On northern-hemisphere wave patterns associated with winter rainfall events in China

During extended winter (November-April) 43% of the intraseasonal rainfall variability in China is explained by three spatial patterns of temporally coherent rainfall. These patterns were identified with Empirical Orthogonal Teleconnection (EOT) analysis of observed 1982-2007 pentad rainfall anomalies and connected to midlatitude disturbances. However, examination of individual strong EOT events shows that there is substantial inter-event variability in their dynamical evolution, which implies that precursor patterns found in regressions cannot serve as useful predictors. To understand the physical nature and origins of the extratropical precursors, the EOT technique is applied to six simulations of the Met Office Unified Model at horizontal resolutions of 200--40 km and with and without air-sea coupling. All simulations reproduce the observed precursor patterns in regressions, indicating robust underlying dynamical processes. Further investigation into the dynamics associated with observed patterns shows that Rossby wave dynamics can explain the large inter-event variability. The results suggest that the apparently slowly evolving or quasi-stationary waves in regression analysis are a statistical amalgamation of more rapidly propagating waves with a variety of origins and properties

Stochastic climate theory and modeling

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models

ESD ideas: translating historical extreme weather events into a warmer world

A new reanalysis-based approach is proposed to examine how reconstructions of extreme weather events differ in warmer or cooler counter-factual worlds. This approach offers a novel way to develop plausible storylines for some types of extreme event that other methods may not be suitable for. As a proof of concept, a reanalysis of a severe windstorm that occurred in February 1903 is translated into a warmer world where it produces higher wind speeds and increased rainfall, suggesting that this storm would be more damaging if it occurred today rather than 120 years ago. Whenever a severe weather event occurs with harmful impacts in a particular region, it is often asked by disaster responders, recovery planners, politicians, and journalists whether climate change caused or affected the event. The harmful impacts are caused by the unusual weather, but climate change may have made the weather event more likely, more severe, or both. In those cases, the harmful impacts may be partly or even mostly due to the change in climate. In some cases, the worst consequences may be due to the vulnerability or exposure of the local population or ecosystems, or due to a combination of many other factors (e.g. Otto et al., 2022). Many methodologies exist to understand how climate change has affected extreme events. These are broadly categorized into risk-based approaches and storyline approaches (Stott and Christidis, 2023). The risk-based approaches assess the change in likelihood and magnitude of a particular class of event (e.g. Stott et al., 2004), whereas storyline approaches consider how climate change may have affected a specific event (Trenberth et al., 2015; Shepherd et al., 2018). Other studies consider the related question of what a plausible worst-case event might look like in a particular climate (e.g. Thompson et al., 2017). Some of these methods are now regularly used to provide attribution statements soon after events occur (van Oldenborgh et al., 2021). Event storyline approaches attempt to quantify how an extreme event would be different in an altered climate. This can be achieved by producing reconstructions of the event as it occurred and in counter-factual cooler or warmer climates and comparing the consequences. Various approaches exist for such analyses, including statistical methods (e.g. Cattiaux et al., 2010), analogues (Ginesta et al., 2023; Faranda et al., 2022), nudging a weather or climate model (e.g. Meredith et al., 2015; van Garderen et al., 2021; Sánchez-Benítez et al., 2022), and forecast-based approaches (e.g. Wehner et al., 2019; Leach et al., 2021). Here, we propose a complementary reanalysis-based approach to translate extreme events into different climates

Comparison of a manual and an automated tracking method for Tibetan Plateau vortices

Tibetan Plateau vortices (TPVs) are mesoscale cyclones originating over the Tibetan Plateau (TP) during the extended summer season (April-September). Most TPVs stay on the TP while a small number can move off the TP to the east. TPVs are known to be one of the main precipitation-bearing systems on the TP and moving-off TPVs have been associated with heavy precipitation and flooding downstream of the TP (e.g. Sichuan province, Yangtze River Valley). Identifying and tracking TPVs is difficult both due to their comparatively small horizontal extent (400 – 800 km) and the limited availability of soundings over the TP, which, in turn, constitutes a challenge for short-term predictions of TPV-related impacts and for the climatological study of TPVs. In this study, (i) manual tracking (MT) results using radiosonde data from a network over and downstream of the TP are compared with (ii) results obtained by an automated tracking (AT) algorithm applied to ERA-Interim reanalysis. Ten MT-TPV cases are selected based on method (i) and matched to and compared with the corresponding AT-TPVs identified with method (ii). Conversely, ten AT-TPVs are selected and compared with the corresponding MT-TPVs. In general, the comparison shows good results in cases where the underlying data are in good agreement, but considerable differences are also seen in some cases and explained in terms of differences in the tracking methods, data availability/coverage and disagreement between sounding and ERA-Interim data. Recommendations are given for future efforts in TPV detection and tracking, including in an operational weather forecasting context

The contribution of tropical cyclones to the atmospheric branch of Middle America's hydrological cycle using observed and reanalysis tracks

Middle America is affected by tropical cyclones (TCs) from the Eastern Pacific and the North Atlantic Oceans. We characterize the regional climatology (1998-2016) of the TC contributions to the atmospheric branch of the hydrological cycle, from May to December. TC contributions to rainfall are quantified using Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product 3B42 and TC tracks derived from three sources: the International Best Track Archive for Climate Stewardship (IBTrACS), and an objective feature tracking method applied to the Japanese 55-year and ERA-Interim reanalyses. From July to October, TCs contribute 10-30% of rainfall over the west and east coast of Mexico and central Mexico, with the largest monthly contribution during September over the Baja California Peninsula (up to 90%). TCs are associated with 40-60% of daily extreme rainfall (above the 95th percentile) over the coasts of Mexico. IBTrACS and reanalyses agree on TC contributions over the Atlantic Ocean but disagree over the Eastern Pacific Ocean and continent; differences over the continent are mainly attributed to discrepancies in TC tracks in proximity to the coast and TC lifetime. Reanalysis estimates of TC moisture transports show that TCs are an important moisture source for the regional water budget. TC vertically integrated moisture flux (VIMF) convergence can turn regions of weak VIMF divergence by the mean circulation into regions of weak VIMF convergence. We discuss deficiencies in the observed and reanalysis TC tracks, which limit our ability to quantify robustly the contribution of TCs to the regional hydrological cycle

Influence of warming and atmospheric circulation changes on multidecadal European flood variability

International audienceEuropean flood frequency and intensity change on a multidecadal scale. Floods were more frequent in the 19th (central Europe) and early 20th century (western Europe) than during the mid-20th century and again more frequent since the 1970s. The causes of this variability are not well understood and the relation to climate change is unclear. Palaeoclimate studies from the northern Alps suggest that past flood-rich periods coincided with cold periods. In contrast, some studies suggest that more floods might occur in a future, warming world. Here we address the contribution of atmospheric circulation and of warming to multidecadal flood variability. For this, we use long series of annual peak streamflow, daily weather data, reanalyses, and reconstructions. We show that both changes in atmospheric circulation and moisture content affected multidecadal changes of annual peak streamflow in central and western Europe over the past two centuries. We find that during the 19th and early 20th century, atmospheric circulation changes led to high peak values of moisture flux convergence. The circulation was more conducive to strong and long-lasting precipitation events than in the mid-20th century. These changes are also partly reflected in the seasonal mean circulation and reproduced in atmospheric model simulations, pointing to a possible role of oceanic variability. For the period after 1980, increasing moisture content in a warming atmosphere led to extremely high moisture flux convergence. Thus, the main atmospheric driver of flood variability changed from atmospheric circulation variability to water vapour increase.La fréquence et l'intensité des inondations en Europe changent à une échelle multidécennale. Les inondations étaient plus fréquentes au 19ème (Europe centrale) et au début du 20ème siècle (Europe occidentale) qu'au milieu du 20ème siècle et à nouveau plus fréquentes depuis les années 1970. Les causes de cette variabilité ne sont pas bien comprises et la relation avec le changement climatique n'est pas claire. Les études paléoclimatiques menées dans les Alpes du Nord suggèrent que les périodes passées riches en inondations coïncidaient avec des périodes froides. En revanche, certaines études suggèrent que davantage d'inondations pourraient se produire dans un monde futur en réchauffement. Nous abordons ici la contribution de la circulation atmosphérique et du réchauffement à la variabilité multidécennale des inondations. Pour cela, nous utilisons de longues séries de débit maximal annuel, des données météorologiques quotidiennes, des réanalyses et des reconstructions climatiques. Nous montrons que les changements de la circulation atmosphérique et du contenu en humidité ont affecté les changements multidécennaux du débit maximal annuel en Europe centrale et occidentale au cours des deux derniers siècles. Nous constatons qu'au cours du 19ème et du début du 20ème siècle, les changements de la circulation atmosphérique ont conduit à des valeurs de pointe élevées de convergence du flux d'humidité. La circulation était plus propice à des événements de précipitations forts et durables qu'au milieu du 20e siècle. Ces changements se reflètent également en partie dans la circulation moyenne saisonnière et sont reproduits dans les simulations des modèles atmosphériques, ce qui indique un rôle possible de la variabilité océanique. Pour la période après 1980, l'augmentation de la teneur en humidité dans une atmosphère qui se réchauffe a conduit à une convergence extrêmement élevée des flux d'humidité. Ainsi, le principal moteur atmosphérique de la variabilité des crues est passé de la variabilité de la circulation atmosphérique à l'augmentation de la vapeur d'eau

Sensitivities of the NCEP Global Forecast System

An important issue in developing a forecast system is its sensitivity to additional observations for improving initial conditions, to the data assimilation (DA) method used, and to improvements in the forecast model. These sensitivities are investigated here for the Global Forecast System (GFS) of the National Centers for Environmental Prediction (NCEP). Four parallel sets of 7-day ensemble forecasts were generated for 100 forecast cases in mid-January to mid-March 2016. The sets differed in their 1) inclusion or exclusion of additional observations collected over the eastern Pacific during the El Ni&ntilde;o Rapid Response (ENRR) field campaign, 2) use of a hybrid 4D&ndash;EnVar versus a pure EnKF DA method to prepare the initial conditions, and 3) inclusion or exclusion of stochastic parameterizations in the forecast model. The Control forecast set used the ENRR observations, hybrid DA, and stochastic parameterizations. Errors of the ensemble-mean forecasts in this Control set were compared with those in the other sets, with emphasis on the upper-tropospheric geopotential heights and vorticity, midtropospheric vertical velocity, column-integrated precipitable water, near-surface air temperature, and surface precipitation. In general, the forecast errors were found to be only slightly sensitive to the additional ENRR observations, more sensitive to the DA methods, and most sensitive to the inclusion of stochastic parameterizations in the model, which reduced errors globally in all the variables considered except geopotential heights in the tropical upper troposphere. The reduction in precipitation errors, determined with respect to two independent observational datasets, was particularly striking.</p

An evaluation of the performance of the twentieth century reanalysis version 3

The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a ‘‘best estimate’’ of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context.The research work of R. Przybylak and P. Wyszynski was supported by the National Science Centre, Poland (Grants DEC-2012/07/B/ST10/04002 and 2015/19/B/ST10/02933)

An Evaluation of the Performance of the Twentieth Century Reanalysis Version 3

The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a “best estimate” of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context

Rossby wave dynamics of the North Pacific extra-tropical response to El Niño: importance of the basic state in coupled GCMs

The extra-tropical response to El Nino in a "low" horizontal resolution coupled climate model, typical of the Intergovernmental Panel on Climate Change fourth assessment report simulations, is shown to have serious systematic errors. A high resolution configuration of the same model has a much improved response that is similar to observations. The errors in the low resolution model are traced to an incorrect representation of the atmospheric teleconnection mechanism that controls the extra-tropical sea surface temperatures (SSTs) during El Nino. This is due to an unrealistic atmospheric mean state, which changes the propagation characteristics of Rossby waves. These erroneous upper tropospheric circulation anomalies then induce erroneous surface circulation features over the North Pacific. The associated surface wind speed and direction errors create erroneous surface flux and upwelling anomalies which finally lead to the incorrect extra-tropical SST response to El Nino in the low resolution model. This highlights the sensitivity of the climate response to a single link in a chain of complex climatic processes. The correct representation of these processes in the high resolution model indicates the importance of horizontal resolution in resolving such processes