The warm and extremely dry spring in 2015 in Tasmania contained the fingerprint of human influence on the climate

2019 ◽  
Vol 69 (1) ◽  
pp. 183
Author(s):  
Michael R. Grose ◽  
Mitchell T. Black ◽  
Guomin Wang ◽  
Andrew D. King ◽  
Pandora Hope ◽  
...  
Keyword(s):  
Drought Index ◽  
Human Influence ◽  
Sea Level Pressure ◽  
Positive Indian Ocean Dipole ◽  
Event Attribution ◽  
Warming Pattern ◽  
Dry Conditions ◽  
Recent Trends ◽  
Higher Temperature ◽  
Human Signal

Tasmania saw a warm and very dry spring and summer in 2015–16, including a record dry October, which had significant, wide-ranging impacts. A previous study using two probabilistic event-attribution techniques found a small but statistically significant increase in the likelihood of the record dry October due to anthropogenic influence. Given the human signal was less clear amid natural variability for rainfall compared to temperature extremes, here we provided further evidence and context for this finding. An additional attribution method supported the October rainfall finding, and the median attributable risk to human influence in the three methods was ~25%, 48% and 75%. The results suggested that human influence on rainfall was partly through increased sea level pressure in the mid-latitudes associated with fewer rainbearing systems, a circulation driver that was consistent with recent trends that have been attributed to human influence. Dry conditions were also driven by a positive Indian Ocean Dipole and El Niño at the time, but this study could not reliably estimate the effect of human influence on these phenomena, as each model gave a different estimate of the ocean warming pattern. Along with rainfall, attribution modelling showed a role for human influence in higher temperature and evaporation through October 2015, as well as a high drought index throughout spring. Confidence in the attribution of a human signal on this extreme dry event increased as multiple attribution methods agreed, a plausible atmospheric circulation driver was identified, and temperature and evaporation also showed an anthropogenic signal.

How to combine climate models and observations in event attribution?

2021 ◽  
Author(s):  
Yoann Robin ◽  
Aurélien Ribes
Keyword(s):  
Bayesian Method ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Model Data ◽  
Human Influence ◽  
Scale Parameters ◽  
Event Attribution ◽  
Intercomparison Project ◽  
Climate Model Simulations

<p>We describe a statistical method to derive event attribution diagnoses combining climate model simulations and observations. We fit nonstationary Generalized Extreme Value (GEV) distributions to extremely hot temperatures from an ensemble of Coupled Model Intercomparison Project phase 5 (CMIP)<br>models. In order to select a common statistical model, we discuss which GEV parameters have to be nonstationary and which do not. Our tests suggest that the location and scale parameters of GEV distributions should be considered nonstationary. Then, a multimodel distribution is constructed and constrained by observations using a Bayesian method. This new method is applied to the July 2019 French heatwave. Our results show that<br>both the probability and the intensity of that event have increased significantly in response to human influence.<br>Remarkably, we find that the heat wave considered might not have been possible without climate change. Our<br>results also suggest that combining model data with observations can improve the description of hot temperature<br>distribution.</p>

scholarly journals Analysis of Severe Droughts in Taiwan and its Related Atmospheric and Oceanic Environments

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 159 ◽  
Author(s):  
Chih-wen Hung ◽  
Ming-Fu Shih
Keyword(s):  
South China Sea ◽  
South China ◽  
Large Scale ◽  
Drought Index ◽  
The South China Sea ◽  
Severe Drought ◽  
The South ◽  
China Sea ◽  
Dry Conditions ◽  
Oceanic Environments

Drought is one of the important issues in climate studies. A drought index, Taiwan Meteorological Drought index (TMD index), was previously proposed and is applied here to identify historical severe droughts in Taiwan in order to clarify the corresponding large-scale backgrounds as a potential alert to the society in future. Through the TMD index, several historical severe drought cases in Taiwan are detected and characterized by significant seasonal variability in the annual cycle. Composites for large-scale atmospheric and oceanic environments over different periods within the dry season are conducted. From October to December, the colder sea surface temperature (SST) pattern of Pacific Meridional Mode (PMM) and the PMM-induced local anomalous anticyclones over the South China Sea are both in charge of the extremely dry conditions in Taiwan. From January to February, cold SST in the South China Sea and its adjacent oceans dominates local atmospheric conditions above these regions and creates an unfavorable environment for convection systems. From March to May, a massive anomalous anticyclonic circulation centering beside Alaska and extending its properties to East Asia and Taiwan generates a descending environment and in turn suppresses convection systems to develop. Therefore, the extremely dry conditions under this system are expected.

Detection of human influence on sea-level pressure

Nature ◽  
2003 ◽  
Vol 422 (6929) ◽  
pp. 292-294 ◽  
Author(s):  
Nathan P. Gillett ◽  
Francis W. Zwiers ◽  
Andrew J. Weaver ◽  
Peter A. Stott
Keyword(s):  
Sea Level ◽  
Human Influence ◽  
Sea Level Pressure ◽  
Level Pressure

scholarly journals ANALISIS KEKERINGAN DI KABUPATEN SRAGEN DENGAN METODE PALMER, THORNTHWAITE, DAN STANDARDIZED PRECIPITATION INDEX

2021 ◽  
Vol 17 (2) ◽  
pp. 111-124
Author(s):  
Safrudin Nor Aripbilah ◽  
Heri Suprapto
Keyword(s):  
Drought Index ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Precipitation Index ◽  
Suitable Method ◽  
Drought Severity ◽  
Severe Drought ◽  
Drought Hazard ◽  
Dry Conditions

El Nino and La Nina in Indonesia are one of the reasons that caused climate changes, which has possibility of drought and flood disasters. Sragen Regency wherethe dry season occurs, drought happened meanwhile other areas experience floods and landslides. A study on drought needs to be carried out so as to reduce the risk of losses due to the drought hazard. This study is to determine the drought index in Sragen Regency based on several methods and the correlation of each methods and its suitability to the Southern Oscillation Index (SOI) and rainfall. Drought was analyzed using several methods such as Palmer Drought Severity Index (PDSI), Thornthwaite-Matter, and Standardized Precipitation Index (SPI) then correlated with SOI to determine the most suitable method for SOI. The variables are applied in this method are rainfall, temperature, and evapotranspiration. The results showed that the drought potential of the Palmer method is only in Near Normal conditions, which is 1%, Severe drought conditions are 29% for the Thornthwaite-Matter method, and Extreme Dry conditions only reach 1,11% for the SPI method. The PDSI and SPI methods are inversely proportional to the Thornthwaite-Matter method and the most suitable method for SOI values or rainfall is the SPI method. These three methods can be identified the potential for drought with only a few variables so that they could be applied if they only have those data.Keywords: Drought, PDSI, Thornthwaite-Matter, SPI, SOI

The effect of human influence on wet and dry European summers

2021 ◽  
Author(s):  
Nikolaos Christidis ◽  
Peter Stott
Keyword(s):  
Climate Change ◽  
Potential Evapotranspiration ◽  
Rainfall Variability ◽  
Climatic Conditions ◽  
Drought Indices ◽  
Human Influence ◽  
The North ◽  
Detection And Attribution ◽  
Standardised Precipitation Index ◽  
Dry Conditions

<p>As the climate becomes warmer under the influence of anthropogenic forcings, increases in the concentration of the atmospheric water vapour may lead to an intensification of wet and dry extremes. Understanding regional hydroclimatic changes can provide actionable information to help communities adapt to impacts specific to their location. This study employs an ensemble of 9 CMIP6 models and compares experiments with and without the effect of human influence using detection and attribution methodologies. The analysis employs two popular drought indices: the rainfall-based standardised precipitation index (SPI), and its extension, the standardized precipitation evapotranspiration index (SPEI), which also accounts for changes in potential evapotranspiration. Both indices are defined relative to the pre-industrial climate, which enables a comparison between past, present and future climatic conditions. Potential evapotranspiration is computed with the simple, temperature-based, Thornthwaite formula. The latter has been criticised for omitting the influences of radiation, humidity and wind, but has been shown to yield very similar trends, spatial averages and correlations with more sophisticated models. It is therefore deemed to be adequate in studies assessing the broader overall effect of climate change, which are more concerned with wet and dry trends and changes in characteristics of extremes rather than the precise estimation of drought index values. The rainfall-based index suggests a shift towards wetter conditions in the north and dryer in the south of the continent, as well as an overall increase in variability. Nevertheless, when the temperature effect is included, the wet trends in the north are largely masked leading to increasingly drier summers across most of the continent. A formal statistical methodology indicates that the fingerprint of forced climate change has emerged above variability and is thus detectable in the observational trends of both indices. A broadening of the SPI distribution also suggests higher rainfall variability in a warmer climate. The study demonstrates a striking drying trend in the Mediterranean region, suggesting that what were extremely dry conditions there in the pre-industrial climate may become normal by the end of the century.</p>

scholarly journals Multidimensional risk in a nonstationary climate: Joint probability of increasingly severe warm and dry conditions

2018 ◽  
Vol 4 (11) ◽  
pp. eaau3487 ◽  
Author(s):  
Ali Sarhadi ◽  
María Concepción Ausín ◽  
Michael P. Wiper ◽  
Danielle Touma ◽  
Noah S. Diffenbaugh
Keyword(s):  
Joint Probability ◽  
Climate Forcing ◽  
Climate Variables ◽  
Human Influence ◽  
Statistical Confidence ◽  
Emissions Mitigation ◽  
Multiple Regions ◽  
Dry Conditions ◽  
Critical Insight ◽  
Nonstationary Climate

We present a framework for quantifying the spatial and temporal co-occurrence of climate stresses in a nonstationary climate. We find that, globally, anthropogenic climate forcing has doubled the joint probability of years that are both warm and dry in the same location (relative to the 1961–1990 baseline). In addition, the joint probability that key crop and pasture regions simultaneously experience severely warm conditions in conjunction with dry years has also increased, including high statistical confidence that human influence has increased the probability of previously unprecedented co-occurring combinations. Further, we find that ambitious emissions mitigation, such as that in the United Nations Paris Agreement, substantially curbs increases in the probability that extremely hot years co-occur with low precipitation simultaneously in multiple regions. Our methodology can be applied to other climate variables, providing critical insight for a number of sectors that are accustomed to deploying resources based on historical probabilities.

scholarly journals The Relationship of Rainfall Variability in Western Equatorial Africa to the Tropical Oceans and Atmospheric Circulation. Part II: The Boreal Autumn

2013 ◽  
Vol 26 (1) ◽  
pp. 66-84 ◽  
Author(s):  
Amin K. Dezfuli ◽  
Sharon E. Nicholson
Keyword(s):  
Atmospheric Circulation ◽  
Rainfall Variability ◽  
Sea Level Pressure ◽  
Tropical Oceans ◽  
Remote Forcing ◽  
Equatorial Africa ◽  
The Pacific ◽  
Dry Conditions ◽  
Relationship Of ◽  
East West

Abstract This paper examines the mechanisms controlling the year-to-year variability of rainfall over western equatorial Africa during the rainy season of October–December. Five regions with distinct behavior are analyzed separately. Only two show strong associations with the ocean and atmospheric features in the global tropics. These two regions, in the east (the eastern Zaire basin) and west (Angolan coast) of the study area, respectively, demonstrate strikingly opposite relationships with the anomalies of sea surface temperatures (SSTs), sea level pressure (SLP), and east–west atmospheric circulation. The wet (dry) conditions in the eastern Zaire basin are associated with El Niño(La Niña)–like phases. The inverse pattern is apparent for the Angolan coast. The other three regions, lying between these two poles of variability, represent a transition zone with a weak linear relationship to the circulation features. The vital impact of the east–west circulation cells on rainfall variability results in a stronger association with zonal wind than with SSTs or SLP. In addition to the zonal shift, changes in intensity of the zonal cells also play a crucial role. Variability in both magnitude and location of the circulation cells appear to be modulated by the remote forcing from the Pacific via an atmospheric bridge. However, the eastern sector is impacted mainly when synchronous changes occur in the Indian Ocean, and the western sector is impacted mainly when synchronous changes occur in the Atlantic Ocean.

scholarly journals Different Ways of Framing Event Attribution Questions: The Example of Warm and Wet Winters in the United Kingdom Similar to 2015/16

2018 ◽  
Vol 31 (12) ◽  
pp. 4827-4845 ◽  
Author(s):  
Nikolaos Christidis ◽  
Andrew Ciavarella ◽  
Peter A. Stott
Keyword(s):  
United Kingdom ◽  
Atmospheric Model ◽  
Human Influence ◽  
Coupled Models ◽  
Modes Of Variability ◽  
The United Kingdom ◽  
Event Attribution ◽  
Key Characteristics ◽  
Reference Event ◽  
Sst Anomalies

Attribution analyses of extreme events estimate changes in the likelihood of their occurrence due to human climatic influences by comparing simulations with and without anthropogenic forcings. Classes of events are commonly considered that only share one or more key characteristics with the observed event. Here we test the sensitivity of attribution assessments to such event definition differences, using the warm and wet winter of 2015/16 in the United Kingdom as a case study. A large number of simulations from coupled models and an atmospheric model are employed. In the most basic case, warm and wet events are defined relative to climatological temperature and rainfall thresholds. Several other classes of events are investigated that, in addition to threshold exceedance, also account for the effect of observed sea surface temperature (SST) anomalies, the circulation flow, or modes of variability present during the reference event. Human influence is estimated to increase the likelihood of warm winters in the United Kingdom by a factor of 3 or more for events occurring under any atmospheric and oceanic conditions, but also for events with a similar circulation or oceanic state to 2015/16. The likelihood of wet winters is found to increase by at least a factor of 1.5 in the general case, but results from the atmospheric model, conditioned on observed SST anomalies, are more uncertain, indicating that decreases in the likelihood are also possible. The robustness of attribution assessments based on atmospheric models is highly dependent on the representation of SSTs without the effect of human influence.

scholarly journals A global analysis of the impact of drought on net primary productivity

2013 ◽  
Vol 17 (10) ◽  
pp. 3885-3894 ◽  
Author(s):  
T. Chen ◽  
G. R. Werf ◽  
R. A. M. Jeu ◽  
G. Wang ◽  
A. J. Dolman
Keyword(s):  
Primary Productivity ◽  
Drought Index ◽  
Net Primary Productivity ◽  
Global Analysis ◽  
Global Scale ◽  
Phase Behaviour ◽  
Positive Relation ◽  
Dry Conditions ◽  
Köppen Climate Classification ◽  
The Impact

Abstract. We investigated the impact of drought on interannual variability of net primary productivity (NPP) from 1997 to 2009, using the standardized precipitation evapotranspiration index (SPEI) drought index and satellite-derived vegetation greenness converted to NPP. SPEI is positive for wet conditions and negative for dry conditions. We found that SPEI and NPP were coupled and showed in-phase behaviour on a global scale. We then used the Köppen climate classification to study the SPEI–NPP relations regionally and found that while NPP and SPEI were positively related (high SPEI, high NPP) in arid and in seasonal dry regions, the opposite occurs in most boreal regions (high SPEI, low NPP). High intensity drought events, such as the 2003 drought in Europe were picked up by our analysis. Our findings suggest that the strong positive relation between global average moisture availability and NPP consists of a composite of the positive relation across dry regions and the coherent NPP decline during and after intensive drought events in humid regions. Importantly, we also found that there are many areas on the globe that show no strong correlation between drought and NPP.

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