Tropical cyclone climatology in a 10-km global atmospheric GCM: toward weather-resolving climate modeling

Northern Hemisphere tropical cyclone (TC) activity is investigated in multiyear global climate simulations with theECMWFIntegrated Forecast System (IFS) at 10-km resolution forced by the observed records of sea surface temperature and sea ice. The results are compared to analogous simulationswith the 16-, 39-, and 125-km versions of the model as well as observations. In the North Atlantic, mean TC frequency in the 10-km model is comparable to the observed frequency, whereas it is too low in the other versions. While spatial distributions of the genesis and track densities improve systematically with increasing resolution, the 10-km model displays qualitatively more realistic simulation of the track density in the western subtropical North Atlantic. In the North Pacific, the TC count tends to be too high in thewest and too low in the east for all resolutions. These model errors appear to be associated with the errors in the large-scale environmental conditions that are fairly similar in this region for all model versions. The largest benefits of the 10-km simulation are the dramatically more accurate representation of the TC intensity distribution and the structure of the most intense storms. The model can generate a supertyphoon with a maximum surface wind speed of 68.4 m s21. The life cycle of an intense TC comprises intensity fluctuations that occur in apparent connection with the variations of the eyewall/rainband structure. These findings suggest that a hydrostatic model with cumulus parameterization and of high enough resolution could be efficiently used to simulate the TC intensity response (and the associated structural changes) to future climate change.

Reliability of regional climate model trends

A necessary condition for a good probabilistic forecast is that the forecast system is shown to be reliable: forecast probabilities should equal observed probabilities verified over a large number of cases. As climate change trends are now emerging from the natural variability, we can apply this concept to climate predictions and compute the reliability of simulated local and regional temperature and precipitation trends (1950–2011) in a recent multi-model ensemble of climate model simulations prepared for the Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5). With only a single verification time, the verification is over the spatial dimension. The local temperature trends appear to be reliable. However, when the global mean climate response is factored out, the ensemble is overconfident: the observed trend is outside the range of modelled trends in many more regions than would be expected by the model estimate of natural variability and model spread. Precipitation trends are overconfident for all trend definitions. This implies that for near-term local climate forecasts the CMIP5 ensemble cannot simply be used as a reliable probabilistic forecast.

Atmospheric predictability revisited

This article examines the potential to improve numerical weather prediction (NWP) by estimating upper and lower bounds on predictability by re-visiting the original study of Lorenz (1982) but applied to the most recent version of the European Centre for Medium Range Weather Forecasts (ECMWF) forecast system, for both the deterministic and ensemble prediction systems (EPS). These bounds are contrasted with an older version of the same NWP system to see how they have changed with improvements to the NWP system. The computations were performed for the earlier seasons of DJF 1985/1986 and JJA 1986 and the later seasons of DJF 2010/2011 and JJA 2011 using the 500-hPa geopotential height field. Results indicate that for this field, we may be approaching the limit of deterministic forecasting so that further improvements might only be obtained by improving the initial state. The results also show that predictability calculations with earlier versions of the model may overestimate potential forecast skill, which may be due to insufficient internal variability in the model and because recent versions of the model are more realistic in representing the true atmospheric evolution. The same methodology is applied to the EPS to calculate upper and lower bounds of predictability of the ensemble mean forecast in order to explore how ensemble forecasting could extend the limits of the deterministic forecast. The results show that there is a large potential to improve the ensemble predictions, but for the increased predictability of the ensemble mean, there will be a trade-off in information as the forecasts will become increasingly smoothed with time. From around the 10-d forecast time, the ensemble mean begins to converge towards climatology. Until this point, the ensemble mean is able to predict the main features of the large-scale flow accurately and with high consistency from one forecast cycle to the next. By the 15-d forecast time, the ensemble mean has lost information with the anomaly of the flow strongly smoothed out. In contrast, the control forecast is much less consistent from run to run, but provides more detailed (unsmoothed) but less useful information.

Satellite-supported flood forecasting in river networks: a real case study

Satellite-based (e.g., Synthetic Aperture Radar [SAR]) water level observations (WLOs) of the floodplain can be sequentially assimilated into a hydrodynamic model to decrease forecast uncertainty. This has the potential to keep the forecast on track, so providing an Earth Observation (EO) based flood forecast system. However, the operational applicability of such a system for floods developed over river networks requires further testing. One of the promising techniques for assimilation in this field is the family of ensemble Kalman (EnKF) filters. These filters use a limited-size ensemble representation of the forecast error covariance matrix. This representation tends to develop spurious correlations as the forecast-assimilation cycle proceeds, which is a further complication for dealing with floods in either urban areas or river junctions in rural environments. Here we evaluate the assimilation of WLOs obtained from a sequence of real SAR overpasses (the X-band COSMO-Skymed constellation) in a case study. We show that a direct application of a global Ensemble Transform Kalman Filter (ETKF) suffers from filter divergence caused by spurious correlations. However, a spatially-based filter localization provides a substantial moderation in the development of the forecast error covariance matrix, directly improving the forecast and also making it possible to further benefit from a simultaneous online inflow error estimation and correction. Additionally, we propose and evaluate a novel along-network metric for filter localization, which is physically-meaningful for the flood over a network problem. Using this metric, we further evaluate the simultaneous estimation of channel friction and spatially-variable channel bathymetry, for which the filter seems able to converge simultaneously to sensible values. Results also indicate that friction is a second order effect in flood inundation models applied to gradually varied flow in large rivers. The study is not conclusive regarding whether in an operational situation the simultaneous estimation of friction and bathymetry helps the current forecast. Overall, the results indicate the feasibility of stand-alone EO-based operational flood forecasting.

Future changes in the Western North Pacific tropical cyclone activity projected by a multidecadal simulation with a 16-km global atmospheric GCM

How tropical cyclone (TC) activity in the northwestern Pacific might change in a future climate is assessed using multidecadal Atmospheric Model Intercomparison Project (AMIP)-style and time-slice simulations with the ECMWF Integrated Forecast System (IFS) at 16-km and 125-km global resolution. Both models reproduce many aspects of the present-day TC climatology and variability well, although the 16-km IFS is far more skillful in simulating the full intensity distribution and genesis locations, including their changes in response to El Niño–Southern Oscillation. Both IFS models project a small change in TC frequency at the end of the twenty-first century related to distinct shifts in genesis locations. In the 16-km IFS, this shift is southward and is likely driven by the southeastward penetration of the monsoon trough/subtropical high circulation system and the southward shift in activity of the synoptic-scale tropical disturbances in response to the strengthening of deep convective activity over the central equatorial Pacific in a future climate. The 16-km IFS also projects about a 50% increase in the power dissipation index, mainly due to significant increases in the frequency of the more intense storms, which is comparable to the natural variability in the model. Based on composite analysis of large samples of supertyphoons, both the development rate and the peak intensities of these storms increase in a future climate, which is consistent with their tendency to develop more to the south, within an environment that is thermodynamically more favorable for faster development and higher intensities. Coherent changes in the vertical structure of supertyphoon composites show system-scale amplification of the primary and secondary circulations with signs of contraction, a deeper warm core, and an upward shift in the outflow layer and the frequency of the most intense updrafts. Considering the large differences in the projections of TC intensity change between the 16-km and 125-km IFS, this study further emphasizes the need for high-resolution modeling in assessing potential changes in TC activity.

The Met Office Global Coupled model 2.0 (GC2) configuration

The latest coupled configuration of the Met Office Unified Model (Global Coupled configuration 2, GC2) is presented. This paper documents the model components which make up the configuration (although the scientific description of these components is detailed elsewhere) and provides a description of the coupling between the components. The performance of GC2 in terms of its systematic errors is assessed using a variety of diagnostic techniques. The configuration is intended to be used by the Met Office and collaborating institutes across a range of timescales, with the seasonal forecast system (GloSea5) and climate projection system (HadGEM) being the initial users. In this paper GC2 is compared against the model currently used operationally in those two systems. Overall GC2 is shown to be an improvement on the configurations used currently, particularly in terms of modes of variability (e.g. mid-latitude and tropical cyclone intensities, the Madden–Julian Oscillation and El Niño Southern Oscillation). A number of outstanding errors are identified with the most significant being a considerable warm bias over the Southern Ocean and a dry precipitation bias in the Indian and West African summer monsoons. Research to address these is ongoing.

Um sistema de previsão de tempo e de ondas oceânicas para o Atlântico Sul

Um sistema de previsão numérica de tempo e de ondas oceânicas (SPTO) que possa ser operacionalizado no Atlântico Sul é proposto. O SPTO é composto por um modelo atmosférico de área limitada (MAL) e um modelo de ondas de superfície do oceano geradas pelo vento, aplicado em duas versões: uma de malha grossa (MPOMG) e outra de malha fina (MPOMF). O MPOMG abrange uma área de 10(6) km², e tem como finalidade gerar e propagar ondas em regiões remotas à costa brasileira. O MPOMF é aplicado em um domínio 10(4) km² com alta resolução, incorporando irregularidades batimétricas e com as condições iniciais e de fronteiras fomecidas pelo MPOMG. Os modelos utilizam dados de vento à 10 m acima da superfície do oceano. Os arquivos de vento, contendo a evolução espacial e temporais são gerados pelo MAL. Um exemplo de um evento real ocorrido no período de 9 a 11 de agosto de 1988 é apresentado utilizando o acoplamento proposto.

A Multiple-Vortex Tornado in Southeastern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

BRAZILIAN OFFSHORE WAVE CLIMATE BASED ON NWW3 REANALYSIS

This paper provides a description of the wave climate off the Brazilian coast based on an eleven-year time series (Jan/1997-Dec/2007) obtained from the NWW3 operational model hindcast reanalysis. Information about wave climate in Brazilian waters is very scarce and mainly based on occasional short-term observations, the present analysis being the first covering such temporal and spatial scales. To define the wave climate, six sectors were defined and analyzed along the Brazilian shelf-break: South (W1), Southeast (W2), Central (W3), East (W4), Northeast (W5) and North (W6). W1, W2 and W3 wave regimes are determined by the South Atlantic High (SAH) and the passage of synoptic cold fronts; W4, W5 and W6 are controlled by the Intertropical Convergence Zone (ITCZ) and its meridional oscillation. The most energetic waves are from the S, generated by the strong winds associated to the passage of cold fronts, which mainly affect the southern region. Wave power presents a decrease in energy levels from south to north, with its annual variation showing that the winter months are the most energetic in W1 to W4, while in W5 and W6 the most energetic conditions occur during the austral summer. The information presented here provides boundary conditions for studies related to coastal processes, fundamental for a better understanding of the Brazilian coastal zone.

Assimilation of Meteosat Second Generation (MSG) satellite data in a regional numerical weather prediction model using a one-dimensional variational approach

The quality of temperature and humidity retrievals from the infrared SEVIRI sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high resolution regional scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO (COnsortium for Small scale MOdelling) in the ARPA-SIM operational configuration is used to provide background fields. Only clear sky observations over sea are processed. An optimised 1D–VAR set-up comprising of the two water vapour and the three window channels is selected. It maximises the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1D–VAR retrieval quality is firstly quantified in relative terms employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed comparing the analysis with independent radiosonde and satellite observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the retrieval profiles generated by the 1D–VAR are well correlated with the radiosonde measurements. Subsequently the 1D–VAR technique is applied to two three–dimensional case–studies: a false alarm case–study occurred in Friuli–Venezia–Giulia on the 8th of July 2004 and a heavy precipitation case occurred in Emilia–Romagna region between 9th and 12th of April 2005. The impact of satellite data for these two events is evaluated in terms of increments in the integrated water vapour and saturation water vapour over the column, in the 2 meters temperature and specific humidity and in the surface temperature. To improve the 1D–VAR technique a method to calculate flow–dependent model error covariance matrices is also assessed. The approach employs members from an ensemble forecast system generated by perturbing physical parameterisation schemes inside the model. The improved set–up applied to the case of 8th of July 2004 shows a substantial neutral impact.

Massenspektrometrische Wasserdampfmessung in der oberen Troposphäre und unteren Stratosphäre

Diese Arbeit beschreibt die Entwicklung des flugzeuggetragenen Atmosphärischen Ionisations-Massenspektrometers AIMS-H2O zur Messung von Wasserdampf in der oberen Troposphäre und unteren Stratosphäre (UTLS) und erste Flugzeugmessungen mit dem Instrument. Wasserdampf beeinflusst das Klima in der UTLS aufgrund seiner Strahlungseigenschaften und agiert als wichtiger Parameter bei der Bildung von Zirruswolken und Kondensstreifen. Deshalb sind genaue Wasserdampfmessungen für das Verständnis vieler atmosphärischer Prozesse unerlässlich. Instrumentenvergleiche wie sie im SPARC Report No. 2 und dem Bericht der AUQAVIT Kampagne zusammengefasst sind, haben gezeigt, dass große Abweichungen zwischen einzelnen Methoden und Instrumenten bestehen. Diese Unsicherheiten limitieren das Verständnis des Einflusses von Wasserdampf auf die Dynamik und die Strahlungseigenschaften in der UTLS. Die in dieser Arbeit vorgestellte Entwicklung einer neuen Messmethode für Wasserdampf mit dem Massenspektrometer AIMS-H2O ist deshalb auf die genaue Messung niedriger Wasserdampfkonzentrationen in der UTLS fokussiert. Mit AIMS H2O wird Umgebungsluft in einer neu entwickelten Gasentladungsquelle ionisiert. Durch eine Reihe von Ionen-Molekül-Reaktionen entstehen H3O+(H2O) und H3O+(H2O)2 Ionen. Diese Ionen werden genutzt, um die Wasserdampfkonzentration in der Atmosphäre zu bestimmen. Um die erforderliche hohe Genauigkeit zu erzielen, wird AIMS H2O im Flug kalibriert. In dem zu diesem Zweck aufgebauten Kalibrationsmodul wird die katalytische Reaktion von Wasserstoff und Sauerstoff auf einer Platinoberfläche genutzt, um definierte Wasserdampfkonzentrationen für die Kalibration im Flug zu erzeugen. Bei ersten Messungen auf der Falcon während der Kampagne CONCERT 2011 konnte dabei eine Genauigkeit von 8 bis 15% für die Messung der Wasserdampfkonzentration in einem Messbereich von 0,5 bis 250 ppmv erreicht werden. Die Messfrequenz betrug 4 Hz, was einer räumlichen Auflösung von etwa 50 m entspricht. Der Vergleich der Messung des Massenspektrometers mit dem Laserhygrometer Waran zeigt eine sehr gute Übereinstimmung im Rahmen der Unsicherheiten. Anhand zweier Fallstudien werden die Messungen von AIMS H2O während CONCERT 2011 detailliert analysiert. In der ersten Studie werden zwei Flüge in eine stratosphärische Intrusion über Nordeuropa untersucht. In dieser Situation wurde stratosphärische Luft bis hinunter auf 6 km Höhe transportiert und war dadurch mit der Falcon erreichbar. Es konnte gezeigt werden, dass AIMS-H2O sehr gut für die genaue Messung niedriger Wasserdampfkonzentrationen, in diesem Fall bis etwa 3,5 ppmv, geeignet ist. Der Vergleich der Messung mit Analysen des ECMWF Integrated Forecast Systems zeigt eine gute Übereinstimmung der gemessenen Wasserdampfstrukturen mit der dynamischen Tropopause. Unterschiede tauchen dagegen beim Vergleich der Wasserdampfkonzentrationen in der unteren Stratosphäre auf. Hier prognostiziert das Modell deutlich höhere Feuchten. Die zweite Fallstudie beschäftigt sich mit der Verteilung der relativen Feuchte in jungen Kondensstreifen im Vergleich zu ihrer direkten Umgebung. Dabei wurde für drei Messsequenzen im Abgasstrahl von Flugzeugen beobachtet, dass die relative Feuchte innerhalb des Kondensstreifens im Vergleich zur Umgebung sowohl bei unter- als auch übersättigten Umgebungsbedingungen in Richtung Sättigung verschoben ist. Die hohe Anzahl an Eispartikeln und die damit verbundene große Eisoberfläche in jungen Kondensstreifen führt also zu einer schnellen Relaxation von Gasphase und Eis in Richtung Gleichgewicht. In der Zukunft soll AIMS-H2O auch auf HALO für die genaue Messung von Wasserdampf bei ML-CIRRUS und weiteren Kampagnen eingesetzt werden.

A Model Study of the Seasonal Circulation in the Gulf of Maine

The Princeton Ocean Model is used to study the circulation in the Gulf of Maine and its seasonal transition in response to wind, surface heat flux, river discharge, and the M-2 tide. The model has an orthogonal-curvature linear grid in the horizontal with variable spacing from 3 km nearshore to 7 km offshore and 19 levels in the vertical. It is initialized and forced at the open boundary with model results from the East Coast Forecast System. The first experiment is forced by monthly climatological wind and heat flux from the Comprehensive Ocean Atmosphere Data Set; discharges from the Saint John, Penobscot, Kennebec, and Merrimack Rivers are added in the second experiment; the semidiurnal lunar tide (M-2) is included as part of the open boundary forcing in the third experiment. It is found that the surface heat flux plays an important role in regulating the annual cycle of the circulation in the Gulf of Maine. The spinup of the cyclonic circulation between April and June is likely caused by the differential heating between the interior gulf and the exterior shelf/slope region. From June to December the cyclonic circulation continues to strengthen, but gradually shrinks in size. When winter cooling erodes the stratification, the cyclonic circulation penetrates deeper into the water column. The circulation quickly spins down from December to February as most of the energy is consumed by bottom friction. While inclusion of river discharge changes details of the circulation pattern, the annual evolution of the circulation is largely unaffected. On the other hand, inclusion of the tide results in not only the anticyclonic circulation on Georges Bank but also modifications to the seasonal circulation.

Retrospective analysis of a nonforecasted rain-on-snow flood in the Alps – a matter of model limitations or unpredictable nature?

A rain-on-snow flood occurred in the Bernese Alps, Switzerland, on 10 October 2011, and caused significant damage. As the flood peak was unpredicted by the flood forecast system, questions were raised concerning the causes and the predictability of the event. Here, we aimed to reconstruct the anatomy of this rain-on-snow flood in the Lötschen Valley (160 km2) by analyzing meteorological data from the synoptic to the local scale and by reproducing the flood peak with the hydrological model WaSiM-ETH (Water Flow and Balance Simulation Model). This in order to gain process understanding and to evaluate the predictability. The atmospheric drivers of this rain-on-snow flood were (i) sustained snowfall followed by (ii) the passage of an atmospheric river bringing warm and moist air towards the Alps. As a result, intensive rainfall (average of 100 mm day-1) was accompanied by a temperature increase that shifted the 0° line from 1500 to 3200 m a.s.l. (meters above sea level) in 24 h with a maximum increase of 9 K in 9 h. The south-facing slope of the valley received significantly more precipitation than the north-facing slope, leading to flooding only in tributaries along the south-facing slope. We hypothesized that the reason for this very local rainfall distribution was a cavity circulation combined with a seeder-feeder-cloud system enhancing local rainfall and snowmelt along the south-facing slope. By applying and considerably recalibrating the standard hydrological model setup, we proved that both latent and sensible heat fluxes were needed to reconstruct the snow cover dynamic, and that locally high-precipitation sums (160 mm in 12 h) were required to produce the estimated flood peak. However, to reproduce the rapid runoff responses during the event, we conceptually represent likely lateral flow dynamics within the snow cover causing the model to react "oversensitively" to meltwater. Driving the optimized model with COSMO (Consortium for Small-scale Modeling)-2 forecast data, we still failed to simulate the flood because COSMO-2 forecast data underestimated both the local precipitation peak and the temperature increase. Thus we conclude that this rain-on-snow flood was, in general, predictable, but requires a special hydrological model setup and extensive and locally precise meteorological input data. Although, this data quality may not be achieved with forecast data, an additional model with a specific rain-on-snow configuration can provide useful information when rain-on-snow events are likely to occur.

Comparison of co-located independent ground-based middle atmospheric wind and temperature measurements with numerical weather prediction models

High-resolution, ground-based and independent observations including co-located wind radiometer, lidar stations, and infrasound instruments are used to evaluate the accuracy of general circulation models and data-constrained assimilation systems in the middle atmosphere at northern hemisphere midlatitudes. Systematic comparisons between observations, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses including the recent Integrated Forecast System cycles 38r1 and 38r2, the NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalyses, and the free-running climate Max Planck Institute–Earth System Model–Low Resolution (MPI-ESM-LR) are carried out in both temporal and spectral dom ains. We find that ECMWF and MERRA are broadly consistent with lidar and wind radiometer measurements up to ~40 km. For both temperature and horizontal wind components, deviations increase with altitude as the assimilated observations become sparser. Between 40 and 60 km altitude, the standard deviation of the mean difference exceeds 5 K for the temperature and 20 m/s for the zonal wind. The largest deviations are observed in winter when the variability from large-scale planetary waves dominates. Between lidar data and MPI-ESM-LR, there is an overall agreement in spectral amplitude down to 15–20 days. At shorter time scales, the variability is lacking in the model by ~10 dB. Infrasound observations indicate a general good agreement with ECWMF wind and temperature products. As such, this study demonstrates the potential of the infrastructure of the Atmospheric Dynamics Research Infrastructure in Europe project that integrates various measurements and provides a quantitative understanding of stratosphere-troposphere dynamical coupling for numerical weather prediction applications.

Comparing CFSR and conventional weather data for discharge and soil loss modelling with SWAT in small catchments in the Ethiopian Highlands

Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.