International Journal of Climatology最新文献

Urbanization alters local climates and exacerbates urban heat islands. Understanding and addressing the impacts of urbanization on regional high impact weather systems is critical. This study examines the feedback loop between urbanization and heatwaves (HWs) in inland and coastal Indian cities of Hyderabad and Bhubaneswar which have been profoundly affected by urbanization and temperature extremes. Observational analysis reveals that during the pre-monsoon season, daytime and nighttime air temperature anomalies, and the frequency of 90th percentile days, have increased by ~0.35°C and ~3 days for Hyderabad, and by ~0.2°C, and ~6 days for Bhubaneswar in the last two decades (2001–2020) relative to the previous decades (1981–2000). Analysis of  land-use land-cover (LULC) datasets shows a dramatic urban expansion by ~13 and ~11 times in Hyderabad and Bhubaneswar, respectively, between 1993 and 2019. Numerical experiments with the Weather Research and Forecasting model were undertaken considering hectometer spatial resolution (~500 m) and a lower boundary conditions representing the 1993 and 2019 LULC. The impact of urbanization on temperature changes and HWs in particular were analyzed. The HW simulations indicate that urbanization significantly enhances air and surface temperatures by ~4–6°C, particularly during nighttime rather than daytime. Urbanization effects are discerned in surface temperatures at night by 1–2°C relative to  air temperatures. Unlike nighttime, urbanization showed a negative or little influence on air and surface temperatures during the daytime. In contrast to surface and air temperatures, increased urbanization runs indicated enhanced regional soil temperature by ~5°C more during the daytime than at nighttime. The rise in nighttime air and surface temperatures is due to an increase in surface sensible heat fluxes by ~40–50 W/m² in urban areas. The influence of urbanization on nighttime temperatures emphasizes the necessity for cool housing and engineering recommendations in urbanized regions of India.

Studies related to monitoring changes in frequency, intensity and duration of precipitation extremes are key to creating efficient climate change measures and forest conservation policies. This study describes new insights into rainfall precipitation extremes over the Amazon basin (AB) during the last four decades (1981–2021) from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPSv2). Here we analysed the trends of daily extreme precipitation indices proposed by the Expert Team on Climate Change Detection and Indices (ETCCDI) at the seasonal scale, using the trend-empirical orthogonal function (TEOF). Our results indicate that the frequency of precipitation extremes increased over Peruvian Amazonia and northeastern Brazilian Amazonia, and reduced in the centre of AB, mainly during the first seasons of the year: December–January–February (DJF) and March–April–May (MAM). The cooling trend over the eastern and central tropical Pacific and the warming trend over the tropical and western subtropical Pacific could associate with the increase in frequency of precipitation extremes in DJF. Furthermore, during June–July–August (JJA) and September–October–November (SON), rainfall intensity indices showed a decrease in Colombia and the Bolivian Amazon; in contrast, northern and southern Peru delivered an increased pattern. The trend pattern in the JJA and SON seasons could be associated with a warming trend over most of the North Atlantic and a cooling in the 40°–60° S band. Our results demonstrate that the precipitation extremes over the AB have spatially varying trends. These heterogeneous trends over the space might be take into account for robust adaptation policies over the countries that are parts of the AB, such as Bolivia, Brazil, Colombia, Ecuador, Guyana, Perú, Surinam and Venezuela.

A WRF-based high-resolution reanalysis of the Irish climate (1981–2010) is used to create proxy daily precipitation observations at the locations of climatological sites used for precipitation monitoring; the data are statistically representative of the real precipitation climate both for mean (over monthly, seasonal and annual periods) and extreme values. The proxy observations are spatially interpolated to the original WRF grid using a typical gridding package and compared against the original data to assess gridding errors. The errors are more complex than the estimates provided by the gridding software; systematic biases are evident which by the inclusion of strategically placed additional observing sites are shown to be greatly reduced. There is also evidence of systematic differences in trend analyses of extreme precipitation over the period. The method provides independent estimates of the errors that arise from actual gridding applications. It also facilitates the testing of the optimality of a network by highlighting possible inadequacies in an existing station layout and suggesting new observing site locations to fill gaps. Uncertainties regarding the errors in real precipitation observations, and possible spurious impacts linked to temporal changes in the real observing network, are avoided by this method.

This report provides a summary of the UK's weather and climate through the calendar year 2023, alongside the historical context for a number of essential climate variables. This is the tenth in a series of annual ‘State of the UK Climate’ publications, published in the International Journal of Climatology (IJC) since 2017, and an update to the 2022 report (Kendon et al., 2023). It provides an accessible, authoritative and up-to-date assessment of UK climate trends, variations and extremes based on the most up to date observational datasets of climate quality.

The Jenkinson-Collison Weather Typing (JC-WT) method uses sea-level pressure gradients to create 27 types based on the geostrophic flow and vorticity around any extratropical target location. Typically, JC-WTs are applied over specific locations or limited domains, thus hampering the understanding of the impact of large-scale mechanisms on regional climate. This study explores the links between regional climate variability, as represented by the JC-WTs, and large-scale phenomena, to describe the synoptic-scale variability in the North Atlantic-European region and evaluate the JC-WT methodology. Large-scale circulation is here characterized by major atmospheric low-frequency modes, namely the North Atlantic Oscillation, the East Atlantic and the Scandinavian teleconnection indices, and by atmospheric blockings. Results show that JC-WTs coherently capture the spatial and temporal variability of the large-scale modes and yields a characteristic response to blocking events. Overall, our results underpin the exploratory potential of this method for the analysis of the near-surface circulation. These findings endorse the use of JC-WTs and support the reliability and utility of the JC-WT classification for process-based model assessments and model selection, a crucial task for climate impact studies.

In midsummer 2023, a record-breaking extreme heatwave hit North China, causing significant impacts on people's daily lives and production. This study comprehensively analysed the unique features of this extreme event based on five indices describing the intensity, frequency and impact range. The results show that four of these indices broke the historical record in 2023, and the spatial extent (T_max >40°C) is the second highest in history. The number of hot days with T_max >40°C (T_max >35°C) even reached 23 times (4.2 times) the normal. The combined results of these five indices undoubtedly indicate that this heatwave event is featured by high intensity, long duration, numerous extremely hot days and wide impact range. Furthermore, physical mechanism study revealed that the abnormally warm high-pressure system persisted in dominating North China, resulting in descending airflow and temperature increases. The enhanced and unprecedented westward extending Western North Pacific Subtropical High, the enhanced and eastward extending Iran Subtropical High and the abnormal high-pressure over southwestern China form an east–west connected anomalous high-pressure zone, blocking the water vapour transport from lower latitude oceans to North China. Noticeably, North China has experienced a reduction in precipitation since about 2 months preceding this extreme heatwave, leading to severe soil moisture deficiency and reduced evaporation. Consequently, it increased surface sensible heat flux that led to a rise in temperature. This local land-atmosphere positive feedback mechanism plays a crucial role in the intensification and maintenance of this extreme heatwave event.

ERA5 reanalysis data, precipitation data from China, and National Oceanic and Atmospheric Administration (NOAA) monthly sea surface temperature (SST) data are used to analyse the impact of the meridional position of the East Asian subtropical jet (EASJ) on summer precipitation in China and its correlation with Atlantic SST. The results indicate that when the EASJ significantly shifts northward, the western North Pacific subtropical high (WNPSH) weakens with an eastward displacement. Upper-level convergence and moisture divergence, corresponding to descending motion, lead to decreased precipitation in the Yangtze River Valley (YRV). Meanwhile, upper-level divergence occurs over South China (SC), the Hexi Corridor (HC), and Northeast China (NEC), where moisture converges and ascends, favouring an increase in precipitation. Conversely, when the EASJ undergoes a significant southward shift, the WNPSH strengthens and expands westward. Opposing atmospheric circulation patterns in these four regions result in reversed precipitation anomalies compared with those observed when the jet shifts northward. The meridional position of the EASJ is closely related to the summer subtropical Atlantic SST. The positive (negative) SST anomaly (SSTA) over the subtropical Atlantic induces negative (positive) geopotential height anomaly in the upper troposphere over the North Atlantic by modulating the atmospheric meridional circulation. Geopotential height anomalies trigger eastward-propagating Rossby waves, generating anomalous cyclones and anticyclones over East Asia. These anomalous cyclones and anticyclones lead to zonal wind anomalies, which alter the strength of the westerlies on both sides of the climatological jet axis, thereby changing the jet's meridional position. Additionally, the difference in the propagation direction of wave activity flux between positive and negative SSTA alters the distribution of wave energy convergence and divergence in the EASJ region, further affecting the intensity of the average westerly winds on both sides of the climatological jet axis, ultimately producing the changes in the meridional position of the EASJ.

One of the frequently used drought metrics in scientific research is the consecutive dry days (CDDs) because it effectively indicates short-term droughts important to ecosystems and agriculture. CDDs are expected to increase in many parts of the world in the future. In Serbia, both the frequency and severity of droughts have increased in recent decades, with most droughts being caused by a lack of precipitation during the warmer months of the year and an increase in evapotranspiration due to higher temperatures. In this study, the frequency and duration of extreme CDDs in the growing season in Serbia were analysed for the past (1950–2019) and the future (2020–2100) period. The Threshold Level Method over precipitation data series was used to analyse CDD events, where extreme CDDs are defined as at least 15 consecutive days without precipitation. In contrast to the original definition of the CDD as the maximum number of consecutive days with precipitation less than 1 mm, here we defined the threshold that is more suitable for agriculture because field crops can experience water stress after 15 days of no rainfall or irrigation. An approach for modelling the stochastic process of extreme CDDs based on the Zelenhasić–Todorović (ZT) method was applied in this research. The ZT method was modified by selecting a different distribution function for modelling the durations of the longest CDD events, enabling a more reliable calculation of probabilities of occurrences. According to the results, future droughts in Serbia are likely to be more frequent and severe than those in the past. The duration of the longest CDDs in a growing season will be extended in the future, lasting up to 62 days with a 10-year return period and up to 94 days with a 100-year return period. Results indicate a worsening of drought conditions, especially in the eastern and northern parts of Serbia. The results can help decision-makers adapt agricultural strategies to climate change by providing information on the expected durations of extreme rainless periods in future growing seasons. Although the analysis was performed in Serbia, it can be applied to any other region.

Three ~12-km reanalysis-driven regional climate models (RCMs) are evaluated in terms of capturing climatologies and extremes of precipitation, temperature and surface wind over Aotearoa/New Zealand (NZ). NZ provides an excellent case study for evaluating high-resolution RCMs due to its coastal and complex terrain and isolated geographical position in the midlatitudes, exposed to both tropical and polar influences. Overall, we find that the RCMs faithfully reproduce the observed climate, with precipitation and temperature climatologies particularly well-captured. However, the RCMs display significant differences from observations in capturing the surface wind climatology, highlighting a remaining key challenge. The excess “drizzle problem” is apparent to varying degrees, leading to a weaker representation in the length of meteorological drought in some regions. The RCMs also diverge in reproducing diurnal temperature range which appears partly related to cloud cover. Finally, we discuss the important role of observational uncertainty in the context of model evaluation.

Southern Africa has been strongly affected by ongoing climate change in recent decades. Rainfall variability is modulated by regional patterns of moisture advection and convergence in the lower troposphere. Using reanalysis, ground and satellite-based rainfall products and observations from 10 weather stations, we perform a synoptic and climatological analysis focussing on atmospheric circulation, moisture transport and their relationship with rainfall anomalies over the Angolan and Namibian Plateau region. Results clearly show that a stronger (weaker) Zambezi low level jet (LLJ) magnitudes are associated with above (below) normal rainfalls over the main Angolan and Namibian plateaus. With lower confidence, a stronger Limpopo LLJ may also lead to enhanced rainfall over Namibia and southeast Angola. The Zambezi LLJ moisture fluxes are moderately controlled by Mozambique Chanel Trough and Angola Low intensities, while the Limpopo LLJ intensities have very low influence from the Mozambique Chanel Trough and Angola Low, respectively. The Angola Low in its tropical phase is associated with deeper moisture convergence and stronger vertical velocities, leading to higher amounts of precipitable water within the air column, thus enhancing precipitation over the region. It is shown that the major moisture source of rainfall, which is advected to via the Zambezi LLJ, is the Indian Ocean. Meanwhile, the Atlantic Ocean plays a minor role. Given the current lack of observations and projected climate change, further research and investments are urgently needed in the region, for example, regarding the expansion of the surface data network.