World Weather Research Programme Research Articles

Tailored Investments Needed to Support Weather, Water, Ice, and Climate Services in the Polar Regions

Abstract The Polar Prediction Project (PPP), one of the flagship programs of the World Meteorological Organization’s (WMO) World Weather Research Programme (WWRP), has come to an end after a decade of intensive and coordinated international observing, modeling, verification, user engagement, and education activities. While PPP facilitated many advancements in modeling and forecasting, critical investment is now required to turn prediction science into salient environmental services for the polar regions. In this commentary, the members of the Societal and Economic Research and Applications task team of PPP, a group of social scientists and service delivery specialists, identify a number of insights and lessons that are critical for the implementation of the follow-up program Polar Coupled Analysis and Prediction for Services (PCAPS). We argue that in order to raise the societal value of polar environmental services, we need to better understand the diversity of highly specific user contexts; to tailor the actionability of weather, water, ice, and climate (WWIC) service development in the polar regions through inclusive transdisciplinary approaches to coproduction; to assess the societal impact of improved environmental services in the polar regions; and to invest and provide dedicated funding for involving the social sciences in research and tailoring processes across all the polar regions.

Using value chain approaches to evaluate the end-to-end warning chain

Abstract. The weather information value chain provides a framework for characterising the production, communication, and use of information by all stakeholders in an end-to-end warning system covering weather and hazard monitoring, modelling and forecasting, risk assessment, communication and preparedness activities. Warning services are typically developed and provided through a multitude of complex and malleable value chains (networks), often established through co-design, co-creation and co-provision. In November 2020, a 4-year international project under the World Meteorological Organization (WMO) World Weather Research Programme was instigated to explore value chain approaches to describe and evaluate warning systems for high impact weather by integrating physical and social science. It aims to create a framework with guidance and tools for using value chain approaches, and to develop a database of high impact weather warning case studies for scientists and practitioners to review, analyse and learn from previous experience using value chain approaches. Here we describe a template for high-impact weather event case study collection that provides a tool for scientists and practitioners involved in researching, designing and evaluating weather-related warning systems to review previous experience of high impact weather events and assess their efficacy.

Reducing the impact of high impact weather

A priority of weather services is to protect lives and property from hazardous weather. Research on how to achieve that most effectively is the mission of the World Weather Research Programme’s High Impact Weather (HIWeather) project. HIWeather brings together physical and social scientists from a wide variety of disciplines and from across the world to study each step of the process from monitoring the weather to making effective protective responses. HIWeather uses a simple model of the warning production and communication chain that highlights the roles of key actors and organisations involved in forecasting the weather, the resulting hazard and its socio-economic impacts, in formulating the warning and communicating it to the end-user. In this paper I draw on the results of that research which has now been published in our book, “Towards the ‘perfect’ weather warning: bridging disciplinary gaps through partnership and communication” (Golding, 2022). In the context of severe weather associated with monsoons, I shall identify key principles for the design of weather-related warning systems, connecting this work with ideas from the design of community-based warning systems, developments in social media communication, research on impact-based forecasting and with progress in convection-permitting and higher resolution NWP models. A key result is that the communication of knowledge is at least as important as its content and that the creation and nurturing of partnerships between organisations is critical to that.

A Collaborative Effort to Better Understand, Measure, and Model Atmospheric Exchange Processes over Mountains

Abstract In this essay, we highlight some challenges the atmospheric community is facing concerning adequate treatment of flows over mountains and their implications for numerical weather prediction (NWP), climate simulations, and impact modeling. With recent increases in computing power (and hence model resolution) numerical models start to face new limitations (such as numerical instability over steep terrain). At the same time there is a growing need for sufficiently reliable NWP model output to drive various impact models (for hydrology, air pollution, agriculture, etc.). The input information for these impact models is largely produced by the boundary layer (BL) parameterizations of NWP models. All known BL parameterizations assume flat and horizontally homogeneous surface conditions, and their performance and interaction with resolved flows is massively understudied over mountains—hence their output may be accidentally acceptable at best. We therefore advocate the systematic investigation of the so-called “mountain boundary layer” (MoBL), introduced to emphasize its many differences to the BL over flat and horizontally homogeneous terrain. An international consortium of scientists has launched a research program, TEAMx (Multi-Scale Transport and Exchange Processes in the Atmosphere over Mountains–Program and Experiment), to address some of the most pressing scientific challenges. TEAMx is endorsed by World Weather Research Programme (WWRP) and the Global Energy and Water Exchanges (GEWEX) project as a “cross-cutting project.” A program coordination office was established at the University of Innsbruck (Austria). This essay introduces the background to and content of a recently published white paper outlining the key research questions of TEAMx.

NAO Influence on the MJO and its Prediction Skill in the Subseasonal-to-Seasonal Prediction Models

AbstractBased on the database of the Subseasonal to Seasonal (S2S) Prediction project of the World Weather Research Programme (WWRP) / World Climate Research Programme (WCRP), the influence of the North Atlantic Oscillation (NAO) on the Madden- Julian Oscillation (MJO) and its forecast skill is investigated. It is found that most models can capture the MJO phase changes following positive and negative NAO events. About 20 days after initialized with a positive (negative) NAO, the forecast MJO appears more frequently in phase 7 (3), which corresponds to reduced (enhanced) convection in the tropical Indian Ocean and enhanced (suppressed) convection in the western Pacific. In most S2S models the MJO prediction skill is dependent on the NAO amplitude and phase in the initial condition. A strong NAO leads to a better MJO forecast skill than a weak NAO. The MJO skill tends to be higher when the forecast starts from a negative NAO than a positive NAO. These results indicates that there is a strong Northern extratropical influence on the MJO and its forecast skill. It is important for numerical models to better represent the NAO influence to improve the simulation and prediction of the MJO.

Current and Emerging Developments in Subseasonal to Decadal Prediction

Abstract Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

Enhanced Northern Hemisphere Correlation Skill of Subseasonal Predictions in the Strong Negative Phase of the Arctic Oscillation

AbstractThe Arctic Oscillation (AO) is the most dominant atmospheric variability in the Northern Hemisphere in boreal winter. Its negative phases sometimes bring extreme cold conditions over Eurasia and North America in boreal winter, impinging on various socioeconomic sectors. Thus, accurate prediction of the AO‐related conditions with a long lead time is greatly anticipated. This study investigates conditional prediction skill in the northern extratropics relative to AO phases using retrospective forecast data of multiple models provided by the Subseasonal to Seasonal Prediction Project, which is jointly conducted by the World Weather Research Programme and the World Climate Research Programme. We found that predictions starting from the strong negative AO phase tend to have enhanced prediction skill in terms of the anomaly correlation coefficient of 500‐hPa geopotential height, which measures the similarity of spatial patterns. The skill enhancement is not apparent in terms of the root mean square error score. We also discuss dynamical mechanisms behind the enhanced prediction skill. The Eliassen‐Palm flux diagnosis indicated that the strong negative AO phase induces the stronger eddy‐zonal flow feedback to sustain the anomalous zonal flow condition than the strong positive AO phase. Moreover, the anomalous zonal flow is associated with an anomalous zonally asymmetric pattern. As a result, the anomalous AO pattern is better predicted in the strong negative AO phase, contributing to the enhancement of the Northern Hemisphere correlation skill. Results highlight that dynamics inherent in the extratropical atmosphere can provide the subseasonal predictability in a certain atmospheric condition.

Subseasonal to Seasonal Prediction of Weather to Climate with Application to Tropical Cyclones

AbstractDemands are growing rapidly in the operational prediction and applications communities for forecasts that fill the gap between daily weather forecasts and seasonal climate outlooks. Recent scientific advances have identified sources of predictability on this time range, and modeling advances are leading to better forecasts. However, much remains to be done to further improve their skill and to develop new climate service forecast products to help countries and sectorial decision makers better manage weather risks and extremes and to adapt to climate change. This paper reviews the history and describes the main challenges and opportunities for the modeling and forecast‐applications communities to improve subseasonal to seasonal (S2S) forecasts and products, along with current developments catalyzed by the World Weather Research Programme and World Climate Research Programme's joint Sub‐Seasonal to Seasonal Prediction Project. The case of tropical cyclones is highlighted as an illustrative example of the points discussed.

Results of the Tokyo Metropolitan Area Convection Study for Extreme Weather Resilient Cities (TOMACS)

AbstractThe Tokyo Metropolitan Area Convection Study for Extreme Weather Resilient Cities (TOMACS) began as a Japanese domestic research project in 2010 and aimed to elucidate the mechanisms behind local high-impact weather (LHIW) in urban areas, to improve forecasting techniques for LHIW, and to provide high-resolution weather information to end-users (local governments, private companies, and the general public) through social experiments. Since 2013, the project has been expanded as an international Research and Development Project (RDP) of the World Weather Research Programme (WWRP) of the World Meteorological Organization (WMO). Through this project, the following results were obtained: 1) observation data for LHIW around Tokyo were recorded using a dense network of X-band radars, a C-band polarimetric radar, a Ku-band fast-scanning radar, coherent Doppler lidars, and the Global Navigation Satellite System; 2) quantitative precipitation estimation algorithms for X-band polarimetric radars have been developed as part of an international collaboration; 3) convection initiation by the interaction of sea breezes and urban impacts on the occurrence of heavy precipitation around Tokyo were elucidated by a dense observation network, high-resolution numerical simulations, and different urban surface models; 4) an “imminent” nowcast system based on the vertically integrated liquid water derived from the X-band polarimetric radar network has been developed; 5) assimilation methods for data from advanced observation instruments such as coherent Doppler lidars and polarimetric radars were developed; and 6) public use of high-resolution radar data were promoted through the social experiments.

Sub-seasonal to Seasonal Hindcasts of Stratospheric Sudden Warming by BCC_CSM1.1(m): A Comparison with ECMWF

This study focuses on model predictive skill with respect to stratospheric sudden warming (SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF’s model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM (ECMWF) is the hindcast initiated two (three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts.

FROST-2014: The Sochi Winter Olympics International Project

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.

Madden—Julian Oscillation prediction and teleconnections in the S2S database

The Madden—Julian Oscillation (MJO) has been diagnosed in the World Weather Research Program (WWRP)/World Climate Research Program (WCRP) Sub‐seasonal to Seasonal prediction project (S2S) database using the Wheeler and Hendon index over the common hindcast period 1999—2010. The S2S models display skill to predict the MJO over a period between two and four weeks. The majority of S2S models tend to produce a weaker MJO than in ERA‐Interim, with a phase speed decreasing with lead time.All the S2S models produce realistic patterns of MJO teleconnections at 500 hPa, with an increased probability of positive North Atlantic Oscillation (NAO) following an active MJO over the Indian Ocean and of negative NAO following an active MJO over the West Pacific. However, the amplitude of the MJO teleconnection patterns are significantly weaker than in ERA‐Interim over the Euro‐Atlantic sector and are often too strong over the western North Pacific. Models with lower horizontal resolution tend to produce weaker teleconnections. In the lower stratosphere, several S2S models produce teleconnections which are too strong compared to ERA‐Interim. These results suggest that, although the S2S models display significant skill in predicting the MJO propagation beyond two weeks, all the S2S models do not fully exploit the predictability associated with the MJO in the Northern Extratropics, particularly over Europe.

The Southern China Monsoon Rainfall Experiment (SCMREX)

AbstractDuring the presummer rainy season (April–June), southern China often experiences frequent occurrences of extreme rainfall, leading to severe flooding and inundations. To expedite the efforts in improving the quantitative precipitation forecast (QPF) of the presummer rainy season rainfall, the China Meteorological Administration (CMA) initiated a nationally coordinated research project, namely, the Southern China Monsoon Rainfall Experiment (SCMREX) that was endorsed by the World Meteorological Organization (WMO) as a research and development project (RDP) of the World Weather Research Programme (WWRP). The SCMREX RDP (2013–18) consists of four major components: field campaign, database management, studies on physical mechanisms of heavy rainfall events, and convection-permitting numerical experiments including impact of data assimilation, evaluation/improvement of model physics, and ensemble prediction. The pilot field campaigns were carried out from early May to mid-June of 2013–15. This paper: i) describes the scientific objectives, pilot field campaigns, and data sharing of SCMREX; ii) provides an overview of heavy rainfall events during the SCMREX-2014 intensive observing period; and iii) presents examples of preliminary research results and explains future research opportunities.

THORPEX Research and the Science of Prediction

AbstractThe Observing System Research and Predictability Experiment (THORPEX) was a 10-yr, international research program organized by the World Meteorological Organization’s World Weather Research Program. THORPEX was motivated by the need to accelerate the rate of improvement in the accuracy of 1-day to 2-week forecasts of high-impact weather for the benefit of society, the economy, and the environment. THORPEX, which took place from 2005 to 2014, was the first major international program focusing on the advancement of global numerical weather prediction systems since the Global Atmospheric Research Program, which took place almost 40 years earlier, from 1967 through 1982. The scientific achievements of THORPEX were accomplished through bringing together scientists from operational centers, research laboratories, and the academic community to collaborate on research that would ultimately advance operational predictive skill. THORPEX included an unprecedented effort to make operational products readily accessible to the broader academic research community, with community efforts focused on problems where challenging science intersected with the potential to accelerate improvements in predictive skill. THORPEX also collaborated with other major programs to identify research areas of mutual interest, such as topics at the intersection of weather and climate. THORPEX research has 1) increased our knowledge of the global-to-regional influences on the initiation, evolution, and predictability of high-impact weather; 2) provided insight into how predictive skill depends on observing strategies and observing systems; 3) improved data assimilation and ensemble forecast systems; 4) advanced knowledge of high-impact weather associated with tropical and polar circulations and their interactions with midlatitude flows; and 5) expanded society’s use of weather information through applied and social science research.

Commentary: Communicating climate complexity

Commentary: Communicating climate complexity

FROST-2014 project and meteorological support of the Sochi-2014 Olympics

In order to provide weather services to the 2014 Winter Olympics, the observational network in the Sochi region was strengthened with more than 40 automatic weather stations, the dual polarization Doppler radar, temperature and wind profilers, micro-rain radars, ets. These observation facilities allowed using the Sochi testbed for the development, testing, and intercomparison of various technologies of nowcasting and short-range numerical weather forecast. It was accomplished in the framework of the international project of the World Weather Research Program of WMO called FROST-2014 (Forecast and Research in the Olympic Sochi Testbed). The prognostic products of the FROST-2014 project was used for the operational meteorological servicing of Olympic events. Presented are the main research directions and the project preliminary results.

Opportunities and challenges in monsoon prediction in a changing climate

The South Asian monsoon is the pulse and life-line of over two billion inhabitants of the Indian subcontinent. The socio-economic development in this part of the world heavily depends on reliable predictions of the seasonal monsoon rainfall. Notwithstanding notable progress made in seasonal prediction of tropical climate during the past few decades, reliable forecasting of the South Asian summer monsoon has remained a ‘grand challenge’ problem. The problem gets more complicated in a warming environment with possible further degradation of the potential predictability. To define a way forward, an international Conference on “Opportunities and Challenges in Monsoon Prediction in a Changing Climate” (OCHAMP-2012) was organized during the period 21–25 February, 2012 at Pune, India, by the Indian Institute of Tropical Meteorology in association with World Climate Research Programme and World Weather Research Programme of World Meteorological Organization (WMO). The Conference was organized also to commemorate the Golden Jubilee of the Indian Institute of Tropical Meteorology

Effect of lateral boundary perturbations on the breeding method and the local ensemble transform Kalman filter for mesoscale ensemble prediction

The effect of lateral boundary perturbations (LBPs) on the mesoscale breeding (MBD) method and the local ensemble transform Kalman filter (LETKF) as the initial perturbations generators for mesoscale ensemble prediction systems (EPSs) was examined. A LBPs method using the Japan Meteorological Agency's (JMA's) operational one-week global ensemble prediction was developed and applied to the mesoscale EPS of the Meteorological Research Institute for the World Weather Research Programme, Beijing 2008 Olympics Research and Development Project. The amplitude of the LBPs was adjusted based on the ensemble spread statistics considering the difference of the forecast times of the JMA's one-week EPS and the associated breeding/ensemble Kalman filter (EnKF) cycles. LBPs in the ensemble forecast increase the ensemble spread and improve the accuracy of the ensemble mean forecast. In the MBD method, if LBPs were introduced in its breeding cycles, the growth rate of the generated bred vectors is increased, and the ensemble spread and the root mean square errors (RMSEs) of the ensemble mean are further improved in the ensemble forecast. With LBPs in the breeding cycles, positional correspondences to the meteorological disturbances and the orthogonality of the bred vectors are improved. Brier Skill Scores (BSSs) also showed a remarkable effect of LBPs in the breeding cycles. LBPs showed a similar effect with the LETKF. If LBPs were introduced in the EnKF data assimilation cycles, the ensemble spread, ensemble mean accuracy, and BSSs for precipitation were improved, although the relative advantage of LETKF as the initial perturbations generator against MDB was not necessarily clear. LBPs in the EnKF cycles contribute not to the orthogonalisation but to prevent the underestimation of the forecast error near the lateral boundary.The accuracy of the LETKF analyses was compared with that of the mesoscale 4D-VAR analyses. With LBPs in the LETKF cycles, the RMSEs of the forecasts from the LETKF analysis were improved and some of them became comparable to those of the mesoscale 4D-VAR analyses based on the JMA's operational data assimilation system. These results show the importance of LBPs in the MBD method and LETKF. LBPs are critical not only to ameliorate the underestimation of the ensemble spread in the ensemble forecast but also to produce better initial perturbations and to improve the LETKF analysis.

Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10): a World Weather Research Programme Project

A World Weather Research Programme (WWRP) project entitled the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) was developed to be associated with the Vancouver 2010 Olympic and Paralympic Winter Games conducted between 12 February and 21 March 2010. The SNOW-V10 international team augmented the instrumentation associated with the Winter Games and several new numerical weather forecasting and nowcasting models were added. Both the additional observational and model data were available to the forecasters in real time. This was an excellent opportunity to demonstrate existing capability in nowcasting and to develop better techniques for short term (0–6 h) nowcasts of winter weather in complex terrain. Better techniques to forecast visibility, low cloud, wind gusts, precipitation rate and type were evaluated. The weather during the games was exceptionally variable with many periods of low visibility, low ceilings and precipitation in the form of both snow and rain. The data collected should improve our understanding of many physical phenomena such as the diabatic effects due to melting snow, wind flow around and over terrain, diurnal flow reversal in valleys associated with daytime heating, and precipitation reductions and increases due to local terrain. Many studies related to these phenomena are described in the Special Issue on SNOW-V10 for which this paper was written. Numerical weather prediction and nowcast models have been evaluated against the unique observational data set now available. It is anticipated that the data set and the knowledge learned as a result of SNOW-V10 will become a resource for other World Meteorological Organization member states who are interested in improving forecasts of winter weather.

Uncertainty propagation for flood forecasting in the Alps: different views and impacts from MAP D-PHASE

Abstract. D-PHASE was a Forecast Demonstration Project of the World Weather Research Programme (WWRP) related to the Mesoscale Alpine Programme (MAP). Its goal was to demonstrate the reliability and quality of operational forecasting of orographically influenced (determined) precipitation in the Alps and its consequences on the distribution of run-off characteristics. A special focus was, of course, on heavy-precipitation events. The D-PHASE Operations Period (DOP) ran from June to November~2007, during which an end-to-end forecasting system was operated covering many individual catchments in the Alps, with their water authorities, civil protection organizations or other end users. The forecasting system's core piece was a Visualization Platform where precipitation and flood warnings from some 30 atmospheric and 7 hydrological models (both deterministic and probabilistic) and corresponding model fields were displayed in uniform and comparable formats. Also, meteograms, nowcasting information and end user communication was made available to all the forecasters, users and end users. D-PHASE information was assessed and used by some 50 different groups ranging from atmospheric forecasters to civil protection authorities or water management bodies. In the present contribution, D-PHASE is briefly presented along with its outstanding scientific results and, in particular, the lessons learnt with respect to uncertainty propagation. A focus is thereby on the transfer of ensemble prediction information into the hydrological community and its use with respect to other aspects of societal impact. Objective verification of forecast quality is contrasted to subjective quality assessments during the project (end user workshops, questionnaires) and some general conclusions concerning forecast demonstration projects are drawn.