Abstract This study analyses the spatio‐temporal variability of heatwave characteristics and their association with large‐scale climate drivers across seven climatic sub‐regions in Vietnam, including the Northwest (R1), Northeast (R2), Red River Delta (R3), North Central (R4), South Central (R5), Central Highlands (R6) and the South (R7). The analysis is based on observed daily maximum temperatures from 102 meteorological stations, spanning the period 1980–2020. The obtained results reveal diverse heatwave patterns across the country. Amongst the seven climatic sub‐regions of Vietnam, the R3 and R4 sub‐regions experienced more frequent heatwaves and a higher number of heatwave days, but shorter durations. In contrast, other sub‐regions had fewer heatwave events and heatwave days but experienced longer‐lasting heatwaves. The intensity of heatwave events varies amongst sub‐regions, with the highest value in the R4 sub‐region, and the lowest in R7. Notably, the R1–R5 sub‐regions are affected by heatwaves over larger areas, compared to others. Additionally, the findings confirm that the lagged influence of El Niño–Southern Oscillation (ENSO) is the primary climatic driver of heatwave characteristics in Vietnam. Generally, heatwaves tend to occur more frequently in the years following El Niño events than after La Niña events. This observation provides opportunities for developing a system of seasonal predictions of heatwaves in Vietnam. The impact of ENSO on the number of heatwave events and heatwave days is evident in five out of seven sub‐regions, with less impact in the R2 and R7 sub‐regions. However, it does not significantly affect heatwave intensity.
Abstract —J. Blunden and T. Boyer In 2023, La Niña conditions that generally prevailed in the eastern Pacific Ocean from mid-2020 into early 2023 gave way to a strong El Niño by October. Atmospheric concentrations of Earth’s major greenhouse gases—carbon dioxide, methane, and nitrous oxide—all increased to record-high levels. The annual global average carbon dioxide concentration in the atmosphere rose to 419.3±0.1 ppm, which is 50% greater than the pre-industrial level. The growth from 2022 to 2023 was 2.8 ppm, the fourth highest in the record since the 1960s. The combined short-term effects of El Niño and the long-term effects of increasing levels of heat-trapping gases in the atmosphere contributed to new records for many essential climate variables reported here. The annual global temperature across land and oceans was the highest in records dating as far back as 1850, with the last seven months (June–December) having each been record warm. Over land, the globally averaged temperature was also record high. Dozens of countries reported record or near-record warmth for the year, including China and continental Europe as a whole (warmest on record), India and Russia (second warmest), and Canada (third warmest). Intense and widespread heatwaves were reported around the world. In Vietnam, an all-time national maximum temperature record of 44.2°C was observed at Tuong Duong on 7 May, surpassing the previous record of 43.4°C at Huong Khe on 20 April 2019. In Brazil, the air temperature reached 44.8°C in Araçuaí in Minas Gerais on 20 November, potentially a new national record and 12.8°C above normal. The effect of rising temperatures was apparent in the cryosphere, where snow cover extent by June 2023 was the smallest in the 56-year record for North America and seventh smallest for the Northern Hemisphere overall. Heatwaves contributed to the greatest average mass balance loss for Alpine glaciers around the world since the start of the record in 1970. Due to rapid volume loss beginning in 2021, St. Anna Glacier in Switzerland and Ice Worm Glacier in the United States disappeared completely. In August, as a direct result of glacial thinning over the past 20 years, a glacial lake on a tributary of the Mendenhall Glacier in Alaska burst through its ice dam and caused unprecedented flooding on Mendenhall River near Juneau. Across the Arctic, the annual surface air temperature was the fourth highest in the 124-year record, and summer (July–September) was record warm. Smaller-than-normal snow cover extent in May and June contributed to the third-highest average peak tundra greenness in the 24-year record. In September, Arctic minimum sea ice extent was the fifth smallest in the 45-year satellite record. The 17 lowest September extents have all occurred in the last 17 years. In Antarctica, temperatures for much of the year were up to 6°C above average over the Weddell Sea and along coastal Dronning Maud Land. The Antarctic Peninsula also experienced well-above-average temperatures during the 2022/23 melt season, which contributed to its fourth consecutive summer of above-average surface melt. On 21 February, Antarctic sea ice extent and sea ice area both reached all-time lows, surpassing records set just a year earlier. Over the course of the year, new daily record-low sea ice extents were set on 278 days. In some instances, these daily records were set by a large margin, for example, the extent on 6 July was 1.8 million km 2 lower than the previous record low for that day. Across the global oceans, the annual sea surface temperature was the highest in the 170-year record, far surpassing the previous record of 2016 by 0.13°C. Daily and monthly records were set from March onward, including an historic-high daily global mean sea surface temperature of 18.99°C recorded on 22 August. Approximately 94% of the ocean surface experienced at least one marine heatwave in 2023, while 27% experienced at least one cold spell. Globally averaged ocean heat content from the surface to 2000-m depth was record high in 2023, increasing at a rate equivalent to ∼0.7 Watts per square meter of energy applied over Earth’s surface. Global mean sea level was also record high for the 12th consecutive year, reaching 101.4 mm above the 1993 average when satellite measurements began, an increase of 8.1±1.5 mm over 2022 and the third highest year-over-year increase in the record. A total of 82 named tropical storms were observed during the Northern and Southern Hemispheres’ storm seasons, below the 1991–2020 average of 87. Hurricane Otis became the strongest landfalling hurricane on record for the west coast of Mexico at 140 kt (72 m s −1 ), causing at least 52 fatalities and $12–16 billion U.S. dollars in damage. Freddy became the world’s longest-lived tropical cyclones on record, developing into a tropical cyclone on 6 February and finally dissipating on 12 March. Freddy crossed the full width of the Indian Ocean and made one landfall in Madagascar and two in Mozambique. In the Mediterranean Sea—outside of traditional tropical cyclone basins—heavy rains and flooding from Storm Daniel killed more than 4300 people and left more than 8000 missing in Libya. The record-warm temperatures in 2023 created conditions that helped intensify the hydrological cycle. Measurements of total-column water vapor in the atmosphere were the highest on record, while the fraction of cloud area in the sky was the lowest since records began in 1980. The annual global mean precipitation total over land surfaces for 2023 was among the lowest since 1979, but global one-day maximum totals were close to average, indicating an increase in rainfall intensity. In July, record-high areas of land across the globe (7.9%) experienced extreme drought, breaking the previous record of 6.2% in July 2022. Overall, 29.7% of land experienced moderate or worse categories of drought during the year, also a record. Mexico reported its driest (and hottest) year since the start of its record in 1950. In alignment with hot and prolonged dry conditions, Canada experienced its worst national wildfire season on record. Approximately 15 million hectares burned across the country, which was more than double the previous record from 1989. Smoke from the fires were transported far into the United States and even to western European countries. August to October 2023 was the driest three-month period in Australia in the 104-year record. Millions of hectares of bushfires burned for weeks in the Northern Territory. In South America, extreme drought developed in the latter half of the year through the Amazon basin. By the end of October, the Rio Negro at Manaus, a major tributary of the Amazon River, fell to its lowest water level since records began in 1902. The transition from La Niña to El Niño helped bring relief to the prolonged drought conditions in equatorial eastern Africa. However, El Niño along with positive Indian Ocean dipole conditions also contributed to excessive rainfall that resulted in devastating floods over southeastern Ethiopia, Somalia, and Kenya during October to December that displaced around 1.5 million people. On 5 September, the town of Zagora, Greece, broke a national record for highest daily rainfall (754 mm in 21 hours, after which the station ceased reporting) due to Storm Daniel; this one-day accumulation was close to Zagora’s normal annual total.
Abstract. Against the background of the rising sea level and land subsidence, protecting the progressively eroding coast along the Vietnam Mekong Delta becomes of tremendous importance. Within the presented work, design conditions for breakwaters were derived from offshore climate reanalysis data (ERA5), which were transferred to the nearshore by two numerical approaches, i.e. SwanOne and Delft3D, for different average and extreme wave and weather conditions. Within this process, design wave heights and periods at the nearshore could be determined for 10- to 100-year recurrence intervals. Both models thereby showed sufficient accuracy according to measurements in the field. Limitations must be made regarding the available spatio-temporal resolution, where reanalysis data showed a lack of short but high peak values compared to the observed measurements. Both numerical approaches showed their capabilities, where SwanOne offers a simple and fast calculation method, while it lacks of continuous effects like wind-generated swell or bottom friction. The Delft3D software on the other hand provides a more complete representation, not only of wave but also current dynamics, while it requires a much broader amount of input parameters and more complex boundary conditions. Within this study, the advantages and disadvantages of both models could be demonstrated, whereas for the final calculation of nearshore wave characteristics, only SwanOne was applicable based on the input parameters extracted from statistical analysis of long term ERA5 data.
Abstract A record-breaking rainfall event occurred in northeastern Vietnam in late July–early August 2015. The coastal region in Quang Ninh Province was hit severely, with station rainfall sums in the range of 1000–1500 mm. The heavy rainfall led to flooding and landslides, which resulted in an estimated economic loss of $108 million (U.S. dollars) and 32 fatalities. Using a multitude of data sources and ECMWF ensemble forecasts, the synoptic–dynamic development and practical predictability of the event is investigated in detail for the 4-day period from 1200 UTC 25 July to 1200 UTC 29 July 2015, during which the major portion of the rainfall was observed. A slowly moving upper-level subtropical trough and the associated surface low in the northern Gulf of Tonkin promoted sustained moisture convergence and convection over northeastern Vietnam. The humidity was advected in a moisture transport band lying across the Indochina Peninsula and emanating from a tropical storm over the Bay of Bengal. Analyses of the ECMWF ensemble forecasts clearly showed a sudden emergence of the predictability of the extreme event at lead times of 3 days that was associated with the correct forecasts of the intensity and location of the subtropical trough in the 51 ensemble members. Thus, the Quang Ninh event is a good example in which the predictability of tropical convection arises from large-scale synoptic forcing; in the present case it was due to a tropical–extratropical interaction that has not been documented before for the region and season.
Abstract. Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics and in particular in studying the life cycle of weather systems. The three-dimensional (3-D) structure and temporal evolution of the associated PV anomalies, however, are not yet fully understood. An automated technique to objectively identify 3-D PV anomalies can help to shed light on 3-D atmospheric dynamics in specific case studies, as well as facilitate statistical evaluations within climatological studies. Such a technique to identify PV anomalies fully in 3-D, however, does not yet exist. This study presents a novel algorithm for the objective identification of PV anomalies in gridded data, as commonly output by numerical simulation models. The algorithm is inspired by morphological image processing techniques and can be applied to both two-dimensional (2-D) and 3-D fields on vertically isentropic levels. The method maps input data to a horizontally stereographic projection and relies on an efficient computation of horizontal distances within the projected field. Candidates for PV anomaly features are filtered according to heuristic criteria, and feature description vectors are obtained for further analysis. The generated feature descriptions are well suited for subsequent case studies of 3-D atmospheric dynamics as represented by the underlying numerical simulation, or for generation of climatologies of feature characteristics. We evaluate our approach by comparison with an existing 2-D technique, and demonstrate the full 3-D perspective by means of a case study of an extreme precipitation event that was dynamically linked to a prominent subtropical PV anomaly. The case study demonstrates variations in the 3-D structure of the detected PV anomalies that would not have been captured by a 2-D method. We discuss further advantages of using a 3-D approach, including elimination of temporal inconsistencies in the detected features due to 3-D structural variation, and elimination of the need to manually select a specific isentropic level on which the anomalies are assumed to be best captured. The method is made available as open-source for straightforward use by the atmospheric community.
Abstract. Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics and in particular in studying the life cycle of weather systems. The three-dimensional (3-D) structure and temporal evolution of the associated PV features, however, are not yet fully understood. An automated technique to objectively identify 3-D PV features can help to shed light on 3-D atmospheric dynamics in specific case studies as well as facilitate statistical evaluations within climatological studies. Such a technique to identify PV features fully in 3-D, however, does not yet exist. This study presents a novel algorithm for the objective identification of PV anomalies along the dynamical tropopause in gridded data, as commonly output by numerical simulation models. The algorithm is inspired by morphological image processing techniques and can be applied to both two-dimensional (2-D) and 3-D fields on vertically isentropic levels. The method maps input data to a horizontally stereographic projection and relies on an efficient computation of horizontal distances within the projected field. Candidates for PV anomaly features are filtered according to heuristic criteria, and feature description vectors are obtained for further analysis. The generated feature descriptions are well suited for subsequent case studies of 3-D atmospheric dynamics as represented by the underlying numerical simulation. We evaluate our approach by comparison with an existing 2-D technique and demonstrate the full 3-D perspective by means of a case study of an extreme precipitation event that was dynamically linked to a prominent subtropical PV anomaly. The case study demonstrates variations in the 3-D structure of the detected PV anomalies that would not have been captured by a 2-D method. We discuss further advantages of using a 3-D approach, including elimination of temporal inconsistencies in the detected features due to 3-D structural variation and elimination of the need to manually select a specific isentropic level on which the anomalies are assumed to be best captured. These advantages, as well as the suitability of the implementation to process big data sets, also open applications for climatological analyses. The method is made available as open-source for straightforward use by the atmospheric community.
Abstract The seasonal cycle of rainfall over the Greater Horn of Africa (GHA) is dominated by the latitudinal migration and activity of the tropical rain belt (TRB). The TRB exhibits high interannual variability in the GHA and the reasons for the recent dry period in the Long Rains (March–May) are poorly understood. In addition, few studies have addressed the rainfall fluctuations during the Msimu Rains (Dec.–Mar.) in the southern GHA region. Interannual variations of the seasonal cycle of the TRB between 1981 and 2018 were analysed using two statistical indices. The Rainfall Cluster Index (RCI) describes the seasonal cycle as a succession of six characteristic rainfall patterns, while the Seasonal Location Index (SLI) captures the latitudinal location of the TRB. The SLI and RCI depict the full seasonal cycle of the TRB supporting interpretations of the interannual variations and trends. The Msimu Rains are dominated by two clusters with opposite rainfall characteristics between the Congo Basin and Tanzania. The associated anomalies in moisture flux and divergence indicate variations in the location of the TRB originating from an interplay between low‐level air flows from the Atlantic and Indian Oceans and tropical and subtropical teleconnections. The peak period of the Long Rains shows a complex composition of five clusters, which is tightly connected to intraseasonal and interannual variability of latitudinal locations of the TRB. A persistent location of the TRB near the equator, evidenced in a frequent occurrence of a cluster related to an anomalously weak Walker circulation, is associated with wet conditions over East Africa. Dry Long Rains are associated with strong and frequent latitudinal variations of the TRB position with a late onset and intermittent rainfall. These results offer new opportunities to understand recent variability and trends in the GHA region.
Supplementary Materials (SM) SM1: a) Input parameter features ind SwanOne, b) The bathymetry profile and respective location of the wave sensors.Example from transect 2.
This article illustrates the impact of potential future climate scenarios on water quantity in time and space for an East African floodplain catchment surrounded by mountainous areas. In East Africa, agricultural intensification is shifting from upland cultivation into the wetlands due to year-round water availability and fertile soils. These advantageous agricultural conditions might be hampered through climate change impacts. Additionally, water-related risks, like droughts and flooding events, are likely to increase. Hence, this study investigates future climate patterns and their impact on water resources in one production cluster in Tanzania. To account for these changes, a regional climate model ensemble of the Coordinated Regional Downscaling Experiment (CORDEX) Africa project was analyzed to investigate changes in climatic patterns until 2060, according to the RCP4.5 (representative concentration pathways) and RCP8.5 scenarios. The semi-distributed Soil and Water Assessment Tool (SWAT) was utilized to analyze the impacts on water resources according to all scenarios. Modeling results indicate increasing temperatures, especially in the hot dry season, intensifying the distinctive features of the dry and rainy season. This consequently aggravates hydrological extremes, such as more-pronounced flooding and decreasing low flows. Overall, annual averages of water yield and surface runoff increase up to 61.6% and 67.8%, respectively, within the bias-corrected scenario simulations, compared to the historical simulations. However, changes in precipitation among the analyzed scenarios vary between −8.3% and +22.5% of the annual averages. Hydrological modeling results also show heterogeneous spatial patterns inside the catchment. These spatio-temporal patterns indicate the possibility of an aggravation for severe floods in wet seasons, as well as an increasing drought risk in dry seasons across the scenario simulations. Apart from that, the discharge peak, which is crucial for the flood recession agriculture in the floodplain, is likely to shift from April to May from the 2020s onwards.
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