scholarly journals What Is the Added Value of a Convection-Permitting Model for Forecasting Extreme Rainfall over Tropical East Africa?

2018 ◽  
Vol 146 (9) ◽  
pp. 2757-2780 ◽  
Author(s):  
Beth J. Woodhams ◽  
Cathryn E. Birch ◽  
John H. Marsham ◽  
Caroline L. Bain ◽  
Nigel M. Roberts ◽  
...  
Keyword(s):  
East Africa ◽  
Lake Victoria ◽  
Weather Prediction ◽  
Extreme Rainfall ◽  
Forecast Model ◽  
Time Of Day ◽  
Global Model ◽  
Added Value ◽  
Forecast Lead Time ◽  
The Tropics

ABSTRACT Forecasting convective rainfall in the tropics is a major challenge for numerical weather prediction. The use of convection-permitting (CP) forecast models in the tropics has lagged behind the midlatitudes, despite the great potential of such models in this region. In the scientific literature, there is very little evaluation of CP models in the tropics, especially over an extended time period. This paper evaluates the prediction of convective storms for a period of 2 years in the Met Office operational CP model over East Africa and the global operational forecast model. A novel localized form of the fractions skill score is introduced, which shows variation in model skill across the spatial domain. Overall, the CP model and the global model both outperform a 24-h persistence forecast. The CP model shows greater skill than the global model, in particular on subdaily time scales and for storms over land. Forecasts over Lake Victoria are also improved in the CP model, with an increase in hit rate of up to 20%. Contrary to studies in the midlatitudes, the skill of both models shows a large dependence on the time of day and comparatively little dependence on the forecast lead time within a 48-h forecast. Although these results provide more motivation for forecasters to use the CP model to produce subdaily forecasts with increased detail, there is a clear need for more in situ observations for data assimilation into the models and for verification. A move toward ensemble forecasting could have further benefits.

scholarly journals Sensitivities of the Madden–Julian oscillation forecasts to configurations of physics in the ECMWF global model

2021 ◽  
Vol 21 (6) ◽  
pp. 4759-4778
Author(s):  
Jun-Ichi Yano ◽  
Nils P. Wedi
Keyword(s):  
Forecast Model ◽  
Global Model ◽  
Madden Julian Oscillation ◽  
Forecast Performance ◽  
Theoretical Investigations ◽  
Forecast Models ◽  
Forecasting System ◽  
The Rich ◽  
The Tropics ◽  
Original Motivation

Abstract. The sensitivities of the Madden–Julian oscillation (MJO) forecasts to various different configurations of the parameterized physics are examined with the global model of ECMWF's Integrated Forecasting System (IFS). The motivation for the study was to simulate the MJO as a nonlinear free wave under active interactions with higher-latitude Rossby waves. To emulate free dynamics in the IFS, various momentum-dissipation terms (“friction”) as well as diabatic heating were selectively turned off over the tropics for the range of the latitudes from 20∘ S to 20∘ N. The reduction of friction sometimes improves the MJO forecasts, although without any systematic tendency. Contrary to the original motivation, emulating free dynamics with an operational forecast model turned out to be rather difficult, because forecast performance sensitively depends on the specific type of friction turned off. The result suggests the need for theoretical investigations that much more closely follow the actual formulations of model physics: a naive approach with a dichotomy of with or without friction simply fails to elucidate the rich behaviour of complex operational models. The paper further exposes the importance of physical processes other than convection for simulating the MJO in global forecast models.

scholarly journals What Is the Predictability Limit of Midlatitude Weather?

2019 ◽  
Vol 76 (4) ◽  
pp. 1077-1091 ◽  
Author(s):  
Fuqing Zhang ◽  
Y. Qiang Sun ◽  
Linus Magnusson ◽  
Roberto Buizza ◽  
Shian-Jiann Lin ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Weather Prediction ◽  
Forecast Model ◽  
Small Scale ◽  
Lead Times ◽  
Winter Storms ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
Forecast Lead Time ◽  
Order Of Magnitude

Abstract Understanding the predictability limit of day-to-day weather phenomena such as midlatitude winter storms and summer monsoonal rainstorms is crucial to numerical weather prediction (NWP). This predictability limit is studied using unprecedented high-resolution global models with ensemble experiments of the European Centre for Medium-Range Weather Forecasts (ECMWF; 9-km operational model) and identical-twin experiments of the U.S. Next-Generation Global Prediction System (NGGPS; 3 km). Results suggest that the predictability limit for midlatitude weather may indeed exist and is intrinsic to the underlying dynamical system and instabilities even if the forecast model and the initial conditions are nearly perfect. Currently, a skillful forecast lead time of midlatitude instantaneous weather is around 10 days, which serves as the practical predictability limit. Reducing the current-day initial-condition uncertainty by an order of magnitude extends the deterministic forecast lead times of day-to-day weather by up to 5 days, with much less scope for improving prediction of small-scale phenomena like thunderstorms. Achieving this additional predictability limit can have enormous socioeconomic benefits but requires coordinated efforts by the entire community to design better numerical weather models, to improve observations, and to make better use of observations with advanced data assimilation and computing techniques.

scholarly journals Coupled Stratospheric Chemistry-Meteorology Data Assimilation. Part II: Weak and Strong Coupling

2019 ◽  
Author(s):  
Richard Ménard ◽  
Pierre Gauthier ◽  
Yves Rochon ◽  
Alain Robichaud ◽  
Jean de Grandpré ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Strong Coupling ◽  
Zonal Wind ◽  
Surf Zone ◽  
Weather Prediction ◽  
Added Value ◽  
Stratospheric Chemistry ◽  
Temperature Bias ◽  
Global Environmental ◽  
The Tropics

We examine data assimilation coupling between meteorology and chemistry in the stratosphere from both weak and strong coupling strategies. The study was performed with the Canadian operational weather prediction Global Environmental Multiscale (GEM) model coupled online with the photochemical stratospheric chemistry developed at the Belgian Institute for Space Aeronomy, described in Part I. Here, the Canadian Meteorological Centre’s operational variational assimilation system was extended to include errors of chemical variables and cross-covariances between meteorological and chemical variables in a 3D-Var configuration, and we added the adjoint of tracer advection in the 4D-Var configuration. Our results show that the assimilation of limb sounding observations from the MIPAS instrument on board Envisat can be used to anchor the AMSU-A radiance bias correction scheme. Also, the added value of limb sounding temperature observations on meteorology and transport is shown to be significant. Weak coupling data assimilation with ozone-radiation interaction is shown to give comparable on meteorology whether a simplified linearized or comprehensive ozone chemistry scheme is used. Strong coupling data assimilation, using static error cross-covariances between ozone and temperature in a 3D-Var context, produced inconclusive results with the approximations we used. We have also conducted the assimilation of long-lived species observations using 4D-Var to infer winds. Our results showed the added value of assimilating several long-lived species, and an improvement in the zonal wind in the Tropics within the troposphere and lower stratosphere. 4D-Var assimilation also induced a correction of zonal wind in the surf zone and a temperature bias in the lower tropical stratosphere

scholarly journals The Pan-Canadian High Resolution (2.5 km) Deterministic Prediction System

2016 ◽  
Vol 31 (6) ◽  
pp. 1791-1816 ◽  
Author(s):  
Jason A. Milbrandt ◽  
Stéphane Bélair ◽  
Manon Faucher ◽  
Marcel Vallée ◽  
Marco L. Carrera ◽  
...  
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Forecast Model ◽  
Added Value ◽  
Precipitation Forecast ◽  
Initial Surface ◽  
Prediction System ◽  
Global Environmental ◽  
Fractional Cloud ◽  
Land Data Assimilation System

Abstract Since November 2014, the Meteorological Services of Canada (MSC) has been running a real-time numerical weather prediction system that provides deterministic forecasts on a regional domain with a 2.5-km horizontal grid spacing covering a large portion of Canada using the Global Environmental Multiscale (GEM) forecast model. This system, referred to as the High Resolution Deterministic Prediction System (HRDPS), is currently downscaled from MSC’s operational 10-km GEM-based regional system but uses initial surface fields from a high-resolution (2.5 km) land data assimilation system coupled to the HRDPS and initial hydrometeor fields from the forecast of a 2.5-km cycle, which reduces the spinup time for clouds and precipitation. Forecast runs of 48 h are provided four times daily. The HRDPS was tested and compared to the operational 10-km system. Model runs from the two systems were evaluated against surface observations for common weather elements (temperature, humidity, winds, and precipitation), fractional cloud cover, and also against upper-air soundings, all using standard metrics. Although the predictions of some fields were degraded in some specific regions, the HRDPS generally outperformed the operational system for a majority of the scores. The evaluation illustrates the added value of the 2.5-km model and the potential for improved numerical guidance for the prediction of high-impact weather.

scholarly journals Operational Implementation of the AROME Model in the Tropics: Multiscale Validation of Rainfall Forecasts

2020 ◽  
Vol 35 (2) ◽  
pp. 691-710 ◽  
Author(s):  
Ghislain Faure ◽  
Philippe Chambon ◽  
Pierre Brousseau
Keyword(s):  
Weather Prediction ◽  
Added Value ◽  
Rainfall Forecasting ◽  
Tropical Regions ◽  
Weather Forecasts ◽  
Time Period ◽  
Resolution Model ◽  
Forecasting System ◽  
The One ◽  
The Tropics

Abstract Météo-France runs operationally, for the needs of several overseas regions in the tropical belt, five numerical weather prediction configurations, based on the convection-permitting model AROME and called the AROME-OM system. These configurations use the high-resolution model [Integrated Forecasting System (IFS)] from the European Centre for Medium-Range Weather Forecasts (ECMWF) for both initialization and lateral forcing. In this study, the performance of the AROME-OM system for rainfall forecasting is compared to the one of ECMWF IFS. The validation uses spatialized rainfall estimates over a 24-h time period at two time scales (daily and annual), from both satellite and ground-based instruments. It has been performed over a 10-month period and across five tropical domains. The intercomparison demonstrates consistent signals across domains and scales. The added value of the AROME-OM system compared to ECMWF IFS is shown for rain/no-rain discrimination and for rain accumulations larger than 10 mm day−1. The AROME-OM system also shows a better ability to forecast realistic rain patterns over these tropical regions. The main weakness found is for an intermediate range of rain accumulations, from 1 to 10 mm day−1, for which the ECMWF IFS forecasts slightly outperform the AROME-OM system forecasts.

scholarly journals Evaluating convection-permitting ensemble forecasts of precipitation over Southeast Asia

2021 ◽  
Author(s):  
Samantha Ferrett ◽  
Thomas H. A. Frame ◽  
John Methven ◽  
Christopher E. Holloway ◽  
Stuart Webster ◽  
...  
Keyword(s):  
Southeast Asia ◽  
Diurnal Cycle ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Model Development ◽  
Skill Score ◽  
The Philippines ◽  
Time Of Day ◽  
Ensemble Forecasts ◽  
The Tropics

AbstractForecasting rainfall in the tropics is a major challenge for numerical weather prediction. Convection-permitting (CP) models are intended to enable forecasts of high-impact weather events. Development and operation of these models in the tropics has only just been realised. This study describes and evaluates a suite of recently developed Met Office Unified Model CP ensemble forecasts over three domains in Southeast Asia, covering Malaysia, Indonesia and the Philippines.Fractions Skill Score is used to assess the spatial scale-dependence of skill in forecasts of precipitation during October 2018 - March 2019. CP forecasts are skilful for 3-hour precipitation accumulations at spatial scales greater than 200 km in all domains during the first day of forecasts. Skill decreases with lead time but varies depending on time of day over Malaysia and Indonesia, due to the importance of the diurnal cycle in driving rainfall in those regions. Skill is largest during daytime when precipitation is over land and is constrained by orography. Comparison of CP ensembles using 2.2, 4.5 and 8.8 km grid spacing and an 8.8km ensemble with parameterised convection reveals that varying resolution has much less effect on ensemble skill and spread than the representation of convection. The parameterised ensemble is less skilful than CP ensembles over Malaysia and Indonesia and more skilful over the Philippines; however, the parameterised ensemble has large drops in skill and spread related to deficiencies in its diurnal cycle representation. All ensembles are under-spread indicating that future model development should focus on this issue.

scholarly journals Causes and consequences of sea ice initialization shock in coupled NWP hindcasts with the GC2 climate model

2021 ◽  
Author(s):  
T. C. Johns ◽  
E. W. Blockley ◽  
J. K. Ridley
Keyword(s):  
Sea Ice ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Forecast Model ◽  
Forecast Skill ◽  
Coupled Analysis ◽  
State Variables ◽  
Forecast Lead Time ◽  
Analysis System ◽  
Model Components

AbstractWe present a coupled retrospective forecast (hindcast) study using the Met Office Global Coupled Model version 2 (GC2) in which we identify and mitigate causes of initialization shock that lead to rapid error growth in sea ice forecasts. Sea ice state variables and volume budget terms as a function of forecast lead time are evaluated relative to analyses from an uncoupled Met Office ocean-sea ice analysis system (FOAMv13). Two sources of initialization shock are highlighted and addressed, both of which are related to effective differences in physics between the analysis system and coupled forecast model. The primary shock to sea ice state variables arises from the use of a salinity-independent freezing temperature for sea water in GC2 as opposed to a salinity-dependent formulation in FOAMv13. A secondary effect arises from differences in the sea ice roughness and hence air-ice drag in the GC2 forecast model compared to the FOAMv13 analysis system. Generalizing from the findings of this study, we suggest that using non-native analyses as initial conditions for coupled Numerical Weather Prediction (NWP) studies will likely make them prone to initialization shock in some model components, to the detriment of forecast skill. To reduce the undesirable impacts of initialization shock on short-range forecast skill noted in this study we would therefore recommend the use of initial conditions (analyses) physically consistent with the native model components of the coupled forecast model, a native coupled analysis likely being the optimal initialization method.

scholarly journals Validation of Satellite Rainfall Estimates over Equatorial East Africa

2021 ◽  
Keyword(s):  
East Africa ◽  
Prediction Models ◽  
Extreme Event ◽  
Weather Prediction ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Annual Rainfall ◽  
Extreme Rainfall Events ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Abstract Rain gauge data sparsity over Africa is known to impede the assessments of hydrometeorological risks and of the skill of numerical weather prediction models. Satellite rainfall estimates (SREs) have been used as surrogate fields for a long time and are continuously replaced by more advanced algorithms and new sensors. Using a unique daily rainfall dataset from 36 stations across equatorial East Africa for the period 2001–2018, this study performs a multi-scale evaluation of gauge-calibrated SREs, namely, IMERG, TMPA, CHIRPS and MSWEP (v2.2 and v2.8). Skills were assessed from daily to annual timescales, for extreme daily precipitation, and for TMPA and IMERG near real-time (NRT) products. Results show that: 1) the SREs reproduce the annual rainfall pattern and seasonal rainfall cycle well, despite exhibiting biases of up to 9%; 2) IMERG is the best for shorter temporal scales while MSWEPv2.2 and CHIRPS perform best at the monthly and annual timesteps, respectively; 3) the performance of all the SREs varies spatially, likely due to an inhomogeneous degree of gauge calibration, with the largest variation seen in MSWEPv2.2; 4) all the SREs miss between 79% (IMERG-NRT) and 98% (CHIRPS) of daily extreme rainfall events recorded by the rain gauges; 5) IMERG-NRT is the best regarding extreme event detection and accuracy; and 6) for return values of extreme rainfall, IMERG and MSWEPv2.2 have the least errors while CHIRPS and MSWEPv2.8 cannot be recommended. The study also highlights; improvements of IMERG over TMPA, the decline in performance of MSWEPv2.8 compared to MSWEPv2.2, and the potential of SREs for flood risk assessment over East Africa.

scholarly journals Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part II: Weak and Strong Coupling

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 798 ◽  
Author(s):  
Richard Ménard ◽  
Pierre Gauthier ◽  
Yves Rochon ◽  
Alain Robichaud ◽  
Jean de Grandpré ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Strong Coupling ◽  
Zonal Wind ◽  
Surf Zone ◽  
Weather Prediction ◽  
Added Value ◽  
Stratospheric Chemistry ◽  
Temperature Bias ◽  
Global Environmental ◽  
The Tropics

We examine data assimilation coupling between meteorology and chemistry in the stratosphere from both weak and strong coupling strategies. The study was performed with the Canadian operational weather prediction Global Environmental Multiscale (GEM) model coupled online with the photochemical stratospheric chemistry model developed at the Belgian Institute for Space Aeronomy, described in Part I. Here, the Canadian Meteorological Centre’s operational variational assimilation system was extended to include errors of chemical variables and cross-covariances between meteorological and chemical variables in a 3D-Var configuration, and we added the adjoint of tracer advection in the 4D-Var configuration. Our results show that the assimilation of limb sounding observations from the MIPAS instrument on board Envisat can be used to anchor the AMSU-A radiance bias correction scheme. Additionally, the added value of limb sounding temperature observations on meteorology and transport is shown to be significant. Weak coupling data assimilation with ozone–radiation interaction is shown to give comparable results on meteorology whether a simplified linearized or comprehensive ozone chemistry scheme is used. Strong coupling data assimilation, using static error cross-covariances between ozone and temperature in a 3D-Var context, produced inconclusive results with the approximations we used. We have also conducted the assimilation of long-lived species observations using 4D-Var to infer winds. Our results showed the added value of assimilating several long-lived species, and an improvement in the zonal wind in the Tropics within the troposphere and lower stratosphere. 4D-Var assimilation also induced a correction of zonal wind in the surf zone and a temperature bias in the lower tropical stratosphere.

scholarly journals Taking the HIGHWAY to Save Lives on Lake Victoria

2021 ◽  
pp. 1-65
Author(s):  
Rita D. Roberts ◽  
Steven J. Goodman ◽  
James W. Wilson ◽  
Paul Watkiss ◽  
Robert Powell ◽  
...  
Keyword(s):  
East Africa ◽  
Prediction Models ◽  
Lake Victoria ◽  
Weather Prediction ◽  
Warning System ◽  
Economic Benefits ◽  
Weather Forecasts ◽  
The People ◽  
Satellite Radar ◽  
Highway Project

AbstractUp to one thousand drowning deaths occur every year on Lake Victoria in East Africa. Nocturnal thunderstorms are one of the main culprits for the high winds and waves that cause fishing boats to capsize. The HIGHWAY project was established to develop an Early Warning System for Lake Victoria. Prior to HIGHWAY, weather forecasts for the lake were overly general and not trusted. Under the HIGHWAY project, forecasters from weather service offices in East Africa worked with leaders of fishing communities and Beach Management Units to develop marine forecasts and hazardous-weather warnings that were meaningful to fishermen and other stakeholders. Forecasters used high-resolution satellite, radar, and lightning observations collected during a HIGHWAY field campaign, along with guidance from numerical weather prediction models and a 4.4-km resolution Tropical Africa model, to produce specific forecasts and warnings for 10 zones over the lake. Forecasts were communicated to thousands of people by radio broadcasters, local intermediaries, and via smartphones using the WhatsApp application. Fishermen, ferry-boat operators, and lakeside communities used the new marine forecasts to plan their daytime and nighttime activities on the lake. A socio-economic benefits study conducted by HIGHWAY found that ~75% of the people are now using the forecasts to decide if and when to travel on the lake. Significantly, a 30% reduction in drowning fatalities on the lake is likely to have occurred, which when combined with the reduction in other weather-related losses, generates estimated socio-economic benefits of $44M/year due to the HIGHWAY project activities; the new marine forecasts and warnings are helping to save lives and property.

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