A Possible Constraint on Regional Precipitation Intensity Changes under Global Warming

2007 ◽  
Vol 8 (6) ◽  
pp. 1382-1396 ◽  
Author(s):  
W. J. Gutowski ◽  
E. S. Takle ◽  
K. A. Kozak ◽  
J. C. Patton ◽  
R. W. Arritt ◽  
...  
Keyword(s):  
Global Warming ◽  
Gamma Distribution ◽  
Daily Precipitation ◽  
Numerical Models ◽  
Regional Climate ◽  
The United States ◽  
Relative Increase ◽  
Precipitation Intensity ◽  
Total Precipitation ◽  
Precipitation Frequency

Abstract Changes in daily precipitation versus intensity under a global warming scenario in two regional climate simulations of the United States show a well-recognized feature of more intense precipitation. More important, by resolving the precipitation intensity spectrum, the changes show a relatively simple pattern for nearly all regions and seasons examined whereby nearly all high-intensity daily precipitation contributes a larger fraction of the total precipitation, and nearly all low-intensity precipitation contributes a reduced fraction. The percentile separating relative decrease from relative increase occurs around the 70th percentile of cumulative precipitation, irrespective of the governing precipitation processes or which model produced the simulation. Changes in normalized distributions display these features much more consistently than distribution changes without normalization. Further analysis suggests that this consistent response in precipitation intensity may be a consequence of the intensity spectrum’s adherence to a gamma distribution. Under the gamma distribution, when the total precipitation or number of precipitation days changes, there is a single transition between precipitation rates that contribute relatively more to the total and rates that contribute relatively less. The behavior is roughly the same as the results of the numerical models and is insensitive to characteristics of the baseline climate, such as average precipitation, frequency of rain days, and the shape parameter of the precipitation’s gamma distribution. Changes in the normalized precipitation distribution give a more consistent constraint on how precipitation intensity may change when climate changes than do changes in the nonnormalized distribution. The analysis does not apply to extreme precipitation for which the theory of statistical extremes more likely provides the appropriate description.

scholarly journals Statistical analysis of daily precipitation in the Bydgoszcz region

2018 ◽  
Vol 23 ◽  
pp. 00004
Author(s):  
Waldemar Bojar ◽  
Leszek Knopik ◽  
Renata Kuśmierek-Tomaszewska ◽  
Jacek Żarski ◽  
Wojciech Żarski
Keyword(s):  
Statistical Analysis ◽  
Gamma Distribution ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
City Centre ◽  
Total Precipitation ◽  
Precipitation Frequency ◽  
Potential Variation ◽  
The City ◽  
Daily Total

The aim of the research has been to provide a statistical analysis of precipitation in the Bydgoszcz region based on the results of the measurements taken at the Experiment Station of the UTP University of Science and Technology in Bydgoszcz, located at Mochle, about 20 km away from the city centre. The paper analyses the daily total precipitation throughout 43 years (1971—2013). The analysis demonstrated a high dependence of the indicators studied on the month, confirming the annual pattern typical for the transitional climate of the temperate zone. In general, it shows an advantage of the amount and variation, and less considerably — the daily precipitation frequency in summer months, as compared with the winter months. The distribution of the probability of the daily precipitation amount for each month turned out to be compliant with gamma distribution, which allows for a potential variation in the future.

Assessing Goodness of Fit to a Gamma Distribution and Estimating Future Projection on Daily Precipitation Frequency Using Regional Climate Model Simulations over Japan with and without the Influence of Tropical Cyclones

2020 ◽  
Vol 21 (12) ◽  
pp. 2997-3010
Author(s):  
Akihiko Murata ◽  
Shun-ichi I. Watanabe ◽  
Hidetaka Sasaki ◽  
Hiroaki Kawase ◽  
Masaya Nosaka
Keyword(s):  
Tropical Cyclones ◽  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Climate Model ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Precipitation Data ◽  
Precipitation Frequency ◽  
Climate Model Simulations ◽  
Two Parameters

AbstractGoodness of fit in daily precipitation frequency to a gamma distribution was examined, focusing on adverse effects originating from the shortage of sampled tropical cyclones, using precipitation data with and without the influence of tropical cyclones. The data used in this study were obtained through rain gauge observations and regional climate model simulations under the RCP8.5 scenario and the present climate. An empirical cumulative distribution function (CDF), calculated from a sample of precipitation data for each location, was compared with a theoretical CDF derived from two parameters of a gamma distribution. Using these two CDFs, the root-mean-square error (RMSE) was calculated as an indicator of the goodness of fit. The RMSE exhibited a decreasing tendency when the influence of tropical cyclones was removed. This means that the empirical CDF derived from sampled precipitation more closely resembled the theoretical CDF when compared with the relationship between empirical and theoretical CDFs, including precipitation data associated with tropical cyclones. Future changes in the two parameters of the gamma distribution, without the influence of tropical cyclones, depend on regions in Japan, indicating a regional dependence on changes in the shape and scale of the CDF. The magnitude of increases in no-rain days was also dependent on regions of Japan, although the number of no-rain days increased overall. This simplified approach is useful for analyzing climate change from a broad perspective.

Quantifying the Sensitivity of Precipitation to the Long-Term Warming Trend and Interannual–Decadal Variation of Surface Air Temperature over China

2017 ◽  
Vol 30 (10) ◽  
pp. 3687-3703 ◽  
Author(s):  
Chunlüe Zhou ◽  
Kaicun Wang
Keyword(s):  
Global Warming ◽  
Surface Air Temperature ◽  
Heavy Precipitation ◽  
Warming Trend ◽  
Precipitation Intensity ◽  
Total Precipitation ◽  
Decadal Variation ◽  
Precipitation Frequency ◽  
Light Precipitation

Abstract Precipitation is expected to increase under global warming. However, large discrepancies in precipitation sensitivities to global warming among observations and models have been reported, partly owing to the large natural variability of precipitation, which accounts for over 90% of its total variance in China. Here, the authors first elucidated precipitation sensitivities to the long-term warming trend and interannual–decadal variations of surface air temperature Ta over China based on daily data from approximately 2000 stations from 1961 to 2014. The results show that the number of dry, trace, and light precipitation days has stronger sensitivities to the warming trend than to the Ta interannual–decadal variation, with 14.1%, −35.7%, and −14.6% K−1 versus 2.7%, −7.9%, and −3.1% K−1, respectively. Total precipitation frequency has significant sensitivities to the warming trend (−18.5% K−1) and the Ta interannual–decadal variation (−3.6% K−1) over China. However, very heavy precipitation frequencies exhibit larger sensitivities to the Ta interannual–decadal variation than to the long-term trend over Northwest and Northeast China and the Tibetan Plateau. A warming trend boosts precipitation intensity, especially for light precipitation (9.8% K−1). Total precipitation intensity increases significantly by 13.1% K−1 in response to the warming trend and by 3.3% K−1 in response to the Ta interannual–decadal variation. Very heavy precipitation intensity also shows significant sensitivity to the interannual–decadal variation of Ta (3.7% K−1), particularly in the cold season (8.0% K−1). Combining precipitation frequency and intensity, total precipitation amount has a negligible sensitivity to the warming trend, and the consequent trend in China is limited. Moderate and heavy precipitation amounts are dominated by their frequencies.

scholarly journals Clustering of Observed Diurnal Cycles of Precipitation over the United States for Evaluation of a WRF Multiphysics Regional Climate Ensemble

2017 ◽  
Vol 30 (22) ◽  
pp. 9267-9286 ◽  
Author(s):  
P. A. Mooney ◽  
C. Broderick ◽  
C. L. Bruyère ◽  
F. J. Mulligan ◽  
A. F. Prein
Keyword(s):  
United States ◽  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Diurnal Cycle ◽  
Regional Climate ◽  
Wrf Model ◽  
The United States ◽  
Total Precipitation ◽  
Precipitation Frequency ◽  
Diurnal Cycle Of Precipitation

The diurnal cycle of precipitation during the summer season over the contiguous United States is examined in eight distinct regions. These were identified using cluster analysis applied to the diurnal cycle characteristics at 2141 rainfall gauges over the 10-yr period 1991–2000. Application of the clustering technique provides a physically meaningful way of identifying regions for comparison of model results with observations. The diurnal cycle for each region is specified in terms of 1) total precipitation, 2) frequency of precipitation occurrence, and 3) intensity of precipitation per occurrence on an hourly basis averaged over the 10-yr period. The amplitude and phase of each element of the diurnal cycle was obtained from harmonic analysis and has been compared with the results of a 24-member multiphysics ensemble of simulations produced by the Weather Research and Forecast (WRF) Model on a region-by-region basis. Three cumulus schemes, two radiation schemes, two microphysics schemes, and two planetary boundary layer schemes were included in the ensemble. Simulations of total precipitation showed reasonable agreement with observations in regions where the diurnal cycle is directly influenced by solar radiation, (e.g., the U.S. Southeast), but they were less successful in regions where other factors influence the diurnal cycle (e.g., the central United States). The diurnal cycle of precipitation frequency and intensity showed substantial biases in the simulations of all eight regions, namely, overestimation of occurrences and underestimation of intensities. Simulations were sensitive to the cumulus and radiation schemes but were largely insensitive to either microphysics or planetary boundary layer schemes.

How Often Will It Rain?

2007 ◽  
Vol 20 (19) ◽  
pp. 4801-4818 ◽  
Author(s):  
Ying Sun ◽  
Susan Solomon ◽  
Aiguo Dai ◽  
Robert W. Portmann
Keyword(s):  
Climate Change ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Heavy Precipitation ◽  
Precipitation Intensity ◽  
First Century ◽  
Simultaneous Increase ◽  
Percentage Increase ◽  
Precipitation Frequency ◽  
Twenty First Century

Abstract Daily precipitation data from climate change simulations using the latest generation of coupled climate system models are analyzed for potential future changes in precipitation characteristics. For the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1 (a low projection), A1B (a medium projection), and A2 (a high projection) during the twenty-first century, all the models consistently show a shift toward more intense and extreme precipitation for the globe as a whole and over various regions. For both SRES B1 and A2, most models show decreased daily precipitation frequency and all the models show increased daily precipitation intensity. The multimodel averaged percentage increase in the precipitation intensity (2.0% K−1) is larger than the magnitude of the precipitation frequency decrease (−0.7% K−1). However, the shift in precipitation frequency distribution toward extremes results in large increases in very heavy precipitation events (>50 mm day−1), so that for very heavy precipitation, the percentage increase in frequency is much larger than the increase in intensity (31.2% versus 2.4%). The climate model projected increases in daily precipitation intensity are, however, smaller than that based on simple thermodynamics (∼7% K−1). Multimodel ensemble means show that precipitation amount increases during the twenty-first century over high latitudes, as well as over currently wet regions in low- and midlatitudes more than other regions. This increase mostly results from a combination of increased frequency and intensity. Over the dry regions in the subtropics, the precipitation amount generally declines because of decreases in both frequency and intensity. This indicates that wet regions may get wetter and dry regions may become drier mostly because of a simultaneous increase (decrease) of precipitation frequency and intensity.

scholarly journals Simulated Changes in Northwest U.S. Climate in Response to Amazon Deforestation*

2013 ◽  
Vol 26 (22) ◽  
pp. 9115-9136 ◽  
Author(s):  
David Medvigy ◽  
Robert L. Walko ◽  
Martin J. Otte ◽  
Roni Avissar
Keyword(s):  
United States ◽  
Sierra Nevada ◽  
Numerical Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
The United States ◽  
Far Field ◽  
Adequate Model ◽  
Thermal Anomalies ◽  
The Andes

Abstract Numerical models have long predicted that the deforestation of the Amazon would lead to large regional changes in precipitation and temperature, but the extratropical effects of deforestation have been a matter of controversy. This paper investigates the simulated impacts of deforestation on the northwest United States December–February climate. Integrations are carried out using the Ocean–Land–Atmosphere Model (OLAM), here run as a variable-resolution atmospheric GCM, configured with three alternative horizontal grid meshes: 1) 25-km characteristic length scale (CLS) over the United States, 50-km CLS over the Andes and Amazon, and 200-km CLS in the far-field; 2) 50-km CLS over the United States, 50-km CLS over the Andes and Amazon, and 200-km CLS in the far-field; and 3) 200-km CLS globally. In the high-resolution simulations, deforestation causes a redistribution of precipitation within the Amazon, accompanied by vorticity and thermal anomalies. These anomalies set up Rossby waves that propagate into the extratropics and impact western North America. Ultimately, Amazon deforestation results in 10%–20% precipitation reductions for the coastal northwest United States and the Sierra Nevada. Snowpack in the Sierra Nevada experiences declines of up to 50%. However, in the coarse-resolution simulations, this mechanism is not resolved and precipitation is not reduced in the northwest United States. These results highlight the need for adequate model resolution in modeling the impacts of Amazon deforestation. It is concluded that the deforestation of the Amazon can act as a driver of regional climate change in the extratropics, including areas of the western United States that are agriculturally important.

scholarly journals Changes in Observed Daily Precipitation over Global Land Areas since 1950

2021 ◽  
Vol 34 (1) ◽  
pp. 3-19
Author(s):  
Steefan Contractor ◽  
Markus G. Donat ◽  
Lisa V. Alexander
Keyword(s):  
Daily Precipitation ◽  
The United States ◽  
Climatic Changes ◽  
High Quality ◽  
Precipitation Frequency ◽  
Uncertainty Estimates ◽  
Global Land ◽  
Intensity Changes ◽  
Entire Distribution

AbstractEstimates of observed long-term changes in daily precipitation globally have been limited due to availability of high-quality observations. In this study, a new gridded dataset of daily precipitation, called Rainfall Estimates on a Gridded Network (REGEN) V1–2019, was used to perform an assessment of the climatic changes in precipitation at each global land location (except Antarctica). This study investigates changes in the number of wet days (≥1 mm) and the entire distribution of daily wet- and all-day records, in addition to trends in annual and seasonal totals from daily records, between 1950 and 2016. The main finding of this study is that precipitation has intensified across a majority of land areas globally throughout the wet-day distribution. This means that when it rains, light, moderate, or heavy wet-day precipitation has become more intense across most of the globe. Widespread increases in the frequency of wet days are observed across Asia and the United States, and widespread increases in the precipitation intensity are observed across Europe and Australia. Based on a comparison of spatial pattern of changes in frequency, intensity, and the distribution of daily totals, we propose that changes in light and moderate precipitation are characterized by changes in precipitation frequency, whereas changes in extreme precipitation are primarily characterized by intensity changes. Based on the uncertainty estimates from REGEN, this study highlights all results in the context of grids with high-quality observations.

scholarly journals A Changing Climatology of Precipitation Persistence across the United States Using Information-Based Measures

2019 ◽  
Vol 20 (8) ◽  
pp. 1649-1666 ◽  
Author(s):  
Allison E. Goodwell ◽  
Praveen Kumar
Keyword(s):  
United States ◽  
Time Scales ◽  
Daily Precipitation ◽  
Temporal Trends ◽  
The United States ◽  
Binary Sequences ◽  
Precipitation Frequency ◽  
Climate Trend ◽  
Information Measures ◽  
Time Lagged

Abstract The sequencing, or persistence, of daily precipitation influences variability in streamflow, soil moisture, and vegetation states. As these factors influence water availability and ecosystem health, it is important to identify spatial and temporal trends in precipitation persistence and predictability. We take an information theoretic perspective to address regional and temporal trends in daily patterns, based on the Climate Prediction Center (CPC) gridded gauge-based dataset of daily precipitation over the continental United States from 1948 to 2018. We apply information measures to binary sequences of precipitation occurrence to quantify uncertainty, predictability in the form of lagged mutual information between the current state and two time-lagged histories, and associated dominant time scales. We find that this information-based predictability is highest in the western United States, but the relative influence of longer lagged histories in comparison to a 1-day history is highest in the east. Information characteristics and time scales vary seasonally and regionally and constitute an information climatology that can be compared with traditional indices of precipitation and climate. Trend analyses over the 70-yr time period also show varying regional characteristics that differ between seasons. In addition to increasing precipitation frequency over most of the country, we detect increasing and decreasing predictability in western and eastern regions, respectively, with average trend magnitudes corresponding to shifts in predictability ranging from −50% to 110%. This new perspective on precipitation persistence has broad potential to link shifts in climate and weather to patterns and predictability of related environmental factors.

Simulation of Northeast U.S. Extreme Precipitation and Its Associated Circulation by CMIP5 Models

2020 ◽  
Vol 33 (22) ◽  
pp. 9817-9834
Author(s):  
Laurie Agel ◽  
Mathew Barlow ◽  
Joseph Polonia ◽  
David Coe
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Coupled Model ◽  
Precipitation Intensity ◽  
Cmip5 Models ◽  
Seasonal Cycles ◽  
Precipitation Frequency ◽  
Circulation Patterns ◽  
Intercomparison Project ◽  
Approximate Magnitude

AbstractHistorical simulations from 14 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to reproduce observed precipitation in the northeastern United States and its associated circulation, with particular emphasis on extreme (top 1%) precipitation. The models are compared to observations in terms of the spatial variations of extreme precipitation, seasonal cycles of precipitation and extreme precipitation frequency and intensity, and extreme precipitation circulation regimes. The circulation regimes are identified using k-means clustering of 500-hPa geopotential heights on extreme precipitation days, in both observations and in the models. While all models capture an observed northwest-to-southeast gradient of precipitation intensity (reflected in the top 1% threshold), there are substantial differences from observations in the magnitude of the gradient. These differences tend to be more substantial for lower-resolution models. However, regardless of resolution, and despite a bias toward too-frequent precipitation, many of the models capture the seasonality of observed daily precipitation intensity, and the approximate magnitude and seasonality of observed extreme precipitation intensity. Many of the simulated extreme precipitation circulation patterns are visually similar to the set of observed patterns. However, the location and magnitude of specific troughs and ridges within the patterns, as well as the seasonality of the patterns, may differ substantially from the observed corresponding patterns. A series of metrics is developed based on the observed regional characteristics to facilitate comparison between models.

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