The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed.

ERA-Interim/Land: a global land surface reanalysis data set

ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.

Improved seasonal prediction of the hot summer of 2003 over Europe through better representation of uncertainty in the land surface

Methods to explicitly represent uncertainties in weather and climate models have been developed and refined over the past decade, and have reduced biases and improved forecast skill when implemented in the atmospheric component of models. These methods have not yet been applied to the land surface component of models. Since the land surface is strongly coupled to the atmospheric state at certain times and in certain places (such as the European summer of 2003), improvements in the representation of land surface uncertainty may potentially lead to improvements in atmospheric forecasts for such events. Here we analyse seasonal retrospective forecasts for 1981–2012 performed with the European Centre for Medium-Range Weather Forecasts’ (ECMWF) coupled ensemble forecast model. We consider two methods of incorporating uncertainty into the land surface model (H-TESSEL): stochastic perturbation of tendencies, and static perturbation of key soil parameters. We find that the perturbed parameter approach considerably improves the forecast of extreme air temperature for summer 2003, through better representation of negative soil moisture anomalies and upward sensible heat flux. Averaged across all the reforecasts the perturbed parameter experiment shows relatively little impact on the mean bias, suggesting perturbations of at least this magnitude can be applied to the land surface without any degradation of model climate. There is also little impact on skill averaged across all reforecasts and some evidence of overdispersion for soil moisture. The stochastic tendency experiments show a large overdispersion for the soil temperature fields, indicating that the perturbation here is too strong. There is also some indication that the forecast of the 2003 warm event is improved for the stochastic experiments, however the improvement is not as large as observed for the perturbed parameter experiment.

The prediction of Northern Hemisphere tropical cyclone extended life cycles by the ECMWF Ensemble and Deterministic Prediction Systems. Part I: tropical cyclone stage

This study has explored the prediction errors of tropical cyclones (TCs) in the European Centre for Medium-Range Weather Forecasts (ECMWF) Ensemble Prediction System (EPS) for the Northern Hemisphere summer period for five recent years. Results for the EPS are contrasted with those for the higher-resolution deterministic forecasts. Various metrics of location and intensity errors are considered and contrasted for verification based on IBTrACS and the numerical weather prediction (NWP) analysis (NWPa). Motivated by the aim of exploring extended TC life cycles, location and intensity measures are introduced based on lower-tropospheric vorticity, which is contrasted with traditional verification metrics. Results show that location errors are almost identical when verified against IBTrACS or the NWPa. However, intensity in the form of the mean sea level pressure (MSLP) minima and 10-m wind speed maxima is significantly underpredicted relative to IBTrACS. Using the NWPa for verification results in much better consistency between the different intensity error metrics and indicates that the lower-tropospheric vorticity provides a good indication of vortex strength, with error results showing similar relationships to those based on MSLP and 10-m wind speeds for the different forecast types. The interannual variation in forecast errors are discussed in relation to changes in the forecast and NWPa system and variations in forecast errors between different ocean basins are discussed in terms of the propagation characteristics of the TCs.

Enhanced long-range forecast skill in boreal winter following stratospheric strong vortex conditions

There has been a great deal of recent interest in producing weather forecasts on the 2–6 week sub-seasonal timescale, which bridges the gap between medium-range (0–10 day) and seasonal (3–6 month) forecasts. While much of this interest is focused on the potential applications of skilful forecasts on the sub-seasonal range, understanding the potential sources of sub-seasonal forecast skill is a challenging and interesting problem, particularly because of the likely state-dependence of this skill (Hudson et al 2011). One such potential source of state-dependent skill for the Northern Hemisphere in winter is the occurrence of stratospheric sudden warming (SSW) events (Sigmond et al 2013). Here we show, by analysing a set of sub-seasonal hindcasts, that there is enhanced predictability of surface circulation not only when the stratospheric vortex is anomalously weak following SSWs but also when the vortex is extremely strong. Sub-seasonal forecasts initialized during strong vortex events are able to successfully capture the associated surface temperature and circulation anomalies. This results in an enhancement of Northern annular mode forecast skill compared to forecasts initialized during the cases when the stratospheric state is close to climatology. We demonstrate that the enhancement of skill for forecasts initialized during periods of strong vortex conditions is comparable to that achieved for forecasts initialized during weak events. This result indicates that additional confidence can be placed in sub-seasonal forecasts when the stratospheric polar vortex is significantly disturbed from its normal state.

Impact of a Fram Strait cyclone on ice edge, drift, divergence, and concentration: Possibilities and limits of an observational analysis

This study aims at the determination of a Fram Strait cyclone track and of the cyclone’s impact on ice edge, drift, divergence, and concentration. A 24 h period on 13–14 March 2002 framed by two RADARSAT images is analyzed. Data are included from autonomous ice buoys, a research vessel, Special Sensor Microwave Imager (SSM/I) and QuikSCAT satellite, and the operational European Centre for Medium-Range Weather Forecasts (ECMWF) model. During this 24 h period the cyclone moved northward along the western ice edge in the Fram Strait, crossed the northern ice edge, made a left-turn loop with 150 km diameter over the sea ice, and returned to the northern ice edge. The ECMWF analysis places the cyclone track 100 km too far west over the sea ice, a deviation which is too large for representative sea ice simulations. On the east side of the northward moving cyclone, the ice edge was pushed northward by 55 km because of strong winds. On the rear side, the ice edge advanced toward the open water but by a smaller distance because of weaker winds there. The ice drift pattern as calculated from the ice buoys and the two RADARSAT images is cyclonically curved around the center of the cyclone loop. Ice drift divergence shows a spatial pattern with divergence in the loop center and a zone of convergence around. Ice concentration changes as retrieved from SSM/I data follow the divergence pattern such that sea ice concentration increased in areas of divergence and decreased in areas of convergence.

Impact of cyclones on sea ice in the Fram Strait: numerical simulations and observations

The sea ice export from the Arctic is of global importance due to its fresh water which influences the oceanic stratification and, thus, the global thermohaline circulation. This study deals with the effect of cyclones on sea ice and sea ice transport in particular on the basis of observations from two field experiments FRAMZY 1999 and FRAMZY 2002 in April 1999 and March 2002 as well as on the basis of simulations with a numerical sea ice model. The simulations realised by a dynamic-thermodynamic sea ice model are forced with 6-hourly atmospheric ECMWF- analyses (European Centre for Medium-Range Weather Forecasts) and 6-hourly oceanic data of a MPI-OM-simulation (Max-Planck-Institute Ocean Model). Comparing the observed and simulated variability of the sea ice drift and of the position of the ice edge shows that the chosen configuration of the model is appropriate for the performed studies. The seven observed cyclones change the position of the ice edge up to 100 km and cause an extensive decrease of sea ice coverage by 2 % up to more than 10 %. The decrease is only simulated by the model if the ocean current is strongly divergent in the centre of the cyclone. The impact is remarkable of the ocean current on divergence and shear deformation of the ice drift. As shown by sensitivity studies the ocean current at a depth of 6 m – the sea ice model is forced with – is mainly responsible for the ascertained differences between simulation and observation. The simulated sea ice transport shows a strong variability on a time scale from hours to days. Local minima occur in the time series of the ice transport during periods with Fram Strait cyclones. These minima are not caused by the local effect of the cyclone’s wind field, but mainly by the large-scale pattern of surface pressure. A displacement of the areas of strongest cyclone activity in the Nordic Seas would considerably influence the ice transport.

Impacts of parameterized orographic drag on the Northern Hemisphere winter circulation

A recent intercomparison exercise proposed by the Working Group for Numerical Experimentation (WGNE) revealed that the parameterized, or unresolved, surface stress in weather forecast models is highly model-dependent, especially over orography. Models of comparable resolution differ over land by as much as 20% in zonal mean total subgrid surface stress (Ttot). The way Ttot is partitioned between the different parameterizations is also model-dependent. In this study, we simulated in a particular model an increase in Ttot comparable with the spread found in the WGNE intercomparison. This increase was simulated in two ways, namely by increasing independently the contributions to Ttot of the turbulent orographic form drag scheme (TOFD) and of the orographic low-level blocking scheme (BLOCK). Increasing the parameterized orographic drag leads to significant changes in surface pressure, zonal wind and temperature in the Northern Hemisphere during winter both in 10 day weather forecasts and in seasonal integrations. However, the magnitude of these changes in circulation strongly depends on which scheme is modified. In 10 day forecasts, stronger changes are found when the TOFD stress is increased, while on seasonal time scales the effects are of comparable magnitude, although different in detail. At these time scales, the BLOCK scheme affects the lower stratosphere winds through changes in the resolved planetary waves which are associated with surface impacts, while the TOFD effects are mostly limited to the lower troposphere. The partitioning of Ttot between the two schemes appears to play an important role at all time scales.

Rossby wave propagation on potential vorticity fronts with finite width

The horizontal gradient of potential vorticity (PV) across the tropopause typically declines with lead time in global numerical weather forecasts and tends towards a steady value dependent on model resolution. This paper examines how spreading the tropopause PV contrast over a broader frontal zone affects the propagation of Rossby waves. The approach taken is to analyse Rossby waves on a PV front of finite width in a simple single-layer model. The dispersion relation for linear Rossby waves on a PV front of infinitesimal width is well known; here an approximate correction is derived for the case of a finite width front, valid in the limit that the front is narrow compared to the zonal wavelength. Broadening the front causes a decrease in both the jet speed and the ability of waves to propagate upstream. The contribution of these changes to Rossby wave phase speeds cancel at leading order. At second order the decrease in jet speed dominates, meaning phase speeds are slower on broader PV fronts. This asymptotic phase speed result is shown to hold for a wide class of single-layer dynamics with a varying range of PV inversion operators. The phase speed dependence on frontal width is verified by numerical simulations and also shown to be robust at finite wave amplitude, and estimates are made for the error in Rossby wave propagation speeds due to the PV gradient error present in numerical weather forecast models.

A process-based evaluation of dust-emitting winds in the CMIP5 simulation of HadGEM2-ES

Despite the importance of dust aerosol in the Earth system, state-of-the-art models show a large variety for North African dust emission. This study presents a systematic evaluation of dust emitting-winds in 30 years of the historical model simulation with the UK Met Office Earth-system model HadGEM2-ES for the Coupled Model Intercomparison Project Phase 5. Isolating the effect of winds on dust emission and using an automated detection for nocturnal low-level jets (NLLJs) allow an in-depth evaluation of the model performance for dust emission from a meteorological perspective. The findings highlight that NLLJs are a key driver for dust emission in HadGEM2-ES in terms of occurrence frequency and strength. The annually and spatially averaged occurrence frequency of NLLJs is similar in HadGEM2-ES and ERA-Interim from the European Centre for Medium-Range Weather Forecasts. Compared to ERA-Interim, a stronger pressure ridge over northern Africa in winter and the southward displaced heat low in summer result in differences in location and strength of NLLJs. Particularly the larger geostrophic winds associated with the stronger ridge have a strengthening effect on NLLJs over parts of West Africa in winter. Stronger NLLJs in summer may rather result from an artificially increased mixing coefficient under stable stratification that is weaker in HadGEM2-ES. NLLJs in the Bodélé Depression are affected by stronger synoptic-scale pressure gradients in HadGEM2-ES. Wintertime geostrophic winds can even be so strong that the associated vertical wind shear prevents the formation of NLLJs. These results call for further model improvements in the synoptic-scale dynamics and the physical parametrization of the nocturnal stable boundary layer to better represent dust-emitting processes in the atmospheric model. The new approach could be used for identifying systematic behavior in other models with respect to meteorological processes for dust emission. This would help to improve dust emission simulations and contribute to decreasing the currently large uncertainty in climate change projections with respect to dust aerosol.

Verification of the role of the low level jets in Amazon squall lines

In this study we present a climatology of the Amazon squall lines (ASLs), between the years 2000 and 2008, using satellite imagery and European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses. The ASLs we are interested in are typically formed along the northern coast of Brazil and sometimes propagate for long distances inland. Results show that, on average, an ASL occurs every 2 days. ASLs are more frequent between April and June and less frequent between October and November. The years of 2005 and 2006 showed 25% more cases than the other years. This might be related to an increase of the Atlantic sea surface temperature. Of the total number of ASL cases, 54% propagated less than 170 km, 26% propagated between 170 and 400 km, and 20% propagated more than 400 km. We also studied the occurrence of low level jets (LLJs) associated with the coastal ASLs. Although LLJs are always present in the environment before the formation of the ASL and even on days without ASL cases, important differences were found, mainly related to the LLJ depths. (C) 2010 Elsevier B.V. All rights reserved.

Sudden stratospheric warmings seen in MINOS deep underground muon data

The rate of high energy cosmic ray muons as measured underground is shown to be strongly correlated with upper-air temperatures during short-term atmospheric (10-day) events. The effects are seen by correlating data from the MINOS underground detector and temperatures from the European Centre for Medium Range Weather Forecasts during the winter periods from 2003-2007. This effect provides an independent technique for the measurement of meteorological conditions and presents a unique opportunity to measure both short and long-term changes in this important part of the atmosphere. Citation: Osprey, S., et al. (2009), Sudden stratospheric warmings seen in MINOS deep underground muon data, Geophys. Res. Lett., 36, L05809, doi: 10.1029/2008GL036359.

A case study of the 9 August 1988 South Atlantic storm: Numerical simulations of the wave activity

During 9-11 August 1988, a cyclone developed over Uruguay in the lee of the Andes Mountains and moved over the South Atlantic Ocean, where it redeveloped into an intense storm. This storm was responsible for unusual wave activity along the Brazilian shoreline from 22° to 32°S. The Brazilian news media reported the loss of at least one life, waves of 3 m and higher, and the disappearance of a drainage pipe, which weighed 8000 kg, off the shores of Rio de Janeiro. In this paper, the evolution of this intense storm and the associated ocean wave response is studied through European Centre for Medium-Range Weather Forecasts analyses, a hydrostatic limited-area meteorological model, and a second-generation prognostic wave model. The atmospheric model results indicated the presence of a long-lived and large fetch with surface wind velocities higher than 12 m s -1 directed toward the coast. Some areas with velocities of 20 m s -1 were embedded in the fetch. The wave model forced by this wind field was able to simulate waves with a significant height of 8 m far from the coast and about 4 m in regions very close to the Brazilian coast in agreement with the occurrence reported at Rio de Janeiro. The swell propagation toward the coast of Rio de Janeiro was obstructed by a northeastward 10-m wind during the first 24-h period of the model's integration. During the second 24-h period, the fetch was still large and strong, but the obstacle was removed by a counterclockwise rotation of wind direction favoring the swell and windsea propagation toward the Rio de Janeiro coast.

Geotecnologias digitais no ensino médio: avaliação prática de seu potencial

Pós-graduação em Geografia - IGCE

Verifikation der Niederschlagsvorhersage für Deutschland von 2001 - 2004

Die Verifikation numerischer Modelle ist für die Verbesserung der Quantitativen Niederschlagsvorhersage (QNV) unverzichtbar. Ziel der vorliegenden Arbeit ist die Entwicklung von neuen Methoden zur Verifikation der Niederschlagsvorhersagen aus dem regionalen Modell der MeteoSchweiz (COSMO-aLMo) und des Globalmodells des Europäischen Zentrums für Mittelfristvorhersage (engl.: ECMWF). Zu diesem Zweck wurde ein neuartiger Beobachtungsdatensatz für Deutschland mit stündlicher Auflösung erzeugt und angewandt. Für die Bewertung der Modellvorhersagen wurde das neue Qualitätsmaß „SAL“ entwickelt. Der neuartige, zeitlich und räumlich hoch-aufgelöste Beobachtungsdatensatz für Deutschland wird mit der während MAP (engl.: Mesoscale Alpine Program) entwickelten Disaggregierungsmethode erstellt. Die Idee dabei ist, die zeitlich hohe Auflösung der Radardaten (stündlich) mit der Genauigkeit der Niederschlagsmenge aus Stationsmessungen (im Rahmen der Messfehler) zu kombinieren. Dieser disaggregierte Datensatz bietet neue Möglichkeiten für die quantitative Verifikation der Niederschlagsvorhersage. Erstmalig wurde eine flächendeckende Analyse des Tagesgangs des Niederschlags durchgeführt. Dabei zeigte sich, dass im Winter kein Tagesgang existiert und dies vom COSMO-aLMo gut wiedergegeben wird. Im Sommer dagegen findet sich sowohl im disaggregierten Datensatz als auch im COSMO-aLMo ein deutlicher Tagesgang, wobei der maximale Niederschlag im COSMO-aLMo zu früh zwischen 11-14 UTC im Vergleich zu 15-20 UTC in den Beobachtungen einsetzt und deutlich um das 1.5-fache überschätzt wird. Ein neues Qualitätsmaß wurde entwickelt, da herkömmliche, gitterpunkt-basierte Fehlermaße nicht mehr der Modellentwicklung Rechnung tragen. SAL besteht aus drei unabhängigen Komponenten und basiert auf der Identifikation von Niederschlagsobjekten (schwellwertabhängig) innerhalb eines Gebietes (z.B. eines Flusseinzugsgebietes). Berechnet werden Unterschiede der Niederschlagsfelder zwischen Modell und Beobachtungen hinsichtlich Struktur (S), Amplitude (A) und Ort (L) im Gebiet. SAL wurde anhand idealisierter und realer Beispiele ausführlich getestet. SAL erkennt und bestätigt bekannte Modelldefizite wie das Tagesgang-Problem oder die Simulation zu vieler relativ schwacher Niederschlagsereignisse. Es bietet zusätzlichen Einblick in die Charakteristiken der Fehler, z.B. ob es sich mehr um Fehler in der Amplitude, der Verschiebung eines Niederschlagsfeldes oder der Struktur (z.B. stratiform oder kleinskalig konvektiv) handelt. Mit SAL wurden Tages- und Stundensummen des COSMO-aLMo und des ECMWF-Modells verifiziert. SAL zeigt im statistischen Sinne speziell für stärkere (und damit für die Gesellschaft relevante Niederschlagsereignisse) eine im Vergleich zu schwachen Niederschlägen gute Qualität der Vorhersagen des COSMO-aLMo. Im Vergleich der beiden Modelle konnte gezeigt werden, dass im Globalmodell flächigere Niederschläge und damit größere Objekte vorhergesagt werden. Das COSMO-aLMo zeigt deutlich realistischere Niederschlagsstrukturen. Diese Tatsache ist aufgrund der Auflösung der Modelle nicht überraschend, konnte allerdings nicht mit herkömmlichen Fehlermaßen gezeigt werden. Die im Rahmen dieser Arbeit entwickelten Methoden sind sehr nützlich für die Verifikation der QNV zeitlich und räumlich hoch-aufgelöster Modelle. Die Verwendung des disaggregierten Datensatzes aus Beobachtungen sowie SAL als Qualitätsmaß liefern neue Einblicke in die QNV und lassen angemessenere Aussagen über die Qualität von Niederschlagsvorhersagen zu. Zukünftige Anwendungsmöglichkeiten für SAL gibt es hinsichtlich der Verifikation der neuen Generation von numerischen Wettervorhersagemodellen, die den Lebenszyklus hochreichender konvektiver Zellen explizit simulieren.