Journal articles: 'Precipitation variability'

1

Maradin, Mladen, and Anita Filipčić. "Spatial Differences in Precipitation Variability of Central Croatia." Hrvatski geografski glasnik/Croatian Geographical Bulletin 74, no. 1 (September 17, 2012): 41–59. http://dx.doi.org/10.21861/hgg.2012.74.01.03.

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Ozcelik, Ceyhun. "A Regional Approach for Investigation of Temporal Precipitation Changes." Sustainability 13, no. 10 (May 20, 2021): 5733. http://dx.doi.org/10.3390/su13105733.

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Climatic variability is one of the fundamental aspects of the climate. Our scope of knowledge of this variability is limited by unavailable long-term high-resolution spatial data. Climatic simulations indicate that warmer climate increases extreme precipitations but decreases high-frequency temperature variability. As an important climatologic variable, the precipitation is reported by the IPCC to increase in mid and high altitudes and decrease in subtropical areas. On a regional scale, such a change needs spatio-parametric justification. In this regard, a regionalization approach relying on frequency characteristics and parameters of heavy precipitation may provide better insight into temporal precipitation changes, and thus help us to understand climatic variability and extremes. This study introduces the “index precipitation method”, which aims to define hydrologic homogeneous regions throughout which the frequency distribution of monthly maximum hourly precipitations remains the same and, therefore, investigate whether there are significant temporal precipitation changes in these regions. Homogenous regions are defined based on L-moment ratios of frequency distributions via cluster analysis and considering the spatial contiguity of gauging sites via GIS. Regarding the main hydrologic characteristics of heavy precipitation, 12 indices are defined in order to investigate the existence of regional trends by means of t- and Mann–Kendall tests for determined homogenous regions with similar frequency behaviors. The case study of Japan, using hourly precipitation data on 150 gauges for 1991–2010, shows that trends that statistically exist for single-site observations should be regionally proved. Trends of heavy precipitation have region-specific properties across Japan. Homogenous regions beneficially define statistically significant trends for heavy precipitation.

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Amundsen, Eirik S., and Sigve Tjøtta. "Hydroelectric rent and precipitation variability." Energy Economics 15, no. 2 (April 1993): 81–91. http://dx.doi.org/10.1016/0140-9883(93)90026-n.

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Maradin, Mladen. "Varijabilnost padalina na području Hrvatske s maritimnim pluviometrijskim režimom." Geoadria 18, no. 1 (June 1, 2013): 3. http://dx.doi.org/10.15291/geoadria.142.

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The paper deals with the precipitation variability areas of Croatia with pluviometric regime. Precipitation variability was analyzed using yearly and monthly values of the mean relative variability for 18 stations in the period 1950-2007. The research results showed that there is relatively large range of precipitation variability in the researched area. The highest precipitation variability was recorded in Lastovo and the lowest in Parg station. The primary maximum of precipitation variability in the northern Adriatic area is in October, while in the southern part of the Adriatic maximum variability occurs during the summer months - July or August. The minimum variability in most of the stations with maritime pluviometric regime occurs in April, except in the central part of the Adriatic, where it occurs in November. The lowest precipitation variability is in the mountain region of Croatia. The highest values of precipitation variability occur during summer months in the southern part of Adriatic. The values of precipitation variability in the Kvarner region are relatively higher than the variability of the surrounding stations in almost all months.

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Leščešen, Igor, Dragan Milošević, and Rastislav Stojsavljević. "Variability and trends of precipitation on lowand high-altitude stations in Serbia." Zbornik radova Departmana za geografiju, turizam i hotelijerstvo, no. 50-1 (2021): 14–23. http://dx.doi.org/10.5937/zbdght2101014l.

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For the trend analysis of the annual, seasonal and monthly precipitation linear regression and Mann-Kendall (MK) tests at the 5% significance level were applied. In this study, precipitation data from two stations in Serbia for the 1949-2019 period were used. Results indicate that increasing trends of precipitation for the selected station can be observed but these trends were not statistically significant according to MK test. Then again, MK test has shown that only on Palić station during autumn precipitations have statistically significant increase during the observed period with a p value of 0.0441 at the significant level p=0.005.

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Kienzler, P. M., and F. Naef. "Temporal variability of subsurface stormflow formation." Hydrology and Earth System Sciences Discussions 4, no. 4 (July 5, 2007): 2143–67. http://dx.doi.org/10.5194/hessd-4-2143-2007.

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Abstract. Subsurface storm flow (SSF) can play a key role for the runoff generation at hillslopes. Quantifications of SSF suffer from the limited understanding of how SSF is formed and how it varies in time and space. This study concentrates on the temporal variability of SSF formation. Controlled sprinkling experiments at three experimental slopes were replicated with varying precipitation intensity and varying antecedent precipitation. SSF characteristics were observed with hydrometric measurements and tracer experiments. SSF response was affected in different ways and to varying degree by changes of precipitation intensity and antecedent precipitation. The study showed that the influence of antecedent soil moisture on SSF response depends on the type of SSF formation. Formation of subsurface stormflow was hardly influenced by the increase of precipitation intensity. As a consequence, subsurface flow rates were not increased by higher precipitation intensity. Different soil structures determined runoff formation at different precipitation intensities. Saturation and flow formation occurred at the base of the soil, but also within the topsoil during high precipitation intensity. This implies that timing and magnitude of flow response can change substantially at different precipitation intensities.

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Ramaroson, Voahirana, Joel Rajaobelison, Lahimamy P. Fareze, Falintsoa A. Razafitsalama, Mamiseheno Rasolofonirina, and Christian U. Rakotomalala. "Water Stable Isotope Composition of Precipitations at Two Stations in Antananarivo-Madagascar: A Comparative Study." Earth Science Research 11, no. 1 (January 26, 2022): 1. http://dx.doi.org/10.5539/esr.v11n1p1.

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In the “Global Network of Isotopes in Precipitation” database, Antananarivo has two distinct datasets from two stations. Thirty-four years separate the two datasets. This study aims on the one hand to depict the variations of the water stable isotopes composition of precipitations from the two stations and understand their origins, mainly in relation to meteorological factors. On the other hand, the Antananarivo data are compared with regional and international data to identify other sources of isotope composition variability in precipitation. Isotope records showed that after thirty-four-year gap, summer and winter (the two main seasons) precipitations are more enriched in heavy isotopes. The precipitation amount fluctuation would mostly contribute to this temporal variation. Opposite to summer and winter precipitations, inter-season rainfalls have similar isotope values after thirty-four years. The two stations are geographically close and the spatial aspect is therefore negligible since there are no latitude nor altitude effects on the isotope composition of precipitations. Regarding the second order parameter d-excess, the monthly mean values from both stations are higher than 100/00 and could indicate moisture recycling. The comparison with regional/international data showed that the isotope variability in precipitation is primarily due to precipitation amount effect, different moisture source, the stations distance from it and the change of meteorological factors along the moisture trajectory.

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Kienzler, P. M., and F. Naef. "Temporal variability of subsurface stormflow formation." Hydrology and Earth System Sciences 12, no. 1 (February 18, 2008): 257–65. http://dx.doi.org/10.5194/hess-12-257-2008.

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Abstract. Subsurface stormflow (SSF) can play a key role for the runoff generation at hillslopes. Quantifications of SSF suffer from the limited ability to predict how SSF is formed at a particular hillslope and how it varies in time and space. This study concentrates on the temporal variability of SSF formation. Controlled sprinkling experiments at three experimental slopes were replicated with varying precipitation intensity and varying antecedent precipitation. SSF characteristics were observed with hydrometric measurements and tracer experiments. SSF response was affected in different ways and to varying degree by changes of precipitation intensity and antecedent precipitation. The study showed that the influence of antecedent precipitation on SSF response depends on how SSF is formed at a particular hillslope. As formation of SSF was hardly influenced by the increase of precipitation intensity subsurface flow rates were not increased by higher intensity. However, timing and relevance of subsurface flow response changed substantially at different precipitation intensities, because saturation and flow formation occurred above the soil-bedrock interface, but also within the topsoil depending on precipitation intensity.

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9

Chelton, Dudley B., and Craig M. Risien. "A Hybrid Precipitation Index Inspired by the SPI, PDSI, and MCDI. Part II: Application to Investigate Precipitation Variability along the West Coast of North America." Journal of Hydrometeorology 21, no. 9 (September 1, 2020): 1977–2002. http://dx.doi.org/10.1175/jhm-d-19-0231.1.

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AbstractThe hybrid precipitation index developed in Part I of this study is applied to investigate precipitation variability along the west coast of North America during the wet season November–March on monthly-to-interannual time scales. The variability in each of six regions considered in this study is negatively correlated with nearby 500-hPa geopotential height anomalies. Except in Southeast Alaska, these correlation patterns indicate that precipitation variability in each region is predominantly influenced by local atmospheric forcing analogous to the ridging of the westerly flow that has been studied extensively with regard to California drought variability. The first empirical orthogonal function (EOF) accounts for nearly all of the Southeast Alaska precipitation variability, which is controlled by the strength of the onshore flow rather than ridging. In association with this mode of variability, precipitation anomalies of opposite sign account for about 40% of the precipitation variance in Northern California and Oregon on all time scales. On short time scales, the second and third EOFs account primarily for precipitation variability in British Columbia/Washington and California, respectively. With increasing time scale, the third EOF diminishes in importance and the second EOF evolves into a pattern of synchronous precipitation anomalies of the same sign from British Columbia to Northern California. Precipitation variability in Southern California is only modestly related to precipitation elsewhere. With increasing time scale, Southern California precipitation variability becomes increasingly related to precipitation anomalies of opposite sign in Washington.

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10

Maradin, Mladen, and Ivan Madžar. "Geographical Distribution of Precipitation Variability in Croatia and Bosnia and Herzegovina." Hrvatski geografski glasnik/Croatian Geographical Bulletin 76, no. 2 (February 23, 2015): 5–26. http://dx.doi.org/10.21861/hgg.2014.76.02.01.

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11

Zhao, C., Y. Ding, B. Ye, S. Yao, Q. Zhao, Z. Wang, and Y. Wang. "An analyses of long-term precipitation variability based on entropy over Xinjiang, northwestern China." Hydrology and Earth System Sciences Discussions 8, no. 2 (March 28, 2011): 2975–99. http://dx.doi.org/10.5194/hessd-8-2975-2011.

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Abstract. Precipitation is one of important supply of water resources in arid and semiarid region of northwestern China, plays the vital role to maintain the fragile ecosystem. The entropy method was employed to detect the spatial variability of precipitation over monthly, seasonal and annual timescales in Xinjiang. The spatial distribution of precipitation variability was significantly affected by topography, and was zonal on annual, seasonal and monthly. The non-parametric Mann-kendall test was used to analyze the change point of trend. A precipitation concentration index has been developed categorize the variability of annual precipitation. The summer variability contributed less than that of other seasons to the annual variability. There is a great difference in the contribution of the different monthly variabilities to the annual mean variability in different years. Overall, the variability of precipitation was shown increase north of Xinjiang, especially in mountainous regions where the increase was statistically (P = 0.05) significant. South of the Xinjiang, the variability increased only slightly, consistent with the distribution of precipitation.

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12

Maradin, Mladen. "Varijabilnost padalina u Osijeku." Hrvatski geografski glasnik/Croatian Geographical Bulletin 69, no. 02 (January 2008): 53–77. http://dx.doi.org/10.21861/hgg.2007.69.02.04.

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13

Rossel, F., and J. Garbrecht. "Spatial variability and downscalling of precipitation." Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere 26, no. 11-12 (January 2001): 863–67. http://dx.doi.org/10.1016/s1464-1909(01)00098-3.

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14

Rajagopalan, B., and U. Lall. "Interannual variability in western US precipitation." Journal of Hydrology 210, no. 1-4 (September 1998): 51–67. http://dx.doi.org/10.1016/s0022-1694(98)00184-x.

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15

Persson, S., A. Aldahan, G. Possnert, V. Alfimov, and X. Hou. "129I Variability in precipitation over Europe." Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 259, no. 1 (June 2007): 508–12. http://dx.doi.org/10.1016/j.nimb.2007.01.193.

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16

Cortesi, Nicola, José Carlos Gonzalez-Hidalgo, Michele Brunetti, and Martín de Luis. "Spatial variability of precipitation in Spain." Regional Environmental Change 14, no. 5 (January 16, 2013): 1743–49. http://dx.doi.org/10.1007/s10113-012-0402-6.

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17

Scinocca, John F., and Norman A. McFarlane. "The Variability of Modeled Tropical Precipitation." Journal of the Atmospheric Sciences 61, no. 16 (August 2004): 1993–2015. http://dx.doi.org/10.1175/1520-0469(2004)061<1993:tvomtp>2.0.co;2.

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18

Ahmad, Iftikhar, Romana Ambreen, Zhaobo Sun, and Weitao Deng. "Winter-Spring Precipitation Variability in Pakistan." American Journal of Climate Change 04, no. 01 (2015): 115–39. http://dx.doi.org/10.4236/ajcc.2015.41010.

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19

Adeniyi, M. O. "Variability of daily precipitation over Nigeria." Meteorology and Atmospheric Physics 126, no. 3-4 (August 20, 2014): 161–76. http://dx.doi.org/10.1007/s00703-014-0340-6.

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20

Álvarez-García, Francisco J., Pilar M. Lorente-Lorente, and María J. OrtizBevia. "Quasi-quadrennial variability in European precipitation." International Journal of Climatology 32, no. 9 (May 17, 2011): 1295–309. http://dx.doi.org/10.1002/joc.2351.

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21

Sun, Bo, and Huijun Wang. "Interannual Variation of the Spring and Summer Precipitation over the Three River Source Region in China and the Associated Regimes." Journal of Climate 31, no. 18 (September 2018): 7441–57. http://dx.doi.org/10.1175/jcli-d-17-0680.1.

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This study analyzes the interannual and interdecadal variability of spring and summer precipitation over the Three River Source (TRS) region in China using four datasets. A general consistency is revealed among the four datasets with regard to the interannual and interdecadal variability of TRS precipitation during 1979–2015, demonstrating a confidence of the four datasets in representing the precipitation variability over the TRS region. The TRS spring and summer precipitation shows distinct interannual and interdecadal variability, with an overall increasing trend in the spring precipitation and an interdecadal oscillation in the summer precipitation. The regimes associated with the interannual variability of TRS spring and summer precipitation are further investigated. The interannual variability of TRS spring precipitation is essentially modulated by an anomalous easterly water vapor transport (WVT) branch associated with the leading mode of Eurasian spring circulation. El Niño–Southern Oscillation (ENSO) may affect the interannual variability of TRS spring precipitation by causing southerly WVT anomalies toward the TRS region. The interannual variability of TRS summer precipitation is essentially modulated by an anomalous southwesterly WVT branch over the TRS region, which is mainly associated with a Eurasian wave train connected with the summer North Atlantic Oscillation. A strong East Asian summer monsoon and an El Niño–decaying summer may also contribute to the southwesterly WVT anomalies over the TRS region.

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Mwale, Davison, Thian Yew Gan, Kevin Devito, Carl Mendoza, Uldis Silins, and Richard Petrone. "Precipitation variability and its relationship to hydrologic variability in Alberta." Hydrological Processes 23, no. 21 (October 15, 2009): 3040–56. http://dx.doi.org/10.1002/hyp.7415.

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23

Shiu, Janice, Sarah Fletcher, and Dara Entekhabi. "Spatiotemporal monsoon characteristics and maize yields in West Africa." Environmental Research Communications 3, no. 12 (December 1, 2021): 125007. http://dx.doi.org/10.1088/2515-7620/ac3776.

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Abstract To assess the vulnerability of rainfed agriculture in West Africa (WA) to climate change, a detailed understanding of the relationship between food crop yields and seasonal rainfall characteristics is required. The highly seasonal rainfall in the region is expected to change characteristics such as seasonal timing, duration, intensity, and intermittency. The food crop yield response to changes in these characteristics needs greater understanding. We follow a data-driven approach based on historical yield and climate data. Such an approach complements model-based approaches. Previous data-driven studies use spatially and temporally averaged precipitation measures, which do not describe the high degree of spatial and temporal variability of the West African Monsoon (WAM), the primary source of water for agriculture in the region. This has led previous studies to find small or insignificant dependence of crop yields on precipitation amount. Here, we develop metrics that characterize important temporal features and variability in growing season precipitation, including total precipitation, onset and duration of the WAM, and number of non-precipitating days. For each temporal precipitation metric, we apply several unique spatial aggregation functions that allow us to assess how different patterns of high-resolution spatial variability are related to country-level maize yields. We develop correlation analyses between spatiotemporal precipitation metrics and detrended country-level maize yields based on findings that non-climatic factors, such as agricultural policy reform and increased investment, have driven the region’s long-term increase in maize yields. Results show that that the variability in the number of days without rain during the monsoon season and the lower bounds to the spatial rain pattern and end to the monsoon season are most strongly associated with maize yields. Our findings highlight the importance of considering spatial and temporal variability in precipitation when evaluating impacts on crop yields, providing a possible explanation for weak connections found in previous studies.

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Petković, Veljko, Marko Orescanin, Pierre Kirstetter, Christian Kummerow, and Ralph Ferraro. "Enhancing PMW Satellite Precipitation Estimation: Detecting Convective Class." Journal of Atmospheric and Oceanic Technology 36, no. 12 (December 2019): 2349–63. http://dx.doi.org/10.1175/jtech-d-19-0008.1.

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AbstractA decades-long effort in observing precipitation from space has led to continuous improvements of satellite-derived passive microwave (PMW) large-scale precipitation products. However, due to a limited ability to relate observed radiometric signatures to precipitation type (convective and stratiform) and associated precipitation rate variability, PMW retrievals are prone to large systematic errors at instantaneous scales. The present study explores the use of deep learning approach in extracting the information content from PMW observation vectors to help identify precipitation types. A deep learning neural network model (DNN) is developed to retrieve the convective type in precipitating systems from PMW observations. A 12-month period of Global Precipitation Measurement mission Microwave Imager (GMI) observations is used as a dataset for model development and verification. The proposed DNN model is shown to accurately predict precipitation types for 85% of total precipitation volume. The model reduces precipitation rate bias associated with convective and stratiform precipitation in the GPM operational algorithm by a factor of 2 while preserving the correlation with reference precipitation rates, and is insensitive to surface type variability. Based on comparisons against currently used convective schemes, it is concluded that the neural network approach has the potential to address regime-specific PMW satellite precipitation biases affecting GPM operations.

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Maradin, Mladen. "Varijabilnost padalina u Hvaru i Crikvenici." Geoadria 13, no. 2 (January 11, 2017): 133. http://dx.doi.org/10.15291/geoadria.561.

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The study analyses the precipitation variability in Hvar and Crikvenica in the period from 1931 to 1990. These stations have a maritime type of the annual course of precipitation. The minimum value of the precipitation variability in Hvar is in autumn, in November, while the secondary minimum of the variability is in spring, in April. The primary maximum of variability is in summer, most often in July, while the secondary maximum is in March. In Crikvenica the minimum values of the precipitation variability in April and November are even, and the same is true for the maximum values of the variability in September and March. The value of the annual precipitation variability is higher in Crikvenica than in Hvar although Crikvenica has higher amount of precipitation. The location of the stations included in this research is relevant. In Crikvenica the variability is higher in autumn and winter. Monthly values of the mean relative variability coincide in the cold part of the year when the variability is only slightly higher in Crikvenica, while in the warm part of the year, with the exception of September, the variability in Hvar is significantly higher.

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Lee, Dong Eun, Mingfang Ting, Nicolas Vigaud, Yochanan Kushnir, and Anthony G. Barnston. "Atlantic Multidecadal Variability as a Modulator of Precipitation Variability in the Southwest United States." Journal of Climate 31, no. 14 (June 18, 2018): 5525–42. http://dx.doi.org/10.1175/jcli-d-17-0372.1.

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AbstractTwo independent atmospheric general circulation models reveal that the positive (negative) phase of Atlantic multidecadal variability (AMV) can reduce (amplify) the variance of the shorter time-scale (e.g., ENSO related) precipitation fluctuations in the United States, especially in the Southwest, as well as decrease (increase) the long-term seasonal mean precipitation for the cold season. The variance is modulated because of changes in 1) dry day frequency and 2) maximum daily rainfall intensity. With positive AMV forcing, the upper-level warming originating from the increased precipitation over the tropical Atlantic Ocean changes the mean vertical thermal structure over the United States continent to a profile less favorable for rain-inducing upward motions. In addition, a northerly low-level dry advection associated with the local overturning leaves less available column moisture for condensation and precipitation. The opposite conditions occur during cold AMV periods.

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Dannenberg, Matthew P., Erika K. Wise, and William K. Smith. "Reduced tree growth in the semiarid United States due to asymmetric responses to intensifying precipitation extremes." Science Advances 5, no. 10 (October 2019): eaaw0667. http://dx.doi.org/10.1126/sciadv.aaw0667.

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Earth’s hydroclimatic variability is increasing, with changes in the frequency of extreme events that may negatively affect forest ecosystems. We examined possible consequences of changing precipitation variability using tree rings in the conterminous United States. While many growth records showed either little evidence of precipitation limitation or linear relationships to precipitation, growth of some species (particularly those in semiarid regions) responded asymmetrically to precipitation such that tree growth reductions during dry years were greater than, and not compensated by, increases during wet years. The U.S. Southwest, in particular, showed a large increase in precipitation variability, coupled with asymmetric responses of growth to precipitation. Simulations suggested roughly a twofold increase in the probability of large negative growth anomalies across the Southwest resulting solely from 20th century increases in variability of cool-season precipitation. Models project continued increases in precipitation variability, portending future growth reductions across semiarid forests of the western United States.

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He, Jie, Clara Deser, and Brian J. Soden. "Atmospheric and Oceanic Origins of Tropical Precipitation Variability." Journal of Climate 30, no. 9 (May 2017): 3197–217. http://dx.doi.org/10.1175/jcli-d-16-0714.1.

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The intrinsic atmospheric and ocean-induced tropical precipitation variability is studied using millennial control simulations with various degrees of ocean coupling. A comparison between the coupled simulation and the atmosphere-only simulation with climatological sea surface temperatures (SSTs) shows that a substantial amount of tropical precipitation variability is generated without oceanic influence. This intrinsic atmospheric variability features a red noise spectrum from daily to monthly time scales and a white noise spectrum beyond the monthly time scale. The oceanic impact is inappreciable for submonthly time scales but important at interannual and longer time scales. For time scales longer than a year, it enhances precipitation variability throughout much of the tropical oceans and suppresses it in some subtropical areas, preferentially in the summer hemisphere. The sign of the ocean-induced precipitation variability can be inferred from the local precipitation–SST relationship, which largely reflects the local feedbacks between the two, although nonlocal forcing associated with El Niño–Southern Oscillation also plays a role. The thermodynamic and dynamic nature of the ocean-induced precipitation variability is studied by comparing the fully coupled and slab ocean simulations. For time scales longer than a year, equatorial precipitation variability is almost entirely driven by ocean circulation, except in the Atlantic Ocean. In the rest of the tropics, ocean-induced precipitation variability is dominated by mixed layer thermodynamics. Additional analyses indicate that both dynamic and thermodynamic oceanic processes are important for establishing the leading modes of large-scale tropical precipitation variability. On the other hand, ocean dynamics likely dampens tropical Pacific variability at multidecadal time scales and beyond.

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Dong, Lu, L. Ruby Leung, Fengfei Song, and Jian Lu. "Roles of SST versus Internal Atmospheric Variability in Winter Extreme Precipitation Variability along the U.S. West Coast." Journal of Climate 31, no. 19 (October 2018): 8039–58. http://dx.doi.org/10.1175/jcli-d-18-0062.1.

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The U.S. West Coast exhibits large variability of extreme precipitation during the boreal winter season (December–February). Understanding the large-scale forcing of such variability is important for improving prediction. This motivates analyses of the roles of sea surface temperature (SST) forcing and internal atmospheric variability on extreme precipitation on the U.S. West Coast. Observations, reanalysis products, and an ensemble of Atmospheric Model Intercomparison Project (AMIP) experiments from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are analyzed. It is found that SST forcing only accounts for about 20% of the variance of both extreme and nonextreme precipitation in winter. Under SST forcing, extreme precipitation is associated with the Pacific–North American teleconnection, while nonextreme precipitation is associated with the North Pacific Oscillation. The remaining 80% of extreme precipitation variations can be explained by internal atmospheric dynamics featuring a circumglobal wave train with a cyclonic circulation located over the U.S. West Coast. The circumglobal teleconnection manifests from the mid- to high-latitude intrinsic variability, but it can also emanate from anomalous convection over the tropical western Pacific, with stronger tropical convection over the Maritime Continent setting the stage for more extreme precipitation in winter. Whether forced by SST or internal atmospheric dynamics, atmospheric rivers are a common and indispensable feature of the large-scale environment that produces concomitant extreme precipitation along the U.S. West Coast.

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Jiang, Jie, Tianjun Zhou, Xiaolong Chen, and Bo Wu. "Central Asian Precipitation Shaped by the Tropical Pacific Decadal Variability and the Atlantic Multidecadal Variability." Journal of Climate 34, no. 18 (September 2021): 7541–53. http://dx.doi.org/10.1175/jcli-d-20-0905.1.

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AbstractKnown as one of the largest semiarid to arid regions in the world, central Asia and its economy and ecosystem are highly sensitivity to the changes in precipitation. The observed precipitation and related hydrographic characteristics have exhibited robust decadal variations in the past decades, but the reason remains unknown. Using the pacemaker experiments of the Community Earth System Model (CESM1.2), we find that the tropical Pacific decadal variability (TPDV) and the Atlantic multidecadal variability (AMV) are the main drivers of the interdecadal variations in central Asian precipitation during 1955–2004. Both the decadal-scale warming of the tropical Pacific and North Atlantic are favorable for wetter conditions over central Asia. The positive TPDV is accompanied with high sea level pressure (SLP) over the Indo–western Pacific warm pool. Southwesterly winds along the northwestern flank of the high SLP can transport more moisture to southeastern central Asia. The warm AMV can excite a circumglobal teleconnection (CGT) pattern. A trough node of the CGT to the west of central Asia drives an anomalous ascending motion and increased precipitation over this region. The results based on the CESM model are further demonstrated by the pacemaker experiments of MRI-ESM2-0. Based on the observational TPDV and AMV indices, we reasonably reconstruct the historical precipitation over central Asia. Our results provide hints for the decadal prediction of precipitation over central Asia.

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Fatichi, S., V. Yu Ivanov, and E. Caporali. "Investigating Interannual Variability of Precipitation at the Global Scale: Is There a Connection with Seasonality?" Journal of Climate 25, no. 16 (August 15, 2012): 5512–23. http://dx.doi.org/10.1175/jcli-d-11-00356.1.

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Abstract Interannual variability of precipitation can directly or indirectly affect many hydrological, ecological, and biogeochemical processes that, in turn, influence climate. Despite the significant importance of the phenomenon, few studies have attempted to elucidate spatial patterns of this variability at the global scale. This study uses land gauge precipitation records of the Global Historical Climatology Network, version 2, as well as reanalysis data to provide an assessment of the spatial organization of characteristics of precipitation interannual variability. The coefficient of variation, skewness, and short- and long-range dependence of the precipitation variability are analyzed. Among the major inferences is that the coefficient of variation of annual precipitation shows a significant correlation with intra-annual seasonality. Specifically, subyearly precipitation anomalies occurring in locations with pronounced seasonality affect the total yearly amount, imposing a higher variability in the annual precipitation fluctuations. Furthermore, the study illustrates that a positive skewness of the distribution of annual precipitation is a robust property worldwide and its magnitude is related to the coefficient of variation. Additionally, annual precipitation exhibits very weak small-lag autocorrelation. Conversely, the intensity of long-memory–long-range dependence is significantly larger than zero, hinting that organized long-term variations are an important feature of the interannual variability of precipitation.

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Formetta, Giuseppe, Jonghun Kam, Sahar Sadeghi, Glenn Tootle, and Thomas Piechota. "Atlantic Ocean Variability and European Alps Winter Precipitation." Water 13, no. 23 (November 30, 2021): 3377. http://dx.doi.org/10.3390/w13233377.

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Winter precipitation (snowpack) in the European Alps provides a critical source of freshwater to major river basins such as the Danube, Rhine, and Po. Previous research identified Atlantic Ocean variability and hydrologic responses in the European Alps. The research presented here evaluates Atlantic Sea Surface Temperatures (SSTs) and European Alps winter precipitation variability using Singular Value Decomposition. Regions in the north and mid-Atlantic from the SSTs were identified as being tele-connected with winter precipitation in the European Alps. Indices were generated for these Atlantic SST regions to use in prediction of precipitation. Regression and non-parametric models were developed using the indices as predictors and winter precipitation as the predictand for twenty-one alpine precipitation stations in Austria, Germany, and Italy. The proposed framework identified three regions in the European Alps in which model skill ranged from excellent (West Region–Po River Basin), to good (East Region) to poor (Central Region). A novel approach for forecasting future winter precipitation utilizing future projections of Atlantic SSTs predicts increased winter precipitation until ~2040, followed by decreased winter precipitation until ~2070, and then followed by increasing winter precipitation until ~2100.

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Borhara, Krishna, Binod Pokharel, Brennan Bean, Liping Deng, and S. Y. Simon Wang. "On Tanzania’s Precipitation Climatology, Variability, and Future Projection." Climate 8, no. 2 (February 20, 2020): 34. http://dx.doi.org/10.3390/cli8020034.

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We investigate historical and projected precipitation in Tanzania using observational and climate model data. Precipitation in Tanzania is highly variable in both space and time due to topographical variations, coastal influences, and the presence of lakes. Annual and seasonal precipitation trend analyses from 1961 to 2016 show maximum rainfall decline in Tanzania during the long rainy season in the fall (March–May), and an increasing precipitation trend in northwestern Tanzania during the short rainy season in the spring (September–November). Empirical orthogonal function (EOF) analysis applied to Tanzania’s precipitation patterns shows a stronger correlation with warmer temperatures in the western Indian Ocean than with the eastern-central Pacific Ocean. Years with decreasing precipitation in Tanzania appear to correspond with increasing sea surface temperatures (SST) in the Indian Ocean, suggesting that the Indian Ocean Dipole (IOD) may have a greater effect on rainfall variability in Tanzania than the El Niño-Southern Oscillation (ENSO) does. Overall, the climate model ensemble projects increasing precipitation trend in Tanzania that is opposite with the historical decrease in precipitation. This observed drying trend also contradicts a slightly increasing precipitation trend from climate models for the same historical time period, reflecting challenges faced by modern climate models in representing Tanzania’s precipitation.

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Łupikasza, Ewa. "Long-Term Variability of Precipitation form in Hornsund (Spitsbergen) in Relation to Atmospheric Circulation (1979–2009)." Bulletin of Geography. Physical Geography Series 3, no. 1 (December 1, 2010): 65–86. http://dx.doi.org/10.2478/bgeo-2010-0004.

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Abstract The paper discusses the impact of the atmospheric circulation on the long-term variability of liquid, mixed and solid precipitation. The three precipitation forms were characterised by their totals, the number of days when they prevailed, and the contribution of each to the overall precipitation totals. Trends, as a background to further analysis, were calculated with regard to each characteristic of each precipitation form. The most significant increases were recorded in the contribution of liquid precipitation to the overall precipitation totals in September and in the mixed precipitation totals in December and November. Arctic Oscillation (AO) was found to have only a minor influence on the long-term variability of precipitation characteristics. The AO phase could to some degree account for the observed variation in the number of days with liquid precipitation. On the other hand, the direction of the local advection could account for considerably more of this variability and also the variability in liquid precipitation totals.

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He, Jie, Nathaniel C. Johnson, Gabriel A. Vecchi, Ben Kirtman, Andrew T. Wittenberg, and Stephan Sturm. "Precipitation Sensitivity to Local Variations in Tropical Sea Surface Temperature." Journal of Climate 31, no. 22 (October 18, 2018): 9225–38. http://dx.doi.org/10.1175/jcli-d-18-0262.1.

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Abstract The driving of tropical precipitation by the variability of the underlying sea surface temperature (SST) plays a critical role in the atmospheric general circulation. To assess the precipitation sensitivity to SST variability, it is necessary to observe and understand the relationship between precipitation and SST. However, the precipitation–SST relationships from any coupled atmosphere–ocean system can be difficult to interpret given the challenge of disentangling the SST-forced atmospheric response and the atmospheric intrinsic variability. This study demonstrates that the two components can be isolated using uncoupled atmosphere-only simulations, which extract the former when driven by time-varying SSTs and the latter when driven by climatological SSTs. With a simple framework that linearly combines the two types of uncoupled simulations, the coupled precipitation–SST relationships are successfully reproduced. Such a framework can be a useful tool for quantitatively diagnosing tropical air–sea interactions. The precipitation sensitivity to SST variability is investigated with the use of uncoupled simulations with prescribed SST anomalies, where the influence of atmospheric intrinsic variability on SST is deactivated. Through a focus on local precipitation–SST relationships, the precipitation sensitivity to local SST variability is determined to be predominantly controlled by the local background SST. In addition, the strength of the precipitation response increases monotonically with the local background SST, with a very sharp growth at high SSTs. These findings are supported by basic principles of moist static stability, from which a simple formula for precipitation sensitivity to local SST variability is derived.

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Zhong, Yafang, Zhengyu Liu, and Michael Notaro. "A GEFA Assessment of Observed Global Ocean Influence on U.S. Precipitation Variability: Attribution to Regional SST Variability Modes." Journal of Climate 24, no. 3 (February 1, 2011): 693–707. http://dx.doi.org/10.1175/2010jcli3663.1.

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Abstract This paper presents a comprehensive assessment of the observed influence of the global ocean on U.S. precipitation variability using the method of Generalized Equilibrium Feedback Assessment (GEFA), which enables an unambiguous attribution of the influence from multiple ocean basins within a unified framework. The GEFA assessment based on observations for 1950–99 suggests that the tropical Pacific SST variability has the greatest consequence for U.S. precipitation, as both ENSO and meridional modes are associated with notable responses in seasonal mean precipitation. The anomalously cold tropical Indian Ocean is a good indicator for U.S. dry conditions during spring and late winter. The impact of North Pacific SST variability is detected in springtime precipitation, yet it is overshadowed by that of the tropical Indo-Pacific on seasonal-to-interannual time scales. Tropical Atlantic forcing of U.S. precipitation appears to be most effective in winter, whereas the northern Atlantic forcing is likely more important during spring and summer. Global ocean influence on U.S. precipitation is found to be most significant in winter, explaining over 20% of the precipitation variability in the Southwest and southern Great Plains throughout the cold seasons and in the northern Great Plains and northeast United States during late winter. The Southwest and southern Great Plains is likely the region that is most susceptible to oceanic influence, primarily to the forcing of the tropical Indo-Pacific. The Pacific Northwest is among the regions that may experience the least oceanic influence as far as precipitation variability is concerned.

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Fyke, Jeremy, Jan T. M. Lenaerts, and Hailong Wang. "Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability." Cryosphere 11, no. 6 (November 15, 2017): 2595–609. http://dx.doi.org/10.5194/tc-11-2595-2017.

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Abstract. Annually averaged precipitation in the form of snow, the dominant term of the Antarctic Ice Sheet surface mass balance, displays large spatial and temporal variability. Here we present an analysis of spatial patterns of regional Antarctic precipitation variability and their impact on integrated Antarctic surface mass balance variability simulated as part of a preindustrial 1800-year global, fully coupled Community Earth System Model simulation. Correlation and composite analyses based on this output allow for a robust exploration of Antarctic precipitation variability. We identify statistically significant relationships between precipitation patterns across Antarctica that are corroborated by climate reanalyses, regional modeling and ice core records. These patterns are driven by variability in large-scale atmospheric moisture transport, which itself is characterized by decadal- to centennial-scale oscillations around the long-term mean. We suggest that this heterogeneity in Antarctic precipitation variability has a dampening effect on overall Antarctic surface mass balance variability, with implications for regulation of Antarctic-sourced sea level variability, detection of an emergent anthropogenic signal in Antarctic mass trends and identification of Antarctic mass loss accelerations.

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Miletić, Milan, and Jovana Vuletić. "Statistical analysis of the mean relative variability of monthly, seasonal and annual precipitation at the main synoptic stations in the South Morava sub-basin to the Korvingrad hydrological station." Zbornik radova - Geografski fakultet Univerziteta u Beogradu, no. 71 (2023): 79–90. http://dx.doi.org/10.5937/zrgfub2371079m.

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The aim of this work is to determine the variability of precipitation in the area of the sub-basin of the South Curve up to the hydrological station Korvingrad. Data from the synoptic stations Leskovac, Vranje and Kuršumlija for a period of 30 years (1991-2020) were used. The mean relative variability of monthly, seasonal and annual precipitation and their ten-year values were used to compare the results of all synoptic stations in the sub-basin. The results showed that the highest mean variability of precipitation in the studied period was recorded at the Vranje synoptic station (22.4%) and the lowest value at the station in Leskovac (18.4%). The comparison of ten-year values showed that the lowest values of mean relative variability of annual precipitation in the period 2001-2010 were recorded at all synoptic stations. The study showed that the extreme values of mean relative variability of precipitation occurred earlier or later during the second and third ten-year periods compared to the first ten-year period. The study showed that the values of mean relative variability of monthly precipitation were lowest in months with high precipitation.

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Luffman, Ingrid, and Arpita Nandi. "Seasonal Precipitation Variability and Gully Erosion in Southeastern USA." Water 12, no. 4 (March 25, 2020): 925. http://dx.doi.org/10.3390/w12040925.

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This study examines the relationship between gully erosion in channels, sidewalls, and interfluves, and precipitation parameters (duration, total accumulation, average intensity, and maximum intensity) annually and seasonally to determine seasonal drivers for precipitation-related erosion. Ordinary Least Square regression models of erosion using precipitation and antecedent precipitation at weekly lags of up to twelve weeks were developed for three erosion variables for each of three geomorphic areas: channels, interfluves, and sidewalls (nine models in total). Erosion was most pronounced in winter months, followed by spring, indicating the influence of high-intensity precipitation from frontal systems and repeated freeze-thaw cycles in winter; erosion in summer was driven by high-intensity precipitation from convectional storms. Annually, duration was the most important driver for erosion, however, during winter and summer months, precipitation intensity was dominant. Seasonal models retained average and maximum precipitation as drivers for erosion in winter months (dominated by frontal systems), and retained maximum precipitation intensity as a driver for erosion in summer months (dominated by convectional storms). In channels, precipitation duration was the dominant driver for erosion due to runoff-related erosion, while in sidewalls and interfluves intensity parameters were equally important as duration, likely related to rain splash erosion. These results show that the character of precipitation, which varies seasonally, is an important driver for gully erosion and that studies of precipitation-driven erosion should consider partitioning data by season to identify these drivers.

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Saidi, H., M. Ciampittiello, C. Dresti, and G. Ghiglieri. "Observed variability and trends in extreme rainfall indices and Peaks-Over-Threshold series." Hydrology and Earth System Sciences Discussions 10, no. 5 (May 15, 2013): 6049–79. http://dx.doi.org/10.5194/hessd-10-6049-2013.

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Abstract. Intensification of heavy precipitation as discussed in climate change studies has become a public concern, but it has not yet been examined well with observed data, particularly with data at short temporal scale like hourly and sub-hourly data. In this research we digitalized sub-hourly precipitation recorded at the stations of Vercelli (since 1927), Bra (since 1933), Lombriasco (since 1939) and Pallanza (since 1950) in order to investigate historical change in extreme short precipitations. These stations are located in the northwest of Italy. Besides seasonal and yearly maximum of precipitation we adopted two indices of extreme rainfall: the number of events above an extreme threshold (extreme frequency), and the average intensity of rainfall from extreme events (extreme intensity). The results showed a statistically significant increase of the extreme frequency index and spring maximum precipitation for Bra and Lombriasco. The extreme intensity index presented by the means of events above 95th percentile is decreasing for Bra regarding hourly precipitation and increasing for Lombriasco regarding 20 min extreme events. In Pallanza, we noticed only a positive trend of the extreme frequency and extreme intensity indices of events with duration of 30 min. For the analyses presented in this paper, a peak-over-threshold approach was chosen. Investigation presented showed that extreme events have risen in the last 20 yr only for short duration. Here it cannot be said that in our study area recent sub-hourly and hourly precipitation have become unprecedently strong or frequent for all the stations and for all the extreme events duration.

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Abatzoglou, John T. "Contribution of Cutoff Lows to Precipitation across the United States." Journal of Applied Meteorology and Climatology 55, no. 4 (April 2016): 893–99. http://dx.doi.org/10.1175/jamc-d-15-0255.1.

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AbstractA chronology of cutoff lows (COL) from 1979 to 2014 alongside daily precipitation observations across the conterminous United States was used to examine the contribution of COL to seasonal precipitation, extreme-precipitation events, and interannual precipitation variability. COL accounted for between 2% and 32% of annual precipitation at stations across the United States, with distinct geographic and seasonal variability. The largest fractional contribution of COL to precipitation totals and precipitation extremes was found across the Great Plains and the interior western United States, particularly during the transition seasons of spring and autumn. Widespread significant correlations between seasonal COL precipitation and total precipitation on interannual time scales were found across parts of the United States, most notably to explain spring precipitation variability in the interior western United States and Great Plains and summer precipitation variability in the northwestern United States. In addition to regional differences, a distinct gradient in the contributions of COL to precipitation was found in the lee of large mountain ranges in the western United States. Differences in orographic precipitation enhancement associated with slow-moving COL resulted in relatively more precipitation at lower elevations and, in particular, east of north–south-oriented mountain ranges that experience a strong rain shadow with progressive disturbances.

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Wang, Weile, Bruce T. Anderson, Dara Entekhabi, Dong Huang, Robert K. Kaufmann, Christopher Potter, and Ranga B. Myneni. "Feedbacks of Vegetation on Summertime Climate Variability over the North American Grasslands. Part II: A Coupled Stochastic Model." Earth Interactions 10, no. 16 (September 1, 2006): 1–30. http://dx.doi.org/10.1175/ei197.1.

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Abstract A coupled linear model is derived to describe interactions between anomalous precipitation and vegetation over the North American Grasslands. The model is based on biohydrological characteristics in the semiarid environment and has components to describe the water-related vegetation variability, the long-term balance of soil moisture, and the local soil–moisture–precipitation feedbacks. Analyses show that the model captures the observed vegetation dynamics and characteristics of precipitation variability during summer over the region of interest. It demonstrates that vegetation has a preferred frequency response to precipitation forcing and has intrinsic oscillatory variability at time scales of about 8 months. When coupled to the atmospheric fields, such vegetation signals tend to enhance the magnitudes of precipitation variability at interannual or longer time scales but damp them at time scales shorter than 4 months; the oscillatory variability of precipitation at the growing season time scale (i.e., the 8-month period) is also enhanced. Similar resonance and oscillation characteristics are identified in the power spectra of observed precipitation datasets. The model results are also verified using Monte Carlo experiments.

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Trammell, James H., Xun Jiang, Liming Li, Angela Kao, Guang J. Zhang, Edmund K. M. Chang, and Yuk Yung. "Temporal and Spatial Variability of Precipitation from Observations and Models*." Journal of Climate 29, no. 7 (March 24, 2016): 2543–55. http://dx.doi.org/10.1175/jcli-d-15-0325.1.

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Abstract Principal component analysis (PCA) is utilized to explore the temporal and spatial variability of precipitation from GPCP and a CAM5 simulation from 1979 to 2010. In the tropical region, the interannual variability of tropical precipitation is characterized by two dominant modes (El Niño and El Niño Modoki). The first and second modes of tropical GPCP precipitation capture 31.9% and 15.6% of the total variance, respectively. The first mode has positive precipitation anomalies over the western Pacific and negative precipitation anomalies over the central and eastern Pacific. The second mode has positive precipitation anomalies over the central Pacific and negative precipitation anomalies over the western and eastern Pacific. Similar variations are seen in the first two modes of tropical precipitation from a CAM5 simulation, although the magnitudes are slightly weaker than in the observations. Over the Northern Hemisphere (NH) high latitudes, the first mode, capturing 8.3% of the total variance of NH GPCP precipitation, is related to the northern annular mode (NAM). During the positive phase of NAM, there are negative precipitation anomalies over the Arctic and positive precipitation anomalies over the midlatitudes. Over the Southern Hemisphere (SH) high latitudes, the first mode, capturing 13.2% of the total variance of SH GPCP precipitation, is related to the southern annular mode (SAM). During the positive phase of the SAM, there are negative precipitation anomalies over the Antarctic and positive precipitation anomalies over the midlatitudes. The CAM5 precipitation simulation demonstrates similar results to those of the observations. However, they do not capture both the high precipitation anomalies over the northern Pacific Ocean or the position of the positive precipitation anomalies in the SH.

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Gherardi, Laureano A., and Osvaldo E. Sala. "Enhanced precipitation variability decreases grass- and increases shrub-productivity." Proceedings of the National Academy of Sciences 112, no. 41 (September 28, 2015): 12735–40. http://dx.doi.org/10.1073/pnas.1506433112.

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Although projections of precipitation change indicate increases in variability, most studies of impacts of climate change on ecosystems focused on effects of changes in amount of precipitation, overlooking precipitation variability effects, especially at the interannual scale. Here, we present results from a 6-y field experiment, where we applied sequences of wet and dry years, increasing interannual precipitation coefficient of variation while maintaining a precipitation amount constant. Increased precipitation variability significantly reduced ecosystem primary production. Dominant plant-functional types showed opposite responses: perennial-grass productivity decreased by 81%, whereas shrub productivity increased by 67%. This pattern was explained by different nonlinear responses to precipitation. Grass productivity presented a saturating response to precipitation where dry years had a larger negative effect than the positive effects of wet years. In contrast, shrubs showed an increasing response to precipitation that resulted in an increase in average productivity with increasing precipitation variability. In addition, the effects of precipitation variation increased through time. We argue that the differential responses of grasses and shrubs to precipitation variability and the amplification of this phenomenon through time result from contrasting root distributions of grasses and shrubs and competitive interactions among plant types, confirmed by structural equation analysis. Under drought conditions, grasses reduce their abundance and their ability to absorb water that then is transferred to deep soil layers that are exclusively explored by shrubs. Our work addresses an understudied dimension of climate change that might lead to widespread shrub encroachment reducing the provisioning of ecosystem services to society.

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Nidzgorska-Lencewicz, Jadwiga, and Małgorzata Czarnecka. "Cyclical variability of seasonal precipitation in Poland." Időjárás 123, no. 4 (2019): 455–68. http://dx.doi.org/10.28974/idojaras.2019.4.3.

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Kolivras, Korine N., and Andrew C. Comrie. "Regionalization and Variability of Precipitation in Hawaii." Physical Geography 28, no. 1 (January 2007): 76–96. http://dx.doi.org/10.2747/0272-3646.28.1.76.

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Lagos, P., Y. Silva, E. Nickl, and K. Mosquera. "El Niño – related precipitation variability in Perú." Advances in Geosciences 14 (April 10, 2008): 231–37. http://dx.doi.org/10.5194/adgeo-14-231-2008.

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Abstract. The relationship between monthly mean sea surface temperature (SST) anomalies in the commonly used El Niño regions and precipitation for 44 stations in Perú is documented for 1950–2002. Linear lag correlation analysis is employed to establish the potential for statistical precipitation forecasts from SSTs. Useful monthly mean precipitation anomaly forecasts are possible for several locations and calendar months if SST anomalies in El Niño 1+2, Niño 3.4, and Niño 4 regions are available. Prediction of SST anomalies in El Niño regions is routinely available from Climate Prediction Center, NOAA, with reasonable skill in the El Niño 3.4 region, but the prediction in El Niño 1+2 region is less reliable. The feasibility of using predicted SST anomalies in the El Niño 3.4 region to predict SST anomalies in El Niño 1+2 region is discussed.

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Mattison, Laura, and Ian D. Phillips. "Winter Daily Precipitation Variability over Northern Scotland." Scottish Geographical Journal 132, no. 1 (June 29, 2015): 21–41. http://dx.doi.org/10.1080/14702541.2015.1051101.

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Hartmann, Heike, Stefan Becker, and Tong Jiang. "Precipitation variability in the Yangtze River subbasins." Water International 37, no. 1 (January 2012): 16–31. http://dx.doi.org/10.1080/02508060.2012.644926.

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Sariş, Faize, David M. Hannah, and Warren J. Eastwood. "Spatial variability of precipitation regimes over Turkey." Hydrological Sciences Journal 55, no. 2 (March 24, 2010): 234–49. http://dx.doi.org/10.1080/02626660903546142.

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Journal articles on the topic 'Precipitation variability'

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