The Observing System Research And Predictability Experiment Research Articles

Impact of the inflow moisture on the evolution of a warm conveyor belt

This case study of a warm conveyor belt (WCB) event that was probed on a research flight during the THORPEX (The Observing‐System Research and Predictability Experiment) Pacific Asian Regional Campaign (T‐PARC) field experiment in 2008, investigates the sensitivity of the forecast of the WCB, the associated cyclone and the downstream waveguide to the moisture content in the inflow region of the WCB. By assimilating water vapour profiles of a differential absorption lidar (DIAL) into the European Centre for Medium Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), the inflow moisture in the analysis fields is adjusted and humidity is reduced in a broad region around the flight track. The initial reduction of moisture in the WCB inflow affects the latent heat release along the WCB, as well as the potential vorticity (PV) production at lower levels. This change led to a substantially lower outflow height of the forecasted WCB. Further, the height of the tropopause was reduced up to 20 hPa, which caused a change in the jet stream wind speeds of up to 15% downstream. Although the impact on the developing surface cyclone was small, improvements of the PV structure as well as of the kinetic energy could be identified.

Structural Characteristics of T-PARC Typhoon Sinlaku during Its Extratropical Transition

Abstract The structure and the environment of Typhoon Sinlaku (2008) were investigated during its life cycle in The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC). On 20 September 2008, during the transformation stage of Sinlaku’s extratropical transition (ET), research aircraft equipped with dual-Doppler radar and dropsondes documented the structure of the convection surrounding Sinlaku and low-level frontogenetical processes. The observational data obtained were assimilated with the recently developed Spline Analysis at Mesoscale Utilizing Radar and Aircraft Instrumentation (SAMURAI) software tool. The resulting analysis provides detailed insight into the ET system and allows specific features of the system to be identified, including deep convection, a stratiform precipitation region, warm- and cold-frontal structures, and a dry intrusion. The analysis offers valuable information about the interaction of the features identified within the transitioning tropical cyclone. The existence of dry midlatitude air above warm-moist tropical air led to strong potential instability. Quasigeostrophic diagnostics suggest that forced ascent during warm frontogenesis triggered the deep convective development in this potentially unstable environment. The deep convection itself produced a positive potential vorticity anomaly at midlevels that modified the environmental flow. A comparison of the operational ECMWF analysis and the observation-based SAMURAI analysis exhibits important differences. In particular, the ECMWF analysis does not capture the deep convection adequately. The nonexistence of the deep convection has considerable implications on the potential vorticity structure of the remnants of the typhoon at midlevels. An inaccurate representation of the thermodynamic structure of the dry intrusion has considerable implications on the frontogenesis and the quasigeostrophic forcing.

Evaluation of Medium-Range Forecasts for Hurricane Sandy

Abstract On 30 October 2012 Hurricane Sandy made landfall on the U.S. East Coast with a devastating impact. Here the performance of the ECMWF forecasts (both high resolution and ensemble) are evaluated together with ensemble forecasts from other numerical weather prediction centers, available from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) archive. The sensitivity to sea surface temperature (SST) and model resolution for the ECMWF forecasts are explored. The results show that the ECMWF forecasts provided a clear indication of the landfall from 7 days in advance. Comparing ensemble forecasts from different centers, the authors find the ensemble forecasts from ECMWF to be the most consistent in the forecast of the landfall of Sandy on the New Jersey coastline. The impact of the warm SST anomaly off the U.S. East Coast is investigated by running sensitivity experiments with climatological SST instead of persisting the SST anomaly from the analysis. The results show that the SST anomaly had a small effect on Sandy’s track in the forecast, but the forecasts initialized with the warm SST anomaly feature a more intense system in terms of the depth of the cyclone, wind speeds, and precipitation. Furthermore, the role of spatial resolution is investigated by comparing four global simulations, spanning from TL159 (150 km) to TL3999 (5 km) horizontal resolution. Forecasts from 3 and 5 days before the landfall are evaluated. While all resolutions predict Sandy’s landfall, at very high resolution the tropical cyclone intensity and the oceanic wave forecasts are greatly improved.

BMA Probabilistic Quantitative Precipitation Forecasting over the Huaihe Basin Using TIGGE Multimodel Ensemble Forecasts

Abstract Bayesian model averaging (BMA) probability quantitative precipitation forecast (PQPF) models were established by calibrating their parameters using 1–7-day ensemble forecasts of 24-h accumulated precipitation, and observations from 43 meteorological stations in the Huaihe Basin. Forecasts were provided by four single-center (model) ensemble prediction systems (EPSs) and their multicenter (model) grand ensemble systems, which consider exchangeable members (EGE) in The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE). The four single-center EPSs were from the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), the National Centers for Environment Prediction (NCEP), and the Met Office (UKMO). Comparisons between the raw ensemble, logistic regression, and BMA for PQPFs suggested that the BMA predictive models performed better than the raw ensemble forecasts and logistic regression. The verification and comparison of five BMA EPSs for PQPFs in the study area showed that the UKMO and ECMWF were a little superior to the NCEP and CMA in general for lead times of 1–7 days for the single-center EPSs. The BMA model for EGE outperformed those for single-center EPSs for all 1–7-day ensemble forecasts, and mostly improved the quality of PQPF. Based on the percentile forecasts from the BMA predictive PDFs for EGE, a heavy-precipitation warning scheme is proposed for the test area.

Probabilistic Evaluation of the Dynamics and Prediction of Supertyphoon Megi (2010)

Abstract Supertyphoon Megi was the most intense tropical cyclone (TC) of 2010. Megi tracked westward through the western North Pacific and crossed the Philippines on 18 October. Two days later, Megi made a sharp turn to the north, an unusual track change that was not forecast by any of the leading operational centers. This failed forecast was a consequence of exceptionally large uncertainty in the numerical guidance—including the operational ensemble of the European Centre for Medium-Range Weather Forecasts (ECMWF)—at various lead times before the northward turn. This study uses The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble dataset to examine the uncertainties in the track forecast of the ECMWF operational ensemble. The results show that Megi's sharp turn is sensitive to its own movement in the early period, the size and structure of the storm, the strength and extent of the western Pacific subtropical high, and an approaching eastward-moving midlatitude trough. In particular, a larger TC (in addition to having a stronger beta effect) may lead to a stronger erosion of the southwestern extent of the subtropical high, which will subsequently lead to an earlier and sharper northward turn.

A Solo-Based Automated Quality Control Algorithm for Airborne Tail Doppler Radar Data

AbstractAn automated quality control preprocessing algorithm for removing nonweather radar echoes in airborne Doppler radar data has been developed. This algorithm can significantly reduce the time and experience level required for interactive radar data editing prior to dual-Doppler wind synthesis or data assimilation. The algorithm uses the editing functions in the Solo software package developed by the National Center for Atmospheric Research to remove noise, Earth-surface, sidelobe, second-trip, and other artifacts. The characteristics of these nonweather radar returns, the algorithm to identify and remove them, and the impacts of applying different threshold levels on wind retrievals are presented. Verification was performed by comparison with published Electra Doppler Radar (ELDORA) datasets that were interactively edited by different experienced radar meteorologists. Four cases consisting primarily of convective echoes from the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX), Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX), Hurricane Rainband and Intensity Change Experiment (RAINEX), and The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC)/Tropical Cyclone Structure-2008 (TCS08) field experiments were used to test the algorithm using three threshold levels for data removal. The algorithm removes 80%, 90%, or 95% of the nonweather returns and retains 95%, 90%, or 85% of the weather returns on average at the low-, medium-, and high-threshold levels. Increasing the threshold level removes more nonweather echoes at the expense of also removing more weather echoes. The low threshold is recommended when weather retention is the highest priority, and the high threshold is recommended when nonweather removal is the highest priority. The medium threshold is a good compromise between these two priorities and is recommended for general use. Dual-Doppler wind retrievals using the automatically edited data compare well to retrievals from interactively edited data.

Physical Mechanisms Underlying Selected Adaptive Sampling Techniques for Tropical Cyclones

Abstract To efficiently and effectively prioritize resources, adaptive observations can be targeted by using some objective criteria to estimate the potential impact an initial condition perturbation (or analysis increment) in a specific region would have on the future forecast. Several objective targeting guidance techniques have been developed, including total-energy singular vectors (TESV), adjoint-derived sensitivity steering vectors (ADSSV), and the ensemble transform Kalman filter (ETKF), all of which were tested during the 2008 The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) and the Office of Naval Research Tropical Cyclone Structure-2008 (TCS-08) field experiments. An intercomparison between these techniques is performed in order to find underlying physical mechanisms in the respective guidance products, based on four tropical cyclone (TC) cases from the T-PARC/TCS-08 field campaigns. It is found that the TESV energy norm and the ADSSV response function are largely indirect measures of the TC track divergence that can be produced by an initial condition perturbation, explaining the strong correlation between these products. The downstream targets routinely chosen by the ETKF guidance system are often not found in the TESV and ADSSV guidance products, and it is found that downstream perturbations can affect the steering of a TC through the development of a Rossby wave in the subtropics that modulates the strength of the nearby subtropical ridge. It is hypothesized that the ubiquitousness of these downstream targets in the ETKF is largely due to the existence of large uncertainties downstream of the TC that are not taken into consideration by either the TESV or ADSSV techniques.

Lead time for medium range prediction of the dry spell of monsoon using multi-models

The purpose of this study is to address prediction of the start date and the duration of breaks in the summer monsoon rains using multi-model superensemble. The availability of datasets from the ‘observing system research and predictability experiment (THORPEX)’ initiated a forecast data archive, called THORPEX interactive grand global ensemble (TIGGE), makes it possible to use forecasts from a suite of individual ensemble prediction systems (member models) and to construct multi-model superensemble forecasts that are designed to remove the collective bias errors of the suite of models. Precipitation datasets are important for this study, we have used high resolution daily gridded rainfall dataset of India Meteorological Department (IMD), in addition to rainfall estimates from tropical rainfall microwave mission (TRMM) satellite and the CPC morphing technique (CMORPH). The scientific approach of this study entails the use of a multi-model superensemble for forecast and to verify against the rainfall information during a training phase, as well as during a forecast phase. We examine the results of forecasts out to day-10 and ask how well do forecast strings of day-1 through day-10 handle the prediction of the onset and duration of the breaks in the summer monsoon rains. Our results confirm that it is possible to predict the onset of a dry spell, around week in advance from the use of the multi-model superensemble and a suite of TIGGE models. We also examine trajectories of the parcels arriving in India in such forecasts from member models and from the multi-model superensemble to validate the arrival of descending dry desert air from the Arabian region during the dry spells and its mode of transition from wet spell. Some phenological features such as a shift in the latitude of the tropical easterly jet and changes in its intensity during break periods are additional observed features that are validated from the history of multi-model superensemble forecasts. Invariably this multi-model superensemble performs better than any single model in proving the better forecasts during our experiment period.

Effect of targeted dropsonde observations and best track data on the track forecasts of Typhoon Sinlaku (2008) using an ensemble Kalman filter

During August and September 2008, The Observing System Research and Predictability Experiment (THORPEX) – Pacific Asian Regional Campaign (T-PARC) was conducted to investigate the formation, structure, targeted observation, extratropical transition (ET) and downstream effects of tropical cyclones (TCs) in the Western North Pacific (WNP) region. This study investigates the effect of targeted dropsonde observations from T-PARC and the TC best track data on the track forecast of Typhoon Sinlaku (2008). A WRF-based ensemble Kalman filter (EnKF) is used for a series of observation system experiments (OSEs). From the innovation statistics and rank histograms, the EnKF behaves well in terms of ensemble spread, despite some spread deficiency in low-tropospheric winds and warm and moist biases. Assimilation of targeted dropsonde observations leads to improved initial position and subsequent track forecast compared with experiments that only assimilate conventional observations. In the meantime, assimilation of TC position reduces the initial position error, whereas assimilation of minimum sea level pressure (SLP) information is efficient to analyse the strong vortex structures of TC and reduces track forecast errors. Assimilation of TC position and minimum SLP information is particularly beneficial when dropsonde observations do not exist.

Adjoint Sensitivity and Predictability of Tropical Cyclogenesis

Abstract The sensitivity of tropical cyclogenesis and subsequent intensification is explored by applying small perturbations to the initial state in the presence of organized mesoscale convection and synoptic-scale forcing using the adjoint and tangent linear models for the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). The forward, adjoint, and tangent linear models are used to compare and contrast predictability characteristics for the disturbance that became Typhoon Nuri and a nondeveloping organized convective cluster in the western Pacific during The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) and the Tropical Cyclone Structure-2008 (TCS-08) experiments. The adjoint diagnostics indicate that the intensity (e.g., maximum surface wind speed, minimum surface pressure) of a tropical disturbance is very sensitive to perturbations in the moisture and temperature fields and to a lesser degree the wind fields. The highest-resolution adjoint simulations (grid increment of 13 km) indicate that the most efficient intensification is through moistening in the lower and middle levels and heating in banded regions that are coincident with vorticity maxima in the initial state. Optimal adjoint perturbations exhibit rapid growth for the Nuri case and only modest growth for the nondeveloping system. The adjoint results suggest that Nuri was near the threshold for development, indicative of low predictability. The low-level sensitivity maximum and tendency for optimal perturbation growth to extend vertically through the troposphere are consistent with a “bottom up” development process of TC genesis, although a secondary midlevel sensitivity maximum is present as well. Growth originates at small scales and projects onto the scale of the vortex, a manifestation of perturbations that project onto organized convection embedded in regions of cyclonic vorticity.

Convection and Rapid Filamentation in Typhoon Sinlaku during TCS-08/T-PARC

Abstract This study examines the convection and rapid filamentation in Typhoon Sinlaku (2008) using the Naval Research Laboratory (NRL) P-3 aircraft data collected during the Tropical Cyclone Structure 2008 (TCS-08) and The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) field experiments. The high-resolution aircraft radar and wind data are used to directly compute the filamentation time, to allow an investigation into the effect of filamentation on convection. During the reintensification stage, some regions of deep convection near the eyewall are found in the vorticity-dominated area where there is little filamentation. In some other parts of the eyewall and the outer spiral rainband region, including areas of upward motion, the filamentation process appears to suppress deep convection. However, the magnitude of the suppression differs greatly in the two regions. In the outer spiral band region, which is about 200 km from the center, the suppression is much more effective, such that the ratio of the deep convective regime occurrence over the stratiform regime varies from around 50% (200%) for filamentation time shorter (longer) than 24 min. In the eyewall cloud region where the conditions are conducive to deep convection, the filamentation effect may be quite limited. While effect of filamentation suppression is only about 10%, it is still systematic and conspicuous for filamentation times shorter than 19 min. The results suggest the possible importance of vortex-scale filamentation dynamics in suppressing deep convection and organizing spiral bands, which may affect the development and evolution of tropical cyclones.

The “Year” of Tropical Convection (May 2008–April 2010): Climate Variability and Weather Highlights

The representation of tropical convection remains a serious challenge to the skillfulness of our weather and climate prediction systems. To address this challenge, the World Climate Research Programme (WCRP) and The Observing System Research and Predictability Experiment (THORPEX) of the World Weather Research Programme (WWRP) are conducting a joint research activity consisting of a focus period approach along with an integrated research framework tailored to exploit the vast amounts of existing observations, expanding computational resources, and the development of new, high-resolution modeling frameworks. The objective of the Year of Tropical Convection (YOTC) is to use these constructs to advance the characterization, modeling, parameterization, and prediction of multiscale tropical convection, including relevant two-way interactions between tropical and extratropical systems. This article highlights the diverse array of scientifically interesting and socially important weather and climate events associated with the WCRP–WWRP/THORPEX YOTC period of interest: May 2008–April 2010. Notable during this 2-yr period was the change from cool to warm El Niño– Southern Oscillation (ENSO) states and the associated modulation of a wide range of smaller time- and space-scale tropical convection features. This period included a near-record-setting wet North American monsoon in 2008 and a very severe monsoon drought in India in 2009. There was also a plethora of tropical wave activity, including easterly waves, the Madden–Julian oscillation, and convectively coupled equatorial wave interactions. Numerous cases of high-impact rainfall events occurred along with notable features in the tropical cyclone record. The intent of this article is to highlight these features and phenomena, and in turn promote their interrogation via theory, observations, and models in concert with the YOTC program so that improved understanding and pre- dictions of tropical convection can be afforded.

Potential Vorticity Diagnosis of the Factors Affecting the Track of Typhoon Sinlaku (2008) and the Impact from Dropwindsonde Data during T-PARC

Abstract In 2008, abundant dropwindsonde data were collected during both reconnaissance and surveillance flights in and around tropical cyclones (TCs) in the western North Pacific basin under the framework of The Observing System Research and Predictability Experiment (THORPEX)–Pacific Asian Regional Campaign (T-PARC). The National Centers for Environmental Prediction Global Forecast System (GFS) showed significant track improvements for Typhoon Sinlaku (2008) after the assimilation of dropwindsonde data. For this particular typhoon, the potential vorticity (PV) diagnosis is adopted to understand the key factors affecting the track. A data denial run initialized at 0000 UTC 10 September is examined to evaluate how the extra data collected during T-PARC improve GFS track forecasts. A quantitative analysis of the steering flow based on the PV diagnosis indicates that the Pacific subtropical high to the east of Sinlaku is a primary factor that advects Sinlaku northwestward, while the monsoon trough plays a secondary role. The assimilation of dropwindsonde data improves the structure and intensity of the initial vortex and maintains the forecast vortex structure in the vertical. The difference in the vertical extent of the vortices could be regarded as a cause for the discrepancy in steering flow between runs with and without the dropwindsonde data. This paper highlights the importance of improved analyses of the vertical TC structure, and thus of a representative steering flow in the deep troposphere during the forecasts.

Verification of TIGGE Multimodel and ECMWF Reforecast-Calibrated Probabilistic Precipitation Forecasts over the Contiguous United States*

Abstract Probabilistic quantitative precipitation forecasts (PQPFs) were generated from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) database from July to October 2010 using data from Europe (ECMWF), the United Kingdom [Met Office (UKMO)], the United States (NCEP), and Canada [Canadian Meteorological Centre (CMC)]. Forecasts of 24-h accumulated precipitation were evaluated at 1° grid spacing within the contiguous United States against analysis data based on gauges and bias-corrected radar data. PQPFs from ECMWF’s ensembles generally had the highest skill of the raw ensemble forecasts, followed by CMC. Those of UKMO and NCEP were less skillful. PQPFs from CMC forecasts were the most reliable but the least sharp, and PQPFs from NCEP and UKMO ensembles were the least reliable but sharper. Multimodel PQPFs were more reliable and skillful than individual ensemble prediction system forecasts. The improvement was larger for heavier precipitation events [e.g., >10 mm (24 h)−1] than for smaller events [e.g., >1 mm (24 h)−1]. ECMWF ensembles were statistically postprocessed using extended logistic regression and the five-member weekly reforecasts for the June–November period of 2002–09, the period where precipitation analyses were also available. Multimodel ensembles were also postprocessed using logistic regression and the last 30 days of prior forecasts and analyses. The reforecast-calibrated ECMWF PQPFs were much more skillful and reliable for the heavier precipitation events than ECMWF raw forecasts but much less sharp. Raw multimodel PQPFs were generally more skillful than reforecast-calibrated ECMWF PQPFs for the light precipitation events but had about the same skill for the higher-precipitation events; also, they were sharper but somewhat less reliable than ECMWF reforecast-based PQPFs. Postprocessed multimodel PQPFs did not provide as much improvement to the raw multimodel PQPF as the reforecast-based processing did to the ECMWF forecast. The evidence presented here suggests that all operational centers, even ECMWF, would benefit from the open, real-time sharing of precipitation forecast data and the use of reforecasts.

Moisture Transport into Midlatitudes ahead of Recurving Tropical Cyclones and Its Relevance in Two Predecessor Rain Events

Abstract Global ensemble forecasts from The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) are used to quantify the magnitude of moisture transport into North America ahead of recurving tropical cyclones (TCs). Two cases in which a predecessor rain event (PRE) occurred ahead of the recurving TC—Erin (2007) and Ike (2008)—are analyzed, with ensemble members correctly predicting TC recurvature contrasted from those predicting the TC to weaken or turn southward. This analysis demonstrates that TC-related moisture transport can increase the total water vapor in the atmosphere over North America by 20 mm or more, and that the moisture transport takes place both in the boundary layer and aloft. The increased moisture does not always correspond to increased rainfall in the ensemble forecasts, however, as the location and strength of baroclinic zones and their attendant secondary circulations that can lift this moist air are also crucial to the development of heavy rains.

An Overview of the Beijing 2008 Olympics Research and Development Project (B08RDP)

The Beijing 2008 Olympics Research and Development Project (B08RDP), initiated in 2004 under the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), undertook the research and development of mesoscale ensemble prediction systems (MEPSs) and their application to weather forecast support during the Beijing Olympic Games. Six MEPSs from six countries, representing the state-of-the-art regional EPSs with near-real-time capabilities and emphasizing on the 6–36-h forecast lead times, participated in the project. The background, objectives, and implementation of B08RDP, as well as the six MEPSs, are reviewed. The accomplishments are summarized, which include 1) providing value-added service to the Olympic Games, 2) advancing MEPS-related research, 3) accelerating the transition from research to operations, and 4) training forecasters in utilizing forecast uncertainty products. The B08RDP has fulfilled its research (MEPS development) and demonstration (value-added service) purposes. The research conducted covers the areas of verification, examining the value of MEPS relative to other numerical weather prediction (NWP) systems, combining multimodel or multicenter ensembles, bias correction, ensemble perturbations [initial condition (IC), lateral boundary condition (LBC), land surface IC, and model physics], downscaling, forecast applications, data assimilation, and storm-scale ensemble modeling. Seven scientific issues important to MEPS have been identified. It is recognized that the daily use of forecast uncertainty information by forecasters remains a challenge. Development of forecaster-friendly products and training activities should be a long-term effort and needs to be continuously enhanced. The B08RDP dataset is also a valuable asset to the research community. The experience gained in international collaboration, organization, and implementation of a multination regional EPS for a common goal and to address common scientific issues can be shared by the ongoing projects The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble—Limited Area Models (TIGGE-LAM) and North American Ensemble Forecast System—Limited Area Models (NAEFS-LAM).

Concentric Eyewall Formation in Typhoon Sinlaku (2008). Part I: Assimilation of T-PARC Data Based on the Ensemble Kalman Filter (EnKF)

Typhoon Sinlaku (2008) is a case in point under The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) with the most abundant flight observations taken and with great potential to address major scientific issues in T-PARC such as structure change, targeted observations, and extratropical transition. A new method for vortex initialization based on ensemble Kalman filter (EnKF) data assimilation and the Weather Research and Forecasting (WRF) model is adopted in this study. By continuously assimilating storm positions (with an update cycle every 30 min), the mean surface wind structure, and all available measurement data, this study constructs a unique high-spatial/temporal-resolution and model/observation-consistent dataset for Sinlaku during a 4-day period. Simulations of Sinlaku starting at different initial times are further investigated to assess the impact of the data. It is striking that some of the simulations are able to capture Sinlaku’s secondary eyewall formation, while others starting the simulation earlier with less data assimilated are not. This dataset provides a unique opportunity to study the dynamical processes of concentric eyewall formation in Sinlaku. In Part I of this work, results from the data assimilation and simulations are presented, including concentric eyewall evolution and the precursors to its formation, while detailed dynamical analyses are conducted in follow-up research.

Development and application of an atmospheric-hydrologic-hydraulic flood forecasting model driven by TIGGE ensemble forecasts

A coupled atmospheric-hydrologic-hydraulic ensemble flood forecasting model, driven by The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) data, has been developed for flood forecasting over the Huaihe River. The incorporation of numerical weather prediction (NWP) information into flood forecasting systems may increase forecast lead time from a few hours to a few days. A single NWP model forecast from a single forecast center, however, is insufficient as it involves considerable non-predictable uncertainties and leads to a high number of false alarms. The availability of global ensemble NWP systems through TIGGE offers a new opportunity for flood forecast. The Xinanjiang model used for hydrological rainfall-runoff modeling and the one-dimensional unsteady flow model applied to channel flood routing are coupled with ensemble weather predictions based on the TIGGE data from the Canadian Meteorological Centre (CMC), the European Centre for Medium-Range Weather Forecasts (ECMWF), the UK Met Office (UKMO), and the US National Centers for Environmental Prediction (NCEP). The developed ensemble flood forecasting model is applied to flood forecasting of the 2007 flood season as a test case. The test case is chosen over the upper reaches of the Huaihe River above Lutaizi station with flood diversion and retarding areas. The input flood discharge hydrograph from the main channel to the flood diversion area is estimated with the fixed split ratio of the main channel discharge. The flood flow inside the flood retarding area is calculated as a reservoir with the water balance method. The Muskingum method is used for flood routing in the flood diversion area. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE ensemble forecasts. The results demonstrate satisfactory flood forecasting with clear signals of probability of floods up to a few days in advance, and show that TIGGE ensemble forecast data are a promising tool for forecasting of flood inundation, comparable with that driven by raingauge observations.

Preliminary comparison of the CMA, ECMWF, NCEP, and JMA ensemble prediction systems

Based on The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) dataset, using various verification methods, the performances of four typical ensemble prediction systems (EPSs) from the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), the US National Centers for Environmental Prediction (NCEP), and the Japan Meteorological Agency (JMA) are compared preliminarily. The verification focuses on the 500-hPa geopotential height forecast fields in the mid- and high-latitude Eurasian region during July 2007 and January 2008. The results show that for the forecast of 500-hPa geopotential height, in both summer and winter, the ECMWF EPS exhibits the highest forecast skill, followed by that of NCEP, then by JMA, and the CMA EPS gets in the last. The better system behaviors benefit from the better combination of the following: data assimilation system, numerical models, initial perturbations, and stochastic model perturbations. For the medium-range forecast, the ensemble forecasting can effectively filter out the forecast errors associated with the initial uncertainty, and the reliability and resolution (the two basic attributions of the forecast system) of these EPSs are better in winter than in summer. Specifically, the CMA EPS has certain advantage on the reliability of ensemble probabilistic forecasts. The forecasts are easy to be underestimated by the JMA EPS. The deficiency of ensemble spread, which is the universal problem of EPS, also turns up in this study. Although the systems of ECMWF, NCEP, and JMA have more ensemble members, this problem cannot be ignored. This preliminary comparison helps to further recognize the prediction capability of the four EPSs over the Eurasian region, provides important references for wide applications of the TIGGE dataset, and supplies useful information for improving the CMA EPS.

Probabilistic flood prediction in the upper Huaihe catchment using TIGGE data

Based on the precipitation and temperature data obtained from THORPEX (The Observing System Research and Predictability Experiment) Interactive Grand Global Ensemble (TIGGE)-China Meteorological Administration (CMA) archiving center and the raingauge data, the three-layer variable infiltration capacity (VIC-3L) land surface model was employed to carry out probabilistic hydrological forecast experiments over the upper Huaihe River catchment from 20 July to 3 August 2008. The results show that the performance of the ensemble probabilistic prediction from each ensemble prediction system (EPS) is better than that of the deterministic prediction. Especially, the 72-h prediction has been improved obviously. The ensemble spread goes widely with increasing lead time and more observed discharge is bracketed in the 5th-99th quantile. The accuracy of river discharge prediction driven by the European Centre (EC)-EPS is higher than that driven by the CMA-EPS and the US National Centers for Environmental Prediction (NCEP)-EPS, and the grand-ensemble prediction is the best for hydrological prediction using the VIC model. With regard to Wangjiaba station, all predictions made with a single EPS are close to the observation between the 25th and 75th quantile. The onset of the flood ascending and the river discharge thresholds are predicted well, and so is the second rising limb. Nevertheless, the flood recession is not well predicted.