The COnvective Precipitation Experiment (COPE): investigating the origins of heavy precipitation in the southwestern UK

A recent field campaign in southwest England used numerical modeling integrated with aircraft and radar observations to investigate the dynamic and microphysical interactions that can result in heavy convective precipitation. The COnvective Precipitation Experiment (COPE) was a joint UK-US field campaign held during the summer of 2013 in the southwest peninsula of England, designed to study convective clouds that produce heavy rain leading to flash floods. The clouds form along convergence lines that develop regularly due to the topography. Major flash floods have occurred in the past, most famously at Boscastle in 2004. It has been suggested that much of the rain was produced by warm rain processes, similar to some flash floods that have occurred in the US. The overarching goal of COPE is to improve quantitative convective precipitation forecasting by understanding the interactions of the cloud microphysics and dynamics and thereby to improve NWP model skill for forecasts of flash floods. Two research aircraft, the University of Wyoming King Air and the UK BAe 146, obtained detailed in situ and remote sensing measurements in, around, and below storms on several days. A new fast-scanning X-band dual-polarization Doppler radar made 360-deg volume scans over 10 elevation angles approximately every 5 minutes, and was augmented by two UK Met Office C-band radars and the Chilbolton S-band radar. Detailed aerosol measurements were made on the aircraft and on the ground. This paper: (i) provides an overview of the COPE field campaign and the resulting dataset; (ii) presents examples of heavy convective rainfall in clouds containing ice and also in relatively shallow clouds through the warm rain process alone; and (iii) explains how COPE data will be used to improve high-resolution NWP models for operational use.

The EarthCARE satellite: the next step forward in global measurements of clouds, aerosols, precipitation, and radiation

The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

Precipitation diurnal cycle and summer climatology assessment over South America: An evaluation of Regional Climate Model version 3 simulations

Regional Climate Model version 3 (RegCM3) simulations of 17 summers (1988-2004) over part of South America south of 5 degrees S were evaluated to identify model systematic errors. Model results were compared to different rainfall data sets (Climate Research Unit (CRU), Climate Prediction Center (CPC), Global Precipitation Climatology Project (GPCP), and National Centers for Environmental Prediction (NCEP) reanalysis), including the five summers mean (1998-2002) precipitation diurnal cycle observed by the Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR). In spite of regional differences, the RegCM3 simulates the main observed aspects of summer climatology associated with the precipitation (northwest-southeast band of South Atlantic Convergence Zone (SACZ)) and air temperature (warmer air in the central part of the continent and colder in eastern Brazil and the Andes Mountains). At a regional scale, the main RegCM3 failures are the underestimation of the precipitation in the northern branch of the SACZ and some unrealistic intense precipitation around the Andes Mountains. However, the RegCM3 seasonal precipitation is closer to the fine-scale analyses (CPC, CRU, and TRMM-PR) than is the NCEP reanalysis, which presents an incorrect north-south orientation of SACZ and an overestimation of its intensity. The precipitation diurnal cycle observed by TRMM-PR shows pronounced contrasts between Tropics and Extratropics and land and ocean, where most of these features are simulated by RegCM3. The major similarities between the simulation and observation, especially the diurnal cycle phase, are found over the continental tropical and subtropical SACZ regions, which present afternoon maximum (1500-1800 UTC) and morning minimum (0900-1200 UTC). More specifically, over the core of SACZ, the phase and amplitude of the simulated precipitation diurnal cycle are very close to the TRMM-PR observations. Although there are amplitude differences, the RegCM3 simulates the observed nighttime rainfall in the eastern Andes Mountains, over the Atlantic Ocean, and also over northern Argentina. The main simulation deficiencies are found in the Atlantic Ocean and near the Andes Mountains. Over the Atlantic Ocean the convective scheme is not triggered; thus the rainfall arises from the grid-scale scheme and therefore differs from the TRMM-PR. Near the Andes, intense (nighttime and daytime) simulated precipitation could be a response of an incorrect circulation and topographic uplift. Finally, it is important to note that unlike most reported bias of global models, RegCM3 does not trigger the moist convection just after sunrise over the southern part of the Amazon.

The first case study of a thunderstorm in South Africa based on dual- Doppler radar observations

On 27 March 1991, an isolated thunderstorm passed between the two CSIR Doppler radars, spaced about 45km apart. Both radars simultaneously recorded Doppler data of the storm, and a detailed case study during an 11-min period is presented. Air motions synthesized from these data provide the first three-dimensional display of Doppler-derived wind fields within a multicell storm on the Transvaal Highveld. Regions of high divergence values (10 -2s -1) at low levels were found mostly in close proximity to reflectivity maxima (45-51 dBZ), which is consistent with findings from North America, that gravitational loading by the precipitation plays a key role in the initiation and maintenance of downdraughts. -from Authors

Statistics on tropical convective storms observed by radar

Convective storm rainfall is of special importance to urban hydrological studies due to its temporal and spatial variability. Although dense networks of recording rain gauges can be employed to characterize such rainfall, very few investigations of this type have been undertaken due to their prohibitive cost. This paper reports some data on characteristics of tropical convective storms obtained from radar at Bauru in the State of São Paulo, Brazil. Periods of convective precipitation were identified by exclusion of those related to frontal activity with the help of synoptic maps and the radar screen record. The occurrence and evolution of convective storms were observed in two 28 km × 28 km windows obtaining information on the life history of convective cells and the magnitude of rainfall. Frequency distributions of the time of occurrence of convective rainfall, cell size, area covered, life duration and maximum and average rainfall observed in the experimental areas are presented and discussed.

Análise de superfície de tendência aplicada à chuva, medida por radar meteorológico, nas regiões de Assis e Piracicaba, SP

This paper presents the results from lineal trend surface analysis technique application. The purpose was to detect positive and negative anomalies in the rain measure distribution obtained by the meteorological radar Doppler, band S, located in Bauru, during the period of 21 of October/2004 to 29 of April/2005 in the areas of Assis and Piracicaba. Using three Z-R radar relations for rain quantification was chosen the specific equation Z = 32R1,65, as the best one. The results showed that the applied methodology was able to indicate the space distribution of the rain accumulated, identifying and locating the regions where there was rainy excess and rainy lack during each analyzed period. Such results indicate areas with larger pluvial impact and consequently more favorable for environmental damages.

Geoestatística aplicada à acumulação da precipitação pluviométrica com radar meteorológico

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Climatologia de tempestades na área central do Estado de São Paulo usando radar meteorológico

A climatological characterization of storm properties during two summer seasons, viz. 1998-1999 and 1999-2000, based on observations from the Bauru S-band Doppler radar, was obtained from the TITAN Software of the National Center for Atmospheric Research (Boulder, Co), implemented at IPMet. Parameters, such as mean volume, mean area, mean and maximum echo tops, mean and maximum reflectivity, as well as speed and direction of precipitating systems were determined using the reflectivity >25, 30 and 40 dBZ and a volume >30 km3 as thresholds for storm identification. For the first time, the spatial distributions of these parameters were determined in the central State of São Paulo, based on radar observations. It was found that some preferential areas, where most of the convective activity was concentrated during the study period, were located along the Tietê River. The mean maximum reflectivity field has highlighted preferential regions for convection to develop over the metropolitan area of Campinas, which in turn was reinforced by the distribution of the echo tops and reflectivity >40 dBZ.

Data assimilation for precipitation nowcasting using Bayesian inference

This work introduces a new variational Bayes data assimilation method for the stochastic estimation of precipitation dynamics using radar observations for short term probabilistic forecasting (nowcasting). A previously developed spatial rainfall model based on the decomposition of the observed precipitation field using a basis function expansion captures the precipitation intensity from radar images as a set of ‘rain cells’. The prior distributions for the basis function parameters are carefully chosen to have a conjugate structure for the precipitation field model to allow a novel variational Bayes method to be applied to estimate the posterior distributions in closed form, based on solving an optimisation problem, in a spirit similar to 3D VAR analysis, but seeking approximations to the posterior distribution rather than simply the most probable state. A hierarchical Kalman filter is used to estimate the advection field based on the assimilated precipitation fields at two times. The model is applied to tracking precipitation dynamics in a realistic setting, using UK Met Office radar data from both a summer convective event and a winter frontal event. The performance of the model is assessed both traditionally and using probabilistic measures of fit based on ROC curves. The model is shown to provide very good assimilation characteristics, and promising forecast skill. Improvements to the forecasting scheme are discussed

A Bayesian state space modelling approach to probabilistic quantitative precipitation forecasting

The generation of very short range forecasts of precipitation in the 0-6 h time window is traditionally referred to as nowcasting. Most existing nowcasting systems essentially extrapolate radar observations in some manner, however, very few systems account for the uncertainties involved. Thus deterministic forecast are produced, which have a limited use when decisions must be made, since they have no measure of confidence or spread of the forecast. This paper develops a Bayesian state space modelling framework for quantitative precipitation nowcasting which is probabilistic from conception. The model treats the observations (radar) as noisy realisations of the underlying true precipitation process, recognising that this process can never be completely known, and thus must be represented probabilistically. In the model presented here the dynamics of the precipitation are dominated by advection, so this is a probabilistic extrapolation forecast. The model is designed in such a way as to minimise the computational burden, while maintaining a full, joint representation of the probability density function of the precipitation process. The update and evolution equations avoid the need to sample, thus only one model needs be run as opposed to the more traditional ensemble route. It is shown that the model works well on both simulated and real data, but that further work is required before the model can be used operationally. © 2004 Elsevier B.V. All rights reserved.

Monitoring of active layer dynamics at two transects on Svalbard using multi-channel ground-penetrating radar

Multi-channel ground-penetrating radar is used to investigate the late-summer evolution of the thaw depth and the average soil water content of the thawed active layer at a high-arctic continuous permafrost site on Svalbard, Norway. Between mid of August and mid of September 2008, five surveys have been conducted over transect lengths of 130 and 175 m each. The maximum thaw depths range from 1.6 m to 2.0 m, so that they are among the deepest thaw depths recorded for Svalbard so far. The thaw depths increase by approximately 0.2 m between mid of August and beginning of September and subsequently remain constant until mid of September. The thaw rates are approximately constant over the entire length of the transects within the measurement accuracy of about 5 to 10 cm. The average volumetric soil water content of the thawed soil varies between 0.18 and 0.27 along the investigated transects. While the measurements do not show significant changes in soil water content over the first four weeks of the study, strong precipitation causes an increase in average soil water content of up to 0.04 during the last week. These values are in good agreement with evapotranspiration and precipitation rates measured in the vicinity of the the study site. While we cannot provide conclusive reasons for the detected spatial variability of the thaw depth at the study site, our measurements show that thaw depth and average soil water content are not directly correlated. The study demonstrates the potential of multi-channel ground-penetrating radar for mapping thaw depth in permafrost areas. The novel non-invasive technique is particularly useful when the thaw depth exceeds 1.5 m, so that it is hardly accessible by manual probing. In addition, multi-channel ground-penetrating radar holds potential for mapping the latent heat content of the active layer and for estimating weekly to monthly averages of the ground heat flux during the thaw period.

Global oceanic precipitation: A joint view by TOPEX and the TOPEX microwave radiometer

The TOPEX/POSEIDON mission offers the first opportunity to observe rain cells over the ocean by a dual-frequency radar altimeter (TOPEX) and simultaneously observe their natural radiative properties by a three-frequency radiometer (TOPEX microwave radiometer (TMR)). This work is a feasibility study aimed at understanding the capability and potential of the active/passive TOPEX/TMR system for oceanic rainfall detection. On the basis of past experiences in rain flagging, a joint TOPEX/TMR rain probability index is proposed. This index integrates several advantages of the two sensors and provides a more reliable rain estimate than the radiometer alone. One year's TOPEX/TMR TMR data are used to test the performance of the index. The resulting rain frequency statistics show quantitative agreement with those obtained from the Comprehensive Ocean-Atmosphere Data Set (COADS) in the Intertropical Convergence Zone (ITCZ), while qualitative agreement is found for other regions of the world ocean. A recent finding that the latitudinal frequency of precipitation over the Southern Ocean increases steadily toward the Antarctic continent is confirmed by our result. Annual and seasonal precipitation maps are derived from the index. Notable features revealed include an overall similarity in rainfall pattern from the Pacific, the Atlantic, and the Indian Oceans and a general phase reversal between the two hemispheres, as well as a number of regional anomalies in terms of rain intensity. Comparisons with simultaneous Global Precipitation Climatology Project (GPCP) multisatellite precipitation rate and COADS rain climatology suggest that systematic differences also exist. One example is that the maximum rainfall in the ITCZ of the Indian Ocean appears to be more intensive and concentrated in our result compared to that of the GPCP. Another example is that the annual precipitation produced by TOPEX/TMR is constantly higher than those from GPCP and COADS in the extratropical regions of the northern hemisphere, especially in the northwest Pacific Ocean. Analyses of the seasonal variations of prominent rainy and dry zones in the tropics and subtropics show various behaviors such as systematic migration, expansion and contraction, merging and breakup, and pure intensity variations, The seasonality of regional features is largely influenced by local atmospheric events such as monsoon, storm, or snow activities. The results of this study suggest that TOPEX and its follow-on may serve as a complementary sensor to the special sensor microwave/imager in observing global oceanic precipitation.

Comprehensive characterization of snowfall in terms of microphysical features, quantitative precipitation estimation and scavenging properties by in situ and remote sensing observations at an Antarctic coastal site

Snow plays a crucial role in the Earth's hydrological cycle and energy budget, making its monitoring necessary. In this context, ground-based radars and in situ instruments are essential thanks to their spatial coverage, resolution, and temporal sampling. Deep understanding and reliable measurements of snow properties are crucial over Antarctica to assess potential future changes of the surface mass balance (SMB) and define the contribution of the Antarctic ice sheet on sea-level rise. However, despite its key role, Antarctic precipitation is poorly investigated due to the continent's inaccessibility and extreme environment. In this framework, this Thesis aims to contribute to filling this gap by in-depth characterization of Antarctic precipitation at the Mario Zucchelli station from different points of view: microphysical features, quantitative precipitation estimation (QPE), vertical structure of precipitation, and scavenging properties. For this purpose, a K-band vertically pointing radar collocated with a laser disdrometer and an optical particle counter (OPC) were used. The radar probed the lowest atmospheric layers with high vertical resolution, allowing the first trusted measurement at only 105 m height. Disdrometer and OPC provided information on the particle size distribution and aerosol concentrations. An innovative snow classification methodology was designed by comparing the radar reflectivity (Ze) and disdrometer-derived reflectivity by means of DDA simulations. Results of classification were exploited in QPE through appropriate Ze-snow rate relationships. The accuracy of the resulting QPE was benchmarked against a collocated weighing gauge. Vertical radar profiles were also investigated to highlight hydrometeors' sublimation and growth processes. Finally, OPC and disdrometer data allowed providing the first-ever estimates of scavenging properties of Antarctic snowfall. Results presented in this Thesis give rise to advances in knowledge of the characteristics of snowfall in Antarctica, contributing to a better assessment of the SMB of the Antarctic ice sheet, the major player in the global sea-level rise.

Continental passive microwave-based rainfall estimation algorithm: Application to the Amazon Basin

This paper presents a new statistical algorithm to estimate rainfall over the Amazon Basin region using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). The algorithm relies on empirical relationships derived for different raining-type systems between coincident measurements of surface rainfall rate and 85-GHz polarization-corrected brightness temperature as observed by the precipitation radar (PR) and TMI on board the TRMM satellite. The scheme includes rain/no-rain area delineation (screening) and system-type classification routines for rain retrieval. The algorithm is validated against independent measurements of the TRMM-PR and S-band dual-polarization Doppler radar (S-Pol) surface rainfall data for two different periods. Moreover, the performance of this rainfall estimation technique is evaluated against well-known methods, namely, the TRMM-2A12 [ the Goddard profiling algorithm (GPROF)], the Goddard scattering algorithm (GSCAT), and the National Environmental Satellite, Data, and Information Service (NESDIS) algorithms. The proposed algorithm shows a normalized bias of approximately 23% for both PR and S-Pol ground truth datasets and a mean error of 0.244 mm h(-1) ( PR) and -0.157 mm h(-1)(S-Pol). For rain volume estimates using PR as reference, a correlation coefficient of 0.939 and a normalized bias of 0.039 were found. With respect to rainfall distributions and rain area comparisons, the results showed that the formulation proposed is efficient and compatible with the physics and dynamics of the observed systems over the area of interest. The performance of the other algorithms showed that GSCAT presented low normalized bias for rain areas and rain volume [0.346 ( PR) and 0.361 (S-Pol)], and GPROF showed rainfall distribution similar to that of the PR and S-Pol but with a bimodal distribution. Last, the five algorithms were evaluated during the TRMM-Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) 1999 field campaign to verify the precipitation characteristics observed during the easterly and westerly Amazon wind flow regimes. The proposed algorithm presented a cumulative rainfall distribution similar to the observations during the easterly regime, but it underestimated for the westerly period for rainfall rates above 5 mm h(-1). NESDIS(1) overestimated for both wind regimes but presented the best westerly representation. NESDIS(2), GSCAT, and GPROF underestimated in both regimes, but GPROF was closer to the observations during the easterly flow.