Manipulating Large-Scale Qualitative Meteorological Information for Drought Outlook

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.

Download Full-text

Future Global Meteorological Drought Hot Spots: A Study Based on CORDEX Data

Journal of Climate ◽

10.1175/jcli-d-19-0084.1 ◽

2020 ◽

Vol 33 (9) ◽

pp. 3635-3661 ◽

Cited By ~ 22

Author(s):

Jonathan Spinoni ◽

Paulo Barbosa ◽

Edoardo Bucchignani ◽

John Cassano ◽

Tereza Cavazos ◽

...

Keyword(s):

Hot Spots ◽

Regional Climate ◽

Standardized Precipitation Index ◽

Meteorological Drought ◽

First Century ◽

Horn Of Africa ◽

Global Circulation ◽

Global Circulation Models ◽

The Standardized Precipitation Index ◽

Meteorological Droughts

AbstractTwo questions motivated this study: 1) Will meteorological droughts become more frequent and severe during the twenty-first century? 2) Given the projected global temperature rise, to what extent does the inclusion of temperature (in addition to precipitation) in drought indicators play a role in future meteorological droughts? To answer, we analyzed the changes in drought frequency, severity, and historically undocumented extreme droughts over 1981–2100, using the standardized precipitation index (SPI; including precipitation only) and standardized precipitation-evapotranspiration index (SPEI; indirectly including temperature), and under two representative concentration pathways (RCP4.5 and RCP8.5). As input data, we employed 103 high-resolution (0.44°) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), based on a combination of 16 global circulation models (GCMs) and 20 regional circulation models (RCMs). This is the first study on global drought projections including RCMs based on such a large ensemble of RCMs. Based on precipitation only, ~15% of the global land is likely to experience more frequent and severe droughts during 2071–2100 versus 1981–2010 for both scenarios. This increase is larger (~47% under RCP4.5, ~49% under RCP8.5) when precipitation and temperature are used. Both SPI and SPEI project more frequent and severe droughts, especially under RCP8.5, over southern South America, the Mediterranean region, southern Africa, southeastern China, Japan, and southern Australia. A decrease in drought is projected for high latitudes in Northern Hemisphere and Southeast Asia. If temperature is included, drought characteristics are projected to increase over North America, Amazonia, central Europe and Asia, the Horn of Africa, India, and central Australia; if only precipitation is considered, they are found to decrease over those areas.

Download Full-text

Review of effective emissions modeling and computation

Geoscientific Model Development ◽

10.5194/gmd-4-643-2011 ◽

2011 ◽

Vol 4 (3) ◽

pp. 643-667 ◽

Cited By ~ 25

Author(s):

R. Paoli ◽

D. Cariolle ◽

R. Sausen

Keyword(s):

Large Scale ◽

Three Dimensional ◽

Reaction Rates ◽

Transport Models ◽

Global Circulation ◽

Global Circulation Models ◽

Emissions Modeling ◽

Exhaust Plumes ◽

Physical And Chemical ◽

Scale Grid

Abstract. An important issue in the evaluation of the environmental impact of emissions from concentrated sources such as transport modes, is to understand how processes occurring at the scales of exhaust plumes can influence the physical and chemical state of the atmosphere at regional and global scales. Indeed, three-dimensional global circulation models or chemistry transport models generally assume that emissions are instantaneously diluted into large-scale grid boxes, which may lead, for example, to overpredict the efficiency of NOx to produce ozone. In recent times, various methods have been developed to incorporate parameterizations of plume processes into global models that are based e.g. on correcting the original emission indexes or on introducing "subgrid" reaction rates in the models. This paper provides a review of the techniques proposed so far in the literature to account for local conversion of emissions in the plume, as well as the implementation of these techniques into atmospheric codes.

Download Full-text

Early warning of drought in Europe using the monthly ensemble system from ECMWF

Hydrology and Earth System Sciences ◽

10.5194/hess-19-3273-2015 ◽

2015 ◽

Vol 19 (7) ◽

pp. 3273-3286 ◽

Cited By ~ 11

Author(s):

C. Lavaysse ◽

J. Vogt ◽

F. Pappenberger

Keyword(s):

Large Scale ◽

Standardized Precipitation Index ◽

Seasonal Forecast ◽

Cumulative Distribution ◽

False Alarms ◽

Negative Effects ◽

European Continent ◽

Probabilistic Forecasts ◽

Extended Range ◽

The Standardized Precipitation Index

Abstract. Timely forecasts of the onset or possible evolution of droughts are an important contribution to mitigate their manifold negative effects. In this paper we therefore analyse and compare the performance of the first month of the probabilistic extended range forecast and of the seasonal forecast from the European Centre for Medium-range Weather Forecasts (ECMWF) in predicting droughts over the European continent. The Standardized Precipitation Index (SPI-1) is used to quantify the onset or likely evolution of ongoing droughts for the next month. It can be shown that on average the extended range forecast has greater skill than the seasonal forecast, whilst both outperform climatology. No significant spatial or temporal patterns can be observed, but the scores are improved when focussing on large-scale droughts. In a second step we then analyse several different methods to convert the probabilistic forecasts of SPI into a Boolean drought warning. It can be demonstrated that methodologies which convert low percentiles of the forecasted SPI cumulative distribution function into warnings are superior in comparison with alternatives such as the mean or the median of the ensemble. The paper demonstrates that up to 40 % of droughts are correctly forecasted one month in advance. Nevertheless, during false alarms or misses, we did not find significant differences in the distribution of the ensemble members that would allow for a quantitative assessment of the uncertainty.

Download Full-text

Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño–Southern Oscillation (ENSO)

Remote Sensing ◽

10.3390/rs13234730 ◽

2021 ◽

Vol 13 (23) ◽

pp. 4730

Author(s):

Malak Henchiri ◽

Tertsea Igbawua ◽

Tehseen Javed ◽

Yun Bai ◽

Sha Zhang ◽

...

Keyword(s):

West Africa ◽

Large Scale ◽

Southern Oscillation ◽

Standardized Precipitation Index ◽

Joint Probability ◽

Meteorological Drought ◽

Socioeconomic Impacts ◽

The North ◽

The Standardized Precipitation Index ◽

The North Atlantic Oscillation

Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the study area, this study adopted multi-source data and various statistical analysis methods, such as the joint probability density function (JPDF), to study the meteorological drought and return years across a long term (1982–2018). The standardized precipitation index (SPI) was used to evaluate the large-scale spatiotemporal drought characteristics at 1–12-month timescales. The intensity, severity, and duration of drought in the study area were evaluated using SPI–12. At the same time, the JPDF was used to determine the return year and identify the intensity, duration, and severity of drought. The Mann-Kendall method was used to test the trend of SPI and annual precipitation at 1–12-month timescales. The pattern of drought occurrence and its correlation with climate factors were analyzed. The results showed that the drought magnitude (DM) of the study area was the highest in 2008–2010, 2000–2003, and 1984–1987, with the values of 5.361, 2.792, and 2.187, respectively, and the drought lasting for three years in each of the three periods. At the same time, the lowest DM was found in 1997–1998, 1993–1994, and 1991–1992, with DM values of 0.113, 0.658, and 0.727, respectively, with a duration of one year each time. It was confirmed that the probability of return to drought was higher when the duration of drought was shorter, with short droughts occurring more regularly, but not all severe droughts hit after longer time intervals. Beyond this, we discovered a direct connection between drought and the North Atlantic Oscillation Index (NAOI) over Morocco, Algeria, and the sub-Saharan countries, and some slight indications that drought is linked with the Southern Oscillation Index (SOI) over Guinea, Ghana, Sierra Leone, Mali, Cote d’Ivoire, Burkina Faso, Niger, and Nigeria.

Download Full-text

Modeling and computation of effective emissions: a position paper

Geoscientific Model Development Discussions ◽

10.5194/gmdd-4-137-2011 ◽

2011 ◽

Vol 4 (1) ◽

pp. 137-196 ◽

Cited By ~ 1

Author(s):

R. Paoli ◽

D. Cariolle ◽

R. Sausen

Keyword(s):

Large Scale ◽

Three Dimensional ◽

Reaction Rates ◽

Position Paper ◽

Transport Models ◽

Global Circulation ◽

Global Circulation Models ◽

Exhaust Plumes ◽

Physical And Chemical ◽

Scale Grid

Abstract. An important issue in the evaluation of the environmental impact of emissions from concentrated sources such as transport modes, is to understand how processes occurring at the scales of exhaust plumes can influence the physical and chemical state of the atmosphere at regional and global scales. Indeed, three-dimensional global circulation models or chemistry transport models generally assume that emissions are instantaneously diluted into large-scale grid boxes, which may lead, for example, to overpredict the efficiency of NOx to produce ozone. In recent times, various methods have been developed to incorporate parameterizations of plume processes into global models that are based either on the correction of the original emissions or on the introduction of subgrid reaction rates in the models. This paper provides a review of the techniques proposed so far in the literature to account for local conversion of emissions in the plume, as well as the implementation of these techniques into atmospheric codes.

Download Full-text

Multidimensional extremes: joint study of precipitation and temperature time series

10.5194/ems2021-223 ◽

2021 ◽

Author(s):

Beatrix Izsák ◽

Tamás Szentimrey ◽

Mónika Lakatos ◽

Rita Pongrácz

Keyword(s):

Climate Change ◽

Time Series ◽

Extreme Values ◽

Standardized Precipitation Index ◽

Single Element ◽

Average Temperature ◽

Temperature And Precipitation ◽

The Standardized Precipitation Index ◽

Climatic Time Series ◽

Precipitation And Temperature

<p>To study climate change, it is essential to analyze extremes as well. The study of extremes can be done on the one hand by examining the time series of extreme climatic events and on the other hand by examining the extremes of climatic time series. In the latter case, if we analyze a single element, the extreme is the maximum or minimum of the given time series. In the present study, we determine the extreme values of climatic time series by examining several meteorological elements together and thus determining the extremes. In general, the main difficulties are connected with the different probability distribution of the variables and the handling of the stochastic connection between them. The first issue can be solved by the standardization procedures, i.e. to transform the variables into standard normal ones. For example, the Standardized Precipitation Index (SPI) uses precipitation sums assuming gamma distribution, or the standardization of temperature series assumes normal distribution. In case of more variables, the problem of stochastic connection can be solved on the basis of the vector norm of the variables defined by their covariance matrix. According to this methodology we have developed a new index in order to examine the precipitation and temperature variables jointly. We present the new index with the mathematical background, furthermore some examples for spatio-temporal examination of these indices using our software MASH (Multiple Analysis of Series for Homogenization; Szentimrey) and MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey, Bihari). For our study, we used the daily average temperature and precipitation time series in Hungary for the period 1870-2020. First of all, our analyses indicate that even though some years may not be considered extreme if only either precipitation or average temperature is taken in to account, but examining the two elements together these years were extreme years indeed. Based on these, therefore, the study of the extremes of multidimensional climate time series complements and thus makes the study of climate change more efficient compared to examining only one-dimensional time series.</p>

Download Full-text

A hybrid downscaling approach for the estimation of climate change effects on droughts using a geo-information tool. Case study: Thessaly, Central Greece

Open Geosciences ◽

10.1515/geo-2016-0069 ◽

2016 ◽

Vol 8 (1) ◽

pp. 728-746 ◽

Cited By ~ 2

Author(s):

John Tzabiras ◽

Athanasios Loukas ◽

Lampros Vasiliades

Keyword(s):

Climate Change ◽

Large Scale ◽

Standardized Precipitation Index ◽

Historical Period ◽

Monthly Precipitation ◽

Max Planck ◽

Climate Change Effects ◽

Geostatistical Approach ◽

The Standardized Precipitation Index ◽

Stochastic Time Series

AbstractMultiple linear regression is used to downscale large-scale outputs from CGCM2 (second generation CGCM of Canadian centre for climate monitoring and analysis) and ECHAM5 (developed at the Max Planck Institute for Meteorology), statistically to regional precipitation over the Thessaly region, Greece. Mean monthly precipitation data for the historical period Oct.1960-Sep.2002 derived from 79 rain gauges were spatially interpolated using a geostatistical approach over the region of Thessaly, which was divided into 128 grid cells of 10 km × 10 km. The methodology is based on multiple regression of large scale GCM predictant variables with observed precipitation and the application of a stochastic time series model for precipitation residuals simulation (white noise). The methodology was developed for historical period (Oct.1960–Sep.1990) and validated against observed monthly precipitation for period (Oct.1990–Sep.2002). The downscaled proposed methodology was used to calculate the standardized precipitation index (SPI) at various timescales (3-month, 6-month, 9-month, 12-month, 24-month) in order to estimate climate change effects on droughts. Various evaluation statistics were calculated in order to validate the process and the results showed that the method is efficient in SPI reproduction but the level of uncertainty is quite high due to its stochastic component.

Download Full-text

Enumerating the Effects of Climate Change on Water Resources Using GCM Scenarios at the Xin’anjiang Watershed, China

Water ◽

10.3390/w10101296 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1296 ◽

Cited By ~ 5

Author(s):

Muhammad Zaman ◽

Muhammad Naveed Anjum ◽

Muhammad Usman ◽

Ijaz Ahmad ◽

Muhammad Saifullah ◽

...

Keyword(s):

Climate Change ◽

Water Resources ◽

Large Scale ◽

Electricity Production ◽

Maximum Increase ◽

Stream Flows ◽

Global Circulation ◽

Global Circulation Models ◽

Novel Approach ◽

Precipitation Increase

The present study developed a novel approach to study the climate change impact on the water resources and generation of hydropower optimally using forecasted stream flows for the Xin’anjiang water shed in China. Future flows were projected using six large-scale Global circulation models (GCMs) with RCP4.5 and RCP8.5 scenarios. A newly developed mathematical modeling using particle swarm optimization was incorporated to work out the projected optimal electricity generation from the Xin’anjiang hydropower station. The results reveal that watershed will be warmer by the end of the 21st century with a maximum increase of up to 4.9 °C for mean maximum, and 4.8 °C for mean minimum temperature. Six GCMs under Representative Concentration pathways (RCPs) showed that future precipitation is complex to predict with certainty and significant differences were observed among the different GCMs. The overall mean monthly and seasonal precipitation increase for most scenarios with the maximum increase during the 2020s and 2080s, whereas 2050s exhibited the lesser increase. Resultantly, there would be an increase in the stream flows during these periods, which was used for electricity production up to 31.41 × 108 kW·h.

Download Full-text

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

Remote Sensing ◽

10.3390/rs12142298 ◽

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.

Download Full-text

Review of Wind Models at a Local Scale: Advantages and Disadvantages

Journal of Marine Science and Engineering ◽

10.3390/jmse9030318 ◽

2021 ◽

Vol 9 (3) ◽

pp. 318

Author(s):

Felix P. Martinez-García ◽

Antonio Contreras-de-Villar ◽

Juan J. Muñoz-Perez

Keyword(s):

Large Scale ◽

Near Field ◽

Wind Farms ◽

Local Scale ◽

Data Driven ◽

Future Scenarios ◽

Global Circulation ◽

Advantages And Disadvantages ◽

Global Circulation Models

Wind forecasts are widely spread because of the growth in wind power, but also because there are other applications to consider, such as the long-term scenario forecasts regarding the effects of global warming. Overall, there have been big developments in global circulation models (GCM) that inform future scenarios at the large scale, but wind forecast at a local scale is a problem that has not totally been solved. It should be possible to estimate the winds in the near field with a certain accuracy, which is interesting for aspects such as the blowing of incident wind at wind farms, the wind on a dune in movement, or the wind blowing in a harbour. Therefore, a data-driven wind transference equation at a local scale is needed. Among the conclusions, it is worthy to state that the statistical downscaling techniques are suitable for application as a statistical inference at small scales. The aim of this paper is therefore to review the current methods and techniques used and show the different methodologies and their applications in the field. Additional targets will be to identify the advantages, disadvantages, or limitations of the current models at the local scale and propose research to find possible improvements.

Download Full-text