Exploring the joint probability of precipitation and soil moisture over Europe using copulas
<p>The joint probability of precipitation and soil moisture is here investigated over Europe with the goal to extrapolate meaningful insights into the potential joint use of these variables for the detection of agricultural droughts within a multivariate probabilistic modeling framework. The u...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2024-01-01
|
| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://hess.copernicus.org/articles/28/103/2024/hess-28-103-2024.pdf |
| _version_ | 1797364837429280768 |
|---|---|
| author | C. Cammalleri C. Cammalleri C. De Michele A. Toreti |
| author_facet | C. Cammalleri C. Cammalleri C. De Michele A. Toreti |
| author_sort | C. Cammalleri |
| collection | DOAJ |
| description | <p>The joint probability of precipitation and soil moisture is here investigated over Europe with the goal to extrapolate meaningful insights into the potential joint use of these variables for the detection of agricultural droughts within a multivariate probabilistic modeling framework. The use of copulas is explored, being the framework often used in hydrological studies for the analysis of bivariate distributions. The analysis is performed for the period 1996–2020 on the empirical frequencies derived from ERA5 precipitation and LISFLOOD soil moisture datasets, both available as part of the Copernicus European Drought Observatory. The results show an overall good correlation between the two standardized series (Kendall's <span class="inline-formula"><i>τ</i>=</span> <span class="inline-formula">0.42±0.1</span>) but also clear spatial patterns in the tail dependence derived with both non-parametric and parametric approaches. About half of the domain shows symmetric tail dependence, well reproduced by the Student's <span class="inline-formula"><i>t</i></span> copula, whereas the rest of the domain is almost equally split between low- and high-tail dependences (both modeled with the Gumbel family of copulas). These spatial patterns are reasonably reproduced by a random forest classifier, suggesting that this outcome is not driven by chance. This study stresses how a joint use of standardized precipitation and soil moisture for agriculture drought characterization may be beneficial in areas with strong low-tail dependence and how this behavior should be carefully considered in multivariate drought studies.</p> |
| first_indexed | 2024-03-08T16:40:49Z |
| format | Article |
| id | doaj.art-191f2e49eb73430385d46161c180e742 |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-03-08T16:40:49Z |
| publishDate | 2024-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-191f2e49eb73430385d46161c180e7422024-01-05T10:14:13ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382024-01-012810311510.5194/hess-28-103-2024Exploring the joint probability of precipitation and soil moisture over Europe using copulasC. Cammalleri0C. Cammalleri1C. De Michele2A. Toreti3Dipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Milan, 20133, ItalyEuropean Commission, Joint Research Centre (JRC), Ispra, 21027, ItalyDipartimento di Ingegneria Civile e Ambientale (DICA), Politecnico di Milano, Milan, 20133, ItalyEuropean Commission, Joint Research Centre (JRC), Ispra, 21027, Italy<p>The joint probability of precipitation and soil moisture is here investigated over Europe with the goal to extrapolate meaningful insights into the potential joint use of these variables for the detection of agricultural droughts within a multivariate probabilistic modeling framework. The use of copulas is explored, being the framework often used in hydrological studies for the analysis of bivariate distributions. The analysis is performed for the period 1996–2020 on the empirical frequencies derived from ERA5 precipitation and LISFLOOD soil moisture datasets, both available as part of the Copernicus European Drought Observatory. The results show an overall good correlation between the two standardized series (Kendall's <span class="inline-formula"><i>τ</i>=</span> <span class="inline-formula">0.42±0.1</span>) but also clear spatial patterns in the tail dependence derived with both non-parametric and parametric approaches. About half of the domain shows symmetric tail dependence, well reproduced by the Student's <span class="inline-formula"><i>t</i></span> copula, whereas the rest of the domain is almost equally split between low- and high-tail dependences (both modeled with the Gumbel family of copulas). These spatial patterns are reasonably reproduced by a random forest classifier, suggesting that this outcome is not driven by chance. This study stresses how a joint use of standardized precipitation and soil moisture for agriculture drought characterization may be beneficial in areas with strong low-tail dependence and how this behavior should be carefully considered in multivariate drought studies.</p>https://hess.copernicus.org/articles/28/103/2024/hess-28-103-2024.pdf |
| spellingShingle | C. Cammalleri C. Cammalleri C. De Michele A. Toreti Exploring the joint probability of precipitation and soil moisture over Europe using copulas Hydrology and Earth System Sciences |
| title | Exploring the joint probability of precipitation and soil moisture over Europe using copulas |
| title_full | Exploring the joint probability of precipitation and soil moisture over Europe using copulas |
| title_fullStr | Exploring the joint probability of precipitation and soil moisture over Europe using copulas |
| title_full_unstemmed | Exploring the joint probability of precipitation and soil moisture over Europe using copulas |
| title_short | Exploring the joint probability of precipitation and soil moisture over Europe using copulas |
| title_sort | exploring the joint probability of precipitation and soil moisture over europe using copulas |
| url | https://hess.copernicus.org/articles/28/103/2024/hess-28-103-2024.pdf |
| work_keys_str_mv | AT ccammalleri exploringthejointprobabilityofprecipitationandsoilmoistureovereuropeusingcopulas AT ccammalleri exploringthejointprobabilityofprecipitationandsoilmoistureovereuropeusingcopulas AT cdemichele exploringthejointprobabilityofprecipitationandsoilmoistureovereuropeusingcopulas AT atoreti exploringthejointprobabilityofprecipitationandsoilmoistureovereuropeusingcopulas |