Hourly Precipitation Observations Research Articles

Unique Seasonal Variation in Rainfall Diurnal Features on the Yunnan–Guizhou Plateau

Based on hourly precipitation observations, the diurnal variation in precipitation and its seasonal evolution over the Yunnan–Guizhou Plateau (YGP) were analyzed. The results indicate that the seasonal variation in hourly rainfall in the western part of the YGP is unique. The rainfall reaches its hourly maximum during the late afternoon in spring (March–April) and during nighttime in summer (July–August), which contrasts with the pattern in most of eastern China. By further classifying the rainfall into short-duration (1–3 h) and long-duration (more than 6 h) events, the unique seasonal variations in the western YGP are found to mainly be comprised of short-duration rainfall. The long-duration rainfall shares similar diurnal peaks year-round for both the western and eastern parts of the YGP. The short-duration rainfall in the western part of the YGP shows a year-round afternoon peak, which is different from that of the eastern YGP, which peaks from midnight to early morning in spring and in the late afternoon in summer. The surface maximum daily temperature and low-level instabilities reach their annual maximum in spring over the western YGP and are also higher than in other parts of the YGP, together providing favorable conditions for convection to be triggered in spring afternoons over the western YGP.

Urbanization reshapes extreme precipitation metrics in typical urban agglomerations of Eastern China

A deeper understanding of the impact of urbanization on hourly extreme precipitation is essential for building sustainable and resilient urban environments. In this study, we used a high-resolution land cover dataset and long time series of hourly precipitation observations to assess the impact of urbanization on long-term trends and diurnal patterns of hourly extreme precipitation in typical urban agglomeration regions of eastern China, during the warm season of 1978–2021. The results showed that eastern China experienced an overall increase in hourly precipitation, while the intensity trends were 0.06 mm/h/decade and 0.03 mm/h/decade for urban and rural areas, respectively. Urban areas more likely to experienced strong precipitation with short duration, but urban-rural differences in extreme precipitation showed obvious regional characteristics. The difference in extreme precipitation intensity between urban and rural areas increased in the regions of the lower Yangtze River (LYR) valley, Sichuan Basin and southern China, but decreased in northeast China and Beijing-Tianjin-Hebei (BTH) regions. For the diurnal cycle, extreme precipitation enhancement in urban areas occurred mostly at peak hours. Urban stations had higher hourly extreme precipitation intensity than rural stations throughout the diurnal cycle, with the maximum difference of 1.79 mm/h occurring at 16:00 LST. It found that extreme precipitation amount and intensity in urban areas increased with urban heat island (UHI) effect, and UHI indeed plays an important role in the convective initiation and strengthening of local extreme precipitation.

Observed response of precipitation intensity to dew point temperature over the contiguous US

Precipitation has an important impact on crop growth, water resources, industrial/agricultural production, and ecological services. Compared to widely used precipitation amount, intensity of precipitation is more important because it determines the partition of precipitation into soil moisture and surface runoff. With hourly precipitation observations collected at 307 stations over the contiguous US from 1984 to 2013, this study investigates the sensitivity of precipitation intensity to warming. To deal with the issues of constant relative humidity assumption in the existing studies, the sensitivities of hourly precipitation intensity at various percentiles to dew point temperature are examined. We find that the results with dew point temperature showed more consistent and robust positive sensitivities than that of air temperature. The sensitivity of precipitation intensity to warming of dew point temperature increases from ~2%/°C for the 50th percentile of precipitation to ~6%/°C for the 99th percentile of precipitation. These sensitivities are the largest in the Southwest region, followed by the Great Lakes and Plains, the Pacific Coast, and the West region. Such spatial contrast is the largest in summer. The results can provide a comprehensive and quantitative documentation of the precipitation sensitivity to warming.

System of Multigrid Nonlinear Least-squares Four-dimensional Variational Data Assimilation for Numerical Weather Prediction (SNAP): System Formulation and Preliminary Evaluation

A new forecasting system—the System of Multigrid Nonlinear Least-squares Four-dimensional Variational (NLS-4DVar) Data Assimilation for Numerical Weather Prediction (SNAP)—was established by building upon the multigrid NLS-4DVar data assimilation scheme, the operational Gridpoint Statistical Interpolation (GSI)-based data-processing and observation operators, and the widely used Weather Research and Forecasting numerical model. Drawing upon lessons learned from the superiority of the operational GSI analysis system, for its various observation operators and the ability to assimilate multiple-source observations, SNAP adopts GSI-based data-processing and observation operator modules to compute the observation innovations. The multigrid NLS-4DVar assimilation framework is used for the analysis, which can adequately correct errors from large to small scales and accelerate iteration solutions. The analysis variables are model state variables, rather than the control variables adopted in the conventional 4DVar system. Currently, we have achieved the assimilation of conventional observations, and we will continue to improve the assimilation of radar and satellite observations in the future. SNAP was evaluated by case evaluation experiments and one-week cycling assimilation experiments. In the case evaluation experiments, two six-hour time windows were established for assimilation experiments and precipitation forecasts were verified against hourly precipitation observations from more than 2400 national observation sites. This showed that SNAP can absorb observations and improve the initial field, thereby improving the precipitation forecast. In the one-week cycling assimilation experiments, six-hourly assimilation cycles were run in one week. SNAP produced slightly lower forecast RMSEs than the GSI 4DEnVar (Four-dimensional Ensemble Variational) as a whole and the threat scores of precipitation forecasts initialized from the analysis of SNAP were higher than those obtained from the analysis of GSI 4DEnVar.

Quality Control and Processing of Cooperative Observer Program Hourly Precipitation Data

AbstractThe National Oceanic and Atmospheric Administration (NOAA) has operated a network of Fischer & Porter gauges providing hourly and subhourly precipitation observations as part of the U.S. Cooperative Observer Program since the middle of the twentieth century. A transition from punched paper recording to digital recording was completed by NOAA’s National Weather Service in 2013. Subsequently, NOAA’s National Centers for Environmental Information (NCEI) upgraded its quality assurance and data stewardship processes to accommodate the new digital record, better assure the quality of the data, and improve the timeliness by which hourly precipitation observations are made available to the user community. Automated methods for removing noise, detecting diurnal variations, and identifying malfunctioning gauges are described along with quality control algorithms that are applied on hourly and daily time scales. The quality of the hourly observations during the digital era is verified by comparison with hourly observations from the U.S. Climate Reference Network and summary of the day precipitation totals from the Global Historical Climatology Network dataset.

Evidence of a Diurnal Cycle in Precipitation over the Southern Ocean as Observed at Macquarie Island

Due to a lack of observations, relatively large discrepancies exist between precipitation products over the Southern Ocean. In this manuscript, surface hourly precipitation observations from Macquarie Island (54.62 ° S, 158.85 ° E) are analysed (1998–2016) to reveal a diurnal cycle. The precipitation rate is at a maximum during night/early morning and a minimum in the afternoon at Macquarie Island station. Seasonally, the diurnal cycle is strongest in summer and negligible over winter. Such a cycle is consistent with precipitation arising from marine boundary layer clouds, suggesting that such clouds are making a substantial contribution to total precipitation over Macquarie Island and the Southern Ocean. Using twice daily upper air soundings (1995–2011), lower troposphere stability parameters show a stronger inversion at night, again consistent with precipitation arising from marine boundary layer clouds. The ERA-Interim precipitation is dominated by a 12 hourly cycle, year around, which is likely to be a consequence of the twice-daily initialisation. The implication of a diurnal cycle in boundary layer clouds over the Southern Ocean to derived A-Train satellite precipitation products is also discussed.

Better knowledge with more gauges? Investigation of the spatiotemporal characteristics of precipitation variations over the Greater Beijing Region

ABSTRACTUsing the hourly precipitation observations from 118 gauge stations and a weather radar in the Greater Beijing Region (GBR) during 2008–2012, we investigate the spatiotemporal characteristics of precipitation and discuss the appropriate observational approach for capturing variability of precipitation over this region. In general, the south central and northeastern GBR receives more intense precipitation than other parts. The diurnal cycle of precipitation amount (PA) peaks in the evening and decreases till noon, whereas precipitation intensity (PI) and precipitation frequency (PF) both have two peaks. The stronger peaks of PI and PF occur in the evening whereas the weaker ones appear in the early nighttime and in the afternoon. Remarkable spatial heterogeneity also exists in the diurnal patterns of PA, PI and PF over the GBR. Rainstorms extracted from radar data feature in short duration (11.4 h in average) and highly localized patterns (4.31–20.58/1.85–9.10 km in major/minor radius direction). The estimated diurnal cycles of PA, PI and PF are found to depend on the gauge density in a sensitivity analysis, where a gauge density ratio of 0.6 (corresponding to 30 gauges in total with a representative area of 239.5 km2 per gauge) is identified as adequate to capture the temporal characteristics of precipitation in the plain area of GBR. However, such a gauge density ratio (i.e. 0.6) is incapable for resolving the spatial characteristics of precipitation in GBR. As such, different instruments (e.g. gauge network, weather radar, etc.) and multiple data sources are suggested to be jointly utilized to better capture the characteristics of rainstorms in GBR.

Predictive ability of severe rainfall events over Catalonia for the year 2008

Abstract. This paper analyses the predictive ability of quantitative precipitation forecasts (QPF) and the so-called "poor-man" rainfall probabilistic forecasts (RPF). With this aim, the full set of warnings issued by the Meteorological Service of Catalonia (SMC) for potentially-dangerous events due to severe precipitation has been analysed for the year 2008. For each of the 37 warnings, the QPFs obtained from the limited-area model MM5 have been verified against hourly precipitation data provided by the rain gauge network covering Catalonia (NE of Spain), managed by SMC. For a group of five selected case studies, a QPF comparison has been undertaken between the MM5 and COSMO-I7 limited-area models. Although MM5's predictive ability has been examined for these five cases by making use of satellite data, this paper only shows in detail the heavy precipitation event on the 9–10 May 2008. Finally, the "poor-man" rainfall probabilistic forecasts (RPF) issued by SMC at regional scale have also been tested against hourly precipitation observations. Verification results show that for long events (>24 h) MM5 tends to overestimate total precipitation, whereas for short events (≤24 h) the model tends instead to underestimate precipitation. The analysis of the five case studies concludes that most of MM5's QPF errors are mainly triggered by very poor representation of some of its cloud microphysical species, particularly the cloud liquid water and, to a lesser degree, the water vapor. The models' performance comparison demonstrates that MM5 and COSMO-I7 are on the same level of QPF skill, at least for the intense-rainfall events dealt with in the five case studies, whilst the warnings based on RPF issued by SMC have proven fairly correct when tested against hourly observed precipitation for 6-h intervals and at a small region scale. Throughout this study, we have only dealt with (SMC-issued) warning episodes in order to analyse deterministic (MM5 and COSMO-I7) and probabilistic (SMC) rainfall forecasts; therefore we have not taken into account those episodes that might (or might not) have been missed by the official SMC warnings. Therefore, whenever we talk about "misses", it is always in relation to the deterministic LAMs' QPFs.

Increase in hourly precipitation extremes beyond expectations from temperature changes

Changes in precipitation extremes under greenhouse warming are commonly assumed to be constrained by the Clausius–Clapeyron relationship, implying an increase in extreme precipitation of 7% per degree of climate warming. An analysis of 99 years of observations along with simulations with a regional climate model show that short-duration precipitation extremes can instead increase in severity twice as fast, by 14% per degree of warming. Changes in precipitation extremes under greenhouse warming are commonly assumed to be constrained by changes in the amounts of precipitable water in the atmosphere1,2,3,4. Global climate models generally predict only marginal changes in relative humidity5, implying that the actual amount of atmospheric precipitable water scales with the water vapour content of saturation, which is governed by the Clausius–Clapeyron relation. Indeed, changes in daily precipitation extremes in global climate models seem to be consistent with the 7% increase per degree of warming given by the Clausius–Clapeyron relation3,4, but it is uncertain how general this scaling behaviour is across timescales. Here, we analyse a 99-year record of hourly precipitation observations from De Bilt, the Netherlands, and find that one-hour precipitation extremes increase twice as fast with rising temperatures as expected from the Clausius–Clapeyron relation when daily mean temperatures exceed 12 ∘C. In addition, simulations with a high-resolution regional climate model show that one-hour precipitation extremes increase at a rate close to 14% per degree of warming in large parts of Europe. Our results demonstrate that changes in short-duration precipitation extremes may well exceed expectations from the Clausius–Clapeyron relation. These short-duration extreme events can have significant impacts, such as local flooding, erosion and water damage.

Estimation of the error distributions of precipitation produced by convective parametrization schemes

AbstractIf a parametrization scheme for convective precipitation is to be used for assimilating observations of precipitation using a statistically based technique, then statistics of the errors produced by that scheme are required. These are the errors produced by the scheme's formulation itself, not counting any errors in the scheme's input. Such errors are extremely difficult to estimate, but examination of differences produced by various suitable schemes can yield qualitative descriptions of such errors. Here, hourly accumulated convective precipitation fields produced from six different versions of a short‐term forecast model are compared. The versions have identical initial and boundary conditions, but vary in the schemes used for either the convection or the planetary boundary layer, or both. The distribution of differences, or differences in logarithms of accumulations, between corresponding precipitating grid points for pairs of forecasts are examined using a simple binning technique. When the convection schemes differ, results reveal that if either a log‐normal or normal distribution is a better characterization of the distributions, it is the log‐normal one. The standard deviations of these logarithmic distributions correspond to different schemes at identical grid points producing values differing by factors of 2 or more. A large proportion of grid points that have non‐zero hourly accumulations using one model version may have no accumulation using another version. For most pairs of forecasts examined, however, grid points having larger values of accumulation for one scheme tend to have a smaller fraction of values having no accumulation in the other scheme. These results suggest that the finite probability that the model produces no precipitation when the corresponding, true atmospheric state does, should be considered in the statistical description of the model errors and that, because of the large standard deviation of model errors as well as large possible errors of hourly precipitation observations, the quantitative usefulness of assimilating such observations may be very limited.

Climatology of Heavy Rain Events in the United States from Hourly Precipitation Observations

Abstract Flash flooding is frequently associated with heavy precipitation (defined here as ≥1 in. h−1) occurring over a short period of time. To begin a study of flash flood–producing rain events, the Hourly Precipitation Dataset (HPD) is used to develop a climatology of heavy rains on timescales of 3 h or less across the contiguous United States. Analyses of this dataset show a distinct seasonal cycle in the distribution of heavy rain events that begins along the Gulf Coast and expands into the midwestern states during the summer. This general evolution is very similar to that observed for flash floods, suggesting that the HPD can help in defining the climatological threat for flash floods.