Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates
Abstract Short‐duration precipitation extremes (PE) increase at a rate of around 7%/K explained by the Clausius‐Clapeyron relationship. Previous studies show uncertainty in the extreme precipitation‐temperature relationship (scaling) due to various thermodynamic/dynamic factors. Here, we show that u...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-06-01
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| Series: | Geophysical Research Letters |
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| Online Access: | https://doi.org/10.1029/2022GL099138 |
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| _version_ | 1832591255512547328 |
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| author | Haider Ali Hayley J. Fowler David Pritchard Geert Lenderink Stephen Blenkinsop Elizabeth Lewis |
| author_facet | Haider Ali Hayley J. Fowler David Pritchard Geert Lenderink Stephen Blenkinsop Elizabeth Lewis |
| author_sort | Haider Ali |
| collection | DOAJ |
| description | Abstract Short‐duration precipitation extremes (PE) increase at a rate of around 7%/K explained by the Clausius‐Clapeyron relationship. Previous studies show uncertainty in the extreme precipitation‐temperature relationship (scaling) due to various thermodynamic/dynamic factors. Here, we show that uncertainty may arise from the choice of data and methods. Using hourly precipitation (PPT) and daily dewpoint temperature (DPT) across 2,905 locations over the United States, we found higher scaling for quality‐controlled data, all locations showing positive (median 6.2%/K) scaling, as compared to raw data showing positive (median 5.3%/K) scaling over 97.5% of locations. We found higher scaling for higher measurement precision of PPT (0.25 mm: median 7.8%/K; 2.54 mm: median 6.6%/K). The method that removes seasonality in PPT and DPT gives higher (with seasonality: median 6.2%/K; without seasonality: median 7.2%/K) scaling. Our results demonstrate the importance of quality‐controlled, high‐precision observations and robust methods in estimating accurate scaling for a better understanding of PE change with warming. |
| format | Article |
| id | doaj-art-b32cfa08e8ed42c08fe452f39f502ecd |
| institution | Kabale University |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2022-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geophysical Research Letters |
| spelling | doaj-art-b32cfa08e8ed42c08fe452f39f502ecd2025-01-22T14:38:16ZengWileyGeophysical Research Letters0094-82761944-80072022-06-014912n/an/a10.1029/2022GL099138Towards Quantifying the Uncertainty in Estimating Observed Scaling RatesHaider Ali0Hayley J. Fowler1David Pritchard2Geert Lenderink3Stephen Blenkinsop4Elizabeth Lewis5School of Engineering Newcastle University Newcastle upon Tyne UKSchool of Engineering Newcastle University Newcastle upon Tyne UKSchool of Engineering Newcastle University Newcastle upon Tyne UKRoyal Netherlands Meteorological Institute De Bilt The NetherlandsSchool of Engineering Newcastle University Newcastle upon Tyne UKSchool of Engineering Newcastle University Newcastle upon Tyne UKAbstract Short‐duration precipitation extremes (PE) increase at a rate of around 7%/K explained by the Clausius‐Clapeyron relationship. Previous studies show uncertainty in the extreme precipitation‐temperature relationship (scaling) due to various thermodynamic/dynamic factors. Here, we show that uncertainty may arise from the choice of data and methods. Using hourly precipitation (PPT) and daily dewpoint temperature (DPT) across 2,905 locations over the United States, we found higher scaling for quality‐controlled data, all locations showing positive (median 6.2%/K) scaling, as compared to raw data showing positive (median 5.3%/K) scaling over 97.5% of locations. We found higher scaling for higher measurement precision of PPT (0.25 mm: median 7.8%/K; 2.54 mm: median 6.6%/K). The method that removes seasonality in PPT and DPT gives higher (with seasonality: median 6.2%/K; without seasonality: median 7.2%/K) scaling. Our results demonstrate the importance of quality‐controlled, high‐precision observations and robust methods in estimating accurate scaling for a better understanding of PE change with warming.https://doi.org/10.1029/2022GL099138rain‐gauge dataextreme precipitationdewpoint temperaturequality‐controlscalingobserved precipitation |
| spellingShingle | Haider Ali Hayley J. Fowler David Pritchard Geert Lenderink Stephen Blenkinsop Elizabeth Lewis Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates Geophysical Research Letters rain‐gauge data extreme precipitation dewpoint temperature quality‐control scaling observed precipitation |
| title | Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates |
| title_full | Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates |
| title_fullStr | Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates |
| title_full_unstemmed | Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates |
| title_short | Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates |
| title_sort | towards quantifying the uncertainty in estimating observed scaling rates |
| topic | rain‐gauge data extreme precipitation dewpoint temperature quality‐control scaling observed precipitation |
| url | https://doi.org/10.1029/2022GL099138 |
| work_keys_str_mv | AT haiderali towardsquantifyingtheuncertaintyinestimatingobservedscalingrates AT hayleyjfowler towardsquantifyingtheuncertaintyinestimatingobservedscalingrates AT davidpritchard towardsquantifyingtheuncertaintyinestimatingobservedscalingrates AT geertlenderink towardsquantifyingtheuncertaintyinestimatingobservedscalingrates AT stephenblenkinsop towardsquantifyingtheuncertaintyinestimatingobservedscalingrates AT elizabethlewis towardsquantifyingtheuncertaintyinestimatingobservedscalingrates |