Climatology of Tibetan Plateau Vortices in reanalysis data and a high-resolution global climate model

The Tibetan Plateau (TP) and surrounding high mountains constitute an important forcing of the atmospheric circulation due to their height and extent, and thereby impact weather and climate in downstream regions of East Asia. Mesoscale Tibetan Plateau Vortices (TPVs) are one of the major precipitation-producing systems on the TP. A fraction of TPVs moves off the TP to the east and can trigger extreme precipitation in parts of China, e.g. the Sichuan province and the Yangtze River valley, that can result in severe flooding. In this study, the climatology of TPV occurrence is examined in two reanalyses and, for the first time, in a high-resolution global climate model using an objective feature tracking algorithm. Most TPVs are generated in the north-western part of the TP; the centre of this main genesis region is small and stable throughout the year. The strength and position of the subtropical westerly jet is correlated to the distance TPVs can travel eastwards and therefore could have an effect on whether or not a TPV is moving-off the TP. TPV-associated precipitation can account for up to 40% of the total precipitation in parts of China in selected months, often due to individual TPVs. The results show that the global climate model is able to simulate TPVs at N512 (~25 km) horizontal resolution and in general agrees with the reanalyses. The fact that the global climate model can represent the TPV climatology opens a wide range of options for future model-based research on TPVs

Different Asian monsoon rainfall responses to idealised orography sensitivity experiments in the HadGEM3-GA6 and FGOALS-FAMIL global climate models

Recent work has shown the dominance of the Himalayas in supporting the Indian summer monsoon (ISM), perhaps by surface sensible heating along its southern slope and by mechanical blocking acting to separate moist tropical flow from drier mid-latitude air. Previous studies have also shown that Indian summer rainfall is largely unaffected in sensitivity experiments that remove only the Tibetan Plateau. However, given the large biases in simulating the monsoon in CMIP5 models, such results may be model dependent. This study investigates the impact of orographic forcing from the Tibetan Plateau, Himalayas and Iranian Plateau on the ISM and East Asian summer monsoons (EASM) in the UK Met Office HadGEM3-GA6 and China’s Institute of Atmospheric Physics FGOALS-FAMIL GCMs. The models chosen feature opposite-signed biases in their simulation of the ISM rainfall and circulation climatology. The changes to ISM and EASM circulation across the sensitivity experiments are similar in both models and consistent with previous studies. However, considerable differences exist in the rainfall responses over India and China, and in the detailed aspects such as onset and retreat dates. In particular, the models show opposing changes in Indian monsoon rainfall when the Himalaya and Tibetan Plateau orography are removed. Our results show that a multi-model approach, as suggested in the forthcoming Global Monsoon Model Intercomparison Project (GMMIP) associated with CMIP6, is needed to clarify the impact of orographic forcing on the Asian monsoon and to fully understand the implications of model systematic error

Added value of high resolution models in simulating global precipitation characteristics

Climate models tend to overestimate percentage of the contribution (to total precipitation) and frequency of light rainfall while underestimate the heavy rainfall. This article investigates the added value of high resolution of atmospheric general circulation models (AGCMs) in simulating the characteristics of global precipitation, in particular extremes. Three AGCMs, global high resolution atmospheric model from the Geophysical Fluid Dynamics Laboratory (GFDL-HiRAM), the Meteorological Research Institute-atmospheric general circulation model (MRI-AGCM) and the Met Office Unified Model (MetUM), each with one high and one low resolution configurations for the period 1998–2008 are used in this study. Some consistent improvements are found across all three AGCMs with increasing model resolution from 50–83 to 20–35 km. A reduction in global mean frequency and amount percentile of light rainfall (20 mm day−1) are shown in high resolution models of GFDL-HiRAM and MRI-AGCM, while the improvement in MetUM is not obvious. A consistent response to high resolution across the three AGCMs is seen from the increase of light rainfall frequency and amount percentile over the desert regions, particularly over the ocean desert regions. It suppresses the overestimation of CDD over ocean desert regions and makes a better performance in high resolution models of GFDL-HiRAM and MRI-AGCM, but worse in MetUM-N512. The impact of model resolution differs greatly among the three AGCMs in simulating the fraction of total precipitation exceeding the 95th percentile daily wet day precipitation. Inconsistencies among models with increased resolution mainly appear over the tropical oceans and in simulating extreme wet conditions, probably due to different reactions of dynamical and physical processes to the resolution, indicating their crucial role in high resolution modelling

Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation period. It is found that both methods yield merged fields of better quality than the original radar field or fields obtained by OK of gauge data. The newly suggested KED formulation is shown to be beneficial, in particular in mountainous regions where the quality of the Swiss radar composite is comparatively low. An analysis of the Kriging variances shows that none of the methods tested here provides a satisfactory uncertainty estimate. A suitable variable transformation is expected to improve this

Bias-corrected nonparametric correlograms for geostatistical radar-raingauge combination

Geostatistical methods have been widely used for quantitative precipitation estimation (QPE) based on the combination of radar and raingauge observations. They are flexible and accurate and allow for radar-raingauge combination in real-time. Even within the area of geostatistical methods, however, a wide range of choices have to be made when planning for a particular application. These choices regard, for example, the actual combination method (e.g., kriging with external drift, cokriging), the kriging neighbourhood (global vs. local), the technique used to estimate the parameters of the geostatical model (e.g., least-squares, maximum-likelihood estimation), and the transformation of the precipitation variable. In addition to these issues, there are a number of options for modeling spatial dependencies in the precipitation data. Correlograms (variograms) for kriging are customarily one-dimensional, but two- or higher-dimensional correlation maps are also used and are one way of taking spatial anisotropy into account. Furthermore, correlograms can be parametric or nonparametric, they can be obtained from the radar or the raingauge data, and they can be estimated flexibly on a case-by-case basis or with data from a longer period of time. Recently, nonparametric correlograms based on spatially complete radar rainfall fields have been used in combining radar and raingauge data [1]. Here, we compare the estimation of nonparametric correlograms with the estimation of parametric semivariogram models conventionally used in geostatistical applications. We identify and explain a bias of the nonparametric correlograms towards too low ranges, and suggest a correction for this bias.Postprint (published version

Clear-air turbulence trends over the North Atlantic in high-resolution climate models

Clear-air turbulence (CAT) has a large impact on the aviation sector. Our current understanding of how CAT may increase with climate change in future is largely based on simulations from CMIP3 and CMIP5 global climate models (GCMs). However, these models have now been superseded by high-resolution CMIP6 GCMs, which for the first time have grid lengths at which individual turbulence patches may start to be resolved. Here we use a multi-model approach to quantify projected moderate CAT changes over the North Atlantic using CMIP6 models. The influence of the model resolution on CAT projections is analysed. Twenty-one CAT diagnostics are used, in order to represent uncertainties in CAT production mechanisms. Each diagnostic responds differently in time, but the majority display an increase in moderate CAT between 1950 and 2050. Although winter is historically the most turbulent season, there is strong multi-model agreement that autumn and summer will have the greatest overall relative increase in CAT frequency. By 2050, summers are projected to become as turbulent as 1950 winters and autumns. The global-mean seasonal near-surface temperature is used as a comparative metric. For every 1 °C of global near-surface warming, autumn, winter, spring, and summer are projected to have an average of 14%, 9%, 9%, and 14% more moderate CAT, respectively. Our results confirm that the aviation sector should prepare for a more turbulent future

Magnitude, scale, and dynamics of the 2020 Mei Yu rains and floods over China

Large parts of East and South Asia were affected by heavy precipitation and flooding during early summer 2020. This study provides both a statistical and dynamical characterization of rains and floods affecting the Yangtze River Basin (YRB). By aggregating daily and monthly precipitation over river basins across Asia, it is shown that the YRB is one of the areas that was particularly affected. June and July 2020 rainfall was higher than in the previous 20 years, and the YRB experienced anomalously high rainfall across most of its sub-basins. YRB discharge also attained levels not seen since 1998/9. An automated method detecting the daily position of the East Asian Summer Monsoon Front (EASMF) is applied to show that the anomalously high YRB precipitation was associated with a halted northward progression of the EASMF and prolonged Mei Yu conditions over the YRB lasting more than one month. Two 5-day heavy-precipitation episodes (12-16 June and 4-8 July 2020) are selected from this period for dynamical characterisation, including Lagrangian trajectory analysis. Particular attention is devoted to the dynamics of the airstreams converging at the EASMF. Both episodes display heavy precipitation and convergence of monsoonal and subtropical air masses. However, clear differences are identified in the upper-level flow pattern, substantially affecting the balance of airmass advection towards the EASMF. This study contextualises heavy precipitation in Asia in summer 2020 and showcases a number of analysis tools developed by the authors for the study of such events

Sahel decadal rainfall variability and the role of model horizontal resolution

Substantial low-frequency rainfall fluctuations occurred in the Sahel throughout the twentieth century, causing devastating drought. Modeling these low-frequency rainfall fluctuations has remained problematic for climate models for many years. Here we show using a combination of state-of-the-art rainfall observations and high-resolution global climate models that changes in organized heavy rainfall events carry most of the rainfall variability in the Sahel at multiannual to decadal time scales. Ability to produce intense, organized convection allows climate models to correctly simulate the magnitude of late-twentieth century rainfall change, underlining the importance of model resolution. Increasing model resolution allows a better coupling between large-scale circulation changes and regional rainfall processes over the Sahel. These results provide a strong basis for developing more reliable and skilful long-term predictions of rainfall (seasons to years) which could benefit many sectors in the region by allowing early adaptation to impending extremes

How interactions between tropical depressions and western disturbances affect heavy precipitation in South Asia

Interactions over South Asia between tropical depressions (TDs) and extratropical storms known as western disturbances (WDs) are known to cause extreme precipitation events, including those responsible for the 2013 floods over northern India. In this study, existing databases of WD and TD tracks are used to identify potential WD–TD interactions from 1979–2015; these are filtered according to proximity and intensity, leaving 59 cases which form the basis of this paper. Synoptic charts, vorticity budgets, and moisture trajectory analyses are employed to identify and elucidate common interaction types among these cases. Two broad families of interaction emerge. Firstly, a dynamical coupling of the WD and TD, whereby either the upper- and lower-level vortices superpose (a vortex merger), or the TD is intensified as it passes into the entrance region of a jet streak associated with the WD (a jet-streak excitation). Secondly, a moisture exchange between the WD and TD, whereby either anomalous moisture is advected from the TD to the WD, resulting in anomalous precipitation near the WD (a TD-to-WD moisture exchange), or anomalous moisture is advected from the WD to the TD (a WD-to-TD moisture exchange). Interactions are most common in the post-monsoon period as the subtropical jet, which brings WDs to the subcontinent, returns south; there is a smaller peak in May and June, driven by monsoon onset vortices. Precipitation is heaviest in dynamically-coupled interactions, particularly jet–streak excitations. Criteria for automated identification of interaction types are proposed, and schematics for each type are presented to highlight key mechanisms

How important are post-tropical cyclones for European windstorm risk?

Post-tropical cyclones (PTCs) extend many hazards associated with tropical cyclones (TCs) to the mid-latitudes. Despite recent high-impact cases affecting Europe such as Ophelia, little research has been done to characterize the risk of PTCs. Here we compare the climatologies and intensity distributions of mid-latitude cyclones (MLCs) and PTCs in the North Atlantic and Europe by tracking cyclones in the ERA5 reanalysis. Considering hurricane-season cyclones impacting Northern Europe, PTCs show a significantly higher mean maximum intensity than MLCs, but make only a small contribution to total windstorm risk. Our results show that a disproportionately large fraction of high-intensity cyclones impacting Europe during hurricane season are PTCs. The fraction of PTCs impacting N Europe with storm-force (>25ms-1) winds is approximately ten times higher than for MLCs. Less than 1% of cyclones impacting Northern Europe are identified to be PTCs. This rises to 8.8% when considering cyclones which impact with storm-force winds