Towards a Link between Climate Extremes and Thermodynamic Patterns in the City of Rio de Janeiro-Brazil: Climatological Aspects and Identified Changes

Modification signs in extreme weather events may be directly related to alterations in the thermodynamic panorama of the atmosphere that need to be better understood. This study aimed to make a first interconnection between climate extremes and thermodynamic patterns in the city of Rio de Janeiro. Maximum and minimum air temperature and precipitation extreme indices from two surface meteorological stations (ABOV and STCZ) and instability indices based on temperature and humidity from radiosonde observations (SBGL) were employed to investigate changes in the periods 1964-1980 (P1), 1981-2000 (P2), and 2001-2020 (P3). Statistical tests were adopted to determine the significance and magnitude of trends. The frequency of warm (cold) days and warm (cold) nights are increasing (decreasing) in the city. Cold (Warm) extremes are changing with greater magnitude in ABOV (STCZ) than in STCZ (ABOV). In ABOV, there is a significant increase of +84 mm/decade in the rainfall volume associated with severe precipitation (above the 95th percentile) and most extreme precipitation indices show an increase in frequency and intensity. In STCZ, there is a decrease in extreme precipitation until the 1990s, and from there, an increase, showing a wetter climate in the most recent years. It is also verified in SBGL that there is a statistically significant increase (decrease) in air temperature of +0.1°C/decade (-0.2°C/decade) and relative humidity of +1.2%/decade (-3%/decade) at the low and middle (high) troposphere. There is a visible rising trend in most of the evaluated instability indices over the last few decades. The increasing trends of some extreme precipitation indices are probably allied to the precipitable water increasing trend of +1.2 mm/decade.

HadISDH.extremes Part Ⅰ:A Gridded Wet Bulb Temperature Extremes Index Product for Climate Monitoring

HadISDH.extremes is an annually updated global gridded monthly monitoring product of wet and dry bulb temperature–based extremes indices,from January 1973 to December 2022.Data quality,including spatial and temporal stability,is a key focus.The hourly data are quality controlled.Homogeneity is assessed on monthly means and used to score each gridbox according to its homogeneity rather than to apply adjustments.This enables user-specific screening for temporal stability and avoids errors from inferring adjustments from monthly means for the daily maximum values.For general use,a score(HQ Flag)of 0 to 6 is recommended.A range of indices are presented,aligning with existing standardised indices.Uniquely,provision of both wet and dry bulb indices allows exploration of heat event character—whether it is a“humid and hot”,“dry and hot”or“humid and warm”event.It is designed for analysis of long-term trends in regional features.HadISDH.extremes can be used to study local events,but given the greater vulnerability to errors of maximum compared to mean values,cross-validation with independent information is advised.

HadISDH.extremes Part Ⅱ:Exploring Humid Heat Extremes Using Wet Bulb Temperature Indices

Heat events may be humid or dry.While several indices incorporate humidity,such combined indices obscure identification and exploration of heat events by their different humidity characteristics.The new HadISDH.extremes global gridded monitoring product uniquely provides a range of wet and dry bulb temperature extremes indices.Analysis of this new data product demonstrates its value as a tool for quantifying exposure to humid verses dry heat events.It also enables exploration into“stealth heat events”,where humidity is high,perhaps enough to affect productivity and health,while temperature remains moderate.Such events may not typically be identified as“heat events”by temperature-focused heat indices.Over 1973-2022,the peak magnitude of humid extremes(maximum daily wet bulb temperature over a month;T_(w)X)for the global annual mean increased significantly at 0.13±0.04℃(10 yr)^(−1),which is slightly slower than the global annual mean T_(w) increase of 0.22±0.04℃(10 yr)^(−1).The frequency of moderate humid extreme events per year(90th per-centile daily maxima wet bulb temperature exceedance;T_(w)X90p)also increased significantly at 4.61±1.07 d yr^(−1)(10 yr)^(−1).These rates were slower than for temperature extremes,TX and TX90p,which respectively increased significantly at 0.27±0.04℃(10 yr)^(−1) and 5.53±0.72 d yr^(−1)(10 yr)^(−1).Similarly,for the UK/Europe focus region,JJA-mean T_(w)X increased significantly,again at a slower rate than for TX and mean T_(w).HadISDH.extremes shows some evidence of“stealth heat events”occurring where humidity is high but temperature remains more moderate.

Projection of precipitation extremes over South Asia from CMIP6 GCMs

Extreme precipitation events are one of the most dangerous hydrometeorological disasters,often resulting in significant human and socio-economic losses worldwide.It is therefore important to use current global climate models to project future changes in precipitation extremes.The present study aims to assess the future changes in precipitation extremes over South Asia from the Coupled Model Intercomparison Project Phase 6(CMIP6)Global Climate Models(GCMs).The results were derived using the modified Mann-Kendall test,Sen's slope estimator,student's t-test,and probability density function approach.Eight extreme precipitation indices were assessed,including wet days(RR1mm),heavy precipitation days(RR10mm),very heavy precipitation days(RR20mm),severe precipitation days(RR50mm),consecutive wet days(CWD),consecutive dry days(CDD),maximum 5-day precipitation amount(RX5day),and simple daily intensity index(SDII).The future changes were estimated in two time periods for the 21^(st) century(i.e.,near future(NF;2021-2060)and far future(FF;2061-2100))under two Shared Socioeconomic Pathway(SSP)scenarios(SSP2-4.5 and SSP5-8.5).The results suggest increases in the frequency and intensity of extreme precipitation indices under the SSP5-8.5 scenario towards the end of the 21^(st) century(2061-2100).Moreover,from the results of multimodel ensemble means(MMEMs),extreme precipitation indices of RR1mm,RR10mm,RR20mm,CWD,and SDII demonstrate remarkable increases in the FF period under the SSP5-8.5 scenario.The spatial distribution of extreme precipitation indices shows intensification over the eastern part of South Asia compared to the western part.The probability density function of extreme precipitation indices suggests a frequent(intense)occurrence of precipitation extremes in the FF period under the SSP5-8.5 scenario,with values up to 35.00 d for RR1mm and 25.00-35.00 d for CWD.The potential impacts of heavy precipitation can pose serious challenges to the study area regarding flooding,soil erosion,water resource management,food security,and agriculture development.

Erratum to: A Two-plume Convective Model forPrecipitation Extremes

Erratum to:Yin,Z.H.,P.X.Dai,and J.Nie,2021:A two-plume convective model for precipitation extremes.Adv.Atmos.Sci.,38(6),957−965,https://doi.org/10.1007/s00376-021-0404-8.

Corrigendum to:“Spectrum-tailored random fiber laser towards ICF laser facility”[Matter and Radiation at Extremes 8,025902(2023)]

The third paragraph in Sec.IV REGENERATIVE AMPLIFICATION erroneously states“In other words,the distribution of spectral components is time-dependent,and the spectral distortion in the amplification process will not change the time-domain shape.”

Evaluation of IMERG, TMPA, ERA5, and CPC precipitation products over China's Mainland: Spatiotemporal patterns and extremes

A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA)),reanalysis-based(fifth generation of atmospheric reanalysis by the European Centre for Medium Range Weather Forecasts(ERA5)),and gauge-estimated(Climate Prediction Center(CPC))precipitation products was conducted using the data from 807 meteorological stations across China's Mainland from 2001 to 2017.Error statistical metrics,precipitation distribution functions,and extreme precipitation indices were used to evaluate the quality of the four precipitation products in terms of multi-timescale accuracy and extreme precipitation estimation.When the timescale increased from daily to seasonal scales,the accuracy of the four precipitation products first increased and then decreased,and all products performed best on the monthly timescale.Their accuracy ranking in descending order was CPC,IMERG,TMPA,and ERA5 on the daily timescale and IMERG,CPC,TMPA,and ERA5 on the monthly and seasonal timescales.IMERG was generally superior to its predecessor TMPA on the three timescales.ERA5 exhibited large statistical errors.CPC provided stable estimated values.For extreme precipitation estimation,the quality of IMERG was relatively consistent with that of TMPA in terms of precipitation distribution and extreme metrics,and IMERG exhibited a significant advantage in estimating moderate and heavy precipitation.In contrast,ERA5 and CPC exhibited poor performance with large systematic underestimation biases.The findings of this study provide insight into the performance of the latest IMERG product compared with the widely used TMPA,ERA5,and CPC datasets,and points to possible directions for improvement of multi-source precipitation data fusion algorithms in order to better serve hydrological applications.

Does CMIP6 Inspire More Confidence in Simulating Climate Extremes over China?

Based on climate extreme indices calculated from a high-resolution daily observational dataset in China during 1961–2005,the performance of 12 climate models from phase 6 of the Coupled Model Intercomparison Project(CMIP6),and 30 models from phase 5 of CMIP(CMIP5),are assessed in terms of spatial distribution and interannual variability.The CMIP6 multi-model ensemble mean(CMIP6-MME)can simulate well the spatial pattern of annual mean temperature,maximum daily maximum temperature,and minimum daily minimum temperature.However,CMIP6-MME has difficulties in reproducing cold nights and warm days,and has large cold biases over the Tibetan Plateau.Its performance in simulating extreme precipitation indices is generally lower than in simulating temperature indices.Compared to CMIP5,CMIP6 models show improvements in the simulation of climate indices over China.This is particularly true for precipitation indices for both the climatological pattern and the interannual variation,except for the consecutive dry days.The arealmean bias for total precipitation has been reduced from 127%(CMIP5-MME)to 79%(CMIP6-MME).The most striking feature is that the dry biases in southern China,very persistent and general in CMIP5-MME,are largely reduced in CMIP6-MME.Stronger ascent together with more abundant moisture can explain this reduction in dry biases.Wet biases for total precipitation,heavy precipitation,and precipitation intensity in the eastern Tibetan Plateau are still present in CMIP6-MME,but smaller,compared to CMIP5-MME.

2021:A Year of Unprecedented Climate Extremes in Eastern Asia,North America,and Europe

The year 2021 was recorded as the 6th warmest since 1880.In addition to large-scale warming,2021 will be remembered for its unprecedented climate extremes.Here,a review of selected high-impact climate extremes in 2021,with a focus on China,along with an extension to extreme events in North America and Europe is presented.Nine extreme events that occurred in 2021 in China are highlighted,including a rapid transition from cold to warm extremes and sandstorms in spring,consecutive drought in South China and severe thunderstorms in eastern China in the first half of the year,extremely heavy rainfall over Henan Province and Hubei Province during summer,as well as heatwaves,persistent heavy rainfall,and a cold surge during fall.Potential links of extremes in China to four global-scale climate extremes and the underlying physical mechanisms are discussed here,providing insights to understand climate extremes from a global perspective.This serves as a reference for climate event attribution,process understanding,and high-resolution modeling of extreme events.

SIMULATING THE RESPONSE OF NON-UNIFORMITY OF PRECIPITATION EXTREMES OVER CHINA TO CO_2 INCREASING BY MIROC_HIRES MODEL

The response of non-uniformity of precipitation extremes over China to doubled CO2has been analyzed using the daily precipitation simulated by a coupled general circulation model,MIROC_Hires.The major conclusions are as follows:under the CO2increasing scenario(SRES A1B),the climatological precipitation extremes are concentrated over the southern China,while they are uniformly distributed over the northern China.For interannual variability,the concentration of precipitation extremes is small over the southern China,but it is opposite over the northern China.The warming effects on the horizontal and vertical scales are different over the northern and southern part of China.Furthermore,the atmospheric stability is also different between the two parts of China.The heterogeneous warming is one of the possible reasons for the changes in non-uniformity of precipitation extremes over China.

Future Precipitation Extremes in China under Climate Change and Their Physical Quantification Based on a Regional Climate Model and CMIP5 Model Simulations

The atmospheric water holding capacity will increase with temperature according to Clausius-Clapeyron scaling and affects precipitation.The rates of change in future precipitation extremes are quantified with changes in surface air temperature.Precipitation extremes in China are determined for the 21st century in six simulations using a regional climate model,RegCM4,and 17 global climate models that participated in CMIP5.First,we assess the performance of the CMIP5 models and RCM runs in their simulation of extreme precipitation for the current period(RF:1982-2001).The CMIP5 models and RCM results can capture the spatial variations of precipitation extremes,as well as those based on observations:OBS and XPP.Precipitation extremes over four subregions in China are predicted to increase in the mid-future(MF:2039-58)and far-future(FF:2079-98)relative to those for the RF period based on both the CMIP5 ensemble mean and RCM ensemble mean.The secular trends in the extremes of the CMIP5 models are predicted to increase from 2008 to 2058,and the RCM results show higher interannual variability relative to that of the CMIP5 models.Then,we quantify the increasing rates of change in precipitation extremes in the MF and FF periods in the subregions of China with the changes in surface air temperature.Finally,based on the water vapor equation,changes in precipitation extremes in China for the MF and FF periods are found to correlate positively with changes in the atmospheric vertical wind multiplied by changes in surface specific humidity(significant at the p<0.1 level).

Asymmetry in the Arctic Oscillation Teleconnection with January Cold Extremes in Northeast China

The connection of the Arctic Oscillation(AO)with the frequency of temperature extremes over East Asia during boreal winter has been documented by many studies.This study describes an asymmetry in the relationship between the January AO and the simultaneous cold extremes in Northeast China(NEC),and further reveals a breakdown of this relationship.It is demonstrated that the frequency of January cold extremes in NEC shows significant(insignificant)negative correlation with the simultaneous negative(positive)phase of the AO.One possible explanation for such an asymmetry is that the Arctic center of negative AO extends more southwards to Siberia compared with that of positive AO,conducive to a closer connection with the frequency of an extreme Siberian high.As a result,the frequency of January cold extremes in NEC shows a more significant relationship with the negative AO.The other related explanation is that,concurrent with the negative phase of the AO,there is an evident meridional stationary planetary wave in the upper troposphere around(30°N,100–300 hP a),which disappears in the positive AO.Therefore,the negative AO could better reflect the fluctuation of the subtropical westerly wind and the synoptic-scale transient wave activity,which is closely related to the frequency of cold extremes in NEC.Along with a positive polarity of the AO trend since the mid-1980s,the connection between the cold extremes over NEC and the AO during January has been weakened.

Dynamic Variability in Daily Temperature Extremes and Their Relationships with Large-scale Atmospheric Circulation During 1960–2015 in Xinjiang, China

Climate changes are likely to increase the risk of numerous extreme weather events throughout the world.The objectives of this study were to investigate and analyze the temporal-spatial variability patterns of temperature extremes based on daily maximum(TX)and minimum temperature(TN)data collected from 49 meteorological stations in Xinjiang of China during 1960–2015.These temperature data were also used to assess the impacts of altitude on the temperature extremes.Additionally,possible teleconnections with the large-scale circulation pattern(the El Nino-Southern Oscillation,ENSO and Arctic Oscillation,AO)were investigated.Results showed that all percentile indices had trends consistent with warming in most parts of Xinjiang during 1960–2015,but the warming was more pronounced for indices derived from TN compared to those from TX.The minimum TN and maximum TX increased at rates of 0.16℃/10 yr and 0.59℃/10 yr,respectively during 1960–2015.Accordingly,the diurnal temperature range showed a significant decreasing trend of–0.23℃/10 yr for the whole study area.The frequency of the annual average of the warm events showed significant increasing trends while that of the cold events presented decreasing trends.Over the same period,the number of frost days showed a statistically significant decreasing trend of–3.37 d/10 yr.The number of the summer days and the growing season showed significant increasing trends at rates of 1.96 and 2.74 d/10 yr,respectively.The abrupt change year of each index was from the 1980 s to the 1990 s,showing that this periodic interval was a transitional phase between cold and warm climate change.Significant correlations of temperature extremes and elevation included the trends of tropical nights,growing season frequency,and cold spell duration indicator.This result also indicated the clear and complex local influence on climatic extremes.In addition,the relationship between each index of the temperature extremes with large-scale atmospheric circulation(ENSO and AO)demonstrated that the influence of ENSO on each index of the temperature extremes was greater than that of the AO in Xinjiang.

Spatial-temporal Analysis and Prediction of Precipitation Extremes: A Case Study in the Weihe River Basin, China

Extreme precipitation events bring considerable risks to the natural ecosystem and human life.Investigating the spatial-temporal characteristics of extreme precipitation and predicting it quantitatively are critical for the flood prevention and water resources planning and management.In this study,daily precipitation data(1957–2019)were collected from 24 meteorological stations in the Weihe River Basin(WRB),Northwest China and its surrounding areas.We first analyzed the spatial-temporal change of precipitation extremes in the WRB based on space-time cube(STC),and then predicted precipitation extremes using long short-term memory(LSTM)network,auto-regressive integrated moving average(ARIMA),and hybrid ensemble empirical mode decomposition(EEMD)-LSTM-ARIMA models.The precipitation extremes increased as the spatial variation from northwest to southeast of the WRB.There were two clusters for each extreme precipitation index,which were distributed in the northwestern and southeastern or northern and southern of the WRB.The precipitation extremes in the WRB present a strong clustering pattern.Spatially,the pattern of only high-high cluster and only low-low cluster were primarily located in lower reaches and upper reaches of the WRB,respectively.Hot spots(25.00%–50.00%)were more than cold spots(4.17%–25.00%)in the WRB.Cold spots were mainly concentrated in the northwestern part,while hot spots were mostly located in the eastern and southern parts.For different extreme precipitation indices,the performances of the different models were different.The accuracy ranking was EEMD-LSTM-ARIMA>LSTM>ARIMA in predicting simple daily intensity index(SDII)and consecutive wet days(CWD),while the accuracy ranking was LSTM>EEMD-LSTM-ARIMA>ARIMA in predicting very wet days(R95 P).The hybrid EEMD-LSTM-ARIMA model proposed was generally superior to single models in the prediction of precipitation extremes.

A Two-plume Convective Model for Precipitation Extremes

In the study of diagnosing climate simulations and understanding the dynamics of precipitation extremes,it is an essential step to adopt a simple model to relate water vapor condensation and precipitation,which occur at cloudmicrophysical and convective scales,to large-scale variables.Several simple models have been proposed;however,improvement is still needed in both their accuracy and/or the physical basis.Here,we propose a two-plume convective model that takes into account the subgrid inhomogeneity of precipitation extremes.The convective model has three components,i.e.,cloud condensation,rain evaporation,and environmental descent,and is built upon the zero-buoyancy approximation and guidance from the high-resolution reanalysis.Evaluated against the CMIP5 climate simulations,the convective model shows large improvements in reproducing precipitation extremes compared to previously proposed models.Thus,the two-plume convective model better captures the main physical processes and serves as a useful diagnostic tool for precipitation extremes.

Timing the market: the economic value of price extremes

By decomposing asset returns into potential maximum gain(PMG)and potential maximum loss(PML)with price extremes,this study empirically investigated the relationships between PMG and PML.We found significant asymmetry between PMG and PML.PML significantly contributed to forecasting PMG but not vice versa.We further explored the power of this asymmetry for predicting asset returns and found it could significantly improve asset return predictability in both in-sample and out-of-sample forecasting.Investors who incorporate this asymmetry into their investment decisions can get substantial utility gains.This asymmetry remains significant even when controlling for macroeconomic variables,technical indicators,market sentiment,and skewness.Moreover,this asymmetry was found to be quite general across different countries.

Corresponding Relation between Warm Season Precipitation Extremes and Surface Air Temperature in South China

Hourly data of 42 rain gauges over South China during 1966–2005 were used to analyze the corresponding relation between precipitation extremes and surface air temperature in the warm season(May to October).The results show that below 25℃,both daily and hourly precipitation extremes in South China increase with rising temperature.More extreme events transit to the two-time Clausius-Clapeyron(CC)relationship at lower temperatures.Daily as well as hourly precipitation extremes have a decreasing tendency nearly above 25℃,among which the decrease of hourly extremes is much more significant.In order to investigate the efects of rainfall durations,hourly precipitation extremes are presented by short duration and long duration precipitation,respectively.Results show that the dramatic decrease of hourly rainfall intensities above 25℃ is mainly caused by short duration precipitation,and long duration precipitation extremes rarely occur in South China when surface air temperature surpasses 28℃.

Log-logistic parameters estimation using moving extremes ranked set sampling design

In statistical parameter estimation problems,how well the parameters are estimated largely depends on the sampling design used.In the current paper,a modification of ranked set sampling(RSS)called moving extremes RSS(MERSS)is considered for the estimation of the scale and shape parameters for the log-logistic distribution.Several traditional estimators and ad hoc estimators will be studied under MERSS.The estimators under MERSS are compared to the corresponding ones under SRS.The simulation results show that the estimators under MERSS are significantly more efficient than the ones under SRS.

Recent Extremes of Drought and Flooding in Amazonia: Vulnerabilities and Human Adaptation

The present study focuses on the impacts of extreme drought and flooding situations in Amazonia, using level/discharge data from some rivers in the Amazon region as indicators of impacts. The last 10 years have featured various “once in a century” droughts and floods in the Amazon basin, which have affected human and natural systems in the region. We assess a history of such hazards based on river data, and discuss some of the observed impacts in terms of vulnerability of human and natural systems, as well as some of adaptation strategies implemented by regional and local governments to cope with them. A critical perspective of mitigation of drought and flood policies in Amazonia suggests that they have been mostly ineffective in reducing vulnerability for the majority of the population, constituting, perhaps, examples of maladaptation via the undermining of resilience.

Permian–Triassic Climatic and Environmental Extremes and Biotic Response (IGCP 630:2014–2018):Goals and Achievements

IGCP 630,with its full title of"Permian-Triassic(P-Tr)climatic and environmental extremes and biotic response",is an International Geoscience Program project sponsored by the United Nation Educational,Scientific&Cultural Organization(UNESCO)and International Union of Geological Sciences(IUGS).This project was approved in 2014 and ended in 2018,and has applied for one-year extension in 2019.IGCP 630 consists of 150 geoscientists across multidisciplinary geosciences from 27 countries around the world.