European Center for Medium Range Weather Forecasting

Shinfield, United Kingdom

European Center for Medium Range Weather Forecasting

Shinfield, United Kingdom
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Toh Y.Y.,University of Reading | Turner A.G.,University of Reading | Johnson S.J.,University of Reading | Johnson S.J.,European Center for Medium Range Weather Forecasting | Holloway C.E.,University of Reading
Climate Dynamics | Year: 2017

The fidelity of 28 Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating mean climate over the Maritime Continent in the Atmospheric Model Intercomparison Project (AMIP) experiment is evaluated in this study. The performance of AMIP models varies greatly in reproducing seasonal mean climate and the seasonal cycle. The multi-model mean has better skill at reproducing the observed mean climate than the individual models. The spatial pattern of 850 hPa wind is better simulated than the precipitation in all four seasons. We found that model horizontal resolution is not a good indicator of model performance. Instead, a model’s local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon. The comparison with coupled models in CMIP5 shows that AMIP models generally performed better than coupled models in the simulation of the global monsoon and local Hadley circulation but less well at simulating the Maritime Continent annual cycle of precipitation. To characterize model systematic biases in the AMIP runs, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I models are able to capture both the winter monsoon and summer monsoon shift, but they overestimate the precipitation; especially during the JJA and SON seasons. Cluster II models simulate weaker seasonal migration than observed, and the maximum rainfall position stays closer to the equator throughout the year. The tropics-wide properties of these clusters suggest a connection between the skill of simulating global properties of the monsoon circulation and the skill of simulating the regional scale of Maritime Continent precipitation. © 2017 The Author(s)


Wetterhall F.,Swedish Meteorological and Hydrological Institute | Wetterhall F.,King's College London | Wetterhall F.,European Center for Medium Range Weather Forecasting | Graham L.P.,Swedish Meteorological and Hydrological Institute | And 3 more authors.
Natural Hazards and Earth System Sciences | Year: 2011

Assessing hydrological effects of global climate change at local scales is important for evaluating future hazards to society. However, applying climate model projections to local impact models can be difficult as outcomes can vary considerably between different climate models, and including results from many models is demanding. This study combines multiple climate model outputs with hydrological impact modelling through the use of response surfaces. Response surfaces represent the sensitivity of the impact model to incremental changes in climate variables and show probabilies for reaching a priori determined thresholds. Response surfaces were calculated using the HBV hydrological model for three basins in Sweden. An ensemble of future climate projections was then superimposed onto each response surface, producing a probability estimate for exceeding the threshold being evaluated. Site specific impacts thresholds were used where applicable. Probabilistic trends for future change in hazards or potential can be shown and evaluated. It is particularly useful for visualising the range of probable outcomes from climate models and can easily be updated with new results as they are made available. © 2012 Author(s).


Lillibridge J.,National Oceanic and Atmospheric Administration | Scharroo R.,European Organisation for the Exploitation of Meteorological Satellites | Abdalla S.,European Center for Medium Range Weather Forecasting | Vandemark D.,University of New Hampshire
Journal of Atmospheric and Oceanic Technology | Year: 2014

SARAL-the Satellite with ARgos and ALtiKa-is the first satellite radar altimetry mission to fly a Ka-band instrument (AltiKa). Ocean backscatter measurements in the Ka band suffer larger signal attenuation due to water vapor and atmospheric liquid water than those from Ku-band altimeters. An attenuation algorithm is provided, based on radar propagation theory, which is a function of atmospheric pressure, temperature, water vapor, and liquid water content. Because of the nature of the air-sea interactions between wind and surface gravity waves, the shorter wavelength Ka-band backscatter exhibits a different relationship with wind speed than at Ku band, particularly at moderate to high wind speeds. This paper presents a new onedimensional wind speed model, as a function of backscatter only, and a two-dimensional model, as a function of backscatter and significant wave height, tuned toAltiKa's backscatter measurements. The performance of these new Ka-band altimeter wind speedmodels is assessed through validation with independent ocean buoy wind speeds. The results indicate wind measurement accuracy comparable to that observed at Ku band with only slightly elevated noise in the wind estimates. ©2014 American Meteorological Society.


Demeritt D.,King's College London | Nobert S.,King's College London | Cloke H.L.,King's College London | Cloke H.L.,European Center for Medium Range Weather Forecasting | Pappenberger F.,European Center for Medium Range Weather Forecasting
Hydrological Processes | Year: 2013

Although ensemble prediction systems (EPS) are increasingly promoted as the scientific state-of-the-art for operational flood forecasting, the communication, perception, and use of the resulting alerts have received much less attention. Using a variety of qualitative research methods, including direct user feedback at training workshops, participant observation during site visits to 25 forecasting centres across Europe, and in-depth interviews with 69 forecasters, civil protection officials, and policy makers involved in operational flood risk management in 17 European countries, this article discusses the perception, communication, and use of European Flood Alert System (EFAS) alerts in operational flood management. In particular, this article describes how the design of EFAS alerts has evolved in response to user feedback and desires for a hydrographic-like way of visualizing EFAS outputs. It also documents a variety of forecaster perceptions about the value and skill of EFAS forecasts and the best way of using them to inform operational decision making. EFAS flood alerts were generally welcomed by flood forecasters as a sort of 'pre-alert' to spur greater internal vigilance. In most cases, however, they did not lead, by themselves, to further preparatory action or to earlier warnings to the public or emergency services. Their hesitancy to act in response to medium-term, probabilistic alerts highlights some wider institutional obstacles to the hopes in the research community that EPS will be readily embraced by operational forecasters and lead to immediate improvements in flood incident management. The EFAS experience offers lessons for other hydrological services seeking to implement EPS operationally for flood forecasting and warning. © 2012 John Wiley & Sons, Ltd.


Seidel D.J.,National Oceanic and Atmospheric Administration | Zhang Y.,Nanjing University of Information Science and Technology | Beljaars A.,European Center for Medium Range Weather Forecasting | Golaz J.-C.,National Oceanic and Atmospheric Administration | And 2 more authors.
Journal of Geophysical Research: Atmospheres | Year: 2012

Although boundary layer processes are important in climate, weather and air quality, boundary layer climatology has received little attention, partly for lack of observational data sets. We analyze boundary layer climatology over Europe and the continental U.S. using a measure of boundary layer height based on the bulk Richardson number. Seasonal and diurnal variations during 1981-2005 are estimated from radiosonde observations, a reanalysis that assimilates observations, and two contemporary climate models that do not. Data limitations in vertical profiles introduce height uncertainties that can exceed 50% for shallow boundary layers (<1 km) but are generally <20% for deeper boundary layers. Climatological heights are typically <1 km during daytime and <0.5 km at night over both regions. Seasonal patterns for daytime and nighttime differ; daytime heights are larger in summer than winter, but nighttime heights are larger in winter. The four data sets show similar patterns of spatial and seasonal variability but with biases that vary spatially, seasonally, and diurnally. Compared with radiosonde observations, the reanalysis and the climate models produce deeper layers due to difficulty simulating stable conditions. The higher-time-resolution reanalysis reveals the diurnal cycle in height, with maxima in the afternoon, and with amplitudes that vary seasonally (larger in summer) and regionally (larger over western U.S. and southern Europe). The lower-time-resolution radiosonde data and climate model simulations capture diurnal variations better over Europe than over the U.S., due to differences in local sampling times. © 2012. American Geophysical Union. All Rights Reserved.


Demeritt D.,King's College London | Nobert S.,King's College London | Cloke H.,King's College London | Pappenberg F.,European Center for Medium Range Weather Forecasting
Meteorological Applications | Year: 2010

Following trends in operational weather forecasting, where ensemble prediction systems (EPS) are now increasingly the norm, flood forecasters are beginning to experiment with using similar ensemble methods. Most of the effort to date has focused on the substantial technical challenges of developing coupled rainfall-runoff systems to represent the full cascade of uncertainties involved in predicting future flooding. As a consequence much less attention has been given to the communication and eventual use of EPS flood forecasts. Drawing on interviews and other research with operational flood forecasters from across Europe, this paper highlights a number of challenges to communicating and using ensemble flood forecasts operationally. It is shown that operational flood forecasters understand the skill, operational limitations, and informational value of EPS products in a variety of different and sometimes contradictory ways. Despite the efforts of forecasting agencies to design effective ways to communicate EPS forecasts to non-experts, operational flood forecasters were often skeptical about the ability of forecast recipients to understand or use them appropriately. It is argued that better training and closer contacts between operational flood forecasters and EPS system designers can help ensure the uncertainty represented by EPS forecasts is represented in ways that are most appropriate and meaningful for their intended consumers, but some fundamental political and institutional challenges to using ensembles, such as differing attitudes to false alarms and to responsibility for management of blame in the event of poor or mistaken forecasts are also highlighted. © 2010 Royal Meteorological Society.


Crow W.T.,U.S. Department of Agriculture | Berg A.A.,University of Guelph | Cosh M.H.,U.S. Department of Agriculture | Loew A.,Max Planck Institute for Meteorology | And 5 more authors.
Reviews of Geophysics | Year: 2012

The contrast between the point-scale nature of current ground-based soil moisture instrumentation and the ground resolution (typically >10 2 km 2) of satellites used to retrieve soil moisture poses a significant challenge for the validation of data products from current and upcoming soil moisture satellite missions. Given typical levels of observed spatial variability in soil moisture fields, this mismatch confounds mission validation goals by introducing significant sampling uncertainty in footprint-scale soil moisture estimates obtained from sparse ground-based observations. During validation activities based on comparisons between ground observations and satellite retrievals, this sampling error can be misattributed to retrieval uncertainty and spuriously degrade the perceived accuracy of satellite soil moisture products. This review paper describes the magnitude of the soil moisture upscaling problem and measurement density requirements for ground-based soil moisture networks. Since many large-scale networks do not meet these requirements, it also summarizes a number of existing soil moisture upscaling strategies which may reduce the detrimental impact of spatial sampling errors on the reliability of satellite soil moisture validation using spatially sparse ground-based observations. © 2012 by the American Geophysical Union.


Boone A.A.,Meteo - France | Poccard-Leclercq I.,University of Nantes | Xue Y.,University of California at Los Angeles | Feng J.,University of California at Los Angeles | de Rosnay P.,European Center for Medium Range Weather Forecasting
Climate Dynamics | Year: 2010

The West African monsoon (WAM) circulation and intensity have been shown to be influenced by the land surface in numerous numerical studies using regional scale and global scale atmospheric climate models (RCMs and GCMs, respectively) over the last several decades. The atmosphere-land surface interactions are modulated by the magnitude of the north-south gradient of the low level moist static energy, which is highly correlated with the steep latitudinal gradients of the vegetation characteristics and coverage, land use, and soil properties over this zone. The African Multidisciplinary Monsoon Analysis (AMMA) has organised comprehensive activities in data collection and modelling to further investigate the significance land-atmosphere feedbacks. Surface energy fluxes simulated by an ensemble of land surface models from AMMA Land-surface Model Intercomparison Project (ALMIP) have been used as a proxy for the best estimate of the "real world" values in order to evaluate GCM and RCM simulations under the auspices of the West African Monsoon Modelling Experiment (WAMME) project, since such large-scale observations do not exist. The ALMIP models have been forced in off-line mode using forcing based on a mixture of satellite, observational, and numerical weather prediction data. The ALMIP models were found to agree well over the region where land-atmosphere coupling is deemed to be most important (notably the Sahel), with a high signal to noise ratio (generally from 0.7 to 0.9) in the ensemble and a inter-model coefficient of variation between 5 and 15%. Most of the WAMME models simulated spatially averaged net radiation values over West Africa which were consistent with the ALMIP estimates, however, the partitioning of this energy between sensible and latent heat fluxes was significantly different: WAMME models tended to simulate larger (by nearly a factor of two) monthly latent heat fluxes than ALMIP. This results due to a positive precipitation bias in the WAMME models and a northward displacement of the monsoon in most of the GCMs and RCMs. Another key feature not found in the WAMME models is peak seasonal latent heat fluxes during the monsoon retreat (approximately a month after the peak precipitation rates) from soil water stores. This is likely related to the WAMME northward bias of the latent heat flux gradient during the WAM onset. © 2009 Springer-Verlag.


Bauer P.,European Center for Medium Range Weather Forecasting | Ohring G.,National Oceanic and Atmospheric Administration | Kummerow C.,Colorado State University | Auligne T.,University Corporation for Atmospheric Research
Bulletin of the American Meteorological Society | Year: 2011

The National Aeronautics and Space Administration (NASA)-National Oceanic and Atmospheric Administration (NOAA), Department of Defense (DoD) Joint Center for Satellite Data Assimilation (JCSDA) sponsored an international workshop on assimilating observations in cloudy and precipitating regions in 2005. The workshop sessions covered the existing status of cloud and precipitation assimilation at NWP centers, special issues related to cloud- and precipitation-affected observations, radiative transfer modeling, cloud and precipitation representation in numerical models, and problems of integrating such data in operational data assimilation systems. Working group summaries and recommendations were discussed in a final plenary session and were integrated into a set of recommendations to ECMWF and JCSDA, and other NWP centers. Some of the major issues that were identified by the workshop's working groups included modeling data assimilation, verification, and observations.


Slingo J.,UK Met Office | Palmer T.,European Center for Medium Range Weather Forecasting | Palmer T.,University of Oxford
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | Year: 2011

Following Lorenz's seminal work on chaos theory in the 1960s, probabilistic approaches to prediction have come to dominate the science of weather and climate forecasting. This paper gives a perspective on Lorenz's work and how it has influenced the ways in which we seek to represent uncertainty in forecasts on all lead times from hours to decades. It looks at how model uncertainty has been represented in probabilistic prediction systems and considers the challenges posed by a changing climate. Finally, the paper considers how the uncertainty in projections of climate change can be addressed to deliver more reliable and confident assessments that support decision-making on adaptation and mitigation. This journal is © 2011 The Royal Society.

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