A New Infrared Atmospheric Sounding Interferometer Channel Selection and Assessment of Its Impact on Met Office NWP Forecasts

A new set of Infrared Atmospheric Sounding Interferometer （IASI） channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis （1D-Var） for the Unified Model （UM） data assimilation system at the Met Office, using the channel score index （CSI） as a figure of merit. Then, 200 channels were selected in order by counting each individual channel＇s CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach, Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum. In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.

All-sky Data Assimilation of MWTS-2 and MWHS-2 in the Met Office Global NWP System.

Microwave radiances from passive polar-orbiting radiometers have been,until recently,assimilated in the Met Office global numerical weather prediction system after the scenes significantly affected by atmospheric scattering are discarded.Recent system upgrades have seen the introduction of a scattering-permitting observation operator and the development of a variable observation error using both liquid and ice water paths as proxies of scattering-induced bias.Applied to the Fengyun 3 Microwave Temperature Sounder 2(MWTS-2)and the Microwave Humidity Sounder 2(MWHS-2),this methodology increases the data usage by up to 8%at 183 GHz.It also allows for the investigation into the assimilation of MWHS-2118 GHz channels,sensitive to temperature and lower tropospheric humidity,but whose large sensitivity to ice cloud have prevented their use thus far.While the impact on the forecast is mostly neutral with small but significant short-range improvements,0.3%in terms of root mean square error,for southern winds and low-level temperature,balanced by 0.2%degradations of short-range northern and tropical low-level temperature,benefits are observed in the background fit of independent instruments used in the system.The lower tropospheric temperature sounding Infrared Atmospheric Sounding Interferometer(IASI)channels see a reduction of the standard deviation in the background departure of up to 1.2%.The Advanced Microwave Sounding Unit A(AMSU-A)stratospheric sounding channels improve by up to 0.5%and the Microwave Humidity Sounder(MHS)humidity sounding channels improve by up to 0.4%.

Assessment and Assimilation of FY-3 Humidity Sounders and Imager in the UK Met Office Global Model

China＇s FengYnn 3 （FY-3） polar orbiting satellites axe set to become an important sonrce of observational data for nu- merical weather prediction （NWP）, atmospheric reanalyses, and climate monitoring studies over the next two decades. As part of the Climate Science for Service Partnership China （CSSP China） prograln, FY-3B Microwave Humidity Sounder 1 （MWHS-1） and FY-3C MWHS-2 observations have been thoroughly assessed and prepared for operational assimilation. This represents the first time observations from China＇s polar orbiting satellites have been used in the UK＇s global NWP model. Since 2016, continuous data quality monitoring has shown occasional bias changes found to be correlated to changes in the energy supply scheme regulating the platform heating system and other transient anomalies. Nonetheless, MWHS-1 and MWHS-2 significantly contribute to the 24-h forecast error reduction by 0.3% and 0.6%, respectively, and the combination of both instruments is shown to improve the fit to the model background of independent sounders by up to 1%. The observations from the Microwave Radiation Imager （MWRI） also are a potentially significant source of benefits for NWP models, but a solar-dependent bias observed in the instrument half-orbits has prevented their assimilation. This paper presents the bases of a correction scheme developed at the Met Office for the purpose of a future assimilation of MWRI data.

Insights into the Microwave Instruments Onboard the Fengyun 3D Satellite:Data Quality and Assimilation in the Met Office NWP System

This paper evaluates the microwave instruments onboard the latest Chinese polar-orbiting satellite, Fengyun 3D (FY- 3D). Comparing three months of observations from the Microwave Temperature Sounder 2 (MWTS-2), the Microwave Humidity Sounder 2 (MWHS-2), and the Microwave Radiation Imager (MWRI) to Met Office short-range forecasts, we characterize the instrumental biases, show how those biases have changed with respect to their predecessors onboard FY- 3C, and how they compare to the Advanced Technology Microwave Sounder (ATMS) onboard NOAA-20 and the Global Precipitation Measurement Microwave Imager (GMI). The MWTS-2 global bias is much reduced with respect to its predecessor and compares well to ATMS at equivalent channel frequencies, differing only by 0.36 ± 0.28 K (1σ) on average. A suboptimal averaging of raw digital counts is found to cause an increase in striping noise and an ascending- descending bias. MWHS-2 benefits from a new calibration method improving the 183-GHz humidity channels with respect to its predecessor and biases for these channels are within ± 1.9 K to ATMS. MWRI presents the largest improvements, with reduced global bias and standard deviation with respect to FY-3C;although, spurious, seemingly transient, brightness temperatures have been detected in the observations at 36.5 GHz (vertical polarization). The strong solar-dependent bias that affects the instrument on FY-3C has been reduced to less than 0.2 K on average for FY-3D MWRI. Experiments where radiances from these instruments were assimilated on top of a full global system demonstrated a neutral to positive impact on the forecasts, as well as on the fit to the background of independent instruments.

Seasonal Prediction Skill and Biases in GloSea5 Relating to the East Asia Winter Monsoon

The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon(EAWM),as well as the associated atmospheric circulation,was investigated using the hindcast data from Global Seasonal Forecast System version 5(GloSea5),with a focus on the evolution of model bias among different forecast lead times.While GloSea5 reproduces the climatological means of large-scale circulation systems related to the EAWM well,systematic biases exist,including a cold bias for most of China’s mainland,especially for North and Northeast China.GloSea5 shows robust skill in predicting the EAWM intensity index two months ahead,which can be attributed to the performance in representing the leading modes of surface air temperature and associated background circulation.GloSea5 realistically reproduces the synergistic effect of El Niño–Southern Oscillation(ENSO)and the Arctic Oscillation(AO)on the EAWM,especially for the western North Pacific anticyclone(WNPAC).Compared with the North Pacific and North America,the representation of circulation anomalies over Eurasia is poor,especially for sea level pressure(SLP),which limits the prediction skill for surface air temperature over East Asia.The representation of SLP anomalies might be associated with the model performance in simulating the interaction between atmospheric circulations and underlying surface conditions.

Use of Targeted Orographic Smoothing in Very High Resolution Simulations of a Downslope Windstorm and Rotor in a Sub-tropical Highland Location

Nested simulations of a downslope windstorm over Cangshan mountain,Yunnan,China,have been used to demonstrate a method of topographic smoothing that preserves a relatively large amount of terrain detail compared to typical smoothing procedures required for models with terrain-following grids to run stably.The simulations were carried out using the Met Office Unified Model(MetUM)to investigate downslope winds.The smoothing method seamlessly blends two terrain datasets to which uniform smoothing has been applied—one with a minimum of smoothing,the other smoothed more heavily to remove gradients that would cause model instabilities.The latter dataset dominates the blend where the steepest slopes exist,but this is localised and recedes outside these areas.As a result,increased detail is starkly apparent in depictions of flow simulated using the blend,compared to one using the default approach.This includes qualitative flow details that were absent in the latter,such as narrow shooting flows emerging from roughly 1-2 km wide leeside channels.Flow separation is more common due to steeper lee slopes.The use of targeted smoothing also results in increased lee side temporal variability at a given point during the windstorm,including over flat areas.Low-/high-pass filtering of the wind perturbation field reveals that relative spatial variability above 30 km in scale(reflecting the background flow)is similar whether or not targeting is used.Beneath this scale,when smoothing is targeted,relative flow variability decreases at the larger scales,and increases at lower scales.This seems linked to fast smaller scale flows disturbing more coherent flows(notably an along-valley current over Erhai Lake).Spatial variability of winds in the model is unsurprisingly weaker at key times than is observed across a local network sampling mesoscale variation,but results are compromised due to relatively few observation locations sampling the windstorm.Only when targeted smoothing is applied does the model capture the downslope windstorm's extension over the city of Dali at the mountain's foot,and the peak mean absolute wind.

Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin

We demonstrate that there is significant skill in the GloSea5 operational seasonal forecasting system for predicting June mean rainfall in the middle/lower Yangtze River basin up to four months in advance.Much of the rainfall in this region during June is contributed by the mei-yu rain band.We find that similar skill exists for predicting the East Asian summer monsoon index(EASMI)on monthly time scales,and that the latter could be used as a proxy to predict the regional rainfall.However,there appears to be little to be gained from using the predicted EASMI as a proxy for regional rainfall on monthly time scales compared with predicting the rainfall directly.Although interannual variability of the June mean rainfall is affected by synoptic and intraseasonal variations,which may be inherently unpredictable on the seasonal forecasting time scale,the major influence of equatorial Pacific sea surface temperatures from the preceding winter on the June mean rainfall is captured by the model through their influence on the western North Pacific subtropical high.The ability to predict the June mean rainfall in the middle and lower Yangtze River basin at a lead time of up to 4 months suggests the potential for providing early information to contingency planners on the availability of water during the summer season.

Contribution of Global Warming and Atmospheric Circulation to the Hottest Spring in Eastern China in 2018

The spring of 2018 was the hottest on record since 1951 over eastern China based on station observations,being 2.5°C higher than the 1961−90 mean and with more than 900 stations reaching the record spring mean temperature.This event exerted serious impacts in the region on agriculture,plant phenology,electricity transmission systems,and human health.In this paper,the contributions of human-induced climate change and anomalous anticyclonic circulation to this event are investigated using the newly homogenized observations and updated Met Office Hadley Centre system for attribution of extreme events,as well as CanESM2(Second Generation Canadian Earth System Model)simulations.Results indicate that both anthropogenic influences and anomalous anticyclonic circulation played significant roles in increasing the probability of the 2018 hottest spring.Quantitative estimates of the probability ratio show that anthropogenic forcing may have increased the chance of this event by ten-fold,while the anomalous circulation increased it by approximately two-fold.The persistent anomalous anticyclonic circulation located on the north side of China blocked the air with lower temperature from high latitudes into eastern China.Without anthropogenic forcing or without the anomalous circulation in northern China,the occurrence probability of the extreme warm spring is significantly reduced.

Erratum to: Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin

The article[Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin],written by[Gill M.MARTIN,Nick J.DUNSTONE,Adam A.SCAIFE,and Philip E.BETT],was originally published electronically on the publisher’s internet portal on[10 December 2019]without open access.

An efficient algorithm for generating a spherical multiple-cell grid

This paper presents an efficient algorithm for generating a spherical multiple-cell(SMC)grid.The algorithm adopts a recursive loop structure and provides two refinement methods:(1)an arbitrary area refinement method and(2)a nearshore refinement method.Numerical experiments are carried out,and the results show that compared with the existing grid generation algorithm,this algorithm is more flexible and operable.

Track forecast:Operational capability and new techniques-Summary from the Tenth International Workshop on Tropical Cyclones(IWTC-10)

In this paper,we summarize findings from the Tenth International Workshop on Tropical Cyclones(IWTC-10)subgroup on operational track forecasting techniques and capability.The rate of improvement in the accuracy of official forecast tracks(OFTs)appears to be slowing down,at least for shorter lead times,where we may be approaching theoretical limits.Operational agencies continue to use consensus methods to produce the OFT with most continuing to rely on an unweighted consensus of four to nine NWP models.There continues to be limited use of weighted consensus techniques,which is likely a result of the skills and additional maintenance needed to support this approach.Improvements in the accuracy of ensemble mean tracks is leading to increased use of ensemble means in consensus tracks.Operational agencies are increasingly producing situation-dependent depictions of track uncertainty,rather than relying on a static depiction of track forecast certainty based on accuracy statistics from the preceding 5 years.This trend has been facilitated by the greater availability of ensemble NWP guidance,particularly vortex parameter files,and improved spread in ensembles.Despite improving spread-skill relationships,most ensemble NWP systems remain under spread.Hence many operational centers are looking to leverage“super-ensembles”(ensembles of ensembles)to ensure the full spread of location probability is captured.This is an important area of service development for multi-hazard impact-based warnings as it supports better decision making by emergency managers and the community in the face of uncertainty.©2023 The Shanghai Typhoon Institute of China Meteorological Administration.Publishing services by Elsevier B.V.on behalf of KeAi Communication Co.Ltd.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Unusual tracks:Statistical,controlling factors and model prediction

The progress of research and forecast techniques for tropical cyclone(TC)unusual tracks(UTs)in recent years is reviewed.A major research focus has been understanding which processes contribute to the evolution of the TC and steering flow over time,especially the reasons for the sharp changes in TC motion over a short period of time.When TCs are located in the vicinity of monsoon gyres,TC track forecast become more difficult to forecast due to the complex interaction between the TCs and the gyres.Moreover,the convection and latent heat can also feed back into the synoptic-scale features and in turn modify the steering flow.In this report,two cases with UTs are examined,along with an assessment of numerical model forecasts.Advances in numerical modelling and in particular the development of ensemble forecasting systems have proved beneficial in the prediction of such TCs.There are still great challenges in operational track forecasts and warnings,such as the initial TC track forecast,which is based on a poor pre-genesis analysis,TC track forecasts during interaction between two or more TCs and track predictions after landfall.Recently,artificial intelligence(AI)methods such as machine learning or deep learning have been widely applied in the field of TC forecasting.For TC track forecasting,a more effective method of center location is obtained by combining data from various sources and fully exploring the potential of AI,which provides more possibilities for improving TC prediction.

Remote sensing and analysis of tropical cyclones:Current and emerging satellite sensors

This article describes recent advances in the capability of new satellite sensors for observing Tropical Cyclones(TC)fine structure,wind field,and temporal evolution.The article is based on a World Meteorological Organization(WMO)report prepared for the 10th International Workshop on Tropical Cyclones(IWTC),held in Bali in December 2022,and its objective is to present updates in TC research and operation every four years.Here we focus on updates regarding the most recent space-based TC observations,and we cover new methodologies and techniques using polar orbiting sensors,such as C-band synthetic aperture radars(SARs),L-band and combined C/X-band radiometers,scatterometers,and microwave imagers/sounders.We additionally address progress made with the new generation of geostationary and small satellites,and discuss future sensors planned to be launched in the next years.We then briefly describe some examples on how the newest sensors are used in operations and data assimilation for TC forecasting and research,and conclude the article with a discussion on the remaining challenges of TC space-based observations and possible ways to address them in the near future.

Recommendations for improved tropical cyclone formation and position probabilistic Forecast products

Prediction of the potentially devastating impact of landfalling tropical cyclones(TCs)relies substantially on numerical prediction systems.Due to the limited predictability of TCs and the need to express forecast confidence and possible scenarios,it is vital to exploit the benefits of dynamic ensemble forecasts in operational TC forecasts and warnings.RSMCs,TCWCs,and other forecast centers value probabilistic guidance for TCs,but the International Workshop on Tropical Cyclones(IWTC-9)found that the“pull-through”of probabilistic information to operational warnings using those forecasts is slow.IWTC-9 recommendations led to the formation of the WMO/WWRP Tropical Cyclone-Probabilistic Forecast Products(TC-PFP)project,which is also endorsed as a WMO Seamless GDPFS Pilot Project.The main goal of TC-PFP is to coordinate across forecast centers to help identify best practice guidance for probabilistic TC forecasts.TC-PFP is being implemented in 3 phases:Phase 1(TC formation and position);Phase 2(TC intensity and structure);and Phase 3(TC related rainfall and storm surge).This article provides a summary of Phase 1 and reviews the current state of the science of probabilistic forecasting of TC formation and position.There is considerable variability in the nature and interpretation of forecast products based on ensemble information,making it challenging to transfer knowledge of best practices across forecast centers.Communication among forecast centers regarding the effectiveness of different approaches would be helpful for conveying best practices.Close collaboration with experts experienced in communicating complex probabilistic TC information and sharing of best practices between centers would help to ensure effective decisions can be made based on TC forecasts.Finally,forecast centers need timely access to ensemble information that has consistent,user-friendly ensemble information.Greater consistency across forecast centers in data accessibility,probabilistic forecast products,and warnings and their communication to users will produce more reliable information and support improved outcomes.

An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones

A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones(IWTC-9)in 2018,improving our understanding of the effect of climate change on tropical cyclones(TCs)and associated hazards and risks.These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change.New modeling and observational studies suggested the potential influence of anthropogenic climate forcings,including greenhouse gases and aerosols,on global and regional TC activity at the decadal and century time scales.However,there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic,and the limitations of observed TC records.The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models.A new paradigm,TC seeds,has been proposed,and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency.New studies also highlighted the importance of large-scale environmental fields on TC activity,such as snow cover and air-sea interactions.Future projections on TC translation speed and medicanes are new additional focus topics in our report.Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers.

CURRENT AND POTENTIAL USE OF ENSEMBLE FORECASTS IN OPERATIONAL TC FORECASTING:RESULTS FROM A GLOBAL FORECASTER SURVEY

In order to understand the current and potential use of ensemble forecasts in operational tropical cyclone(TC)forecasting,a questionnaire on the use of dynamic ensembles was conducted at operational TC forecast centers across the world,in association with the World Meteorological Organisation(WMO)High-Impact Weather Project(HIWeather).The results of the survey are presented,and show that ensemble forecasts are used by nearly all respondents,particularly in TC track and genesis forecasting,with several examples of where ensemble forecasts have been pulled through successfully into the operational TC forecasting process.There is still however,a notable difference between the high proportion of operational TC forecasters who use and value ensemble forecast information,and the slower pull-through into operational forecast warnings and products of the probabilistic guidance and uncertainty information that ensembles can provide.Those areas of research and development that would help TC forecasters to make increased use of ensemble forecast information in the future include improved access to ensemble forecast data,verification and visualizations,the development of hazard and impact-based products,an improvement in the skill of the ensembles(particularly for intensity and structure),and improved guidance on how to use ensembles and optimally combine forecasts from all available models.A change in operational working practices towards using probabilistic information,and providing and communicating dynamic uncertainty information in operational forecasts and warnings,is also recommended.

The Process and Benefits of Developing Prototype Climate Services——Examples in China

Changes in climate pose major challenges to society, and so decision-makers need actionable climate information to inform their planning and policies to make society more resilient to climatic changes. Climate services are being developed to provide such actionable climate information. The successful development and use of climate services benefits greatly from close engagement between developers, providers, and users of the services. The Climate Science for Service Partnership China(CSSP China) is a China–UK collaboration fostering closer engagement between climate scientists, providers of climate services, and users of climate services. We describe the process within CSSP China of co-developing climate services through trials with users to revise and improve a prototype. Examples are provided covering various scientific capabilities, user needs, and parts of China. The development process is yielding many benefits, such as increasing the engagement between providers and users, making users more aware of how climate information can be of use in their decision-making, giving the climate service providers a better understanding of the users’ requirements for climate information, and shaping future scientific research and development. In addition to the benefits, we also document some challenges that have emerged, along with ways of alleviating them. We have two key recommendations from our experiences: make the time and space for effective engagement between the users and developers of any climate service;bring the needs of the users in to the design and delivery of the climate service as early as possible and throughout the development cycle.

Science and prediction of monsoon heavy rainfall

With the increasing incidence of heavy rainfall events,particularly over the monsoon regions,the highly dense populations are more vulnerable[1].Research initiatives on observation,modeling,and prediction of monsoon heavy rainfall have been promoted actively by World Weather Research Programme's(WWRP)Working Group on Tropical Meteorology Research(WGTMR)of the World Meteorological Organization(WMO)since 2010.Series of monsoon-heavy-rainfall workshops were held in Beijing(2011),Petaling Jaya(2012),and New Delhi(2015)to benefit scientists worldwide and forecasters from the National Meteorological and Hydrological Services.An international Research and Development Project,namely,the Southern China Monsoon Rainfall Experiment(SCMREX)[2]was established in 2013 to coordinate field campaign experiments and to conduct scientific research on presummer(April-June)heavy rainfall processes in southern China.

SEASONAL TROPICAL CYCLONE FORECASTING

This paper summarizes the forecast methods,outputs and skill offered by twelve agencies for seasonal tropical cyclone(TC)activity around the world.These agencies use a variety of techniques ranging from statistical models to dynamical models to predict basinwide activity and regional activity.In addition,several dynamical and hybrid statistical/dynamical models now predict TC track density as well as landfall likelihood.Realtime Atlantic seasonal hurricane forecasts have shown low skill in April modest skill in June and good skill in August at predicting basinwide TC activity when evaluated over 2003-2018.Real-time western North Pacific seasonal TC forecasts have shown good skill by July for basinwide intense typhoon numbers and the ACE index when evaluated for 2003-2018.Both hindcasts and real-time forecasts have shown skill for other TC basins.A summary of recent research into forecasting TC activity beyond seasonal(e.g.,multi-year)timescales is included.Recommendations for future areas of research are also discussed.

Increasing the value of weather-related warnings

Despite advances in forecasting and emergency preparedness, weather related disasters continue to cost many lives, to displace populations and to cause wide-spread damage. Therefore, High Impact Weather Project (HIWeather), a 10-year research project (https://public.wmo.int/en/resources/buHetin/hiweather-10-yearresearch- project), was established in 2016 by WM0 (World Meteorology Organization) WWRP (World Weather Research Program: https://www.wmo.int/pages/prog/arep/wwrp/new/wwrp_new_en. html). HIWeather aimed at achieving dramatic improvements in the effectiveness of weather-related hazard warnings, following recent advancement in numerical weather prediction at km-scale and in disaster risk reduction. The implementation plan was developed under the concept of warning chain, which comprises all components and the connections between to a successful weather-hazards warning: observations, weather forecast, hazard forecast, impact forecast, the generation of warnings and decision making (Fig. 1). A successful warning relies on information produced by the meteorological and related physical sciences, thus its effectiveness of delivery depends on applications of social, behavioral and economic sciences. The workshop of WM0 High Impact Weather Project was held in Beijing during 20-22 November of 2018, attracted a diverse and interdisciplinary group of over 70 scientists from 25 countries in the broad field of physical and social science, during which all elements of the warning chain were discussed critically.