Passive millimeter-wave retrieval of global precipitation utilizing satellites and a numerical weather prediction model

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 229-234).This thesis develops and validates the MM5/TBSCAT/F([lambda]) model, composed of a mesoscale numerical weather prediction (NWP) model (MM5), a two-stream radiative transfer model (TBSCAT), and electromagnetic models for icy hydrometeors (F([lambda])), to be used as a global precipitation ground-truth for evaluating alternative millimeter-wave satellite designs and for developing methods for millimeter-wave precipitation retrieval and assimilation. The model's predicted millimeter-wave atmospheric radiances were found to statistically agree with those observed by satellite instruments [Advanced Microwave Sounding Unit-A/B (AMSU-A/B)] on the United States National Ocean and Atmospheric Administration NOAA-15, -16, and -17 satellites over 122 global representative storms. Whereas such radiance agreement was found to be sensitive to assumptions in MM5 and the radiative transfer model, precipitation retrieval accuracies predicted using the MM5/TBSCAT/F([lambda]) model were found to be robust to the assumptions.(cont.) Appropriate specifications for geostationary microwave sounders and their precipitation retrieval accuracies were studied. It was found that a 1.2-m micro-scanned filled-aperture antenna operating at 118/166/183/380/425 GHz, which is relatively inexpensive, simple to build, technologically mature, and readily installed on a geostationary satellite, could provide useful observation of important global precipitation with ~20-km resolution every 15 minutes. AMSU global precipitation retrieval algorithms for retrieving surface precipitation rate, peak vertical wind, and water-paths for rainwater, snow, graupel, cloud water, cloud ice, and the sum of rainwater, snow, and graupel, over non-icy surfaces were developed separately using a statistical ensemble of global precipitation predicted by the MM5/TBSCAT/F([lambda]) model. Different algorithms were used for land and sea, where principal component analysis was used to attenuate unwanted noises, such as surface effects and angle dependence. The algorithms were found to perform reasonably well for all types of precipitation as evaluated against MM5 ground-truth. The algorithms also work over land with snow and sea ice, but with a strong risk of false detections. AMSU surface precipitation rates retrieved using the algorithm developed in this thesis reasonably agree with those retrieved for the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) aboard the Aqua satellite over both land and sea.(cont.) Surface precipitation rates retrieved using the Advanced Microwave Sounding Unit (AMSU) aboard NOAA-15 and -16 satellites were further compared with four similar products derived from other systems that also observed the United States Great Plains (USGP) during the summer of 2004. These systems include AMSR-E aboard the Aqua satellite, the Special Sensor Microwave/Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) F-13, -14, and -15 satellites, the passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) aboard the TRMM satellite, and a surface precipitation rate product (NOWRAD), produced and marketed by Weather Services International Corporation (WSI) using observations from the Weather Surveillance Radar-1988 Doppler (WSR-88D) systems of the Next-Generation Weather Radar (NEXRAD) program. The results show the reasonable agreement among these surface precipitation rate products where the difference is mostly in the retrieval resolution, which depends on instruments' characteristics. A technique for assimilating precipitation information from observed millimeter-wave radiances to MM5 model was proposed. Preliminary study shows that wind and other correction techniques could help align observations at different times so that information from observed radiances is used at appropriate locations.by Chinnawat Surussavadee.Ph.D

The FLASH project: using lightning data to better understand and predict flash floods

The FLASH project was implemented from 2006 to 2010 underthe EU FP6 framework. The project focused on using lightning observations to better understand and predict convective storms that result in flash floods. As part of the project 23 case studies of flash floods in the Mediterranean region were examined. For the analysis of these storms lightning data from the ZEUS network were used together with satellite derived rainfall estimates in orderto understand the storm development and electrification. In addition, these case studies were simulated using mesoscale meteorological models to better understand the meteorological and synoptic conditions leading up to these intense storms. As part of this project tools for short term predictions (nowcasts) of intenseconvection across the Mediterranean and Europe, and long term forecasts (a few days) of the likelihood of intense convection were developed. The project also focused on educationaloutreach through our website http://flashproject.orgsupplying real time lightning observations, real time experimental nowcasts, forecasts and educational materials. While flash floods and intense thunderstorms cannot be preventedas the climate changes, long-range regional lightning networks can supply valuable data, in realtime, for warningend-users and stakeholders of imminent intense rainfall and possible flash floods

Lightning-based propagation of convective rain fields

Abstract. This paper describes a new multi-sensor approach for continuously monitoring convective rain cells. It exploits lightning data from surface networks to propagate rain fields estimated from multi-frequency brightness temperature measurements taken by the AMSU/MHS microwave radiometers onboard NOAA/EUMETSAT low Earth orbiting operational satellites. Specifically, the method allows inferring the development (movement, morphology and intensity) of convective rain cells from the spatial and temporal distribution of lightning strokes following any observation by a satellite-borne microwave radiometer. Obviously, this is particularly attractive for real-time operational purposes, due to the sporadic nature of the low Earth orbiting satellite measurements and the continuous availability of ground-based lightning measurements – as is the case in most of the Mediterranean region. A preliminary assessment of the lightning-based rainfall propagation algorithm has been successfully made by using two pairs of consecutive AMSU observations, in conjunction with lightning measurements from the ZEUS network, for two convective events. Specifically, we show that the evolving rain fields, which are estimated by applying the algorithm to the satellite-based rainfall estimates for the first AMSU overpass, show an overall agreement with the satellite-based rainfall estimates for the second AMSU overpass

Precipitation products from the hydrology SAF

Abstract. The EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) was established by the EUMETSAT Council on 3 July 2005, starting activity on 1 September 2005. The Italian Meteorological Service serves as Leading Entity on behalf of twelve European member countries. H-SAF products include precipitation, soil moisture and snow parameters. Some products are based only on satellite observations, while other products are based on the assimilation of satellite measurements/products into numerical models. In addition to product development and generation, H-SAF includes a product validation program and a hydrological validation program that are coordinated, respectively, by the Italian Department of Civil Protection and by the Polish Institute of Meteorology and Water Management. The National Center of Aeronautical Meteorology and Climatology (CNMCA) of the Italian Air Force is responsible for operational product generation and dissemination. In this paper we describe the H-SAF precipitation algorithms and products, which have been developed by the Italian Institute of Atmospheric Sciences and Climate (in collaboration with the international community) and by CNMCA during the Development Phase (DP, 2005–2010) and the first Continuous Development and Operations Phase (CDOP-1, 2010–2012). The precipitation products are based on passive microwave measurements obtained from radiometers onboard different sun-synchronous low-Earth-orbiting satellites (especially, the SSM/I and SSMIS radiometers onboard DMSP satellites and the AMSU-A + AMSU-B/MHS radiometer suites onboard EPS-MetOp and NOAA-POES satellites), as well as on combined infrared/passive microwave measurements in which the passive microwave precipitation estimates are used in conjunction with SEVIRI images from the geostationary MSG satellite. Moreover, the H-SAF product generation and dissemination chain and independent product validation activities are described. Also, the H-SAF program and its associated activities that currently are being carried out or are planned to be performed within the second CDOP phase (CDOP-2, 2012–2017) are presented in some detail. Insofar as CDOP-2 is concerned, it is emphasized that all algorithms and processing schemes will be improved and enhanced so as to extend them to satellites that will be operational within this decade – particularly the geostationary Meteosat Third Generation satellites and the low-Earth-orbiting Core Observatory of the international Global Precipitation Measurement mission. Finally, the role of H-SAF within the international science and operations community is explained.</p

The GSMaP Precipitation Retrieval Algorithm for Microwave Sounders-Part I: Over-Ocean Algorithm

Abstract-We develop an over-ocean rainfall retrieval algorithm for the Advanced Microwave Sounding Unit (AMSU) based on the Global Satellite Mapping of Precipitation (GSMaP) microwave radiometer algorithm. This algorithm combines an emissionbased estimate from brightness temperature (Tb) at 23 GHz and a scattering-based estimate from Tb at 89 GHz, depending on a scattering index (SI) computed from Tb at both 89 and 150 GHz. Precipitation inhomogeneities are also taken into account. The GSMaP-retrieved rainfall from the AMSU (GSMaP_AMSU) is compared with the National Oceanic and Atmospheric Administration (NOAA) standard algorithm (NOAA_AMSU)-retrieved data using Tropical Rainfall Measuring Mission (TRMM) data as a reference. Rain rates retrieved by GSMaP_AMSU have better agreement with TRMM estimates over midlatitudes during winter. Better estimates over multitudes over winter are given by the use of Tb at 23 GHz in the GSMaP_AMSU algorithm. It was also shown that GSMaP_AMSU has higher rain detection than NOAA_AMSU. Index Terms-Microwave radiometer (MWR), microwave sounder, precipitation, rain-rate retrieval

Combined MW-IR Precipitation Evolving Technique (PET) of convective rain fields

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

Wind power forecasting and integration to power grids

This is a summary of the presentation in the special session: "Digital Signal Processing for Green Power Systems and Delivery". In recent years, wind power penetration level in power systems has increased significantly. Grid integration has become one of the major issues for wind power growth due to the intermittent characteristics of wind power. The uncertainty of power generation from wind farms may result in power system stability and security problems. Accurate wind power forecasting could reduce the uncertainty to generation scheduling to certain extent, hence increase the wind power penetration level in the system. © 2010 IEEE.published_or_final_versionThe 1st International Conference on Green Circuits and Systems (ICGCS 2010), Shanghai, China, 21-23 June 2010. In Proceedings of ICGCS, 2010, p. 555-56