scholarly journals Climate drivers of the 2017 devastating fires in Portugal

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Marco Turco ◽  
Sonia Jerez ◽  
Sofia Augusto ◽  
Patricia Tarín-Carrasco ◽  
Nuno Ratola ◽  
...  
Keyword(s):  
High Temperature ◽  
Climatic Factors ◽  
Standardized Precipitation Index ◽  
Fire Risk ◽  
Fire Season ◽  
Burned Area ◽  
Moisture Index ◽  
Temperature Conditions ◽  
The Standardized Precipitation Index ◽  
Extreme Fire

Abstract A record 500,000 hectares burned in Portugal during the extreme wildfire season of 2017, with more than 120 human lives lost. Here we analyse the climatic factors responsible for the burned area (BA) from June to October series in Portugal for the period 1980–2017. Superposed onto a substantially stationary trend on BA data, strong oscillations on shorter time scales were detected. Here we show that they are significantly affected by the compound effect of summer (June-July-August) drought and high temperature conditions during the fire season. Drought conditions were calculated using the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSI). Then the extent to which the burned area has diverged from climate-expected trends was assessed. Our results indicate that in the absence of other drivers, climate change would have led to higher BA values. In addition, the 2017 extreme fire season is well captured with the model forced with climate drivers only, suggesting that the extreme fire season of 2017 could be a prelude to future conditions and likewise events. Indeed, the expected further increase of drought and high temperature conditions in forthcoming decades, point at a potential increase of fire risk in this region. The climate-fire model developed in this study could be useful to develop more skilled seasonal predictions capable of anticipating potentially hazardous conditions.

scholarly journals An Assessment of Drought Stress in Tea Estates Using Optical and Thermal Remote Sensing

2021 ◽  
Vol 13 (14) ◽  
pp. 2730
Author(s):  
Animesh Chandra Das ◽  
Ryozo Noguchi ◽  
Tofael Ahamed
Keyword(s):  
Remote Sensing ◽  
Drought Stress ◽  
Land Surface ◽  
Climatic Factors ◽  
Standardized Precipitation Index ◽  
Landsat 8 ◽  
Drought Frequency ◽  
Moisture Index ◽  
Area Index ◽  
Drought Period

Drought is one of the detrimental climatic factors that affects the productivity and quality of tea by limiting the growth and development of the plants. The aim of this research was to determine drought stress in tea estates using a remote sensing technique with the standardized precipitation index (SPI). Landsat 8 OLI/TIRS images were processed to measure the land surface temperature (LST) and soil moisture index (SMI). Maps for the normalized difference moisture index (NDMI), normalized difference vegetation index (NDVI), and leaf area index (LAI), as well as yield maps, were developed from Sentinel-2 satellite images. The drought frequency was calculated from the classification of droughts utilizing the SPI. The results of this study show that the drought frequency for the Sylhet station was 38.46% for near-normal, 35.90% for normal, and 25.64% for moderately dry months. In contrast, the Sreemangal station demonstrated frequencies of 28.21%, 41.02%, and 30.77% for near-normal, normal, and moderately dry months, respectively. The correlation coefficients between the SMI and NDMI were 0.84, 0.77, and 0.79 for the drought periods of 2018–2019, 2019–2020 and 2020–2021, respectively, indicating a strong relationship between soil and plant canopy moisture. The results of yield prediction with respect to drought stress in tea estates demonstrate that 61%, 60%, and 60% of estates in the study area had lower yields than the actual yield during the drought period, which accounted for 7.72%, 11.92%, and 12.52% yield losses in 2018, 2019, and 2020, respectively. This research suggests that satellite remote sensing with the SPI could be a valuable tool for land use planners, policy makers, and scientists to measure drought stress in tea estates.

Seasonal predictability of summer fires in a Mediterranean environment

2015 ◽  
Vol 24 (8) ◽  
pp. 1076 ◽  
Author(s):  
Raül Marcos ◽  
Marco Turco ◽  
Joaquín Bedía ◽  
Maria Carmen Llasat ◽  
Antonello Provenzale
Keyword(s):  
Climatic Factors ◽  
Time Lag ◽  
Multiple Linear Regression Model ◽  
Added Value ◽  
Fire Season ◽  
Burned Area ◽  
Summer Drought ◽  
Seasonal Predictability ◽  
Standardised Precipitation Index ◽  
North Eastern

In this study we explore the seasonal predictability of summer wildfires in a Mediterranean region (north-eastern Spain), developing a multiple linear regression model with antecedent and current-summer drought indices (Standardised Precipitation Index; and Standardised Precipitation Evapotranspiration Index). This model is based on the assumption that large summer fires in Mediterranean environments are favoured by current-summer drought (proxy for the climatic factors that affect fuel flammability) and by antecedent wet conditions (proxies for the climatic factors influencing fine fuel availability and connectivity). We test three forecast systems based on (i) seasonal European Centre for Medium-Range Weather Forecasts (ECMWF) System-4 forecasts; (ii) persistence and (iii) climatology. These approaches are evaluated through a leave-one-out cross-validation over the period 1983–2012. The climatology forecast, which considers only antecedent wet or dry conditions with a time lag of 2 years, shows some amount of skill in simulating above- or below-normal summer fire activity. ECMWF System-4 proves to be of limited added value with respect to the climatology forecast. Finally, the persistence forecast, which is driven by antecedent conditions and drought conditions just before the start of the fire season, allows more satisfactory results (correlation of 0.49). The results suggest that long-term forecasts of above-normal burned area are feasible in Catalonia (north-eastern Spain), information that could be potentially applied also to other Mediterranean-type regions.

scholarly journals Assessing the role of compound drought and heatwave events on unprecedented 2020 wildfires in the Pantanal

2021 ◽  
Author(s):  
Renata Libonati ◽  
João Lucas Geirinhas ◽  
Patrícia S. Silva ◽  
Ana Russo ◽  
Julia A Rodrigues ◽  
...  
Keyword(s):  
Fire Risk ◽  
Fire Season ◽  
Maximum Temperature ◽  
Burned Area ◽  
Simultaneous Occurrence ◽  
Limiting Factor ◽  
Driving Mechanisms ◽  
Synoptic Conditions ◽  
Dry Conditions ◽  
Forested Areas

Abstract The year 2020 had the most catastrophic fire season over the last two decades in the Pantanal, which led to outstanding environmental impacts. Indeed, much of the Pantanal has been affected by severe dry conditions since 2019, with evidence of the 2020’s drought being the most extreme and widespread ever recorded in the last 70 years. Although it is unquestionable that this mega-drought contributed significantly to the increase of fire risk, so far, the 2020’s fire season has been analyzed at the univariate level of a single climate event, not considering the co-occurrence of extreme and persistent temperatures with soil dryness conditions. Here, we show that similarly to other areas of the globe, the influence of land-atmosphere feedbacks contributed decisively to the simultaneous occurrence of dry and hot spells (HPs), exacerbating fire risk. The ideal synoptic conditions for strong atmospheric heating and large evaporation rates were present, in particular during the HPs, when the maximum temperature was, on average, 6 ºC above the normal. The short span of the period during those compound drought-heatwave (CDHW) events accounted for 55% of the burned area of 2020. The vulnerability in the northern forested areas was higher than in the other areas, revealing a synergistic effect between fuel availability and weather-hydrological conditions. Accordingly, where fuel is not a limiting factor, fire activity tends to be more modelled by CDHW events. Our work advances beyond an isolated event-level basis towards a compound and cascading natural hazards approach, simultaneously estimating the contribution of drought and heatwaves to fuelling extreme fire outbreaks in the Pantanal such as those in 2020. Thus, these findings are relevant within a broader context, as the driving mechanisms apply across other ecosystems, implying higher flammability conditions and further efforts for monitoring and predicting such extreme events.

scholarly journals Monitoring and Predicting Drought Based on Multiple Indicators in an Arid Area, China

2020 ◽  
Vol 12 (14) ◽  
pp. 2298
Author(s):  
Yunqian Wang ◽  
Jing Yang ◽  
Yaning Chen ◽  
Zhicheng Su ◽  
Baofu Li ◽  
...  
Keyword(s):  
Lead Time ◽  
Standardized Precipitation Index ◽  
Arid Area ◽  
Lead Times ◽  
Moisture Index ◽  
Predictive Skill ◽  
Drought Prediction ◽  
Spatial Coverage ◽  
Soil Moisture Index ◽  
The Standardized Precipitation Index

Droughts are one of the costliest natural disasters. Reliable drought monitoring and prediction are valuable for drought relief management. This study monitors and predicts droughts in Xinjiang, an arid area in China, based on the three drought indicators, i.e., the Standardized Precipitation Index (SPI), the Standardized Soil Moisture Index (SSMI) and the Multivariate Standardized Drought Index (MSDI). Results indicate that although these three indicators could capture severe historical drought events in the study area, the spatial coverage, persistence and severity of the droughts would vary regarding different indicators. The MSDI could best describe the overall drought conditions by incorporating the characteristics of the SPI and SSMI. For the drought prediction, the predictive skill of all indicators gradually decayed with the increasing lead time. Specifically, the SPI only showed the predictive skill at a 1-month lead time, the MSDI performed best in capturing droughts at 1- to 2-month lead times and the SSMI was accurate up to a 3-month lead time owing to its high persistence. These findings might provide scientific support for the local drought management.

Evaluating the Utility of Drought Indices as Soil Moisture Proxies for Drought Monitoring and Land–Atmosphere Interactions

2020 ◽  
Vol 21 (9) ◽  
pp. 2157-2175
Author(s):  
Shanshui Yuan ◽  
Steven M. Quiring ◽  
Chen Zhao
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Soil Layer ◽  
Standardized Precipitation Index ◽  
Drought Indices ◽  
Moisture Index ◽  
Drought Conditions ◽  
Crop Moisture Index ◽  
The Standardized Precipitation Index ◽  
The Relationship

AbstractThere are a variety of metrics that are used to monitor drought conditions, including soil moisture and drought indices. This study examines the relationship between in situ soil moisture, NLDAS-2 soil moisture, and four drought indices: the standardized precipitation index, the standardized precipitation evapotranspiration index, the crop moisture index, and the Palmer Z index. We evaluate how well drought indices and the modeled soil moisture represent the intensity, variability, and persistence of the observed soil moisture in the southern Great Plains. We also apply the drought indices to evaluate land–atmosphere interactions and compare the results with soil moisture. The results show that the SPI, SPEI, and Z index have higher correlations with 0–10-cm soil moisture, while the CMI is more strongly correlated with 0–100-cm soil moisture. All the drought indices tend to overestimate the area affected by moderate to extreme drought conditions. Significant drying trends from 2003 to 2017 are evident in SPEI, Z index, and CMI, and they agree with those in the observed soil moisture. The CMI captures the intra- and interannual variability of 0–100-cm soil moisture better than the other drought indices. The persistence of CMI is longer than that of 0–10-cm soil moisture and shorter than that of 0–100-cm soil moisture. Model-derived soil moisture does not outperform the CMI in the 0–100-cm soil layer. The Z index and CMI are better drought indices to use as a proxy for soil moisture when examining land–atmosphere interactions while the SPI is not recommended. Soil type and climate affect the relationship between drought indices and observed soil moisture.

scholarly journals Integrating past variability in climate-driven Mediterranean fire hazard assessments for 2020-2100

2021 ◽  
Author(s):  
Marion Lestienne ◽  
Boris Vannière ◽  
Thomas Curt ◽  
Isabelle Jouffroy-Bapicot ◽  
Christelle Hély
Keyword(s):  
Fire Hazard ◽  
Fire Risk ◽  
Future Climate ◽  
Effect Of Temperature ◽  
Fire Season ◽  
Burned Area ◽  
Prevention Policy ◽  
Rcp Scenarios ◽  
Precipitation Decrease ◽  
The Future

Abstract In the Mediterranean basin, Corsica (French island) harbours among the best-preserved Mediterranean forest ecosystems and its high biodiversity could be threatened by the climate and disturbance-regime changes due to the global warming. This study aims i) to estimate the future climate-related fire hazard in Corsica for the current century (2020–2100) based on two RCP scenarios (RCP4.5 and RCP8.5), and ii) to compare the predicted trends with the entire Holocene period for which fire hazard has previously been assessed. An ensemble of future climate simulations from two IPCC RCP scenarios has been used to compute the Monthly Drought Code (MDC) and the Fire Season Length (FSL) and to assess the level of fire hazard assessment. Here, we show that the MDC and the FSL would both strongly increase over the next decades due to the combined effect of temperature increase and precipitation decrease in the Corsica region. Moreover, the maximum Holocene FLS (7000 to 9000 years ago), will be reached (and even exceeded depending upon the scenario) after 2040. For the first time in the Holocene, we may be confronted to an increase in the number of fire-prone months driven by climate combined with many human-caused ignitions. This combination should increase the burned area from 15–140%. For the next 30 years, the game seems to be already played as both RCP scenarios resulted in similar increase in fire hazard intensity and duration. It is thus mandatory to reconsider fire-management and fire-prevention policy to mitigate the future fire risk, and its catastrophic consequences for ecosystems, population, and economy.

scholarly journals Manipulating Large-Scale Qualitative Meteorological Information for Drought Outlook

2012 ◽  
Vol 140 (10) ◽  
pp. 3250-3258 ◽  
Author(s):  
Kuk-Hyun Ahn ◽  
Young-Oh Kim ◽  
Sang Jin Ahn
Keyword(s):  
Large Scale ◽  
Standardized Precipitation Index ◽  
Skill Score ◽  
Moisture Index ◽  
Probability Forecast ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Temperature And Precipitation ◽  
The Standardized Precipitation Index ◽  
Interval Forecast

Abstract Despite many strides made in the development of global circulation models as well as the expansive understanding of meteorological phenomena, many countries still lack sufficient meteorological information that can be conveniently utilized for a hydrologic outlook. This paper suggests a technique of processing the meteorological information, which is not only difficult to differentiate by reducing to a specific basin because of extensive data, but is also impossible to be led to a quantitative drought outlook because of its presentation in qualitative forms. To assess the drought conditions, two indices were selected—the standardized precipitation index (SPI), which is a meteorological index, and the soil moisture index (SMI), an agricultural index. The long-range forecasts, provided by the Korea Meteorological Administration (KMA) to target the Korean peninsula, were used to predict these indices. As a means to convert the qualitative interval forecast into a quantitative probability forecast, previous data on temperature and precipitation were used to create a compatible probability distribution that was then divided into three intervals. Based on the interval forecast provided by the KMA, the forecast probability of corresponding intervals were differentiated and optimized for each study basin by modifying the probability adjustment coefficient. The quantified probability forecast established in this manner was applied to three basins in Korea, and was verified by applying the ranked probability skill score (RPSS). The results proved that accuracy was ensured in both SPI and SMI.

DROUGHT OCCURRENCE UNDER LITHUANIAN CLIMATIC CONDITIONS

2015 ◽  
Author(s):  
Laima TAPARAUSKIENĖ ◽  
Veronika LUKŠEVIČIŪTĖ
Keyword(s):  
Meteorological Data ◽  
Standardized Precipitation Index ◽  
Vegetation Period ◽  
Climatic Conditions ◽  
Precipitation Record ◽  
Calculation Step ◽  
Drought Conditions ◽  
The Standardized Precipitation Index ◽  
June July

This study provides the analysis of drought conditions of vegetation period in 1982-2014 year in two Lithuanian regions: Kaunas and Telšiai. To identify drought conditions the Standardized Precipitation Index (SPI) was applied. SPI was calculated using the long-term precipitation record of 1982–2014 with in-situ meteorological data. Calculation step of SPI was taken 1 month considering only vegetation period (May, June, July, August, September). The purpose of investigation was to evaluate the humidity/aridity of vegetation period and find out the probability of droughts occurrence under Lithuanian climatic conditions. It was found out that according SPI results droughts occurred in 14.5 % of all months in Kaunas region and in 15.8 % in Telšiai region. Wet periods in Kaunas region occurred in 15.8 %, and in Telšiai region occurrence of wet periods was – 18.8 % from all evaluated months. According SPI evaluation near normal were 69.7 % of total months during period of investigation in Kaunas and respectively – 65.5 % in Telšiai. The probability for extremely dry period under Lithuania climatic conditions are pretty low – 3.0 % in middle Lithuania and 2.4 % in western part of Lithuania.

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