave (PM) from radiometers onboard satellites, has been well known for several years (Ebert et al, 1996; Smith et al, 1998; Kummerow et al, 2001), since the launch of the first Special Sensor Microwave/Imager (SSM/I) radiometer in 1987 – and especially after the launch of the Tropical Rainfall Measuring Mission (TRMM) space observatory in 1997. We describe the PET algorithm which is a new combined MW-IR technique that employs IR observations from GEO satellite to propagate forward in time the rain field of convective storms. 10.8 μm brightness temperatures allows to recognize convective areas in a better way than the use of a single IR channel, highly reducing the number of false alarms such as those caused by the cirrus or others non-precipitating clouds that are one of the error main sources of some IR-based rainrate estimate techniques Another reason to use a 6.2 μm and 10.8 μm brightness temperature combination instead of a single thermal-IR radiance is that the latter shows very small variation, while GCD value tends to decrease from the core convective cell to the anvil region.
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