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R. Buizza
and
A. Montani

Abstract

Singular vectors with maximum energy at final time inside a verification area are used to identify the target area where extra observations should be taken, at an initial time, to reduce the forecast error inside the verification area itself. This technique is applied to five cases of cyclone development in the Atlantic Ocean, with cyclones reaching the British Isles at the final time. Three verification areas centered around this region are considered.

First, the sensitivity of the target area to the choice of the forecast trajectory along which the singular vectors are evolved, to the choice of the verification area where singular vector energy is maximized, and to the number of singular vectors used to define the target area is investigated. Results show little sensitivity to the choice of the verification area, but high sensitivity to the choice of the trajectory. Regarding the number of singular vectors used, results based on the first 4 or the first 10 singular vectors are shown to be very similar.

Second, the potential forecast error reduction that could be achieved by taking extra observations inside the target area is estimated by contrasting the error of a forecast started from the unperturbed analysis with the error of a forecast started by subtracting so-called pseudo-inverse perturbations (estimated using the leading singular vectors) to the unperturbed analysis. Results indicate that root-mean-square errors in the verification region could be reduced by up to 13% by adding targeted observations.

Overall, results suggest that linear models can be used to define the target area where adaptive observations should be taken.

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M. Verbunt
,
A. Walser
,
J. Gurtz
,
A. Montani
, and
C. Schär

Abstract

A high-resolution atmospheric ensemble forecasting system is coupled to a hydrologic model to investigate probabilistic runoff forecasts for the alpine tributaries of the Rhine River basin (34 550 km2). Five-day ensemble forecasts consisting of 51 members, generated with the global ensemble prediction system (EPS) of the European Centre for Medium-Range Weather Forecasts (ECMWF), are downscaled with the limited-area model Lokal Modell (LM). The resulting limited-area ensemble prediction system (LEPS) uses a horizontal grid spacing of 10 km and provides one-hourly output for driving the distributed hydrologic model Precipitation–Runoff–Evapotranspiration–Hydrotope (PREVAH) hydrologic response unit (HRU) with a resolution of 500 × 500 m2 and a time step of 1 h. The hydrologic model component is calibrated for the river catchments considered, which are characterized by highly complex topography, for the period 1997–98 using surface observations, and validated for 1999–2002.

This study explores the feasibility of atmospheric ensemble predictions for runoff forecasting, in comparison with deterministic atmospheric forcing. Detailed analysis is presented for two case studies: the spring 1999 flood event affecting central Europe due to a combination of snowmelt and heavy precipitation, and the November 2002 flood in the Alpine Rhine catchment. For both cases, the deterministic simulations yield forecast failures, while the coupled atmospheric–hydrologic EPS provides appropriate probabilistic forecast guidance with early indications for extreme floods. It is further shown that probabilistic runoff forecasts using a subsample of EPS members, selected by a cluster analysis, properly represent the forecasts using all 51 EPS members, while forecasts from randomly chosen subsamples reveal a reduced spread compared to the representative members. Additional analyses show that the representation of horizontal advection of precipitation in the atmospheric model may be crucial for flood forecasts in alpine catchments.

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K. A. Browning
,
A. J. Thorpe
,
A. Montani
,
D. Parsons
,
M. Griffiths
,
P. Panagi
, and
E. M. Dicks

Abstract

This paper focuses on the coupling between an ex–tropical cyclone and two preexisting mesoscale tropopause depressions (TDs). The TDs approached the cyclone from widely separated sources after becoming cut off from different upper-level troughs upstream. The first part of the paper combines Meteosat imagery with products from the limited-area version of the operational U.K. Meteorological Office Unified Model to reveal the 3D structure and evolution of the mesoscale features. Each TD was a potential vorticity (PV) maximum characterized by dry-intrusion air descending slantwise beneath an upper-level jet streak. Each TD generated its own cloud head and each is believed to have contributed to the deepening of the surface cyclone. Later parts of the paper identify errors in model forecasts and attribute them to analysis errors in the position of one of the TDs. Two methods are used to locate the analysis errors. Both are capable of being used in real time. The first is the identification via satellite imagery of an error in the model’s water vapor analysis. The second method, using singular vectors calculated for the ECMWF model, involves the identification of sensitive regions where any analysis error would be expected to grow rapidly. The regions highlighted by these two methods were broadly collocated. The present case is unusual in that the most sensitive region was in the upper troposphere. Forecast reruns made with the Met Office and ECMWF models after modifying the upper-level PV in the analysis showed some limited improvements.

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Dmitry Kiktev
,
Paul Joe
,
George A. Isaac
,
Andrea Montani
,
Inger-Lise Frogner
,
Pertti Nurmi
,
Benedikt Bica
,
Jason Milbrandt
,
Michael Tsyrulnikov
,
Elena Astakhova
,
Anastasia Bundel
,
Stéphane Bélair
,
Matthew Pyle
,
Anatoly Muravyev
,
Gdaly Rivin
,
Inna Rozinkina
,
Tiziana Paccagnella
,
Yong Wang
,
Janti Reid
,
Thomas Nipen
, and
Kwang-Deuk Ahn

Abstract

The World Meteorological Organization (WMO) World Weather Research Programme’s (WWRP) Forecast and Research in the Olympic Sochi Testbed program (FROST-2014) was aimed at the advancement and demonstration of state-of-the-art nowcasting and short-range forecasting systems for winter conditions in mountainous terrain. The project field campaign was held during the 2014 XXII Olympic and XI Paralympic Winter Games and preceding test events in Sochi, Russia. An enhanced network of in situ and remote sensing observations supported weather predictions and their verification. Six nowcasting systems (model based, radar tracking, and combined nowcasting systems), nine deterministic mesoscale numerical weather prediction models (with grid spacings down to 250 m), and six ensemble prediction systems (including two with explicitly simulated deep convection) participated in FROST-2014. The project provided forecast input for the meteorological support of the Sochi Olympic Games. The FROST-2014 archive of winter weather observations and forecasts is a valuable information resource for mesoscale predictability studies as well as for the development and validation of nowcasting and forecasting systems in complex terrain. The resulting innovative technologies, exchange of experience, and professional developments contributed to the success of the Olympics and left a post-Olympic legacy.

Open access