Wintertime Rossby Wave Breaking Persistence in Extended-range Seasonal Forecasts of Atlantic Tropical Cyclone Activity

In this study, we examine the wintertime environmental precursors of summer anticyclonic wave breaking (AWB) over the North Atlantic region and assess the applicability of these precursors in predicting AWB impacts on seasonal tropical cyclone (TC) activity. We show that predictors representing the environmental impacts of subtropical AWB on seasonal TC activity improve the skill of extended-range seasonal forecasts of TC activity. There is a significant correlation between boreal winter and boreal summer AWB activity via AWB-forced phases of the quasi-stationary North Atlantic Oscillation (NAO). Years with above-normal boreal summer AWB activity over the North Atlantic region also show above-normal AWB activity in the preceding boreal winter that tends to force a positive phase of the NAO that persists through the spring. These conditions are sustained by continued AWB throughout the year, particularly when El Niño-Southern Oscillation plays less of a role at forcing the large-scale circulation. While individual AWB events are synoptic and nonlinear with little predictability beyond 8-10 days, the strong dynamical connection between winter and summer wave breaking lends enough persistence to AWB activity to enable predictability of its potential impacts on TC activity. We find that the winter-summer relationship improves the skill of extended-range seasonal forecasts from as early as an April lead time, particularly for years when wave breaking has played a crucial role in suppressing TC development.

Comparing seasonal streamflow forecast systems for management of a fresh water reservoir in the Netherlands

For efficient management of the Dutch surface water reservoir Lake IJssel, (sub)seasonal forecasts of the water volumes going in and out of the reservoir are potentially of great interest. Here, streamflow forecasts were analyzed for the river Rhine at Lobith, which is partly routed through the river IJssel, the main influx into the reservoir. We analyzed multiple seasonal forecast data sets derived from EFAS, E-HYPE and HTESSEL, which differ in their underlying hydrological formulation, but are all forced with similar input from the ECMWF SEAS5 meteorological forecasts. We post-processed the streamflow forecasts using quantile matching (QM) and analyzed several forecast quality metrics. Forecast performance was assessed based on the available reforecast period, as well as on individual summer seasons. QM increased forecast skill for nearly all metrics evaluated. Particularly HTESSEL, a land surface scheme that is not optimized for hydrology, needed the largest correction. Averaged over the reforecast period, forecasts were skillful for the longest lead times in spring and early summer. For this period, E-HYPE showed the highest skill; Later in summer, however, skill deteriorated after 1–2 months. When investigating specific years with either low or high flow conditions, forecast skill increased with the extremity of the event. Although raw forecasts for both E-HYPE and EFAS were more skilful than HTESSEL, bias correction based on QM can significantly reduce the difference. In operational mode, the three forecast systems show comparable skill. In general, dry conditions can be forecasted with high success rates up to three months ahead, which is very promising for successful use of Rhine streamflow forecasts in downstream reservoir management.

Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): A Protocol for Investigating the Role of the Stratospheric Polar Vortex in Subseasonal to Seasonal Forecasts

Major disruptions of the winter season, high-latitude, stratospheric polar vortices can result in stratospheric anomalies that persist for months. These sudden stratospheric warming events are recognized as an important potential source of forecast skill for surface climate on subseasonal to seasonal timescales. Realizing this skill in operational subseasonal forecast models remains a challenge, as models must capture both the evolution of the stratospheric polar vortices in addition to their coupling to the troposphere. The processes involved in this coupling remain a topic of open research. We present here the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. SNAPSI is a new model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortices in sub-seasonal to seasonal forecast models. Based on a set of controlled, subseasonal, ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. First, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. Second, to attribute specific extreme events to stratospheric variability. Third, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models, and fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. Although not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. The output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of subseasonal forecasts.

Recent models for long range forecasting of Southwest monsoon rainfall in India

India has a long tradition of scientific work or, long range forecasting of the southwest monsoon ever since the times of Blanford and Walker In the early Parts of this century, the recent decades have witnessed increased research in regard to the development of new long range forecast models in the India Meteorological Department which have, given correct long range (seasonal) forecasts of southwest monsoon rainfall, over the country as a whole, during, the successive four year~, 1988 to 1991, Presently, four models namely, Para-metric Power Regression, Dynamic Stochastic Transfer and Improved Multiple Regression models are being used for formulating the seasonal forecast of monsoon rainfall over the country as a whole, The forecast is issued in two stages, In the first stage a tentative inference which is qualitative in nature is issued before the middle of April based mainly on the Parametric model which utilizes signals from 16 regional and global parameters that are related to land, ocean and atmospheric forcing and show physical linkages with monsoon. In the second stage, a firm quantitative forecast is issued towards the end of the May and is based on the remaining three models mentioned above, although higher weight age is given to the Power Regression Model which has shown encouraging performance during the last four years. In this paper, these recently developed models and the scientific basis underlying these are discussed, Data on validation of these Operational models, used for the long range forecast during the past four years (1988-91) are also presented.

Onset and Decline Rates of Marine Heatwaves: Global Trends, Seasonal Forecasts and Marine Management

Changing ocean conditions due to anthropogenic climate change, particularly the increasing severity and frequency of extreme events, are a growing concern for a range of marine sectors. Here we explore the global trends in marine heatwaves (MHWs), specifically onset and decline rates, two metrics which describe how quickly a MHW will emerge or disappear from a location. These rates determine the reaction window—the start of a MHW event to peak MHW temperatures—and the coping window—time from peak temperatures to the end of an event—two important time periods relevant to a marine decision-maker. We show that MHW onset and decline rates are fastest in dynamic ocean regions and that overall, the global trend in onset rate is greater than the global trend in decline rate. We map ocean regions where these rates are changing together with forecast skill from a seasonal dynamical model (ACCESS-S). This analysis highlights areas where the length of the preparation window for impending MHWs is increased by using forecasts, and areas where marine decision-makers should be prepared for rapid responses based on realtime observations as MHWs evolve. In regions such as south Africa and Kerguelen, northwest Atlantic, northwest Pacific, southwest South Atlantic and off Australian east coast where rapid median onset and decline rates are observed, there is also a positive trend in onset and decline rates i.e., MHWs are developing and declining more rapidly. This will be a concern for many decision-makers operating in these regions.

Impact of Eurasian autumn snow on the winter North Atlantic Oscillation in seasonal forecasts of the 20th century

As the leading climate mode of wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Eurasian cryosphere as a possible predictor for the wintertime NAO. However, missing correlation between snow cover and wintertime NAO in climate model experiments and strong non-stationarity of this link in reanalysis data are questioning the causality of this relationship. Here we use the large ensemble of Atmospheric Seasonal Forecasts of the 20th Century (ASF-20C) with the European Centre for Medium-Range Weather Forecasts model, focusing on the winter season. Besides the main 110-year ensemble of 51 members, we investigate a second, perturbed ensemble of 21 members where initial (November) land conditions over the Northern Hemisphere are swapped from neighboring years. The Eurasian snow–NAO linkage is examined in terms of a longitudinal snow depth dipole across Eurasia. Subsampling the perturbed forecast ensemble and contrasting members with high and low initial snow dipole conditions, we found that their composite difference indicates more negative NAO states in the following winter (DJF) after positive west-to-east snow depth gradients at the beginning of November. Surface and atmospheric forecast anomalies through the troposphere and stratosphere associated with the anomalous positive snow dipole consist of colder early winter surface temperatures over eastern Eurasia, an enhanced Ural ridge and increased vertical energy fluxes into the stratosphere, with a subsequent negative NAO-like signature in the troposphere. We thus confirm the existence of a causal connection between autumn snow patterns and subsequent winter circulation in the ASF-20C forecasting system.

Verification and Bias Adjustment of ECMWF SEAS5 Seasonal Forecasts over Europe for Climate Service Applications

This work discusses the ability of a bias-adjustment method using empirical quantile mapping to improve the skills of seasonal forecasts over Europe for three key climate variables, i.e., temperature, precipitation and wind speed. In particular, the suitability of the approach to be integrated in climate services and to provide tailored predictions for local applications was evaluated. The workflow was defined in order to allow a flexible implementation and applicability while providing accurate results. The scheme adjusted monthly quantities from the seasonal forecasting system SEAS5 of the European Centre for Medium-Range Forecasts (ECMWF) by using ERA5 reanalysis as reference. Raw and adjusted forecasts were verified through several metrics analyzing different aspects of forecast skills. The applied method reduced model biases for all variables and seasons even though more limited improvements were obtained for precipitation. In order to further assess the benefits and limitations of the procedure, the results were compared with those obtained by the ADAMONT method, which calibrates daily quantities by empirical quantile mapping conditioned by weather regimes. The comparable performances demonstrated the overall suitability of the proposed method to provide end users with calibrated predictions of monthly and seasonal quantities.

Communicating Properties of Changes in Lagged Weather Forecasts

Weather forecasts, seasonal forecasts, and climate projections can help their users make good decisions. It has recently been shown that when the decisions include the question of whether to act now or wait for the next forecast, even better decisions can be made if information describing potential forecast changes is also available. In this article, we discuss another set of situations in which forecast change information can be useful, which arise when forecast users need to decide which of a series of lagged forecasts to use. Motivated by these potential applications of forecast change information, we then discuss a number of ways in which forecast change information can be presented, using ECMWF reforecasts and corresponding observations as illustration. We first show metrics that illustrate changes in forecast values, such as average sizes of changes, probabilities of changes of different sizes, and percentiles of the distribution of changes, and then show metrics that illustrate changes in forecast skill, such as increase in average skill and probabilities that later forecasts will be more accurate. We give four illustrative numerical examples in which these metrics determine which of a series of lagged forecasts to use. In conclusion, we suggest that providers of weather forecasts, seasonal forecasts, and climate projections might consider presenting forecast change information, in order to help forecast users make better decisions.