Tropical Rainfall Measuring Mission Satellite Research Articles

Response of African elephants (Loxodonta africana) to seasonal changes in rainfall.

The factors that trigger sudden, seasonal movements of elephants are uncertain. We hypothesized that savannah elephant movements at the end of the dry season may be a response to their detection of distant thunderstorms. Nine elephants carrying Global Positioning System (GPS) receivers were tracked over seven years in the extremely dry and rugged region of northwestern Namibia. The transition date from dry to wet season conditions was determined annually from surface- and satellite-derived rainfall. The distance, location, and timing of rain events relative to the elephants were determined using the Tropical Rainfall Measurement Mission (TRMM) satellite precipitation observations. Behavioral Change Point Analysis (BCPA) was applied to four of these seven years demonstrating a response in movement of these elephants to intra- and inter-seasonal occurrences of rainfall. Statistically significant changes in movement were found prior to or near the time of onset of the wet season and before the occurrence of wet episodes within the dry season, although the characteristics of the movement changes are not consistent between elephants and years. Elephants in overlapping ranges, but following separate tracks, exhibited statistically valid non-random near-simultaneous changes in movements when rainfall was occurring more than 100 km from their location. While the environmental trigger that causes these excursions remains uncertain, rain-system generated infrasound, which can travel such distances and be detected by elephants, is a possible trigger for such changes in movement.

The dominant synoptic‐scale modes of North American monsoon precipitation

ABSTRACTIn this study, we explore the mechanisms of synoptic rainfall variability using observations from the Tropical Rainfall Measuring Mission satellite. Although previously shown to have an important impact on North American monsoon rainfall, tropical cyclones are excluded from this analysis, in order to focus on more frequent synoptic disturbances within the region. A rotated empirical orthogonal function (EOF) analysis of North American monsoon rainfall during June to September 2002–2009 suggests that low‐level tropical disturbances contribute to the leading two modes of precipitation variability within this region. These disturbances result in gulf surges or low‐level surges of moisture up the Gulf of California, and provide a key moisture source to facilitate the development of organized convection. In the first mode, the low‐level trough brings precipitation to lower elevations along the western slopes of the Sierra Madre Occidental south of Hermosillo, Mexico and over the southern Baja Peninsula. In the second mode, the low‐level trough interacts with an upper‐level inverted trough enhancing precipitation into the southwestern United States and northwest Mexico. In particular, the upper‐level trough contributes to the easterly to northeasterly shear across the region, favouring mesoscale convective organization and enhanced deep convection over the Sierra Madre Occidental and higher elevations in southeast Arizona. The EOF methodology offers an objective approach for determining the dominant modes of precipitation for the monsoon region useful for identifying past and monitoring future low‐frequency impacts on these modes.

Evaluation of the Tropical Rainfall Measuring Mission 3B43 product over an inland area in Brazil and the effects of satellite boost on rainfall estimates

The main objective of this study was to evaluate the monthly mean areal rainfall estimated using the Tropical Rainfall Measuring Mission (TRMM) 3B43 version 7 product over an inland area in Central Brazil. Furthermore, we investigated the effect of TRMM orbit boost (in August 2001) over the 3B43 estimates. The TRMM 3B43 estimates were compared to reference rainfall data, collected at 67 rain gauge stations irregularly distributed in the study area. The results showed a good agreement between the TRMM 3B43 areal monthly mean rainfall estimations and reference data (r>0.97). The error analysis showed that the TRMM 3B43 product tends to overestimate the areal monthly mean rainfall at approximately 1.24%. The root-mean-square error (RMSE) for the entire period was 19.66 mm month−1 (15.75%). A Monte Carlo simulation and Wilcoxon statistical test showed that the RMSE increased significantly (p-value <0.01) after the boost, rising from 15.20 to 23.06 mm month−1. However, the increase in the RMSE does not preclude the use of the TRMM 3B43 product for estimating the monthly mean areal rainfall over the Upper Paraná watershed. The impacts of boost on TRMM 3B43 estimates were observed only for rainfall rates higher than 250 mm month−1.

The role of temperature and humidity on seasonal influenza in tropical areas: Guatemala, El Salvador and Panama, 2008-2013.

BackgroundThe role of meteorological factors on influenza transmission in the tropics is less defined than in the temperate regions. We assessed the association between influenza activity and temperature, specific humidity and rainfall in 6 study areas that included 11 departments or provinces within 3 tropical Central American countries: Guatemala, El Salvador and Panama.Method/FindingsLogistic regression was used to model the weekly proportion of laboratory-confirmed influenza positive samples during 2008 to 2013 (excluding pandemic year 2009). Meteorological data was obtained from the Tropical Rainfall Measuring Mission satellite and the Global Land Data Assimilation System. We found that specific humidity was positively associated with influenza activity in El Salvador (Odds Ratio (OR) and 95% Confidence Interval of 1.18 (1.07–1.31) and 1.32 (1.08–1.63)) and Panama (OR = 1.44 (1.08–1.93) and 1.97 (1.34–2.93)), but negatively associated with influenza activity in Guatemala (OR = 0.72 (0.6–0.86) and 0.79 (0.69–0.91)). Temperature was negatively associated with influenza in El Salvador's west-central departments (OR = 0.80 (0.7–0.91)) whilst rainfall was positively associated with influenza in Guatemala's central departments (OR = 1.05 (1.01–1.09)) and Panama province (OR = 1.10 (1.05–1.14)). In 4 out of the 6 locations, specific humidity had the highest contribution to the model as compared to temperature and rainfall. The model performed best in estimating 2013 influenza activity in Panama and west-central El Salvador departments (correlation coefficients: 0.5–0.9).Conclusions/SignificanceThe findings highlighted the association between influenza activity and specific humidity in these 3 tropical countries. Positive association with humidity was found in El Salvador and Panama. Negative association was found in the more subtropical Guatemala, similar to temperate regions. Of all the study locations, Guatemala had annual mean temperature and specific humidity that were lower than the others.

Comparison of drought indicators derived from multiple data sets over Africa

Abstract. Drought monitoring is a key component to mitigate impacts of droughts. Lack of reliable and up-to-date precipitation data sets is a common challenge across the globe. This study investigates different data sets and drought indicators on their capability to improve drought monitoring in Africa. The study was performed for four river basins located in different climatic regions (the Oum er-Rbia in Morocco, the Blue Nile in eastern Africa, the Upper Niger in western Africa, and the Limpopo in southeastern Africa) as well as the Greater Horn of Africa. The five precipitation data sets compared are the ECMWF ERA-Interim reanalysis, the Tropical Rainfall Measuring Mission satellite monthly rainfall product 3B-43, the Global Precipitation Climatology Centre gridded precipitation data set, the Global Precipitation Climatology Project Global Monthly Merged Precipitation Analyses, and the Climate Prediction Center Merged Analysis of Precipitation. The set of drought indicators used includes the Standardized Precipitation Index, the Standardized Precipitation-Evaporation Index, and Soil Moisture Anomalies. A comparison of the annual cycle and monthly precipitation time series shows a good agreement in the timing of the rainy seasons. The main differences between the data sets are in the ability to represent the magnitude of the wet seasons and extremes. Moreover, for the areas affected by drought, all the drought indicators agree on the time of drought onset and recovery although there is disagreement on the extent of the affected area. In regions with limited rain gauge data the estimation of the different drought indicators is characterized by a higher uncertainty. Further comparison suggests that the main source of differences in the computation of the drought indicators is the uncertainty in the precipitation data sets rather than the estimation of the distribution parameters of the drought indicators.

위성 자료를 이용한 도시지역 극치강우 모니터링: 2011년 7월 집중호우를 중심으로

본 논문에서는 천리안(Communication, Ocean and Meteorological Satellite; COMS)과 TRMM(Tropical Rainfall Measurement Mission)을 통하여 관측한 위성영상자료를 이용한 극치강우(Extreme Rainfall) 추정 알고리즘을 개발하였으며, 2011년 7월 집중호우를 대상으로 그 적용성을 평가하였다. TRMM/PR(TRMM/Precipitation Radar)과 AWS(Automatic Weather System) 자료를 이용하여 고도에 따른 멱급수 회귀방정식으로 Z-R관계식을 추정한 결과 <TEX>$Z=303R^{0.72}$</TEX>를 산출하였으며, 지상관측 자료와 비교한 결과 상관계수가 0.57로 분석되었다. 이 값과 TRMM/VIRS(TRMM/Visible Infrared Scanner)와의 관계를 이용하여 극치강우알고리즘을 개발하였으며, 천리안 위성에 적용하여 10분강 우를 추정한 결과 강우강도가 큰 경우에는 과소 추정하는 경향이, 작은 경우에는 과대 추정하는 경향이 있는 것으로 분석되었으나, 전반적인 패턴은 관측과 유사한 경향이 있는 것으로 분석되었다. 또한 이 알고리즘을 같은 센서를 이용하는 천리안 위성에 적용하여 AWS의 상관관계를 분석한 결과, 10분 강우량의 경우 상관계수는 0.517로 평균제곱근 오차는 3.146으로 분석되었고, 공간 상관행렬 오차의 평균은 -0.530~-0.228의 음의 상관을 보이는 것으로 분석되었다. 위성자료를 이용한 극치강우량 추정의 오차 발생 원인은 여러 가지 외부적인 요인으로 판단되며, 지속적인 알고리즘 개선 및 오차보정을 통한 정확도 개선이 필요한 것으로 사료된다. 본 연구의 결과는 추후 다양한 정지궤도위성의 이용을통 한 다중 원격탐사자료의 활용으로 보다 정확한 미계측 유역 수문자료 확충 및 실시간 홍수 예 경보 시스템 구축에 활용이 가능할 것으로 사료된다. This study developed a new algorithm of extreme rainfall extraction based on the Communication, Ocean and Meteorological Satellite (COMS) and the Tropical Rainfall Measurement Mission (TRMM) Satellite image data and evaluated its applicability for the heavy rainfall event in July-2011 in Seoul, South Korea. The power-series-regression-based Z-R relationship was employed for taking into account for empirical relationships between TRMM/PR, TRMM/VIRS, COMS, and Automatic Weather System(AWS) at each elevation. The estimated Z-R relationship (<TEX>$Z=303R^{0.72}$</TEX>) agreed well with observation from AWS (correlation coefficient=0.57). The estimated 10-minute rainfall intensities from the COMS satellite using the Z-R relationship generated underestimated rainfall intensities. For a small rainfall event the Z-R relationship tended to overestimated rainfall intensities. However, the overall patterns of estimated rainfall were very comparable with the observed data. The correlation coefficients and the Root Mean Square Error (RMSE) of 10-minute rainfall series from COMS and AWS gave 0.517, and 3.146, respectively. In addition, the averaged error value of the spatial correlation matrix ranged from -0.530 to -0.228, indicating negative correlation. To reduce the error by extreme rainfall estimation using satellite datasets it is required to take into more extreme factors and improve the algorithm through further study. This study showed the potential utility of multi-geostationary satellite data for building up sub-daily rainfall and establishing the real-time flood alert system in ungauged watersheds.

Non-parametric rain/no rain screening method for satellite-borne passive microwave radiometers at 19–85 GHz channels with the Random Forests algorithm

This paper presents a novel non-parametric pattern recognition method to screen rain/no rain status for satellite-borne passive microwave radiometers in the 19–85 GHz channels. The method is based on randomized decision trees with bootstrap aggregation (Random Forests (RF) algorithm). It relies on pragmatic associations between the input features using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) calibrated brightness temperatures and precipitation radar (PR) rain/no rain information as targets. Both these instruments are carried on board the TRMM satellite. In order to develop the method, first, the 10 most significant input features are selected by using feature importance criteria through out-of-bag (OOB) statistics from a total of 17 input features. The input features include the brightness temperatures, as well as some computed signatures – polarization differences (PD), polarization-corrected temperatures (PCT), and scattering indices (SI) at in the 19–85 GHz channels. The feature selection is carried out for different types of surface terrain (ocean, land, and coast), and the selected features are then used for final RF algorithm development. During the dichotomous statistical assessment of the method against the PR rain/no rain status as ‘truth’, the presented method produced reasonable threat scores of 0.50, 0.43, and 0.39, respectively, over ocean, land, and coast surface terrains. Furthermore, the results are compared with the dichotomous scores derived by the Goddard profiling algorithm (GPROF) and, remarkably, the RF-based method corroborated better statistical scores than that of the GPROF. The presented method does not rely on any a priori information and is applicable to other passive microwave radiometers at similar frequencies.

Identification of convective/stratiform dominance over surface rainfall

In order to find out the characteristics of stratiform/convective dominance over surface rainfall, upper-air meteorological elements like cloud liquid water (CLW), precipitation water (PW) and latent heat (LH) have been analysed from the surface to a height of 18 km, for a few selected stations in India and a few other global locations. The data required for the study are the CLW, PW, LH and rainfall data from the data product 2A12 of the Tropical Rainfall Measuring Mission satellite (TRMM) Microwave Imager (TMI) for the period 1999-2002, 2007 and 2008; bright band height (BBH) and freezing level height (HFL) data from 2A23 of the Precipitation Radar (PR) onboard TRMM for the period 1999 - 2002. Vertical profiles of PW, LH and CLW have been presented. Two new parameters, called height of peak cloud liquid water (HPCL) and precipitation water at HPCL have been introduced. HPCL is defined as the height where CLW shows its peak. It is found that absorption and evolution of LH along the vertical column, PW values at HPCL and the level of LH absorption peak are able to explain stratiform/convective dominance over surface rainfall.

Investigating Hector Convective Development and Microphysical Structure Using High-Resolution Model Simulations, Ground-Based Radar Data, and TRMM Satellite Data

Abstract One event of a tropical thunderstorm typically observed in northern Australia, known as Hector, is investigated using high-resolution model output from the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) observations from a ground-based weather radar located in Berrimah (Australia) and data from the Tropical Rainfall Measuring Mission (TRMM) satellite. The analysis is carried out by tracking the full life cycle of Hector from prestorm stage to the decaying stage. In both the prestorm stage, characterized by nonprecipitating cells, and the triggering stage, when the Hector storm is effectively initiated, an analysis is performed with the aid of high-spatial-and-temporal-resolution MM5 output and the Berrimah ground-based radar imagery. During the mature (“old”) stage of Hector, considering the conceptual model for tropical convection suggested by R. Houze, TRMM Microwave Imager satellite-based data were added to ground-based radar data to analyze the storm vertical structure (dynamics, thermodynamics, and hydrometeor contents). Model evaluation with respect to observations (radar reflectivity and TRMM data) suggests that MM5 performed fairly well in reproducing the dynamics of Hector, providing support to the assertion that the strength of convection, in terms of vertical velocity, largely contributes to the vertical distribution of hydrometeors. Moreover, the stages of the storm and its vertical structure display good agreement with Houze’s aforementioned conceptual model. Finally, it was found that the most important triggering mechanisms for this Hector event are topography, the sea breeze, and a gust front produced by previous convection.

Challenge and opportunities of space-based precipitation radar for spatio-temporal hydrology analysis in tropical maritime influenced catchment: Case study on the hilly tropical watershed of Peninsular Malaysia

This paper highlights two critical issues regarding hilly watershed in Peninsular Malaysia; (1) current status of spatio-temporal condition of rain gauge based measurement, and (2) potential of space-based precipitation radar to study the rainfall dynamics. Two analyses were carried out represent each issue consecutively. First, the spatial distribution and efficiency of rain gauge in hilly watershed Peninsular Malaysia is evaluated with respect to the land use and elevation information using Geographical Information System (GIS) approach. Second, the spatial pattern of rainfall changes is analysed using the Tropical Rainfall Measuring Mission (TRMM) satellite information. The spatial analysis revealed that the rain gauge distribution had sparse coverage on hilly watershed and possessed inadequate efficiency for effective spatial based assessment. Significant monthly rainfall changes identified by TRMM satellite on the upper part of the watershed had occurred occasionally in 1999, 2000, 2001, 2006, and 2009 went undetected by conventional rain gauge. This study informed the potential and opportunities of space-based precipitation radar to fill the gaps of knowledge on spatio-temporal rainfall patterns for hydrology and related fields in tropical region.

Diurnal variations of turbulence parameters over the tropical oceanic upper troposphere during SCSMEX

Using the method of Thorpe analysis, the TKE (turbulence kinematic energy) dissipation rate (ɛ) and turbulence diffusivity (K) were derived from the RS (radiosounding) measurements in the tropical oceanic upper troposphere. The measurements were performed four times per day during two intense observation periods (May 5–25, and June 5–25) on the Kexue #1 scientific observation ship of SCSMEX (South China Sea Monsoon EXperiment) in 1998. There are three new features obtained from our analysis. First, the responses of ɛ and K to the onset of monsoon are negligible over the ocean at least for the data used here. Second, the temporal variations of ɛ and K are in a similar manner and exhibit strong diurnal variations. The diurnal variations achieve their maxima in the morning (08 LT) and early afternoon (14 LT), and achieve their minima in the evening (20 LT) and early morning hours (02 LT). The diurnal variations of turbulence parameters (ɛ and K) and their responses to the onset of monsoon are entirely different from those derived over land at similar latitudes. Finally, although the correlations between the variations of ɛ and MCSs (mesoscale convective systems), which were derived from TRMM (tropical rainfall measuring mission) satellite, are not very well in only few days, the diurnal variations of ɛ averaged over May and June are strongly correlated with the diurnal variations of MCSs with correlation factors of 0.79 and 0.94, respectively. This indicates that the turbulence and its diurnal variations over the tropic oceanic upper stratosphere region are highly related to the MCSs.

Diurnal variation of the global electric circuit from clustered thunderstorms

The diurnal variation of the global electric circuit is investigated using the World Wide Lightning Location Network (WWLLN), which has been shown to identify nearly all thunderstorms (using WWLLN data from 2005). To create an estimate of global electric circuit activity, a clustering algorithm is applied to the WWLLN data set to identify global thunderstorms from 2010 to 2013. Annual, seasonal, and regional thunderstorm activity is investigated in this new WWLLN thunderstorm data set in order to estimate the source behavior of the global electric circuit. Through the clustering algorithm, the total number of active thunderstorms are counted every 30 min creating a measure of the global electric circuit source function. The thunderstorm clusters are compared to precipitation radar data from the Tropical Rainfall Measurement Mission satellite and with case studies of thunderstorm evolution. The clustering algorithm reveals an average of 660±70 thunderstorms active at any given time with a peak‐to‐peak variation of 36%. The highest number of thunderstorms occurs in November (720±90), and the lowest number occurs in January (610±80). Thunderstorm cluster and electrified storm cloud activity are combined with thunderstorm overflight current measurements to estimate the global electric circuit thunderstorm contribution current to be 1090±70 A with a variation of 24%. By utilizing the global coverage and high time resolution of WWLLN, the total active thunderstorm count and current is shown to be less than previous estimates based on compiled climatologies.

Suitability of TRMM satellite rainfall in driving a distributed hydrological model in the source region of Yellow River

Satellite-based precipitation products with high spatial and temporal resolution and large areal coverage offer a potential alternative or supplement to ground-based rainfall estimates over sparsely gauged or ungauged basins. The original intention of the Tropical Rainfall Measuring Mission (TRMM) was to provide rainfall products over the global tropics. Although numerous efforts have been made to evaluate the applicability of TRMM precipitation in the low altitude of the tropics and the mid-latitudes, its applicability in high altitude is rare. The source region of Yellow River and its neighbor regions in the northeastern Tibetan Plateau provide a good example of high altitude and higher latitude for this purpose. In this study, we first provided a quantitative assessment of the TRMM Multisatellite Precipitation Analysis (TMPA) products (3B42V6) against the gauge rainfall from 1998 to 2008. In general, the TMPA rainfall captures the spatial and temporal rainfall characteristics less well over the region on daily time scales. However, the monthly TMPA data have a much better linear relationship with the gauge rainfall data with a high determination coefficient (R2) of 0.96. The distribution of the barycentre of the precipitation concentrates on the south-central of the study area, and the TMPA rainfall scatter in the west in comparison with the gauge rainfall. This study also concluded that the validation indices of TMPA were closely associated with latitude and annual precipitation. We subsequently evaluated the utility of the TMPA rainfall for daily and monthly hydrological process simulation by applying the rainfall data to a raster-based distributed hydrological model, Coupled Routing and Excess Storage (CREST). The results showed that the conventional areal rainfall based on gauge data produces an overall good fit, while the TMPA-driven simulations tend to yield an unsatisfied result in the daily discharge simulations. This analysis implies that TMPA cannot be acceptable to drive hydrological models for daily stream flow simulation in the study area. However, at the monthly time scale, the TMPA rainfall performs quite well. This study concluded that TMPA is more suitable for the long-term hydrological prediction.

Potential impacts of climate and environmental change on the stored water of Lake Victoria Basin and economic implications

[1] The changing climatic patterns and increasing human population within the Lake Victoria Basin (LVB), together with overexploitation of water for economic activities call for assessment of water management for the entire basin. This study focused on the analysis of a combination of available in situ climate data, Gravity Recovery And Climate Experiment (GRACE), Tropical Rainfall Measuring Mission (TRMM) observations, and high resolution Regional Climate simulations during recent decade(s) to assess the water storage changes within LVB that may be linked to recent climatic variability/changes and anomalies. We employed trend analysis, principal component analysis (PCA), and temporal/spatial correlations to explore the associations and covariability among LVB stored water, rainfall variability, and large-scale forcings associated with El-Nino/Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Potential economic impacts of human and climate-induced changes in LVB stored water are also explored. Overall, observed in situ rainfall from lake-shore stations showed a modest increasing trend during the recent decades. The dominant patterns of rainfall data from the TRMM satellite estimates suggest that the spatial and temporal distribution of precipitation have not changed much during the period of 1998–2012 over the basin consistent with in situ observations. However, GRACE-derived water storage changes over LVB indicate an average decline of 38.2 mm/yr for 2003–2006, likely due to the extension of the Owen Fall/Nalubale dam, and an increase of 4.5 mm/yr over 2007–2013, likely due to two massive rainfalls in 2006–2007 and 2010–2011. The temporal correlations between rainfall and ENSO/IOD indices during the study period, based on TRMM and model simulations, suggest significant influence of large-scale forcing on LVB rainfall, and thus stored water. The contributions of ENSO and IOD on the amplitude of TRMM-rainfall and GRACE-derived water storage changes, for the period of 2003–2013, are estimated to be ∼2.5 cm and ∼1.5 cm, respectively.

Seawater temperature changes associated with the North Brazil current dynamics

This study used hydrographic data (CTD and ADCP) collected along the north Brazilian continental shelf and the adjacent oceanic area (the north Brazilian zone) and 13 years of monthly data of sea surface temperatures (SSTs) obtained from the Tropical Rainfall Measuring Mission satellite microwave images. In July and August 2001, the core of the North Brazil Current (NBC) with a velocity exceeding 1.2 m s−1 in the upper 150 m was observed near the break of the north Brazilian continental shelf. The satellite and in situ SSTs from the same time indicate that relatively cold waters (<27.5 °C) extended throughout the NBC region where the vertical distribution of temperature displayed a rise of the 26 °C isotherm to near the surface on transects where the NBC was more intense. These observations indicated that the NBC plays an important role in temperature changes in the water column near and/or over the north Brazilian continental shelf margin even at times when, theoretically, the NBC may be expected to be less intense (April–May) and warm waters dominate the area. The distribution of accumulated temperature change reveals that the NBC may contribute to possible nutrient upwelling of the bottom boundary layer along the continental shelf to surficial areas and offshore following the NBC deflection or merely into the North Atlantic.

Distribution of one-minute rain rate in Malaysia derived from TRMM satellite data

Abstract. Total rainfall accumulation, as well as convective and stratiform rainfall rate data from the Tropical Rainfall Measuring Mission (TRMM) satellite sensors have been used to derive the thunderstorm ratio and one-minute rainfall rates, R0.01, for 57 stations in Malaysia for exceedance probabilities of 0.001–1% for an average year, for the period 1998–2010. The results of the rain accumulations from the TRMM satellite were validated with the data collected from different ground data sources from the National Oceanic and Atmospheric Administration (NOAA) global summary of the day (1949–2010), Global Precipitation Climatology Centre (GPCC) (1986–2010), and NASA (1950–1999). The correlation coefficient and the average bias error between TRMM and GPCC for Malaysia were found to be 0.79–0.89 and ±50 mm, respectively. The deduced one-minute rainfall rates correlated fairly well with those obtained from the previous work carried out in Malaysia, with correlation coefficients of 0.7 in all the 57 locations. The inferred mean annual one-minute rainfall rates were found to be highest in the eastern Malaysia, with values between 84.7 and 153.9 mm h−1 for 0.01% exceedance, and in western Malaysia with values between 81.8 and 143.8 mm h−1. The present results will be useful for satellite rain attenuation modeling in tropical and subtropical stations around the world.

Analyzing Spatiotemporal Patterns of Extreme Precipitation Events in Southeastern Anatolia

Abstract. Extreme environmental events, such as floods, droughts, rainstorms, and strong winds have severe consequences for human society. Changes in extreme weather and climate events have significant impacts and are among the most serious challenges to society in coping with a changing climate. The cost of damage caused by extreme climate events is rising all over the world. The European Environment Agency (EEA) report ("Climate Change, Impacts and Vulnerabilities in Europe 2012") stated that the cost of damage had increased from € 9 billion in the 1980s to € 13 billions in the 2000s. In the United States, the National Oceanic and Atmospheric Administration (NOAA) reported that $ 188 billion in damage was caused by the severe weather events in 2011 and 2012. Understanding and identifying hydrometeorologic extreme events and their changes through time are key in sustaining agriculture and socio-economic development. Planning for weather-related emergencies, agricultural and reservoir management and insurance risk calculations, all rely on knowledge of the frequency of these extreme events. The assessment of extreme precipitation is an important problem in hydrologic risk analysis and design. Erosion and removal of the fertile soil layer through hydroclimatic extreme events is also a serious problem in semi-arid to arid regions, especially in mediterranean climates. Accurate measurements of precipitation on a variety of space and time scales are important to climate scientists and decision makers, including hydrologists, agriculturalists and emergency managers. The historical record of precipitation observations is limited mostly to land areas where rain gauges can be deployed, and measurements from those instruments are sparse over large and meteorologically important regions of the Turkey, such as over the Southeastern Anatolia Region. While rain gauge measurements are often used to tune hydrologic models, they are limited by their spatial coverage. Remote sensing techniques using spaceborne sensors provide an excellent complement to continuous monitoring of rain events both spatially and temporally. In this study we compare ground-station data with Tropical Rainfall Measurement Mission (TRMM) products at the 3-hour time scale to evaluate satellite rain estimates for agricultural and hydrological applications in Turkey. The remote sensing dataset TRMM product 3B42 has been validated with daily rain gauge measurements in order to characterize rainfall variability in the Southeastern Anatolia region. The precipitation retrievals from the TRMM satellite were compared with data from 7 surface rain gauges within the period of 1998–2012. Spatiotemporal patterns through statistical analyses were identified by fitting Generalized Extreme Value (GEV) rainfall distribution to the rainfall time series, and the fitting results were analyzed focusing on the behaviour of the shape parameter. Spatial patterns and correlations of rainfall events across the study area were also analysed by the calculation of the 90th, 95th and 99th percentiles. Regional frequency relationship were developed using the chosen GEV distribution. The recurrence intervals for different years have been estimated using the GEV distribution and their spatial variability has been described. The recurrence intervals of large rainstorms have also been identified for the rain gauge stations with the related TRMM pixel time series and spatial patterns in the study area have been evaluated. Preliminary results indicate that there exist large discrepancies between rain gauge and TRMM data at mean rainfall values; however, least squares fits indicate reliable and quite linear correlation for the 90th, 95th, 99th percentiles (r2 = 0.70, 0.77, and 0.75 respectively) and the annual maximum daily amount of precipitation (r2 = 0.69). In other words, TRMM product 3B42 can be used to assess first-order rainfall statistics and recurrence intervals, but rainfall magnitudes vary significantly from ground measurements.

Characteristics of lightning flashes with exceptional illuminated areas, durations, and optical powers and surrounding storm properties in the tropics and inner subtropics

Twelve years (1998–2009) of Lightning Imaging Sensor (LIS) observations are used to characterize lightning flashes by illuminated area, duration, and optical power, particularly for exceptional flashes defined as those above the 90th percentile of each parameter. Statistics of lightning are summarized over land, ocean, and coastal regions of the Tropical Rainfall Measuring Mission satellite's domain extending from 36°S to 36°N. The degree to which optical flash parameters are interrelated is discussed, as well as coincident environmental properties and the overall characteristics of parent thunderstorms. LIS flashes over the southern United States are also collocated to National Lightning Detection Network (NLDN) observations, and relationships between LIS optical flash properties and corresponding NLDN strengths are discussed. Daytime (nighttime) oceanic flashes are shown to be 31.7% (39.4%) larger and 55.2% (75.1%) brighter in terms of maximum event pixel radiance. At the same time, daytime (nighttime) coastal flashes have 22.1% (7.8%) longer durations than flashes over land and 15.6% (11.4%) longer durations than oceanic flashes. Particularly, large and bright flashes observed by LIS are typically centered in weak storm regions, but thunderstorms with exceptional flashes are, themselves, more intense overall than those with only small and dim flashes. Diurnally, the top 10% brightest lightning flashes peak about 2 h earlier than the top 10% largest and long‐lasting flashes over land, implying that lightning flash characteristics vary with the life cycle of thunderstorms. Larger and more radiant flashes are also shown to be associated with stronger NLDN flashes of positive and negative polarity.

Deforestation‐induced reduction in rainfall

Copyright © 2013 John Wiley & Sons, Ltd. Borneo is the third largest island in the world and famous for its majestic rainforests (Figure 1a). Southeast Asian tropical forests have the highest relative deforestation rate in the world (Canadell et al., 2007). More than 80% of the total land area of Borneo was covered with pristine forest in the 1950s; however, the high deforestation rate (1.7%year ), which is almost double that of the already intense deforestation rate of the whole Southeast Asian region, has resulted in the current estimation of forest cover being ~50% (Langner et al., 2007) (Figure 1b). Since 1965, production of tropical hardwood timber in Borneo sharply increased and reached a plateau and maximum in the early 1980s (Brookfield and Byron, 1990). Although the recent and rapid decline in timber production has been evident throughout Borneo owing to over-logging, over the past decades, more timber was exported from Borneo than from tropical Africa and Latin America combined (Curran et al., 2004). The land cover area categorized as ‘degraded forest and regrowth’, ‘cultivation forest mosaic’ and ‘dry/wet bare soil; grasslands; agriculture’ reached up to 33 million ha, ~45% of the total area of Borneo (Langner et al., 2007). Tropical forests are a major source of global hydrologic fluxes, and thus, this forest cover change has potential to significantly alter the global and regional climate and hydrologic cycling (Nobre et al., 1991;Kanae et al., 2001; Avissar andWerth, 2005). Because tropical rainforests exist where ecosystem water resources are greatest, the hydrologic changes could significantly alter ecological patterns and processes (Malhi et al., 2009; Phillips et al., 2009; Kumagai and Porporato, 2012), in turn affecting feedback to the atmosphere (Meir et al., 2006; Bonan, 2008). It is a matter of course that the drastic deforestation and forest degradation in Borneo should be anticipated to impact the regional hydro-climate; in fact, the long-term daily grid precipitation datasets (APHRODITE’s Water Resources, available via http://www.chikyu.ac.jp/precip/, Yatagai et al., 2012) over Borneo showed a significant decline in precipitation over the period 1951–2007 (Figure 1c). An abrupt decline in precipitation in the late 1980s can be seen (Figure 1c), which was consistent with a time when deforestation, i.e. logging for timber production, might have become intensive (Brookfield and Byron, 1990; Curran et al., 2004). Furthermore, it should be noted that such a decreasing trend in precipitationmight cause frequent extreme droughts and subsequent fires, resulting in more severe deforestation and forest degradation (van Nieuwstadt and Sheil, 2005; Wooster et al., 2012). A spatial distribution of atmospheric moisture convergence averaged over 1998–2010 in the eastern Pacific Ocean (built using a reanalyzed and gridded four-dimensional meteorology dataset, Japanese 25-year ReAnalysis and the JapanMeteorologicalAgencyClimateDataAssimilation System available via http://jra.kishou.go.jp/JRA-25/index_en.html) suggests less moisture convergence and divergence over Borneo compared with other regions (Figure 2a). On the other hand, the Tropical Rainfall Measuring Mission satellite measurements from 1998 to 2010 (NASA Goddard Earth Sciences Data and Information Services Center, available via http://disc.sci.gsfc.nasa.gov/ about-us) showed a larger amount of precipitation above islands of the maritime continent in the western Pacific Ocean compared with sea areas,

The lightning activity associated with the dry and moist convections in the Himalayan Regions

AbstractLightning activity in the dry environment of northwest India and Pakistan (NW) and in the moist environment of northeast India (NE) has been examined from the Optical Transient Detector and Lightning Imaging Sensor data obtained from the Tropical Rainfall Measuring Mission satellite during 1995–2010. In the NW region, seasonal variation of flash rate is annual with a maximum in July but is semi‐annual with a primary maximum in April and a secondary maximum in September, in the NE region. On diurnal scale, flash rate is the maximum in the afternoons, in both the NE and NW regions. The correlation of flash rate with convective parameters, viz. surface temperature, convective available potential energy (CAPE) and outgoing long‐wave radiation is better with convective activity in the NW than in the NE region. Mean value of aerosol optical depth at 550 nm is ~ 26% higher and is highly correlated with flash rate in NW as compared to that in NE. Results indicate that CAPE is ~ 120 times more efficient in NW than in the NE region for production of lightning. The empirical orthogonal function analysis of flash rate, surface temperature, and CAPE shows that variance of lightning activity in these regions cannot be fully explained by the variance in the surface temperature and CAPE alone, and that some other factors, such as orographic lifting, precipitation, topography, etc., may also contribute to this variance in these mountainous regions. Further, the increase in CAPE due to orographic lifting in the Himalayan foothills in the NE region may contribute to ~ 7.5% increase in lightning activity. Relative roles of the thermally induced and moisture‐induced changes in CAPE are examined in these regions. This study merely raises the questions, and that additional research is required for explaining the fundamental reasons for the reported observations here.