Have precipitation extremes and annual totals been increasing in the world's dry regions over the last 60 years?

NASA Astrophysics Data System (ADS)

Sippel, Sebastian; Zscheischler, Jakob; Heimann, Martin; Lange, Holger; Mahecha, Miguel D.; van Oldenborgh, Geert Jan; Otto, Friederike E. L.; Reichstein, Markus

2017-01-01

Daily precipitation extremes and annual totals have increased in large parts of the global land area over the past decades. These observations are consistent with theoretical considerations of a warming climate. However, until recently these trends have not been shown to consistently affect dry regions over land. A recent study, published by Donat et al. (2016), now identified significant increases in annual-maximum daily extreme precipitation (Rx1d) and annual precipitation totals (PRCPTOT) in dry regions. Here, we revisit the applied methods and explore the sensitivity of changes in precipitation extremes and annual totals to alternative choices of defining a dry region (i.e. in terms of aridity as opposed to precipitation characteristics alone). We find that (a) statistical artifacts introduced by data pre-processing based on a time-invariant reference period lead to an overestimation of the reported trends by up to 40 %, and that (b) the reported trends of globally aggregated extremes and annual totals are highly sensitive to the definition of a dry region of the globe. For example, using the same observational dataset, accounting for the statistical artifacts, and based on different aridity-based dryness definitions, we find a reduction in the positive trend of Rx1d from the originally reported +1.6 % decade-1 to +0.2 to +0.9 % decade-1 (period changes for 1981-2010 averages relative to 1951-1980 are reduced to -1.32 to +0.97 % as opposed to +4.85 % in the original study). If we include additional but less homogenized data to cover larger regions, the global trend increases slightly (Rx1d: +0.4 to +1.1 % decade-1), and in this case we can indeed confirm (partly) significant increases in Rx1d. However, these globally aggregated estimates remain uncertain as considerable gaps in long-term observations in the Earth's arid and semi-arid regions remain. In summary, adequate data pre-processing and accounting for uncertainties regarding the definition of

Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

DOE PAGES

Ashouri, Hamed; Sorooshian, Soroosh; Hsu, Kuo-Lin; ...

2016-02-03

This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC)U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scalemore » patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRAtends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1)MERRAshows a spurious negative trend in Nebraska andKansas, which ismost likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over theGulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2015-04-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

Observation-Corrected Precipitation Estimates in GEOS-5

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; Liu, Qing

2014-01-01

Several GEOS-5 applications, including the GEOS-5 seasonal forecasting system and the MERRA-Land data product, rely on global precipitation data that have been corrected with satellite and or gauge-based precipitation observations. This document describes the methodology used to generate the corrected precipitation estimates and their use in GEOS-5 applications. The corrected precipitation estimates are derived by disaggregating publicly available, observationally based, global precipitation products from daily or pentad totals to hourly accumulations using background precipitation estimates from the GEOS-5 atmospheric data assimilation system. Depending on the specific combination of the observational precipitation product and the GEOS-5 background estimates, the observational product may also be downscaled in space. The resulting corrected precipitation data product is at the finer temporal and spatial resolution of the GEOS-5 background and matches the observed precipitation at the coarser scale of the observational product, separately for each day (or pentad) and each grid cell.

Trend analysis of annual precipitation of Mauritius for the period 1981-2010

NASA Astrophysics Data System (ADS)

Raja, Nussaïbah B.; Aydin, Olgu

2018-04-01

This study researched the precipitation variability across 53 meteorological stations in Mauritius and different subregions of the island, over a 30-year study period (1981-2010). Time series was investigated for each 5-year interval and also for the whole study period. Non-parametric Mann-Kendall and Spearman's rho statistical tests were used to detect trends in annual precipitation. A mix of positive (increasing) and negative (decreasing) trends was highlighted for the 5-year interval analysis. The statistical tests nevertheless agreed on the overall trend for Mauritius and the subregions. Most regions showed a decrease in precipitation during the period 1996-2000. This is attributed to the 1998-2000 drought period which was brought about by a moderate La Niña event. In general, an increase in precipitation levels was observed across the country during the study period. This increase is the result of an increase in extreme precipitation events in the region. On the other hand, two subregions, both located in the highlands, experienced a decline in precipitation levels. Since most of the reservoirs in Mauritius are located in these two subregions, this implies serious consequences for water availability in the country if existing storage capacities are kept.

Establishing a baseline precipitation and temperature regime for the Guianas from observations and reanalysis data

NASA Astrophysics Data System (ADS)

Bovolo, C. Isabella; Pereira, Ryan; Parkin, Geoff; Wagner, Thomas

2010-05-01

annual average spatial correlations are examined between modelled ERA40 and observed time series comparing the seasonal cycles and the yearly, monthly and monthly anomaly time series. This is to evaluate if the reanalysis data correctly reproduces the areally averaged observed mean annual precipitation, interannual variability and seasonal precipitation cycle over the region. Results show that reanalysis precipitation for the region compares favourably with areally averaged observations where available, although the model underestimates precipitation in some zones of higher elevation. Also ERA40 data is slightly positively biased along the coast and negatively biased inland. Comparisons between observed and modelled data show that although correlations of annual time series are low (<0.6), correlations of monthly time series reach 0.8 demonstrating that the model captures much of the seasonal variation in precipitation. However correlations between monthly precipitation anomalies, where the averaged seasonal cycle has been removed from the comparison, are lower (< 0.6). As precipitation observations are not assimilated into the reanalysis these results provide a good validation of model performance. The seasonal cycle of precipitation is found to be highly variable across the region. Two wet-seasons (June and December) occur in northern Guyana which relate to the twice yearly passage of the inter-tropical convergence zone whereas a single wet season (April-August) occurs in the savannah zone, which stretches from Venezuela through the southern third of Guyana. The climate transition zone lies slightly north of the distinctive forest-savannah boundary which suggests that the boundary may be highly sensitive to future alterations in climate, such as those due to climate change or deforestation.

Climatology and Interannual Variability of Quasi-Global Intense Precipitation Using Satellite Observations

NASA Technical Reports Server (NTRS)

Ricko, Martina; Adler, Robert F.; Huffman, George J.

2016-01-01

Climatology and variations of recent mean and intense precipitation over a near-global (50 deg. S 50 deg. N) domain on a monthly and annual time scale are analyzed. Data used to derive daily precipitation to examine the effects of spatial and temporal coverage of intense precipitation are from the current Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7 precipitation product, with high spatial and temporal resolution during 1998 - 2013. Intense precipitation is defined by several different parameters, such as a 95th percentile threshold of daily precipitation, a mean precipitation that exceeds that percentile, or a fixed threshold of daily precipitation value [e.g., 25 and 50 mm day(exp -1)]. All parameters are used to identify the main characteristics of spatial and temporal variation of intense precipitation. High correlations between examined parameters are observed, especially between climatological monthly mean precipitation and intense precipitation, over both tropical land and ocean. Among the various parameters examined, the one best characterizing intense rainfall is a fraction of daily precipitation Great than or equal to 25 mm day(exp. -1), defined as a ratio between the intense precipitation above the used threshold and mean precipitation. Regions that experience an increase in mean precipitation likely experience a similar increase in intense precipitation, especially during the El Nino Southern Oscillation (ENSO) events. Improved knowledge of this intense precipitation regime and its strong connection to mean precipitation given by the fraction parameter can be used for monitoring of intense rainfall and its intensity on a global to regional scale.

Long-term Observations of Intense Precipitation Small-scale Spatial Variability in a Semi-arid Catchment

NASA Astrophysics Data System (ADS)

Cropp, E. L.; Hazenberg, P.; Castro, C. L.; Demaria, E. M.

2017-12-01

In the southwestern US, the summertime North American Monsoon (NAM) provides about 60% of the region's annual precipitation. Recent research using high-resolution atmospheric model simulations and retrospective predictions has shown that since the 1950's, and more specifically in the last few decades, the mean daily precipitation in the southwestern U.S. during the NAM has followed a decreasing trend. Furthermore, days with more extreme precipitation have intensified. The current work focuses the impact of these long-term changes on the observed small-scale spatial variability of intense precipitation. Since limited long-term high-resolution observational data exist to support such climatological-induced spatial changes in precipitation frequency and intensity, the current work utilizes observations from the USDA-ARS Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. Within this 150 km^2 catchment over 90 rain gauges have been installed since the 1950s, measuring at sub-hourly resolution. We have applied geospatial analyses and the kriging interpolation technique to identify long-term changes in the spatial and temporal correlation and anisotropy of intense precipitation. The observed results will be compared with the previously model simulated results, as well as related to large-scale variations in climate patterns, such as the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO).

Trend and change point analyses of annual precipitation in the Souss-Massa Region in Morocco during 1932-2010

NASA Astrophysics Data System (ADS)

Abahous, H.; Ronchail, J.; Sifeddine, A.; Kenny, L.; Bouchaou, L.

2017-11-01

In the context of an arid area such as Souss Massa Region, the availability of time series analysis of observed local data is vital to better characterize the regional rainfall configuration. In this paper, dataset of monthly precipitation collected from different local meteorological stations during 1932-2010, are quality controlled and analyzed to detect trend and change points. The temporal distribution of outliers shows an annual cycle and a decrease of their number since the 1980s. The results of the standard normal homogeneity test, penalized maximal t test, and Mann-Whitney-Pettit test show that 42% of the series are homogeneous. The analysis of annual precipitation in the region of Souss Massa during 1932-2010 shows wet conditions with a maximum between 1963 and 1965 followed by a decrease since 1973. The latter is identified as a statistically significant regional change point in Western High Atlas and Anti Atlas Mountains highlighting a decline in long-term average precipitation.

Atlas of depth-duration frequency of precipitation annual maxima for Texas

USGS Publications Warehouse

Asquith, William H.; Roussel, Meghan C.

2004-01-01

The objective of this Texas Department of Transportation (TxDOT) and U.S. Geological Survey (USGS) cooperatively funded project was to develop a simple-to-use atlas of precipitation depths in Texas for selected storm durations and frequencies on the basis of the research results and unpublished digital archives of Asquith (1998). The selected storm durations are 15 and 30 minutes; 1, 2, 3, 6, and 12 hours; and 1, 2, 3, 5, and 7 days. The selected storm frequencies or annual recurrence intervals are 2, 5, 10, 25, 50, 100, 250, and 500 years. Depth-duration frequency (DDF) of annual precipitation maxima is important for cost-effective, risk-mitigated hydrologic design. DDF values are in common and wide-spread use by public and private entities throughout Texas.

Observed rainfall trends and precipitation uncertainty in the vicinity of the Mediterranean, Middle East and North Africa

NASA Astrophysics Data System (ADS)

Zittis, G.

2017-11-01

The present study investigates the century-long and more recent rainfall trends over the greater region of Middle East and North Africa (MENA). Five up-to-date gridded observational datasets are employed. Besides mean annual values, trends of six indices of drought and extreme precipitation are also considered in the analysis. Most important findings include the significant negative trends over the Maghreb, Levant, Arabian Peninsula, and Sahel regions that are evident since the beginning of the twentieth century and are more or less extended to today. On the other hand, for some Mediterranean regions such as the Balkans and the Anatolian Plateau, precipitation records during the most recent decades indicate a significant increasing trend and a recovering from the dry conditions that occurred during the mid-1970s and mid-1980s. The fact that over parts of the study region the selected datasets were found to have substantial differences in terms of mean climate, trends, and interannual variability, motivated the more thorough investigation of the precipitation observational uncertainty. Several aspects, such as annual and monthly mean climatologies and also discrepancies in the monthly time-series distribution, are discussed using common methods in the field of climatology but also more sophisticated, nonparametric approaches such as the Kruskal-Wallis and Dunn's tests. Results indicate that in the best case, the data sources are found to have statistically significant differences in the distribution of monthly precipitation for about 50% of the study region extent. This percentage is increased up to 70% when particular datasets are compared. Indicatively, the range between the tested rainfall datasets is found to be more than 20% of their mean annual values for most of the extent of MENA, while locally, for the hyper-arid regions, this percentage is increased up to 100%. Precipitation observational uncertainty is also profound for parts of southern Europe. Outlier

Projected Changes in the Annual Cycle of Precipitation over Central Asia by CMIP5 Models

NASA Astrophysics Data System (ADS)

Yu, X.; Zhao, Y.

2017-12-01

Future changes in the annual cycle of the precipitation in central Asia (CA) were estimated based on the historical and Representative Concentration Pathway 8.5 (RCP8.5) experiments from 25 models of the Coupled Model Intercomparison Project phase 5 (CMIP5). Compared with the Global Precipitation Climatology Project (GPCP) observations, the historical (1979-1999) experiments showed that most models can capture the migration of rainfall centers, but remarkable discrepancies exist in the location and intensity of rainfall centers between simulations and observations. Considering the skill scores of precipitation and pattern correlations of circulations, which are closely related to the precipitation for each month, for the 25 models, the four best models (e.g., CanESM2, CMCC-CMS, MIROC5 and MPI-ESM-LR) with relatively good performance were selected. The four models' ensemble mean indicated that the migration and location of the precipitation centers were better reproduced, except the intensity of the centers was overestimated, compared with the result that only considered precipitation. Based on the four best models' ensemble mean under RCP8.5 scenarios, precipitation was projected to increase dramatically over most of the CA region in the boreal cold seasons (November, December, January, February, March, April and May) with the maximum in December in the end of twenty-first century (2079-2099), and several positive centers were located in the Pamirs Plateau and the Tianshan Mountains. By contrast, the precipitation changes were weak in the boreal warm seasons (June, July, August, September and October), with a wet center located in the northern Himalayas. Furthermore, there remain some uncertainties in the projected precipitation regions and periods obtained by comparing models' ensemble results of this paper and the results of previous studies. These uncertainties should be investigated in future work.

Synoptic Drivers of Precipitation in the Atlantic Sector of the Arctic

NASA Astrophysics Data System (ADS)

Cohen, L.; Hudson, S.; Graham, R.; Renwick, J. A.

2017-12-01

Precipitation in the Arctic has been shown to be increasing in recent decades, from both observational and modelling studies, with largest trends seen in autumn and winter. This trend is attributed to a combination of the warming atmosphere and reduced sea ice extent. The seasonality of precipitation in the Arctic is important as it largely determines whether the precipitation falls as snow or rain. This study assesses the spatial and temporal variability of the synoptic drivers of precipitation in the Atlantic (European) sector of the Arctic. This region of the Arctic is of particular interest as it has the largest inter-annual variability in sea ice extent and is the primary pathway for moisture transport into the Arctic from lower latitudes. This study uses the ECMWF ERA-I reanalysis total precipitation to compare to long-term precipitation observations from Ny Ålesund, Svalbard to show that the reanalysis captures the synoptic variability of precipitation well and that most precipitation in this region is synoptically driven. The annual variability of precipitation in the Atlantic Arctic shows strong regionality. In the Svalbard and Barents Sea region, most of the annual total precipitation occurs during autumn and winter (Oct-Mar) (>60% of annual total), while the high-Arctic (> 80N) and Kara Sea receives most of the annual precipitation ( 60% of annual total) during summer (July-Sept). Using a synoptic classification developed for this region, this study shows that winter precipitation is driven by winter cyclone occurrence, with strong correlations to the AO and NAO indices. High precipitation over Svalbard is also strongly correlated with the Scandinavian blocking pattern, which produces a southerly flow in the Greenland Sea/Svalbard area. An increasing occurrence of these synoptic patterns are seen for winter months (Nov and Jan), which may explain much of the observed winter increase in precipitation.

Variability of precipitation in Poland under climate change

NASA Astrophysics Data System (ADS)

Szwed, Małgorzata

2018-02-01

The surface warming has been widespread over the entire globe. Central Europe, including Poland, is not an exception. Global temperature increases are accompanied by changes in other climatic variables. Climate change in Poland manifests itself also as change in annual sums of precipitation. They have been slightly growing but, what is more important, seasonal and monthly distributions of precipitation have been also changing. The most visible increases have been observed during colder half-year, especially in March. A decreasing contribution of summer precipitation total (June-August) to the annual total is observed. Climate projections for Poland predict further warming and continuation of already observed changes in the quantity of precipitation as well as its spatial and seasonal distribution.

Trend analysis of precipitation in Jharkhand State, India. Investigating precipitation variability in Jharkhand State

NASA Astrophysics Data System (ADS)

Chandniha, Surendra Kumar; Meshram, Sarita Gajbhiye; Adamowski, Jan Franklin; Meshram, Chandrashekhar

2017-10-01

Jharkhand is one of the eastern states of India which has an agriculture-based economy. Uncertain and erratic distribution of precipitation as well as a lack of state water resources planning is the major limitation to crop growth in the region. In this study, the spatial and temporal variability in precipitation in the state was examined using a monthly precipitation time series of 111 years (1901-2011) from 18 meteorological stations. Autocorrelation and Mann-Kendall/modified Mann-Kendall tests were utilized to detect possible trends, and the Theil and Sen slope estimator test was used to determine the magnitude of change over the entire time series. The most probable change year (change point) was detected using the Pettitt-Mann-Whitney test, and the entire time series was sub-divided into two parts: before and after the change point. Arc-Map 9.3 software was utilized to assess the spatial patterns of the trends over the entire state. Annual precipitation exhibited a decreasing trend in 5 out of 18 stations during the whole period. For annual, monsoon and winter periods of precipitation, the slope test indicated a decreasing trend for all stations during 1901-2011. The highest variability was observed in post-monsoon precipitation (77.87 %) and the lowest variability was observed in the annual series (15.76 %) over the 111 years. An increasing trend in precipitation in the state was found during the period 1901-1949, which was reversed during the subsequent period (1950-2011).

A method to reconstruct long precipitation series using systematic descriptive observations in weather diaries: the example of the precipitation series for Bern, Switzerland (1760-2003)

NASA Astrophysics Data System (ADS)

Gimmi, U.; Luterbacher, J.; Pfister, C.; Wanner, H.

2007-01-01

In contrast to barometric and thermometric records, early instrumental precipitation series are quite rare. Based on systematic descriptive daily records, a quantitative monthly precipitation series for Bern (Switzerland) was reconstructed back to the year 1760 (reconstruction based on documentary evidence). Since every observer had his own personal style to fill out his diary, the main focus was to avoid observer-specific bias in the reconstruction. An independent statistical monthly precipitation reconstruction was performed using instrumental data from European sites. Over most periods the reconstruction based on documentary evidence lies inside the 2 standard errors of the statistical estimates. The comparison between these two approaches enables an independent verification and a reliable error estimate. The analysis points to below normal rainfall totals in all seasons during the late 18th century and in the 1820s and 1830s. Increased precipitation occurred in the early 1850s and the late 1870s, particularly from spring to autumn. The annual precipitation totals generally tend to be higher in the 20th century than in the late 18th and 19th century. Precipitation changes are discussed in the context of socioeconomic impacts and Alpine glacier dynamics. The conceptual design of the reconstruction procedure is aimed at application for similar descriptive precipitation series, which are known to be abundant from the mid-18th century in Europe and the U.S.

Comparison of three-parameter probability distributions for representing annual extreme and partial duration precipitation series

NASA Astrophysics Data System (ADS)

Wilks, Daniel S.

1993-10-01

Performance of 8 three-parameter probability distributions for representing annual extreme and partial duration precipitation data at stations in the northeastern and southeastern United States is investigated. Particular attention is paid to fidelity on the right tail, through use of a bootstrap procedure simulating extrapolation on the right tail beyond the data. It is found that the beta-κ distribution best describes the extreme right tail of annual extreme series, and the beta-P distribution is best for the partial duration data. The conventionally employed two-parameter Gumbel distribution is found to substantially underestimate probabilities associated with the larger precipitation amounts for both annual extreme and partial duration data. Fitting the distributions using left-censored data did not result in improved fits to the right tail.

Digital-map grids of mean-annual precipitation for 1961-90, and generalized skew coefficients of annual maximum streamflow for Oklahoma

USGS Publications Warehouse

Rea, A.H.; Tortorelli, R.L.

1997-01-01

This digital report contains two digital-map grids of data that were used to develop peak-flow regression equations in Tortorelli, 1997, 'Techniques for estimating peak-streamflow frequency for unregulated streams and streams regulated by small floodwater retarding structures in Oklahoma,' U.S. Geological Survey Water-Resources Investigations Report 97-4202. One data set is a grid of mean annual precipitation, in inches, based on the period 1961-90, for Oklahoma. The data set was derived from the PRISM (Parameter-elevation Regressions on Independent Slopes Model) mean annual precipitation grid for the United States, developed by Daly, Neilson, and Phillips (1994, 'A statistical-topographic model for mapping climatological precipitation over mountainous terrain:' Journal of Applied Meteorology, v. 33, no. 2, p. 140-158). The second data set is a grid of generalized skew coefficients of logarithms of annual maximum streamflow for Oklahoma streams less than or equal to 2,510 square miles in drainage area. This grid of skew coefficients is taken from figure 11 of Tortorelli and Bergman, 1985, 'Techniques for estimating flood peak discharges for unregulated streams and streams regulated by small floodwater retarding structures in Oklahoma,' U.S. Geological Survey Water-Resources Investigations Report 84-4358. To save disk space, the skew coefficient values have been multiplied by 100 and rounded to integers with two significant digits. The data sets are provided in an ASCII grid format.

Precipitation information from GNSS Polarimetric Radio Occultation observations

NASA Astrophysics Data System (ADS)

Padulles, R.; Cardellach, E.; Turk, J.; Tomás, S.; Ao, C. O.; de la Torre-Juárez, M.

2017-12-01

There is currently a gap in satellite observations of the moisture structure during heavy precipitation conditions, since infrared and microwave sounders cannot sense water vapor structure near the surface in the presence of intense precipitation. Conversely, Global Navigation Satellite System (GNSS) Radio Occultations (RO) can profile the moisture structure with high precision and vertical resolution, but cannot directly indicate the presence of precipitation. Polarimetric RO (PRO) measurements have been proposed as a method to characterize heavy rain in GNSS RO, by measuring the polarimetric differential phase delay induced by large size hydrometeors. The PRO concept will be tested from space for the first time on board the Spanish PAZ satellite, planned for launch by the end of 2017. Therefore, for the first time ever, GNSS RO measurements will be taken at two polarizations, to exploit the potential capabilities of polarimetric RO for detecting and quantifying heavy precipitation events. If the concept is proved, PAZ will mean a new application of the GNSS Radio-Occultation observations, by providing coincident thermodynamic and precipitation information with high vertical resolution within regions with thick clouds. Before the launch, a series of studies have been performed in order to assess the retrieval of precipitation information from the polarimetric observations. These studies have been based on coincident observations from the COSMIC / FORMOSAT-3 RO satellite constellation, and TRMM and GPM missions. This massive collocation exercise allowed us to build a series of Look Up Tables that relate probabilistically the precipitation intensity to the polarimetric observables. Such studies needed a previous characterization of the polarimetric observable, since it contains contributions from the ionosphere and the emitting and receiving systems. For this purpose, complete end-to-end simulations have been performed, where information from the ionospheric state

On the long-range dependence properties of annual precipitation using a global network of instrumental measurements

NASA Astrophysics Data System (ADS)

Tyralis, Hristos; Dimitriadis, Panayiotis; Koutsoyiannis, Demetris; O'Connell, Patrick Enda; Tzouka, Katerina; Iliopoulou, Theano

2018-01-01

The long-range dependence (LRD) is considered an inherent property of geophysical processes, whose presence increases uncertainty. Here we examine the spatial behaviour of LRD in precipitation by regressing the Hurst parameter estimate of mean annual precipitation instrumental data which span from 1916-2015 and cover a big area of the earth's surface on location characteristics of the instrumental data stations. Furthermore, we apply the Mann-Kendall test under the LRD assumption (MKt-LRD) to reassess the significance of observed trends. To summarize the results, the LRD is spatially clustered, it seems to depend mostly on the location of the stations, while the predictive value of the regression model is good. Thus when investigating for LRD properties we recommend that the local characteristics should be considered. The application of the MKt-LRD suggests that no significant monotonic trend appears in global precipitation, excluding the climate type D (snow) regions in which positive significant trends appear.

An Evaluation of CMIP5 Precipitation Variability for China Relative to Observations and CMIP3

NASA Astrophysics Data System (ADS)

Frauenfeld, O. W.; Chen, L.

2013-12-01

Precipitation represents an important link between the atmosphere, hydrosphere, and biosphere and is thus a key component of the climate system. As indicated by the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), global surface air temperatures increased by 0.74°C during the 20th century, with further warming of 0.2°C/decade projected by the 2030s. Projected changes in precipitation, however, are much more variable, and exhibit more complex temporal and spatial patterns. This presentation focuses on precipitation variability based on 20 general circulation models (GCMs) participating in the fifth coupled model intercomparison project (CMIP5). Specifically, we focus on China and provide a comprehensive evaluation of the CMIP5 models compared to historical 20th century precipitation variability from two observational precipitation products: the University of East Anglia's Climatic Research Unit (CRU) time series (TS) dataset version 3.10, and the Global Precipitation Climatology Centre (GPCC) version 6. We also reassess the performance of the third CMIP (CMIP3) to quantify potential improvements in CMIP5 over the previous generation of GCMs. Finally, we provide 21st century precipitation projections for China based on three representative concentration pathways (RCP): RCP 8.5, 4.5, and 2.6. These future precipitation projections are presented in light of the observed 20th century biases in the models. We find that CMIP5 models are able to better reproduce the general spatial pattern of observed 20th century precipitation than CMIP3. However, for China as a whole, the annual precipitation magnitude is overestimated in CMIP5, more so than in CMIP3. This smaller overestimation in CMIP3 was primarily driven by a large underestimation of summer precipitation. Spatially, overestimated precipitation magnitudes are evident for most regions of China, especially along the eastern margin of the Tibetan Plateau. Over southeastern China

Benchmarking a geostatistical procedure for the homogenisation of annual precipitation series

NASA Astrophysics Data System (ADS)

Caineta, Júlio; Ribeiro, Sara; Henriques, Roberto; Soares, Amílcar; Costa, Ana Cristina

2014-05-01

The European project COST Action ES0601, Advances in homogenisation methods of climate series: an integrated approach (HOME), has brought to attention the importance of establishing reliable homogenisation methods for climate data. In order to achieve that, a benchmark data set, containing monthly and daily temperature and precipitation data, was created to be used as a comparison basis for the effectiveness of those methods. Several contributions were submitted and evaluated by a number of performance metrics, validating the results against realistic inhomogeneous data. HOME also led to the development of new homogenisation software packages, which included feedback and lessons learned during the project. Preliminary studies have suggested a geostatistical stochastic approach, which uses Direct Sequential Simulation (DSS), as a promising methodology for the homogenisation of precipitation data series. Based on the spatial and temporal correlation between the neighbouring stations, DSS calculates local probability density functions at a candidate station to detect inhomogeneities. The purpose of the current study is to test and compare this geostatistical approach with the methods previously presented in the HOME project, using surrogate precipitation series from the HOME benchmark data set. The benchmark data set contains monthly precipitation surrogate series, from which annual precipitation data series were derived. These annual precipitation series were subject to exploratory analysis and to a thorough variography study. The geostatistical approach was then applied to the data set, based on different scenarios for the spatial continuity. Implementing this procedure also promoted the development of a computer program that aims to assist on the homogenisation of climate data, while minimising user interaction. Finally, in order to compare the effectiveness of this methodology with the homogenisation methods submitted during the HOME project, the obtained results

Precipitation observations for operational flood forecasting in Scotland: Data availability, limitations and the impact of observational uncertainty

NASA Astrophysics Data System (ADS)

Parry, Louise; Neely, Ryan, III; Bennett, Lindsay; Collier, Chris; Dufton, David

2017-04-01

The Scottish Environment Protection Agency (SEPA) has a statutory responsibility to provide flood warning across Scotland. It achieves this through an operational partnership with the UK Met Office wherein meteorological forecasts are applied to a national distributed hydrological model, Grid- to- Grid (G2G), and catchment specific lumped PDM models. Both of these model types rely on observed precipitation input for model development and calibration, and operationally for historical runs to generate initial conditions. Scotland has an average annual precipitation of 1430mm per annum (1971-2000), but the spatial variability in totals is high, predominantly in relation to the topography and prevailing winds, which poses different challenges to both radar and point measurement methods of observation. In addition, the high elevations mean that in winter a significant proportion of precipitation falls as snow. For the operational forecasting models, observed rainfall data is provided in Near Real Time (NRT) from SEPA's network of approximately 260 telemetered TBR gauges and 4 UK Met Office C-band radars. Both data sources have their strengths and weaknesses, particularly in relation to the orography and spatial representativeness, but estimates of rainfall from the two methods can vary greatly. Northern Scotland, particularly near Inverness, is a comparatively sparse part of the radar network. Rainfall totals and distribution in this area are determined by the Northern Western Highlands and Cairngorms mountain ranges, which also have a negative impact on radar observations. In recognition of this issue, the NCAS mobile X-band weather radar (MXWR) was deployed in this area between February and August 2016. This study presents a comparison of rainfall estimates for the Inverness and Moray Firth region generated from the operational radar network, the TBR network, and the MXWR. Quantitative precipitation estimates (QPEs) from both sources of radar data were compared to

Observed heavy precipitation increase confirms theory and early model

NASA Astrophysics Data System (ADS)

Fischer, E. M.; Knutti, R.

2016-12-01

Environmental phenomena are often first observed, and then explained or simulated quantitatively. The complexity and diversity of processes, the range of scales involved, and the lack of first principles to describe many processes make it challenging to predict conditions beyond the ones observed. Here we use the intensification of heavy precipitation as a counterexample, where seemingly complex and potentially computationally intractable processes to first order manifest themselves in simple ways: the intensification of heavy precipitation is now emerging in the observed record across many regions of the world, confirming both theory and a variety of model predictions made decades ago, before robust evidence arose from observations. We here compare heavy precipitation changes over Europe and the contiguous United States across station series and gridded observations, theoretical considerations and multi-model ensembles of GCMs and RCMs. We demonstrate that the observed heavy precipitation intensification aggregated over large areas agrees remarkably well with Clausius-Clapeyron scaling. The observed changes in heavy precipitation are consistent yet somewhat larger than predicted by very coarse resolution GCMs in the 1980s and simulated by the newest generation of GCMs and RCMs. For instance the number of days with very heavy precipitation over Europe has increased by about 45% in observations (years 1981-2013 compared to 1951-1980) and by about 25% in the model average in both GCMs and RCMs, although with substantial spread across models and locations. As the anthropogenic climate signal strengthens, there will be more opportunities to test climate predictions for other variables against observations and across a hierarchy of different models and theoretical concepts. *Fischer, E.M., and R. Knutti, 2016, Observed heavy precipitation increase confirms theory and early models, Nature Climate Change, in press.

EnviroAtlas - Average Annual Precipitation 1981-2010 by HUC12 for the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset provides the average annual precipitation by 12-digit Hydrologic Unit (HUC). The values were estimated from maps produced by the PRISM Climate Group, Oregon State University. The original data was at the scale of 800 m grid cells representing average precipitation from 1981-2010 in mm. The data was converted to inches of precipitation and then zonal statistics were estimated for a final value of average annual precipitation for each 12 digit HUC. For more information about the original dataset please refer to the PRISM website at http://www.prism.oregonstate.edu/. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Annual precipitation in the Yellowstone National Park region since AD 1173

USGS Publications Warehouse

Gray, Stephen T.; Graumlich, Lisa J.; Betancourt, Julio L.

2007-01-01

Cores and cross sections from 133 limber pine (Pinus flexilis James) and Douglas fir (Pseudotsuga menziesii (Mirbel) Franco) at four sites were used to estimate annual (July to June) precipitation in the Yellowstone National Park region for the period from AD 1173 to 1998. Examination of the long-term record shows that the early 20th century was markedly wet compared to the previous 700 yr. Extreme wet and dry years within the instrumental period fall within the range of past variability, and the magnitude of the worst-case droughts of the 20th century (AD 1930s and 1950s) was likely equaled or exceeded on numerous occasions before AD 1900. Spectral analysis showed significant decadal to multidecadal precipitation variability. At times this lower frequency variability produces strong regime-like behavior in regional precipitation, with the potential for rapid, high-amplitude switching between predominately wet and predominately dry conditions. Over multiple time scales, strong Yellowstone region precipitation anomalies were almost always associated with spatially extensive events spanning various combinations of the central and southern U.S. Rockies, the northern U.S.-Southern Canadian Rockies and the Pacific Northwest.

Annual precipitation in the Yellowstone National Park region since AD 1173

USGS Publications Warehouse

Gray, S.T.; Graumlich, L.J.; Betancourt, J.L.

2007-01-01

Cores and cross sections from 133 limber pine (Pinus flexilis James) and Douglas fir (Pseudotsuga menziesii (Mirbel) Franco) at four sites were used to estimate annual (July to June) precipitation in the Yellowstone National Park region for the period from AD 1173 to 1998. Examination of the long-term record shows that the early 20th century was markedly wet compared to the previous 700??yr. Extreme wet and dry years within the instrumental period fall within the range of past variability, and the magnitude of the worst-case droughts of the 20th century (AD 1930s and 1950s) was likely equaled or exceeded on numerous occasions before AD 1900. Spectral analysis showed significant decadal to multidecadal precipitation variability. At times this lower frequency variability produces strong regime-like behavior in regional precipitation, with the potential for rapid, high-amplitude switching between predominately wet and predominately dry conditions. Over multiple time scales, strong Yellowstone region precipitation anomalies were almost always associated with spatially extensive events spanning various combinations of the central and southern U.S. Rockies, the northern U.S.-Southern Canadian Rockies and the Pacific Northwest. ?? 2007 University of Washington.

Watershed-scale response of groundwater recharge to inter-annual and inter-decadal variability in precipitation (Alberta, Canada)

NASA Astrophysics Data System (ADS)

Hayashi, Masaki; Farrow, Christopher R.

2014-12-01

Groundwater recharge sets a constraint on aquifer water balance in the context of water management. Historical data on groundwater and other relevant hydrological processes can be used to understand the effects of climatic variability on recharge, but such data sets are rare. The climate of the Canadian prairies is characterized by large inter-annual and inter-decadal variability in precipitation, which provides opportunities to examine the response of groundwater recharge to changes in meteorological conditions. A decadal study was conducted in a small (250 km2) prairie watershed in Alberta, Canada. Relative magnitude of annual recharge, indicated by water-level rise, was significantly correlated with a combination of growing-season precipitation and snowmelt runoff, which drives depression-focussed infiltration of meltwater. Annual precipitation was greater than vapour flux at an experimental site in some years and smaller in other years. On average precipitation minus vapour flux was 10 mm y-1, which was comparable to the magnitude of watershed-scale groundwater recharge estimated from creek baseflow. Average baseflow showed a distinct shift from a low value (4 mm y-1) in 1982-1995 to a high value (15 mm y-1) in 2003-2013, indicating the sensitivity of groundwater recharge to a decadal-scale variability of meteorological conditions.

Frequency of annual maximum precipitation in the City of Charlotte and Mecklenburg County, North Carolina, through 2004

USGS Publications Warehouse

Weaver, J. Curtis

2006-01-01

A study of annual maximum precipitation frequency in Mecklenburg County, North Carolina, was conducted to characterize the frequency of precipitation at sites having at least 10 years of precipitation record. Precipitation-frequency studies provide information about the occurrence of precipitation amounts for given durations (for example, 1 hour or 24 hours) that can be expected to occur within a specified recurrence interval (expressed in years). In this study, annual maximum precipitation totals were determined for durations of 15 and 30 minutes; 1, 2, 3, 6, 12, and 24 hours; and for recurrence intervals of 2, 5, 10, 25, 50, 100, and 500 years. Precipitation data collected by the U.S. Geological Survey network of raingages in the city of Charlotte and Mecklenburg County were analyzed for this study. In September 2004, more than 70 precipitation sites were in operation; 27 of these sites had at least 10 years of record, which is the minimum record typically required in frequency studies. Missing record at one site, however, resulted in its removal from the dataset. Two datasets--the Charlotte Raingage Network (CRN) initial and CRN modified datasets--were developed from the U.S. Geological Survey data, which represented relatively short periods of record (10 and 11 years). The CRN initial dataset included very high precipitation totals from two storms that caused severe flooding in areas of the city and county in August 1995 and July 1997, which could significantly influence the statistical results. The CRN modified dataset excluded the highest precipitation totals from these two storms but included the second highest totals. More...

An Observation-based Assessment of Instrument Requirements for a Future Precipitation Process Observing System

NASA Astrophysics Data System (ADS)

Nelson, E.; L'Ecuyer, T. S.; Wood, N.; Smalley, M.; Kulie, M.; Hahn, W.

2017-12-01

Global models exhibit substantial biases in the frequency, intensity, duration, and spatial scales of precipitation systems. Much of this uncertainty stems from an inadequate representation of the processes by which water is cycled between the surface and atmosphere and, in particular, those that govern the formation and maintenance of cloud systems and their propensity to form the precipitation. Progress toward improving precipitation process models requires observing systems capable of quantifying the coupling between the ice content, vertical mass fluxes, and precipitation yield of precipitating cloud systems. Spaceborne multi-frequency, Doppler radar offers a unique opportunity to address this need but the effectiveness of such a mission is heavily dependent on its ability to actually observe the processes of interest in the widest possible range of systems. Planning for a next generation precipitation process observing system should, therefore, start with a fundamental evaluation of the trade-offs between sensitivity, resolution, sampling, cost, and the overall potential scientific yield of the mission. Here we provide an initial assessment of the scientific and economic trade-space by evaluating hypothetical spaceborne multi-frequency radars using a combination of current real-world and model-derived synthetic observations. Specifically, we alter the field of view, vertical resolution, and sensitivity of a hypothetical Ka- and W-band radar system and propagate those changes through precipitation detection and intensity retrievals. The results suggest that sampling biases introduced by reducing sensitivity disproportionately affect the light rainfall and frozen precipitation regimes that are critical for warm cloud feedbacks and ice sheet mass balance, respectively. Coarser spatial resolution observations introduce regime-dependent biases in both precipitation occurrence and intensity that depend on cloud regime, with even the sign of the bias varying within a

A 3,500-year tree-ring record of annual precipitation on the northeastern Tibetan Plateau.

PubMed

Yang, Bao; Qin, Chun; Wang, Jianglin; He, Minhui; Melvin, Thomas M; Osborn, Timothy J; Briffa, Keith R

2014-02-25

An annually resolved and absolutely dated ring-width chronology spanning 4,500 y has been constructed using subfossil, archaeological, and living-tree juniper samples from the northeastern Tibetan Plateau. The chronology represents changing mean annual precipitation and is most reliable after 1500 B.C. Reconstructed precipitation for this period displays a trend toward more moist conditions: the last 10-, 25-, and 50-y periods all appear to be the wettest in at least three and a half millennia. Notable historical dry periods occurred in the 4th century BCE and in the second half of the 15th century CE. The driest individual year reconstructed (since 1500 B.C.) is 1048 B.C., whereas the wettest is 2010. Precipitation variability in this region appears not to be associated with inferred changes in Asian monsoon intensity during recent millennia. The chronology displays a statistical association with the multidecadal and longer-term variability of reconstructed mean Northern Hemisphere temperatures over the last two millennia. This suggests that any further large-scale warming might be associated with even greater moisture supply in this region.

The effects of precipitation and soil type on three invasive annual grasses in the western United States

Treesearch

Sheel Bansal; Jeremy J. James; Roger L. Sheley

2014-01-01

Multiple species of annual grasses are invading sagebrush-steppe communities throughout the western United States. Most research has focused on dominant species such as Bromus tectorum (cheatgrass), yet other, less studied annual grasses such as Taeniatherum caput-medusae (medusahead) and Ventenata dubia (ventenata) are spreading rapidly. Future precipitation regimes...

On the teleconnection patterns to precipitation in the eastern Tianshan Mountains, China

NASA Astrophysics Data System (ADS)

Zhong, Yu; Wang, Binbin; Zou, Chris B.; Hu, Bill X.; Liu, Youcun; Hao, Yonghong

2017-11-01

The Tianshan Mountains are known as the "water tower" in the arid region of Central Asia. Change in precipitation amount and pattern can have a profound impact on regional civilization and life supporting ecosystems. For this study, a systematic analysis of long-term precipitation data for the eastern Tianshan Mountains was conducted to investigate the influence of climate teleconnections on annual and intra-annual precipitation using data collected between 1951 and 2014 from 39 meteorological stations. Annual precipitation has increased during the past six decades at an average rate of 6.7 mm/10 years largely due to the increase in precipitation during the intra-annual wet period (May-October). The annual precipitation and its rate of increase were higher in the northwestern region. Annual precipitation was found to be most strongly correlated with index of Indian Summer Monsoon (ISM), and partially correlated with indices of Pacific Decadal Oscillation (PDO), Pacific North American Teleconnection Pattern (PNA), Arctic Oscillation (AO), El Nino-Southern Oscillation (ENSO), and North Atlantic Oscillation (NAO). ISM was positively correlated with the precipitation in almost the entire region during the intra-annual wet period, while it showed positive correlations in the northern slope and the alpine region, and negative correlations in the southern slope during the intra-annual dry period (November to April). PDO had much weaker influence both in spatial scale and strength and primarily affected low elevations on the southern slopes of the middle and western regions. The impacts of PNA and AO on precipitation were weak and localized. ENSO and NAO indices were almost not correlated with annual precipitation observation in the eastern Tianshan Mountains.

Climate, interseasonal storage of soil water, and the annual water balance

USGS Publications Warehouse

Milly, P.C.D.

1994-01-01

The effects of annual totals and seasonal variations of precipitation and potential evaporation on the annual water balance are explored. It is assumed that the only other factor of significance to annual water balance is a simple process of water storage, and that the relevant storage capacity is the plant-available water-holding capacity of the soil. Under the assumption that precipitation and potential evaporation vary sinusoidally through the year, it is possible to derive an analytic solution of the storage problem, and this yields an expression for the fraction of precipitation that evaporates (and the fraction that runs off) as a function of three dimensionless numbers: the ratio of annual potential evaporation to annual precipitation (index of dryness); an index of the seasonality of the difference between precipitation and potential evaporation; and the ratio of plant-available water-holding capacity to annual precipitation. The solution is applied to the area of the United States east of 105??W, using published information on precipitation, potential evaporation, and plant-available water-holding capacity as inputs, and using an independent analysis of observed river runoff for model evaluation. The model generates an areal mean annual runoff of only 187 mm, which is about 30% less than the observed runoff (263 mm). The discrepancy is suggestive of the importance of runoff-generating mechanisms neglected in the model. These include intraseasonal variability (storminess) of precipitation, spatial variability of storage capacity, and finite infiltration capacity of land. ?? 1994.

Some statistics of freezing precipitation and rime for the territory of the former USSR from ground-based weather observations

NASA Astrophysics Data System (ADS)

Bezrukova, Natalia A.; Jeck, Richard K.; Khalili, Marat F.; Minina, Ludmila S.; Naumov, Alexander Ya.; Stulov, Evgeny A.

2006-11-01

This work is a continuation of the previous climatological study of freezing precipitation and rime over the USSR territory [ Bezrukova, N.A., Minina, L.S., Naumov, A.Ya., 2000. Freezing precipitation climatology in the former European USSR. Proceedings of the 13th International Conference on Clouds and Precipitation, pp.737-739, Reno, Nevada, USA, 14-18 August 2000; Bezrukova, N.A., Jeck, R.K., Minina, L.S., Khalili, M.F., Stulov, E.A., 2004. 10-year Statistics on Freezing Precipitation across the former USSR from surface weather observations. Proceedings of the 14th International Conference on Clouds and Precipitation, pp.731-734, Bologna, Italy, 19-23 August 2004.] aimed at creating an atlas of the frequency of these phenomena. This study gives considerable information about and a statistical analysis of freezing precipitation and rime events observed over the territory of the former USSR during a decade (1981-1990) and over the European territory of the USSR during two decades (1971-1990). This paper intends to draw the attention of the reader to the atlas and statistics by showing some interesting points. The authors used the data provided by the ground-based weather stations involved in the international exchange of meteorological data. The USSR network's Monthly Meteorological Tables (1971-1990) [Monthly Meteorological Tables, 1971-1990. Part 1, Novosibirsk-Obninsk. (in Russian).] comprising selected daily ground-based meteorological observations from more than 220 stations served as a basis for the analysis. All the types of freezing precipitation (FP) events were given as WMO Codes 56, 57, 66, 67, 24 and freezing fog (FF) deposited rime as WMO Codes 48, 49. The entire territory was divided into six major regions: the Arctic, the European part of the USSR, the Trans-Caucasus, Central Asia, Siberia, and the Far East. The frequency and distribution of events by regions versus temperature, atmospheric pressure, clouds base height, and some other meteorological

Potential relationships between the river discharge and the precipitation in the Jinsha River basin, China

NASA Astrophysics Data System (ADS)

Wang, Gaoxu; Zeng, Xiaofan; Zhao, Na; He, Qifang; Bai, Yiran; Zhang, Ruoyu

2018-02-01

The relationships between the river discharge and the precipitation in the Jinsha River basin are discussed in this study. In addition, the future precipitation trend from 2011-2050 and its potential influence on the river discharge are analysed by applying the CCLM-modelled precipitation. According to the observed river discharge and precipitation, the annual river discharge at the two main hydrological stations displays good correlations with the annual precipitation in the Jinsha River basin. The predicted future precipitation tends to change similarly as the change that occurred during the observation period, whereas the monthly distributions over a year could be more uneven, which is unfavourable for water resources management.

The response of soil microbial communities to variation in annual precipitation depends on soil nutritional status in an oligotrophic desert

PubMed Central

Montiel-González, Cristina; Tapia-Torres, Yunuen; Souza, Valeria

2017-01-01

Background Soil microbial communities (SMC) play a central role in the structure and function of desert ecosystems. However, the high variability of annual precipitation could results in the alteration of SMC and related biological processes depending on soil water potential. The nature of the physiological adjustments made by SMC in order to obtain energy and nutrients remains unclear under different soil resource availabilities in desert ecosystems. In order to examine this dynamic, the present study examined the effects of variation in annual precipitation on physiological adjustments by the SMC across two vegetation-soil systems of different soil organic matter input in an oligotrophic desert ecosystem. Methods We collected soil samples in the Cuatro Ciénegas Basin (Mexico) under two vegetation covers: rosetophylous scrub (RS) and grassland (G), that differ in terms of quantity and quality of organic matter. Collections were conducted during the years 2011, 2012, 2013 and 2014, over which a noticeable variation in the annual precipitation occurred. The ecoenzymatic activity involved in the decomposition of organic matter, and the concentration of dissolved, available and microbial biomass nutrients, were determined and compared between sites and years. Results In 2011, we observed differences in bacterial taxonomic composition between the two vegetation covers. The lowest values of dissolved, available and microbial nutrients in both cover types were found in 2012. The G soil showed higher values of dissolved and available nutrients in the wet years. Significant positive correlations were detected between precipitation and the ratios Cmic:Nmic and Cmic:Pmic in the RS soil and Cmic:Pmic and Nmic:Pmic in the G soil. The slopes of the regression with Cmic and Nmic were higher in the G soil and lower in the RS soil. Moreover, the SMC under each vegetation cover were co-limited by different nutrients and responded to the sum of water stress and nutrient limitation

The response of soil microbial communities to variation in annual precipitation depends on soil nutritional status in an oligotrophic desert.

PubMed

Montiel-González, Cristina; Tapia-Torres, Yunuen; Souza, Valeria; García-Oliva, Felipe

2017-01-01

Soil microbial communities (SMC) play a central role in the structure and function of desert ecosystems. However, the high variability of annual precipitation could results in the alteration of SMC and related biological processes depending on soil water potential. The nature of the physiological adjustments made by SMC in order to obtain energy and nutrients remains unclear under different soil resource availabilities in desert ecosystems. In order to examine this dynamic, the present study examined the effects of variation in annual precipitation on physiological adjustments by the SMC across two vegetation-soil systems of different soil organic matter input in an oligotrophic desert ecosystem. We collected soil samples in the Cuatro Ciénegas Basin (Mexico) under two vegetation covers: rosetophylous scrub (RS) and grassland (G), that differ in terms of quantity and quality of organic matter. Collections were conducted during the years 2011, 2012, 2013 and 2014, over which a noticeable variation in the annual precipitation occurred. The ecoenzymatic activity involved in the decomposition of organic matter, and the concentration of dissolved, available and microbial biomass nutrients, were determined and compared between sites and years. In 2011, we observed differences in bacterial taxonomic composition between the two vegetation covers. The lowest values of dissolved, available and microbial nutrients in both cover types were found in 2012. The G soil showed higher values of dissolved and available nutrients in the wet years. Significant positive correlations were detected between precipitation and the ratios Cmic:Nmic and Cmic:Pmic in the RS soil and Cmic:Pmic and Nmic:Pmic in the G soil. The slopes of the regression with Cmic and Nmic were higher in the G soil and lower in the RS soil. Moreover, the SMC under each vegetation cover were co-limited by different nutrients and responded to the sum of water stress and nutrient limitation. Soil community within both

The influence of annual precipitation, topography, and vegetative cover on soil moisture and summer drought in southern California.

PubMed

Miller, P C; Poole, D K

1983-02-01

The influence of annual precipitation and vegetation cover on soil moisture and on the length of the summer drought was estimated quantitatively using 9 years of soil moisture data collected at Echo Valley in southern California. The measurements support the conclusions that in the semi-arid mediterranean climate a soil drought will occur regardless of vegetation cover and annual precipitation, but the length of the drought is greatly dependent on soil depth and rockiness. Evergreen species which can survive this drought tend to accentuate the drought, especially in deep soil levels, by developing a canopy with a large transpiring surface.

Evaluation of satellite-retrieved extreme precipitation using gauge observations

NASA Astrophysics Data System (ADS)

Lockhoff, M.; Zolina, O.; Simmer, C.; Schulz, J.

2012-04-01

Precipitation extremes have already been intensively studied employing rain gauge datasets. Their main advantage is that they represent a direct measurement with a relatively high temporal coverage. Their main limitation however is their poor spatial coverage and thus a low representativeness in many parts of the world. In contrast, satellites can provide global coverage and there are meanwhile data sets available that are on one hand long enough to be used for extreme value analysis and that have on the other hand the necessary spatial and temporal resolution to capture extremes. However, satellite observations provide only an indirect mean to determine precipitation and there are many potential observational and methodological weaknesses in particular over land surfaces that may constitute doubts concerning their usability for the analysis of precipitation extremes. By comparing basic climatological metrics of precipitation (totals, intensities, number of wet days) as well as respective characteristics of PDFs, absolute and relative extremes of satellite and observational data this paper aims at assessing to which extent satellite products are suitable for analysing extreme precipitation events. In a first step the assessment focuses on Europe taking into consideration various satellite products available, e.g. data sets provided by the Global Precipitation Climatology Project (GPCP). First results indicate that satellite-based estimates do not only represent the monthly averaged precipitation very similar to rain gauge estimates but they also capture the day-to-day occurrence fairly well. Larger differences can be found though when looking at the corresponding intensities.

a Climatology of Global Precipitation.

NASA Astrophysics Data System (ADS)

Legates, David Russell

A global climatology of mean monthly precipitation has been developed using traditional land-based gage measurements as well as derived oceanic data. These data have been screened for coding errors and redundant entries have been removed. Oceanic precipitation estimates are most often extrapolated from coastal and island observations because few gage estimates of oceanic precipitation exist. One such procedure, developed by Dorman and Bourke and used here, employs a derived relationship between observed rainfall totals and the "current weather" at coastal stations. The combined data base contains 24,635 independent terrestial station records and 2223 oceanic grid-point records. Raingage catches are known to underestimate actual precipitation. Errors in the gage catch result from wind -field deformation, wetting losses, and evaporation from the gage and can amount to nearly 8, 2, and 1 percent of the global catch, respectively. A procedure has been developed to correct many of these errors and has been used to adjust the gage estimates of global precipitation. Space-time variations in gage type, air temperature, wind speed, and natural vegetation were incorporated into the correction procedure. Corrected data were then interpolated to the nodes of a 0.5^circ of latitude by 0.5^circ of longitude lattice using a spherically-based interpolation algorithm. Interpolation errors are largest in areas of low station density, rugged topography, and heavy precipitation. Interpolated estimates also were compared with a digital filtering technique to access the aliasing of high-frequency "noise" into the lower frequency signals. Isohyetal maps displaying the mean annual, seasonal, and monthly precipitation are presented. Gage corrections and the standard error of the corrected estimates also are mapped. Results indicate that mean annual global precipitation is 1123 mm with 1251 mm falling over the oceans and 820 mm over land. Spatial distributions of monthly precipitation

Interannual and low-frequency variability of Upper Indus Basin winter/spring precipitation in observations and CMIP5 models

NASA Astrophysics Data System (ADS)

Greene, Arthur M.; Robertson, Andrew W.

2017-12-01

An assessment is made of the ability of general circulation models in the CMIP5 ensemble to reproduce observed modes of low-frequency winter/spring precipitation variability in the region of the Upper Indus basin (UIB) in south-central Asia. This season accounts for about two thirds of annual precipitation totals in the UIB and is characterized by "western disturbances" propagating along the eastward extension of the Mediterranean storm track. Observational data are utilized for for spatiotemporal characterization of the precipitation seasonal cycle, to compute seasonalized spectra and finally, to examine teleconnections, in terms of large-scale patterns in sea-surface temperature (SST) and atmospheric circulation. Annual and lowpassed variations are found to be associated primarily with SST modes in the tropical and extratropical Pacific. A more obscure link to North Atlantic SST, possibly related to the North Atlantic Oscillation, is also noted. An ensemble of 31 CMIP5 models is then similarly assessed, using unforced preindustrial multi-century control runs. Of these models, eight are found to reproduce well the two leading modes of the observed seasonal cycle. This model subset is then assessed in the spectral domain and with respect to teleconnection patterns, where a range of behaviors is noted. Two model families each account for three members of this subset. The degree of within-family similarity in behavior is shown to reflect underlying model differences. The results provide estimates of unforced regional hydroclimate variability over the UIB on interannual and decadal scales and the corresponding far-field influences, and are of potential relevance for the estimation of uncertainties in future water availability.

Mean annual precipitation predicts primary production resistance and resilience to extreme drought.

PubMed

Stuart-Haëntjens, Ellen; De Boeck, Hans J; Lemoine, Nathan P; Mänd, Pille; Kröel-Dulay, György; Schmidt, Inger K; Jentsch, Anke; Stampfli, Andreas; Anderegg, William R L; Bahn, Michael; Kreyling, Juergen; Wohlgemuth, Thomas; Lloret, Francisco; Classen, Aimée T; Gough, Christopher M; Smith, Melinda D

2018-04-27

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitation (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought - a vulnerability that is expected to compound as extreme drought frequency increases in the future. Copyright © 2018. Published by Elsevier B.V.

Annual variations in chemical composition of atmospheric precipitation, eastern North Carolina and southeastern Virginia

USGS Publications Warehouse

Fisher, Donald W.

1967-01-01

A 2-year study of precipitation composition over eastern North Carolina and southeastern Virginia has been completed. Chemical analyses were made of the major ions in monthly rainfall samples from each of 12 sampling locations. Areal and seasonal distributions were determined for chloride, calcium, magnesium, sodium, potassium, sulfate, and nitrate. Annual changes in loads and in geographical distribution of sulfate and of nitrate are small. Yearly rainfall sulfate loads amount to approximately 7 tons per square mile, whereas deposition of nitrate is about 2 tons per square mile per year in the interior of the network and less near the coast. Areal patterns of chloride content are consistent with the assumption that the ocean is the only major source of rainfall chloride in the area. Chloride loads were 2.1 and 1.8 tons per square mile per year; the difference can be attributed to meteorological conditions. Cation concentrations in network precipitation appear to depend on localized sources, probably soil dust. Annual loads of the major cations are approximately 2 tons per square mile of calcium, 1.8 tons per square mile of sodium, 0.5 ton per square mile of magnesium, and 0.3 ton per square mile of potassium; considerable year-to-year differences were noted in these values. Bicarbonate and hydrogen ion in network rainfall are closely related to the relative concentrations of sulfate and calcium. Apparently, reaction of an acidic sulfur-containing aerosol with an alkaline calcium source is one of the principal controls on precipitation alkalinity and pH. Ions in precipitation contribute substantially to the quality of surface water in the network area. Comparisons between precipitation input and stream export of ions for four North Carolina rivers show that rainfall sulfate is equal to sulfate discharged, whereas nitrate in rain slightly exceeds stream nitrate. Contributions of cations to the streams by way of precipitation range from about 20 percent for potassium

Annual variation in event-scale precipitation δ2H at Barrow, AK, reflects vapor source region

NASA Astrophysics Data System (ADS)

Putman, Annie L.; Feng, Xiahong; Sonder, Leslie J.; Posmentier, Eric S.

2017-04-01

In this study, precipitation isotopic variations at Barrow, AK, USA, are linked to conditions at the moisture source region, along the transport path, and at the precipitation site. Seventy precipitation events between January 2009 and March 2013 were analyzed for δ2H and deuterium excess. For each precipitation event, vapor source regions were identified with the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) air parcel tracking program in back-cast mode. The results show that the vapor source region migrated annually, with the most distal (proximal) and southerly (northerly) vapor source regions occurring during the winter (summer). This may be related to equatorial expansion and poleward contraction of the polar circulation cell and the extent of Arctic sea ice cover. Annual cycles of vapor source region latitude and δ2H in precipitation were in phase; depleted (enriched) δ2H values were associated with winter (summer) and distal (proximal) vapor source regions. Precipitation δ2H responded to variation in vapor source region as reflected by significant correlations between δ2H with the following three parameters: (1) total cooling between lifted condensation level (LCL) and precipitating cloud at Barrow, ΔTcool, (2) meteorological conditions at the evaporation site quantified by 2 m dew point, Td, and (3) whether the vapor transport path crossed the Brooks and/or Alaskan ranges, expressed as a Boolean variable, mtn. These three variables explained 54 % of the variance (p<0. 001) in precipitation δ2H with a sensitivity of -3.51 ± 0.55 ‰ °C-1 (p<0. 001) to ΔTcool, 3.23 ± 0.83 ‰ °C-1 (p<0. 001) to Td, and -32.11 ± 11.04 ‰ (p = 0. 0049) depletion when mtn is true. The magnitude of each effect on isotopic composition also varied with vapor source region proximity. For storms with proximal vapor source regions

Development of Innovative Technology to Expand Precipitation Observations in Satellite Precipitation Validation in Under-developed Data-sparse Regions

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Steinson, M.

2016-12-01

Accurate and reliable real-time monitoring and dissemination of observations of precipitation and surface weather conditions in general is critical for a variety of research studies and applications. Surface precipitation observations provide important reference information for evaluating satellite (e.g., GPM) precipitation estimates. High quality surface observations of precipitation, temperature, moisture, and winds are important for applications such as agriculture, water resource monitoring, health, and hazardous weather early warning systems. In many regions of the World, surface weather station and precipitation gauge networks are sparsely located and/or of poor quality. Existing stations have often been sited incorrectly, not well-maintained, and have limited communications established at the site for real-time monitoring. The University Corporation for Atmospheric Research (UCAR)/National Center for Atmospheric Research (NCAR), with support from USAID, has started an initiative to develop and deploy low-cost weather instrumentation including tipping bucket and weighing-type precipitation gauges in sparsely observed regions of the world. The goal is to improve the number of observations (temporally and spatially) for the evaluation of satellite precipitation estimates in data-sparse regions and to improve the quality of applications for environmental monitoring and early warning alert systems on a regional to global scale. One important aspect of this initiative is to make the data open to the community. The weather station instrumentation have been developed using innovative new technologies such as 3D printers, Raspberry Pi computing systems, and wireless communications. An initial pilot project have been implemented in the country of Zambia. This effort could be expanded to other data sparse regions around the globe. The presentation will provide an overview and demonstration of 3D printed weather station development and initial evaluation of observed

Asymmetry in ecosystem responses to precipitation: Theory, observation and experimentation

NASA Astrophysics Data System (ADS)

Sala, O.; Gherardi, L.; Reichmann, L.; Peters, D.

2017-12-01

Ecosystem processes such as primary production respond to changes in precipitation that occur annually and at longer time scales. The questions guiding this presentation are whether ecosystem responses to wet and dry years are symmetrical. Is the increase in productivity in a wet year similar in absolute value to the decrease in productivity in a dry year following a wet year? Is the response to one dry or wet year similar tot response of several consecutive wet and dry years? Do all plant-functional groups respond in a similar way to changes in precipitation? To address the questions we explore the theory behind a potential asymmetry and report on experimental results. Analysis of the cost and benefits of plant responses to changes in precipitation support the idea asymmetrical responses because the threshold for abscising organs that have already been deployed should be higher than the threshold to deploy new organs. However, experiments in a desert grassland in New Mexico where we experimentally increased and decreased precipitation from one year to the next showed that the response was symmetrical. Another mechanism that may yield asymmetries is the productivity response to changes in precipitation is associated with the shape of the relationship between precipitation and productivity. Straight-line relationship may yield no asymmetries whereas a saturating or concave up relationship may result in different asymmetries. Here, we report results from an experiment that yielded concave down responses for grasses and concave up for shrubs. Finally, we report results from a 10-year experiment showing asymmetric responses of grasses and shrubs. Moreover, the magnitude of the sign of the responses changed with the time since the beginning of the precipitation manipulation.

Precipitation climatology over India: validation with observations and reanalysis datasets and spatial trends

NASA Astrophysics Data System (ADS)

Kishore, P.; Jyothi, S.; Basha, Ghouse; Rao, S. V. B.; Rajeevan, M.; Velicogna, Isabella; Sutterley, Tyler C.

2016-01-01

Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial-temporal analyses of rainfall have been studied by using 107 (1901-2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and

High-resolution in situ observations of electron precipitation-causing EMIC waves

DOE PAGES

Rodger, Craig J.; Hendry, Aaron T.; Clilverd, Mark A.; ...

2015-11-21

Electromagnetic ion cyclotron (EMIC) waves are thought to be important drivers of energetic electron losses from the outer radiation belt through precipitation into the atmosphere. While the theoretical possibility of pitch angle scattering-driven losses from these waves has been recognized for more than four decades, there have been limited experimental precipitation observations to support this concept. We have combined satellite-based observations of the characteristics of EMIC waves, with satellite and ground-based observations of the EMIC-induced electron precipitation. In a detailed case study, supplemented by an additional four examples, we are able to constrain for the first time the location, size,more » and energy range of EMIC-induced electron precipitation inferred from coincident precipitation data and relate them to the EMIC wave frequency, wave power, and ion band of the wave as measured in situ by the Van Allen Probes. As a result, these observations will better constrain modeling into the importance of EMIC wave-particle interactions.« less

Further Evaluation of an Emperical Equation for Annual Total Evaporation

NASA Technical Reports Server (NTRS)

Choudhury, Bhaskar J.

1999-01-01

An empirical equation for annual total evaporation based on annual precipitation and net radiation was found to provide evaporation within 10% of the observed values at seven locations within temperate and tropical regions, but it overestimated evaporation by 90% at one location within the tundra region. A synthesis of observations at two other locations within the tundra region gives overestimates of about 65%. A general analysis of observed precipitation, net radiation, and runoff within the tundra region shows that the empirical equation is generally biased to overestimate annual evaporation within the tundra region. A theoretical analysis is being done to understand the reason behind this bias.

Climate, soil water storage, and the average annual water balance

USGS Publications Warehouse

Milly, P.C.D.

1994-01-01

This paper describes the development and testing of the hypothesis that the long-term water balance is determined only by the local interaction of fluctuating water supply (precipitation) and demand (potential evapotranspiration), mediated by water storage in the soil. Adoption of this hypothesis, together with idealized representations of relevant input variabilities in time and space, yields a simple model of the water balance of a finite area having a uniform climate. The partitioning of average annual precipitation into evapotranspiration and runoff depends on seven dimensionless numbers: the ratio of average annual potential evapotranspiration to average annual precipitation (index of dryness); the ratio of the spatial average plant-available water-holding capacity of the soil to the annual average precipitation amount; the mean number of precipitation events per year; the shape parameter of the gamma distribution describing spatial variability of storage capacity; and simple measures of the seasonality of mean precipitation intensity, storm arrival rate, and potential evapotranspiration. The hypothesis is tested in an application of the model to the United States east of the Rocky Mountains, with no calibration. Study area averages of runoff and evapotranspiration, based on observations, are 263 mm and 728 mm, respectively; the model yields corresponding estimates of 250 mm and 741 mm, respectively, and explains 88% of the geographical variance of observed runoff within the study region. The differences between modeled and observed runoff can be explained by uncertainties in the model inputs and in the observed runoff. In the humid (index of dryness <1) parts of the study area, the dominant factor producing runoff is the excess of annual precipitation over annual potential evapotranspiration, but runoff caused by variability of supply and demand over time is also significant; in the arid (index of dryness >1) parts, all of the runoff is caused by variability

Detection of spatio-temporal variability of air temperature and precipitation based on long-term meteorological station observations over Tianshan Mountains, Central Asia

NASA Astrophysics Data System (ADS)

Xu, Min; Kang, Shichang; Wu, Hao; Yuan, Xu

2018-05-01

As abundant distribution of glaciers and snow, the Tianshan Mountains are highly vulnerable to changes in climate. Based on meteorological station records during 1960-2016, we detected the variations of air temperature and precipitation by using non-parametric method in the different sub-regions and different elevations of the Tianshan Mountains. The mutations of climate were investigated by Mann-Kendall abrupt change test in the sub-regions. The periodicity is examined by wavelet analysis employing a chi-square test and detecting significant time sections. The results show that the Tianshan Mountains experienced an overall rapid warming and wetting during study period, with average warming rate of 0.32 °C/10a and wet rate of 5.82 mm/10a, respectively. The annual and seasonal spatial variation of temperature showed different scales in different regions. The annual precipitation showed non-significant upward trend in 20 stations, and 6 stations showed a significant upward trend. The temperatures in the East Tianshan increased most rapidly at rates of 0.41 °C/10a. The increasing magnitudes of annual precipitation were highest in the Boertala Vally (8.07 mm/10a) and lowest in the East Tianshan (2.64 mm/10a). The greatest and weakest warming was below 500 m (0.42 °C/10a) and elevation of 1000-1500 m (0.23 °C/10a), respectively. The increasing magnitudes of annual precipitation were highest in the elevation of 1500 m-2000 m (9.22 mm/10a) and lowest in the elevation of below 500 m (3.45 mm/10a). The mutations of annual air temperature and precipitation occurred in 1995 and 1990, respectively. The large atmospheric circulation influenced on the mutations of climate. The significant periods of air temperature were 2.4-4.1 years, and annual precipitation was 2.5-7.4 years. Elevation dependency of temperature trend magnitude was not evidently in the Tianshan Mountains. The annual precipitation wetting trend was amplified with elevation in summer and autumn. The strong

Microwave Observations of Precipitation and the Atmosphere

NASA Technical Reports Server (NTRS)

Staelin, David H.; Rosenkranz, Philip W.

2004-01-01

This research effort had three elements devoted to improving satellite-derived passive microwave retrievals of precipitation rate: morphological rain-rate retrievals, warm rain retrievals, and extension of a study of geostationary satellite options. The morphological precipitation-rate retrieval method uses for the first time the morphological character of the observed storm microwave spectra. The basic concept involves: 1) retrieval of point rainfall rates using current algorithms, 2) using spatial feature vectors of the observations over segmented multi-pixel storms to estimate the integrated rainfall rate for that storm (cu m/s), and 3) normalization of the point rain-rate retrievals to ensure consistency with the storm-wide retrieval. This work is ongoing, but two key steps have been completed: development of a segmentation algorithm for defining spatial regions corresponding to single storms for purposes of estimation, and reduction of some of the data from NAST-M that will be used to support this research going forward. The warm rain retrieval method involved extension of Aquai/AIRS/AMSU/HSB algorithmic work on cloud water retrievals. The central concept involves the fact that passive microwave cloud water retrievals over approx. 0.4 mm are very likely associated with precipitation. Since glaciated precipitation is generally detected quite successfully using scattering signatures evident in the surface-blind 54- and 183-GHz bands, this new method complements the first by permitting precipitation retrievals of non-glaciated events. The method is most successful over ocean, but has detected non-glaciated convective cells over land, perhaps in their early formative stages. This work will require additional exploration and validation prior to publication. Passive microwave instrument configurations for use in geostationary orbit were studied. They employ parabolic reflectors between 2 and 4 meters in diameter, and frequencies up to approx.430 GHz; this

EMIC Waves Observed in Conjunction with BARREL Electron Precipitation

NASA Astrophysics Data System (ADS)

Weaver, C.; Engebretson, M. J.; Lessard, M.; Halford, A. J.; Millan, R. M.; Horne, R. B.; Singer, H. J.

2013-05-01

Electromagnetic ion-cyclotron (EMIC) waves have been detected at Halley, Antarctica coinciding with observations of electron precipitation on high altitude balloons from the Balloon Array for RBSP Relativistic Electron Losses (BARREL) campaign launched in early 2013 from SANAE IV and Halley Station. The balloons were launched such that both spatial and temporal properties of electron precipitation might be examined. With a magnetic foot point mapped to the radiation belts, Halley is an ideal location to capture ground based signatures that coincide with electron precipitation. EMIC waves have been shown, both theoretically and through statistical surveys, to pitch angle scatter energetic protons and relativistic electrons via cyclotron resonance and contribute to radiation belt dynamics. EMIC waves were detected at Halley Station 23 times from 12 Jan - 4 Feb with 17 of those waves occurring during times when at least one BARREL balloon observed precipitation in one or more energy channels. High resolution magnetometer data from GOES 13 (which has a magnetic foot point near WAIS Divide, Antarctica-located about 2.5 hours, in MLT, west of Halley) show similar EMIC wave structure and frequency to 9 waves observed at Halley, suggesting the source region extended to at least the longitude and L value of GOES 13 during some events. The ground observed waves appeared in all local times and during both quiet and disturbed intervals.

Potential Influence of Arctic Sea Ice to the Inter-annual Variations of East Asian Spring Precipitation

NASA Astrophysics Data System (ADS)

Li, Xinxin; Wu, Zhiwei; Li, Yanjie

2016-04-01

Arctic sea ice (ASI) and its potential climatic impacts have received increasing attention during the past decades, yet the relevant mechanisms are far from being understood, particularly on how anomalous ASI affects climate in midlatitudes. The spring precipitation takes up as much as 30% of the annual total and has significant influences to agriculture in East Asia. Here, observed evidence and numerical experiment results manifest that the ASI variability in the Norwegian Sea and the Barents Sea in preceding winter is intimately connected with interannual variations of the East Asian spring precipitation (EAP). The former can explain about 14% of the total variances of the latter. The ASI anomalies persist from winter through the ensuing spring and excite downstream tele-connections of a distinct Rossby wave train prevailing over the Eurasian continent. For the reduced ASI, such a wave train pattern is usually associated with an anomalous low pressure center over Mongolian Plateau, which accelerates the East Asian subtropical westerly jet. The intensified subtropical westerly jet, concurrent with lower-level convergence and upper-level divergence, enhances the local convection and consequently favors rich spring precipitation over East Asia. For the excessive ASI, the situation tends to be opposite. Given that seasonal prediction of the EAP remains a challenging issue, the winter ASI variability may provide another potential predictability source besides El Niño-Southern Oscillation.

An appraisal of precipitation distribution in the high-altitude catchments of the Indus basin.

PubMed

Dahri, Zakir Hussain; Ludwig, Fulco; Moors, Eddy; Ahmad, Bashir; Khan, Asif; Kabat, Pavel

2016-04-01

Scarcity of in-situ observations coupled with high orographic influences has prevented a comprehensive assessment of precipitation distribution in the high-altitude catchments of Indus basin. Available data are generally fragmented and scattered with different organizations and mostly cover the valleys. Here, we combine most of the available station data with the indirect precipitation estimates at the accumulation zones of major glaciers to analyse altitudinal dependency of precipitation in the high-altitude Indus basin. The available observations signified the importance of orography in each sub-hydrological basin but could not infer an accurate distribution of precipitation with altitude. We used Kriging with External Drift (KED) interpolation scheme with elevation as a predictor to appraise spatiotemporal distribution of mean monthly, seasonal and annual precipitation for the period of 1998-2012. The KED-based annual precipitation estimates are verified by the corresponding basin-wide observed specific runoffs, which show good agreement. In contrast to earlier studies, our estimates reveal substantially higher precipitation in most of the sub-basins indicating two distinct rainfall maxima; 1st along southern and lower most slopes of Chenab, Jhelum, Indus main and Swat basins, and 2nd around north-west corner of Shyok basin in the central Karakoram. The study demonstrated that the selected gridded precipitation products covering this region are prone to significant errors. In terms of quantitative estimates, ERA-Interim is relatively close to the observations followed by WFDEI and TRMM, while APHRODITE gives highly underestimated precipitation estimates in the study area. Basin-wide seasonal and annual correction factors introduced for each gridded dataset can be useful for lumped hydrological modelling studies, while the estimated precipitation distribution can serve as a basis for bias correction of any gridded precipitation products for the study area

Disentangling Seasonality and Mean Annual Precipitation in the Indo-Pacific Warm Pool: Insights from Coupled Plant Wax C and H Isotope Measurements

NASA Astrophysics Data System (ADS)

Galy, V.; Oppo, D.; Dubois, N.; Arbuszewski, J. A.; Mohtadi, M.; Schefuss, E.; Rosenthal, Y.; Linsley, B. K.

2016-12-01

There is ample evidence suggesting that rainfall distribution across the Indo-Pacific Warm Pool (IPWP) - a key component of the global climate system - has substantially varied over the last deglaciation. Yet, the precise nature of these hydroclimate changes remains to be elucidated. In particular, the relative importance of variations in precipitation seasonality versus annual precipitation amount is essentially unknown. Here we use a set of surface sediments from the IPWP covering a wide range of modern hydroclimate conditions to evaluate how plant wax stable isotope composition records rainfall distribution in the area. We focus on long chain fatty acids, which are exclusively produced by vascular plants living on nearby land and delivered to the ocean by rivers. We relate the C (δ13C) and H (δD) isotope composition of long chain fatty acids preserved in surface sediments to modern precipitation distribution and stable isotope composition in their respective source area. We show that: 1) δ13C values reflect vegetation distribution (in particular the relative abundance of C3 and C4 plants) and are primarily recording precipitation seasonality (Dubois et al., 2014) and, 2) once corrected for plant fractionation effects, δD values reflect the amount-weighted average stable isotope composition of precipitation and are primarily recording annual precipitation amounts. We propose that combining the C and H isotope composition of long chain fatty acids thus allows independent reconstructions of precipitation seasonality and annual amounts in the IPWP. The practical implications for reconstructing past hydroclimate in the IPWP will be discussed.

A Bayesian kriging approach for blending satellite and ground precipitation observations

USGS Publications Warehouse

Verdin, Andrew P.; Rajagopalan, Balaji; Kleiber, William; Funk, Christopher C.

2015-01-01

Drought and flood management practices require accurate estimates of precipitation. Gauge observations, however, are often sparse in regions with complicated terrain, clustered in valleys, and of poor quality. Consequently, the spatial extent of wet events is poorly represented. Satellite-derived precipitation data are an attractive alternative, though they tend to underestimate the magnitude of wet events due to their dependency on retrieval algorithms and the indirect relationship between satellite infrared observations and precipitation intensities. Here we offer a Bayesian kriging approach for blending precipitation gauge data and the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates for Central America, Colombia, and Venezuela. First, the gauge observations are modeled as a linear function of satellite-derived estimates and any number of other variables—for this research we include elevation. Prior distributions are defined for all model parameters and the posterior distributions are obtained simultaneously via Markov chain Monte Carlo sampling. The posterior distributions of these parameters are required for spatial estimation, and thus are obtained prior to implementing the spatial kriging model. This functional framework is applied to model parameters obtained by sampling from the posterior distributions, and the residuals of the linear model are subject to a spatial kriging model. Consequently, the posterior distributions and uncertainties of the blended precipitation estimates are obtained. We demonstrate this method by applying it to pentadal and monthly total precipitation fields during 2009. The model's performance and its inherent ability to capture wet events are investigated. We show that this blending method significantly improves upon the satellite-derived estimates and is also competitive in its ability to represent wet events. This procedure also provides a means to estimate a full conditional distribution

Spatial decorrelation stretch of annual (2003-2014) Daymet precipitation summaries on a 1-km grid for California, Nevada, Arizona, and Utah.

PubMed

Ch Miliaresis, George

2016-06-01

A method is presented for elevation (H) and spatial position (X, Y) decorrelation stretch of annual precipitation summaries on a 1-km grid for SW USA for the period 2003 to 2014. Multiple linear regression analysis of the first and second principal component (PC) quantifies the variance in the multi-temporal precipitation imagery that is explained by X, Y, and elevation (h). The multi-temporal dataset is reconstructed from the PC1 and PC2 residual images and the later PCs by taking into account the variance that is not related to X, Y, and h. Clustering of the reconstructed precipitation dataset allowed the definition of positive (for example, in Sierra Nevada, Salt Lake City) and negative (for example, in San Joaquin Valley, Nevada, Colorado Plateau) precipitation anomalies. The temporal and spatial patterns defined from the spatially standardized multi-temporal precipitation imagery provide a tool of comparison for regions in different geographic environments according to the deviation from the precipitation amount that they are expected to receive as function of X, Y, and h. Such a standardization allows the definition of less or more sensitive to climatic change regions and gives an insight in the spatial impact of atmospheric circulation that causes the annual precipitation.

Temperature and precipitation in the context of the annual cycle over Asia: Model evaluation and future change

NASA Astrophysics Data System (ADS)

Moon, Suyeon; Ha, Kyung-Ja

2017-05-01

Since the early or late arrival of monsoon rainfall can be devastating to agriculture and economy, the prediction of the onset of monsoon is a very important issue. The Asian monsoon is characterized by a strong annual cycle with rainy summer and dry winter. Nevertheless, most of monsoon studies have focused on the seasonal-mean of temperature and precipitation. The present study aims to evaluate a total of 27 coupled models that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) for projection of the time evolution and the intensity of Asian monsoon on the basis of the annual cycle of temperature and precipitation. And future changes of onset, retreat, and intensity of monsoon are analyzed. Four models for good seasonal-mean (GSM) and good harmonic (GH) groups, respectively, are selected. GSM is based on the seasonal-mean of temperature and precipitation in summer and winter, and GH is based on the annual cycle of temperature and precipitation which represents a characteristic of the monsoon. To compare how well the time evolution of the monsoon is simulated in each group, the onset, retreat, and duration of Asian monsoon are examined. The highest pattern correlation coefficient (PCC) of onset, retreat, and duration between the reanalysis data and model outputs demonstrates that GH models' MME predicts time evolution of monsoon most precisely, with PCC values of 0.80, 0.52, and 0.63, respectively. To predict future changes of the monsoon, the representative concentration pathway 4.5 (RCP 4.5) experiments for the period of 2073-2099 are compared with historical simulations for the period of 1979-2005 from CMIP5 using GH models' MME. The Asian monsoon domain is expanded by 22.6% in the future projection. The onset date in the future is advanced over most parts of Asian monsoon region. The duration of summer Asian monsoon in the future projection will be lengthened by up to 2 pentads over the Asian monsoon region, as a result of advanced

Areal and Temporal Analysis of Precipitation Patterns In Slovakia Using Spectral Analysis

NASA Astrophysics Data System (ADS)

Pishvaei, M. R.

Harmonic analysis as an objective method of precipitation seasonality studying is ap- plied to the 1901-2000 monthly precipitation averages at five stations in the low-land part of Slovakia with elevation less than 800 m a.s.l. The significant harmonics of long-term precipitation series have been separately computed for eight 30-year peri- ods, which cover the 20th century and some properties and the variations are com- pared to 100-year monthly precipitation averages. The selected results show that the first and the second harmonics pre-dominantly influence on the annual distribution and climatic seasonal regimes of pre-cipitation that contribute to the precipitation am- plitude/pattern with about 20% and 10%, respectively. These indicate annual and half year variations. The rest harmon-ics often have each less than 5% contribution on the Fourier interpolation course. Maximum in yearly precipitation course, which oc- curs approximately at the begin-ning of July, because of phase changing shifts then to the middle of June. Some probable reasons regarding to Fourier components are discussed. In addition, a tem-poral analysis over precipitation time series belonging to the Hurbanovo Observa-tory as the longest observational series on the territory of Slovakia (with 130-year precipitation records) has been individually performed and possible meteorological factors responsible for the observed patterns are suggested. A comparison of annual precipitation course obtained from daily precipitation totals analysis and polynomial trends with Fourier interpolation has been done too. Daily precipitation data in the latest period are compared for some stations in Slovakia as well. Only selected results are pre-sented in the poster.

Large uncertainties in observed daily precipitation extremes over land

NASA Astrophysics Data System (ADS)

Herold, Nicholas; Behrangi, Ali; Alexander, Lisa V.

2017-01-01

We explore uncertainties in observed daily precipitation extremes over the terrestrial tropics and subtropics (50°S-50°N) based on five commonly used products: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset, the Global Precipitation Climatology Centre-Full Data Daily (GPCC-FDD) dataset, the Tropical Rainfall Measuring Mission (TRMM) multi-satellite research product (T3B42 v7), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Global Precipitation Climatology Project's One-Degree Daily (GPCP-1DD) dataset. We use the precipitation indices R10mm and Rx1day, developed by the Expert Team on Climate Change Detection and Indices, to explore the behavior of "moderate" and "extreme" extremes, respectively. In order to assess the sensitivity of extreme precipitation to different grid sizes we perform our calculations on four common spatial resolutions (0.25° × 0.25°, 1° × 1°, 2.5° × 2.5°, and 3.75° × 2.5°). The impact of the chosen "order of operation" in calculating these indices is also determined. Our results show that moderate extremes are relatively insensitive to product and resolution choice, while extreme extremes can be very sensitive. For example, at 0.25° × 0.25° quasi-global mean Rx1day values vary from 37 mm in PERSIANN-CDR to 62 mm in T3B42. We find that the interproduct spread becomes prominent at resolutions of 1° × 1° and finer, thus establishing a minimum effective resolution at which observational products agree. Without improvements in interproduct spread, these exceedingly large observational uncertainties at high spatial resolution may limit the usefulness of model evaluations. As has been found previously, resolution sensitivity can be largely eliminated by applying an order of operation where indices are calculated prior to regridding. However, this approach is not appropriate when true area averages are desired

Precipitation Extremes in Dynamically Downscaled Climate Scenarios over the Greater Horn of Africa

NASA Astrophysics Data System (ADS)

Shiferaw, A. S.; Tadesse, T.; Oglesby, R. J.; Rowe, C. M.

2017-12-01

The precipitation extremes were generated over the Greater Horn of Africa (GHA) using the Regional Climate Models (RCMs) simulations from the Coordinated Regional Downscaling Experiment (CORDEX). To assess how well the RCM simulations are capturing the historical observed precipitation extremes, they were compared with the precipitation extremes derived from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS v2). The result shows that RCM simulations have reasonably captured observed patterns of the precipitation extremes (i.e., the pattern correlation is greater than 0.5). However, significant overestimations or underestimations were observed over some localized areas in the region. The study then assessed the projected changes in these precipitation extremes during 2069-2098 and compared to the 1976-2005 period that were both derived from the RCM simulations. Projected changes in total annual precipitation (PRCPTOT), annual number of heavy (>10mm) and very heavy (>20mm) precipitation days by 2069-2098 show a general north-south pattern with a decrease over southern-half and increase over the northern-half of GHA. These changes are often greatest over parts of Somalia, Eritrea, Ethiopian highlands and southern Tanzania. Maximum 1 and 5-day total precipitation in a year and "Simple Daily Precipitation Intensity Index" (ratio of PRCPTOT to rainy days) are projected to increase over majority of GHA, including areas where PRCPTOT is projected to decrease, suggesting fewer but heavier rainy days in the future. Changes in annual sum of daily precipitation above 95th and 99th percentile are not statistically significant except Eritrea and northwestern Sudan/Somalia. Projected changes in consecutive dry days (CDD) suggest longer periods of dryness over majority of GHA. Among these areas, a substantial increases in CDD are located over southern Tanzania and Ethiopian highlands.

Annual Variations in Water Storage and Precipitation in the Amazon Basin: Bounding Sink Terms in the Terrestrial Hydrological Balance using GRACE Satellite Gravity Data

NASA Technical Reports Server (NTRS)

Crowley, John W.; Mitrovica, Jerry X.; Bailey, Richard C.; Tamisiea, Mark E.; Davis, James L.

2007-01-01

We combine satellite gravity data from the Gravity Recovery and Climate Experiment (GRACE) and precipitation measurements from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center's (CPC) Merged Analysis of Precipitation (CMAP) and the Tropical Rainfall Measuring Mission (TRMM), over the period from mid-2002 to mid-2006, to investigate the relative importance of sink (runoff and evaporation) and source (precipitation) terms in the hydrological balance of the Amazon Basin. When linear and quadratic terms are removed, the time series of land water storage variations estimated from GRACE exhibits a dominant annual signal of 250 mm peak-to-peak, which is equivalent to a water volume change of approximately 1800 cubic kilometers. A comparison of this trend with accumulated (i.e., integrated) precipitation shows excellent agreement and no evidence of basin saturation. The agreement indicates that the net runoff and evaporation contributes significantly less than precipitation to the annual hydrological mass balance. Indeed, raw residuals between the detrended water storage and precipitation anomalies range from plus or minus 40 mm. This range is consistent with streamflow measurements from the region, although the latter are characterized by a stronger annual signal than ow residuals, suggesting that runoff and evaporation may act to partially cancel each other.

Estimating mountain basin-mean precipitation from streamflow using Bayesian inference

NASA Astrophysics Data System (ADS)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Lundquist, Jessica D.

2015-10-01

Estimating basin-mean precipitation in complex terrain is difficult due to uncertainty in the topographical representativeness of precipitation gauges relative to the basin. To address this issue, we use Bayesian methodology coupled with a multimodel framework to infer basin-mean precipitation from streamflow observations, and we apply this approach to snow-dominated basins in the Sierra Nevada of California. Using streamflow observations, forcing data from lower-elevation stations, the Bayesian Total Error Analysis (BATEA) methodology and the Framework for Understanding Structural Errors (FUSE), we infer basin-mean precipitation, and compare it to basin-mean precipitation estimated using topographically informed interpolation from gauges (PRISM, the Parameter-elevation Regression on Independent Slopes Model). The BATEA-inferred spatial patterns of precipitation show agreement with PRISM in terms of the rank of basins from wet to dry but differ in absolute values. In some of the basins, these differences may reflect biases in PRISM, because some implied PRISM runoff ratios may be inconsistent with the regional climate. We also infer annual time series of basin precipitation using a two-step calibration approach. Assessment of the precision and robustness of the BATEA approach suggests that uncertainty in the BATEA-inferred precipitation is primarily related to uncertainties in hydrologic model structure. Despite these limitations, time series of inferred annual precipitation under different model and parameter assumptions are strongly correlated with one another, suggesting that this approach is capable of resolving year-to-year variability in basin-mean precipitation.

Decreased runoff response to precipitation, Little Missouri River Basin, northern Great Plains, USA

USGS Publications Warehouse

Griffin, Eleanor R.; Friedman, Jonathan M.

2017-01-01

High variability in precipitation and streamflow in the semiarid northern Great Plains causes large uncertainty in water availability. This uncertainty is compounded by potential effects of future climate change. We examined historical variability in annual and growing season precipitation, temperature, and streamflow within the Little Missouri River Basin and identified differences in the runoff response to precipitation for the period 1976-2012 compared to 1939-1975 (n = 37 years in both cases). Computed mean values for the second half of the record showed little change (<5%) in annual or growing season precipitation, but average annual runoff at the basin outlet decreased by 22%, with 66% of the reduction in flow occurring during the growing season. Our results show a statistically significant (p < 0.10) 27% decrease in the annual runoff response to precipitation (runoff ratio). Surface-water withdrawals for various uses appear to account for <12% of the reduction in average annual flow volume, and we found no published or reported evidence of substantial flow reduction caused by groundwater pumping in this basin. Results of our analysis suggest that increases in monthly average maximum and minimum temperatures, including >1°C increases in January through March, are the dominant driver of the observed decrease in runoff response to precipitation in the Little Missouri River Basin.

The role of proton precipitation in Jovian aurora: Theory and observation

NASA Technical Reports Server (NTRS)

Waite, J. H., Jr.; Curran, D. B.; Cravens, T. E.; Clarke, J. T.

1992-01-01

It was proposed that the Jovian auroral emissions observed by Voyager spacecraft could be explained by energetic protons precipitating into the upper atmosphere of Jupiter. Such precipitation of energetic protons results in Doppler-shifted Lyman alpha emission that can be quantitatively analyzed to determine the energy flux and energy distribution of the incoming particle beam. Modeling of the expected emission from a reasonably chosen Voyager energetic proton spectrum can be used in conjunction with International Ultraviolet Explorer (IUE) observations, which show a relative lack of red-shifted Lyman alpha emission, to set upper limits on the amount of proton precipitation taking place in the Jovian aurora. Such calculations indicate that less than 10 percent of the ultraviolet auroral emissions at Jupiter can be explained by proton precipitation.

Impact of Asian Aerosols on Precipitation Over California: An Observational and Model Based Approach

NASA Technical Reports Server (NTRS)

Naeger, Aaron R.; Molthan, Andrew L.; Zavodsky, Bradley T.; Creamean, Jessie M.

2015-01-01

Dust and pollution emissions from Asia are often transported across the Pacific Ocean to over the western United States. Therefore, it is essential to fully understand the impact of these aerosols on clouds and precipitation forming over the eastern Pacific and western United States, especially during atmospheric river events that account for up to half of California's annual precipitation and can lead to widespread flooding. In order for numerical modeling simulations to accurately represent the present and future regional climate of the western United States, we must account for the aerosol-cloud-precipitation interactions associated with Asian dust and pollution aerosols. Therefore, we have constructed a detailed study utilizing multi-sensor satellite observations, NOAA-led field campaign measurements, and targeted numerical modeling studies where Asian aerosols interacted with cloud and precipitation processes over the western United States. In particular, we utilize aerosol optical depth retrievals from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS), NOAA Geostationary Operational Environmental Satellite (GOES-11), and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT) to effectively detect and monitor the trans-Pacific transport of Asian dust and pollution. The aerosol optical depth (AOD) retrievals are used in assimilating the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in order to provide the model with an accurate representation of the aerosol spatial distribution across the Pacific. We conduct WRF-Chem model simulations of several cold-season atmospheric river events that interacted with Asian aerosols and brought significant precipitation over California during February-March 2011 when the NOAA CalWater field campaign was ongoing. The CalWater field campaign consisted of aircraft and surface measurements of aerosol and precipitation processes that help extensively validate our WRF

Effective precipitation duration for runoff peaks based on catchment modelling

NASA Astrophysics Data System (ADS)

Sikorska, A. E.; Viviroli, D.; Seibert, J.

2018-01-01

Despite precipitation intensities may greatly vary during one flood event, detailed information about these intensities may not be required to accurately simulate floods with a hydrological model which rather reacts to cumulative precipitation sums. This raises two questions: to which extent is it important to preserve sub-daily precipitation intensities and how long does it effectively rain from the hydrological point of view? Both questions might seem straightforward to answer with a direct analysis of past precipitation events but require some arbitrary choices regarding the length of a precipitation event. To avoid these arbitrary decisions, here we present an alternative approach to characterize the effective length of precipitation event which is based on runoff simulations with respect to large floods. More precisely, we quantify the fraction of a day over which the daily precipitation has to be distributed to faithfully reproduce the large annual and seasonal floods which were generated by the hourly precipitation rate time series. New precipitation time series were generated by first aggregating the hourly observed data into daily totals and then evenly distributing them over sub-daily periods (n hours). These simulated time series were used as input to a hydrological bucket-type model and the resulting runoff flood peaks were compared to those obtained when using the original precipitation time series. We define then the effective daily precipitation duration as the number of hours n, for which the largest peaks are simulated best. For nine mesoscale Swiss catchments this effective daily precipitation duration was about half a day, which indicates that detailed information on precipitation intensities is not necessarily required to accurately estimate peaks of the largest annual and seasonal floods. These findings support the use of simple disaggregation approaches to make usage of past daily precipitation observations or daily precipitation simulations

An Ecoinformatic Analysis of the Effect of Seasonal and Annual Variation in Temperature, Precipitation, and Solar Irradiance on Pollen Productivity in Two Neotropical Forests

NASA Astrophysics Data System (ADS)

Haselhorst, D. S.; Tcheng, D. K.; Moreno, J. E.; Punyasena, S. W.

2014-12-01

Observational data provide a powerful source of information for understanding the phenological response of tropical forests to a changing climate. Annual changes in mean temperature, precipitation, and solar irradiance, in part driven by ENSO cycles, provide a natural experiment. However, these time series are often relatively short (several years to several decades), the average climatic variability experienced in that timeframe is relatively small, and the corresponding response is therefore often very weak. As a result, standard statistical approaches may fail in detecting a biological response. We present an alternative ecoinformatic analysis that demonstrates the power of weak models in the discovery and interpretation of statistically significant signals in short, noisy, ecological time series. We developed a simple response prediction model that uses cross-validation to explore a landscape of models that correlate the phenological behavior of individual taxa (pollen production, flowering, fruiting) to seasonal and annual mean temperature, precipitation, and solar irradiance using multivariate linear regression. We use a sign slope sensitivity analysis of each linear model that tallies positive and negative slope counts of a taxon's phenological behavior to our environmental and null variables. We applied this analysis to pollen trap data collected from 1996 to 2006 from two lowland Panamanian forests, Barro Colorado Island and Parque National San Lorenzo. We also tested the performance of our predictive model using published data of annual flowering and fruiting from BCI to corroborate that our approach could reproduce previously published results on tropical phenology. Our results indicate that although the overall variation in temperature was 3.28 °C over the ten year period, pollen productivity at both sites was most consistently affected by changes in temperature. This result was replicated by the published BCI flower and fruit data, which also

Global Precipitation at One-Degree Daily Resolution From Multi-Satellite Observations

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Morrissey, Mark M.; Curtis, Scott; Joyce, Robert; McGavock, Brad; Susskind, Joel

2000-01-01

The One-Degree Daily (1DD) technique is described for producing globally complete daily estimates of precipitation on a 1 deg x 1 deg lat/long grid from currently available observational data. Where possible (40 deg N-40 deg S), the Threshold-Matched Precipitation Index (TMPI) provides precipitation estimates in which the 3-hourly infrared brightness temperatures (IR T(sub b)) are thresholded and all "cold" pixels are given a single precipitation rate. This approach is an adaptation of the Geostationary Operational Environmental Satellite (GOES) Precipitation Index (GPI), but for the TMPI the IR Tb threshold and conditional rain rate are set locally by month from Special Sensor Microwave/Imager (SSM/I)-based precipitation frequency and the Global Precipitation Climatology Project (GPCP) satellite-gauge (SG) combined monthly precipitation estimate, respectively. At higher latitudes the 1DD features a rescaled daily Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) precipitation. The frequency of rain days in the TOVS is scaled down to match that in the TMPI at the data boundaries, and the resulting non-zero TOVS values are scaled locally to sum to the SG (which is a globally complete monthly product). The time series of the daily 1DD global images shows good continuity in time and across the data boundaries. Various examples are shown to illustrate uses. Validation for individual grid -box values shows a very high root-mean-square error but, it improves quickly when users perform time/space averaging according to their own requirements.

Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2014-10-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets (bias-adjusted TMPA 3B42, near-real time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (± 6%). However, differences at the RFC are more important in particular for near-real time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near real time counterpart 3B42RT. However, large biases remained for 3B42 over the Western US for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in day-1) over the Northwest. Furthermore, the conditional analysis and the contingency analysis conducted illustrated the challenge of retrieving extreme precipitation from remote sensing estimates.

Seasonal temperature and precipitation recorded in the intra-annual oxygen isotope pattern of meteoric water and tree-ring cellulose

NASA Astrophysics Data System (ADS)

Schubert, Brian A.; Jahren, A. Hope

2015-10-01

Modern and ancient wood is a valuable terrestrial record of carbon ultimately derived from the atmosphere and oxygen inherited from local meteoric water. Many modern and fossil wood specimens display rings sufficiently thick for intra-annual sampling, and analytical techniques are rapidly improving to allow for precise carbon and oxygen isotope measurements on very small samples, yielding unprecedented resolution of seasonal isotope records. However, the interpretation of these records across diverse environments has been problematic because a unifying model for the quantitative interpretation of seasonal climate parameters from oxygen isotopes in wood is lacking. Towards such a model, we compiled a dataset of intra-ring oxygen isotope measurements on modern wood cellulose (δ18Ocell) from 33 globally distributed sites. Five of these sites represent original data produced for this study, while the data for the other 28 sites were taken from the literature. We defined the intra-annual change in oxygen isotope value of wood cellulose [Δ(δ18Ocell)] as the difference between the maximum and minimum δ18Ocell values determined within the ring. Then, using the monthly-resolved dataset of the oxygen isotope composition of meteoric water (δ18OMW) provided by the Global Network of Isotopes in Precipitation database, we quantified the empirical relationship between the intra-annual change in meteoric water [Δ(δ18OMW)] and Δ(δ18Ocell). We then used monthly-resolved datasets of temperature and precipitation to develop a global relationship between Δ(δ18OMW) and maximum/minimum monthly temperatures and winter/summer precipitation amounts. By combining these relationships we produced a single equation that explains much of the variability in the intra-ring δ18Ocell signal through only changes in seasonal temperature and precipitation amount (R2 = 0.82). We show how our recent model that quantifies seasonal precipitation from intra-ring carbon isotope profiles can be

Recent changes in the spatial distribution of annual precipitation in Israel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steinberger, E.H.; Gazit-Yaari, N.

1996-12-01

Analysis of rainfall series in Israel during the period 1960-1990 for 99 stations has revealed that precipitation amounts have decreased in the northern and central coastal areas and in the northern mountain area. In the southern coastal area and the western slopes of the central mountains precipitation increased. There are indications that the observed trends may be the outcome of changes in the synoptic climate during the winter in the Eastern Mediterranean region. 8 refs., 12 figs., 1 tab.

Extreme daily precipitation: the case of Serbia in 2014

NASA Astrophysics Data System (ADS)

Tošić, Ivana; Unkašević, Miroslava; Putniković, Suzana

2017-05-01

The extreme daily precipitation in Serbia was examined at 16 stations during the period 1961-2014. Two synoptic situations in May and September of 2014 were analysed, when extreme precipitation was recorded in western and eastern Serbia, respectively. The synoptic situation from 14 to 16 May 2014 remained nearly stationary over the western and central Serbia for the entire period. On 15 May 2014, the daily rainfall broke previous historical records in Belgrade (109.8 mm), Valjevo (108.2 mm) and Loznica (110 mm). Precipitation exceeded 200 mm in 72 h, producing the most catastrophic floods in the recent history of Serbia. In Negotin (eastern Serbia), daily precipitation of 161.3 mm was registered on 16 September 2014, which was the maximum value recorded during the period 1961-2014. The daily maximum in 2014 was registered at 6 out of 16 stations. The total annual precipitation for 2014 was the highest for the period 1961-2014 at almost all stations in Serbia. A non-significant positive trend was found for all precipitation indices: annual daily maximum precipitation, the total precipitation in consecutive 3 and 5 days, the total annual precipitation, and number of days with at least 10 and 20 mm of precipitation. The generalised extreme value distribution was fitted to the annual daily maximum precipitation. The estimated 100-year return levels were 123.4 and 147.4 mm for the annual daily maximum precipitation in Belgrade and Negotin, respectively.

Comparison between POES energetic electron precipitation observations and riometer absorptions: Implications for determining true precipitation fluxes

NASA Astrophysics Data System (ADS)

Rodger, Craig J.; Kavanagh, Andrew J.; Clilverd, Mark A.; Marple, Steve R.

2013-12-01

electron precipitation (EEP) impacts the chemistry of the middle atmosphere with growing evidence of coupling to surface temperatures at high latitudes. To better understand this link, it is essential to have realistic observations to properly characterize precipitation and which can be incorporated into chemistry-climate models. The Polar-orbiting Operational Environmental Satellite (POES) detectors measure precipitating particles but only integral fluxes and only in a fraction of the bounce loss cone. Ground-based riometers respond to precipitation from the whole bounce loss cone; they measure the cosmic radio noise absorption (CNA), a qualitative proxy with scant direct information on the energy flux of EEP. POES observations should have a direct relationship with ΔCNA and comparing the two will clarify their utility in studies of atmospheric change. We determined ionospheric changes produced by the EEP measured by the POES spacecraft in ~250 overpasses of an imaging riometer in northern Finland. The ΔCNA modeled from the POES data is 10-15 times less than the observed ΔCNA when the >30 keV flux is reported as <106 cm-2 s-1 sr-1. Above this level, there is relatively good agreement between the space-based and ground-based measurements. The discrepancy occurs mostly during periods of low geomagnetic activity, and we contend that weak diffusion is dominating the pitch angle scattering into the bounce loss cone at these times. A correction to the calculation using measurements of the trapped flux considerably reduces the discrepancy and provides further support to our hypothesis that weak diffusion leads to underestimates of the EEP.

Improving the Canadian Precipitation Analysis Estimates through an Observing System Simulation Experiment

NASA Astrophysics Data System (ADS)

Abbasnezhadi, K.; Rasmussen, P. F.; Stadnyk, T.

2014-12-01

To gain a better understanding of the spatiotemporal distribution of rainfall over the Churchill River basin, this study was undertaken. The research incorporates gridded precipitation data from the Canadian Precipitation Analysis (CaPA) system. CaPA has been developed by Environment Canada and provides near real-time precipitation estimates on a 10 km by 10 km grid over North America at a temporal resolution of 6 hours. The spatial fields are generated by combining forecasts from the Global Environmental Multiscale (GEM) model with precipitation observations from the network of synoptic weather stations. CaPA's skill is highly influenced by the number of weather stations in the region of interest as well as by the quality of the observations. In an attempt to evaluate the performance of CaPA as a function of the density of the weather station network, a dual-stage design algorithm to simulate CaPA is proposed which incorporates generated weather fields. More specifically, we are adopting a controlled design algorithm which is generally known as Observing System Simulation Experiment (OSSE). The advantage of using the experiment is that one can define reference precipitation fields assumed to represent the true state of rainfall over the region of interest. In the first stage of the defined OSSE, a coupled stochastic model of precipitation and temperature gridded fields is calibrated and validated. The performance of the generator is then validated by comparing model statistics with observed statistics and by using the generated samples as input to the WATFLOOD™ hydrologic model. In the second stage of the experiment, in order to account for the systematic error of station observations and GEM fields, representative errors are to be added to the reference field using by-products of CaPA's variographic analysis. These by-products explain the variance of station observations and background errors.

Extreme Precipitation in Poland in the Years 1951-2010

NASA Astrophysics Data System (ADS)

Malinowska, Miroslawa

2017-12-01

The characteristics of extreme precipitation, including the dominant trends, were analysed for eight stations located in different parts of Poland for the period 1951-2010. Five indices enabling the assessment of the intensity and frequency of both extremely dry and wet conditions were applied. The indices included the number of days with precipitation ≥10mm·d-1 (R10), maximum number of consecutive dry days (CDD), maximum 5-day precipitation total (R5d), simple daily intensity index (SDII), and the fraction of annual total precipitation due to events exceeding the 95th percentile calculated for the period 1961-1990. Annual trends were calculated using standard linear regression method, while the fit of the model was assessed with the F-test at the 95% confidence level. The analysed changes in extreme precipitation showed mixed patterns. A significant positive trend in the number of days with precipitation ≥10mm·d-1 (R10) was observed in central Poland, while a significant negative one, in south-eastern Poland. Based on the analysis of maximum 5-day precipitation totals (R5d), statistically significant positive trends in north-western, western and eastern parts of the country were detected, while the negative trends were found in the central and northeastern parts. Daily precipitation, expressed as single daily intensity index (SDII), increased over time in northern and central Poland. In southern Poland, the variation of SDII index showed non-significant negative tendencies. Finally, the fraction of annual total precipitation due to the events exceeding the 1961-1990 95th percentile increased at one station only, namely, in Warsaw. The indicator which refers to dry conditions, i.e. maximum number of consecutive dry days (CDD) displayed negative trends throughout the surveyed area, with the exception of Szczecin that is a representative of north-western Poland.

Spatial analysis of precipitation time series over the Upper Indus Basin

NASA Astrophysics Data System (ADS)

Latif, Yasir; Yaoming, Ma; Yaseen, Muhammad

2018-01-01

The upper Indus basin (UIB) holds one of the most substantial river systems in the world, contributing roughly half of the available surface water in Pakistan. This water provides necessary support for agriculture, domestic consumption, and hydropower generation; all critical for a stable economy in Pakistan. This study has identified trends, analyzed variability, and assessed changes in both annual and seasonal precipitation during four time series, identified herein as: (first) 1961-2013, (second) 1971-2013, (third) 1981-2013, and (fourth) 1991-2013, over the UIB. This study investigated spatial characteristics of the precipitation time series over 15 weather stations and provides strong evidence of annual precipitation by determining significant trends at 6 stations (Astore, Chilas, Dir, Drosh, Gupis, and Kakul) out of the 15 studied stations, revealing a significant negative trend during the fourth time series. Our study also showed significantly increased precipitation at Bunji, Chitral, and Skardu, whereas such trends at the rest of the stations appear insignificant. Moreover, our study found that seasonal precipitation decreased at some locations (at a high level of significance), as well as periods of scarce precipitation during all four seasons. The observed decreases in precipitation appear stronger and more significant in autumn; having 10 stations exhibiting decreasing precipitation during the fourth time series, with respect to time and space. Furthermore, the observed decreases in precipitation appear robust and more significant for regions at high elevation (>1300 m). This analysis concludes that decreasing precipitation dominated the UIB, both temporally and spatially including in the higher areas.

Annual and average estimates of water-budget components based on hydrograph separation and PRISM precipitation for gaged basins in the Appalachian Plateaus Region, 1900-2011

USGS Publications Warehouse

Nelms, David L.; Messinger, Terence; McCoy, Kurt J.

2015-07-14

As part of the U.S. Geological Survey’s Groundwater Resources Program study of the Appalachian Plateaus aquifers, annual and average estimates of water-budget components based on hydrograph separation and precipitation data from parameter-elevation regressions on independent slopes model (PRISM) were determined at 849 continuous-record streamflow-gaging stations from Mississippi to New York and covered the period of 1900 to 2011. Only complete calendar years (January to December) of streamflow record at each gage were used to determine estimates of base flow, which is that part of streamflow attributed to groundwater discharge; such estimates can serve as a proxy for annual recharge. For each year, estimates of annual base flow, runoff, and base-flow index were determined using computer programs—PART, HYSEP, and BFI—that have automated the separation procedures. These streamflow-hydrograph analysis methods are provided with version 1.0 of the U.S. Geological Survey Groundwater Toolbox, which is a new program that provides graphing, mapping, and analysis capabilities in a Windows environment. Annual values of precipitation were estimated by calculating the average of cell values intercepted by basin boundaries where previously defined in the GAGES–II dataset. Estimates of annual evapotranspiration were then calculated from the difference between precipitation and streamflow.

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis.

PubMed

Prein, Andreas F; Gobiet, Andreas

2017-01-01

Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio-temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan-European data sets and a set that combines eight very high-resolution station-based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post-processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small-scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate-mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments.

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis

PubMed Central

Gobiet, Andreas

2016-01-01

ABSTRACT Gridded precipitation data sets are frequently used to evaluate climate models or to remove model output biases. Although precipitation data are error prone due to the high spatio‐temporal variability of precipitation and due to considerable measurement errors, relatively few attempts have been made to account for observational uncertainty in model evaluation or in bias correction studies. In this study, we compare three types of European daily data sets featuring two Pan‐European data sets and a set that combines eight very high‐resolution station‐based regional data sets. Furthermore, we investigate seven widely used, larger scale global data sets. Our results demonstrate that the differences between these data sets have the same magnitude as precipitation errors found in regional climate models. Therefore, including observational uncertainties is essential for climate studies, climate model evaluation, and statistical post‐processing. Following our results, we suggest the following guidelines for regional precipitation assessments. (1) Include multiple observational data sets from different sources (e.g. station, satellite, reanalysis based) to estimate observational uncertainties. (2) Use data sets with high station densities to minimize the effect of precipitation undersampling (may induce about 60% error in data sparse regions). The information content of a gridded data set is mainly related to its underlying station density and not to its grid spacing. (3) Consider undercatch errors of up to 80% in high latitudes and mountainous regions. (4) Analyses of small‐scale features and extremes are especially uncertain in gridded data sets. For higher confidence, use climate‐mean and larger scale statistics. In conclusion, neglecting observational uncertainties potentially misguides climate model development and can severely affect the results of climate change impact assessments. PMID:28111497

Statistical Properties of Global Precipitation in the NCEP GFS Model and TMPA Observations for Data Assimilation

NASA Technical Reports Server (NTRS)

Lien, Guo-Yuan; Kalnay, Eugenia; Miyoshi, Takemasa; Huffman, George J.

2016-01-01

Assimilation of satellite precipitation data into numerical models presents several difficulties, with two of the most important being the non-Gaussian error distributions associated with precipitation, and large model and observation errors. As a result, improving the model forecast beyond a few hours by assimilating precipitation has been found to be difficult. To identify the challenges and propose practical solutions to assimilation of precipitation, statistics are calculated for global precipitation in a low-resolution NCEP Global Forecast System (GFS) model and the TRMM Multisatellite Precipitation Analysis (TMPA). The samples are constructed using the same model with the same forecast period, observation variables, and resolution as in the follow-on GFSTMPA precipitation assimilation experiments presented in the companion paper.The statistical results indicate that the T62 and T126 GFS models generally have positive bias in precipitation compared to the TMPA observations, and that the simulation of the marine stratocumulus precipitation is not realistic in the T62 GFS model. It is necessary to apply to precipitation either the commonly used logarithm transformation or the newly proposed Gaussian transformation to obtain a better relationship between the model and observational precipitation. When the Gaussian transformations are separately applied to the model and observational precipitation, they serve as a bias correction that corrects the amplitude-dependent biases. In addition, using a spatially andor temporally averaged precipitation variable, such as the 6-h accumulated precipitation, should be advantageous for precipitation assimilation.

Combined effects of precipitation and nitrogen deposition on native and invasive winter annual production in California deserts.

PubMed

Rao, Leela E; Allen, Edith B

2010-04-01

Primary production in deserts is limited by soil moisture and N availability, and thus is likely to be influenced by both anthropogenic N deposition and precipitation regimes altered as a consequence of climate change. Invasive annual grasses are particularly responsive to increases in N and water availabilities, which may result in competition with native forb communities. Additionally, conditions favoring increased invasive grass production in arid and semi-arid regions can increase fire risk, negatively impacting woody vegetation that is not adapted to fire. We conducted a seeded garden experiment and a 5-year field fertilization experiment to investigate how winter annual production is altered by increasing N supply under a range of water availabilities. The greatest production of invasive grasses and native forbs in the garden experiment occurred under the highest soil N (inorganic N after fertilization = 2.99 g m(-2)) and highest watering regime, indicating these species are limited by both water and N. A classification and regression tree (CART) analysis on the multi-year field fertilization study showed that winter annual biomass was primarily limited by November-December precipitation. Biomass exceeded the threshold capable of carrying fire when inorganic soil N availability was at least 3.2 g m(-2) in piñon-juniper woodland. Due to water limitation in creosote bush scrub, biomass exceeded the fire threshold only under very wet conditions regardless of soil N status. The CART analyses also revealed that percent cover of invasive grasses and native forbs is primarily dependent on the timing and amount of precipitation and secondarily dependent on soil N and site-specific characteristics. In total, our results indicate that areas of high N deposition will be susceptible to grass invasion, particularly in wet years, potentially reducing native species cover and increasing the risk of fire.

Effects of anthropogenic activity emerging as intensified extreme precipitation over China

NASA Astrophysics Data System (ADS)

Li, Huixin; Chen, Huopo; Wang, Huijun

2017-07-01

This study aims to provide an assessment of the effects of anthropogenic (ANT) forcings and other external factors on observed increases in extreme precipitation over China from 1961 to 2005. Extreme precipitation is represented by the annual maximum 1 day precipitation (RX1D) and the annual maximum 5 day consecutive precipitation (RX5D), and these variables are investigated using observations and simulations from the Coupled Model Intercomparison Project phase 5. The analyses mainly focus on the probability-based index (PI), which is derived from RX1D and RX5D by fitting generalized extreme value distributions. The results indicate that the simulations that include the ANT forcings provide the best representation of the spatial and temporal characteristics of extreme precipitation over China. We use the optimal fingerprint method to obtain the univariate and multivariate fingerprints of the responses to external forcings. The results show that only the ANT forcings are detectable at a 90% confidence level, both individually and when natural forcings are considered simultaneously. The impact of the forcing associated with greenhouse gases (GHGs) is also detectable in RX1D, but its effects cannot be separated from those of combinations of forcings that exclude the GHG forcings in the two-signal analyses. Besides, the estimated changes of PI, extreme precipitation, and events with a 20 year return period under nonstationary climate states are potentially attributable to ANT or GHG forcings, and the relationships between extreme precipitation and temperature from ANT forcings show agreement with observations.

Comparing NEXRAD Operational Precipitation Estimates and Raingage Observations of Intense Precipitation in the Missouri River Basin.

NASA Astrophysics Data System (ADS)

Young, C. B.

2002-05-01

Accurate observation of precipitation is critical to the study and modeling of land surface hydrologic processes. NEXRAD radar-based precipitation estimates are increasingly used in field experiments, hydrologic modeling, and water and energy budget studies due to their high spatial and temporal resolution, national coverage, and perceived accuracy. Extensive development and testing of NEXRAD precipitation algorithms have been carried out in the Southern Plains. Previous studies (Young et al. 2000, Young et al. 1999, Smith et al. 1996) indicate that NEXRAD operational products tend to underestimate precipitation at light rain rates. This study investigates the performance of NEXRAD precipitation estimates of high-intensity rainfall, focusing on flood-producing storms in the Missouri River Basin. NEXRAD estimates for these storms are compared with data from multiple raingage networks, including NWS recording and non-recording gages and ALERT raingage data for the Kansas City metropolitan area. Analyses include comparisons of gage and radar data at a wide range of temporal and spatial scales. Particular attention is paid to the October 4th, 1998, storm that produced severe flooding in Kansas City. NOTE: The phrase `NEXRAD operational products' in this abstract includes precipitation estimates generated using the Stage III and P1 algorithms. Both of these products estimate hourly accumulations on the (approximately) 4 km HRAP grid.

Temperature and Precipitation trends in Kashmir valley, North Western Himalayas

NASA Astrophysics Data System (ADS)

Shafiq, Mifta Ul; Rasool, Rehana; Ahmed, Pervez; Dimri, A. P.

2018-01-01

Climate change has emerged as an important issue ever to confront mankind. This concern emerges from the fact that our day-to-day activities are leading to impacts on the Earth's atmosphere that has the potential to significantly alter the planet's shield and radiation balance. Developing countries particularly whose income is particularly derived from agricultural activities are at the forefront of bearing repercussions due to changing climate. The present study is an effort to analyze the changing trends of precipitation and temperature variables in Kashmir valley along different elevation zones in the north western part of India. As the Kashmir valley has a rich repository of glaciers with its annual share of precipitation, slight change in the temperature and precipitation regime has far reaching environmental and economic consequences. The results from Indian Meteorological Department (IMD) data of the period 1980-2014 reveals that the annual mean temperature of Kashmir valley has increased significantly. Accelerated warming has been observed during 1980-2014, with intense warming in the recent years (2001-2014). During the period 1980-2014, steeper increase, in annual mean maximum temperature than annual mean minimum temperature, has been observed. In addition, mean maximum temperature in plain regions has shown higher rate of increase when compared with mountainous areas. In case of mean minimum temperature, mountainous regions have shown higher rate of increase. Analysis of precipitation data for the same period shows a decreasing trend with mountainous regions having the highest rate of decrease which can be quite hazardous for the fragile mountain environment of the Kashmir valley housing a large number of glaciers.

Spatio-temporal changes in precipitation over Beijing-Tianjin-Hebei region, China

NASA Astrophysics Data System (ADS)

Zhao, Na; Yue, Tianxiang; Li, Han; Zhang, Lili; Yin, Xiaozhe; Liu, Yi

2018-04-01

Changes in precipitation have a large effect on human society and are of primary importance for many scientific fields such as hydrology, agriculture and eco-environmental sciences. The present study intended to investigate the spatio-temporal characteristics of precipitation in Beijing-Tianjin-Hebei (BTH) region by using 316 meteorological stations during the period 1965-2014. Geographical Weighted Regression (GWR) method and High Accuracy Surface Modeling (HASM) method were applied to produce the precipitation patterns at different time scales. Mann-Kendall (MK) statistical test was applied to analyze the precipitation temporal variations. Results indicated that annual precipitation over the past 50 years appeared to be a non-periodic oscillation phenomenon; the number of wet years was approximately the same as that of dry years; significant positive trends were observed in spring during 1978-2014 and summer during 1996-2014; on the whole, precipitation in May, June, September, and December showed increasing trends at the 95% confidence level; and significant positive trends were also identified in July during 2000-2013 and August during 1997-2010, while slight decreasing trends were observed in February and November. Summer (June, July, and August) was the wettest season, accounting for 68.73% of annual totals in BTH. In general, northeastern BTH received the highest range of precipitation while northwestern area had the lowest. It was found that precipitation variation in this region had been closely linked to latitude, Digital Elevation Model (DEM), distance to the sea, and urbanization rate. In addition, land use played an important role in the decadal precipitation changes in BTH.

Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology.

PubMed

Baisden, W Troy; Keller, Elizabeth D; Van Hale, Robert; Frew, Russell D; Wassenaar, Leonard I

2016-01-01

Predictive understanding of precipitation δ(2)H and δ(18)O in New Zealand faces unique challenges, including high spatial variability in precipitation amounts, alternation between subtropical and sub-Antarctic precipitation sources, and a compressed latitudinal range of 34 to 47 °S. To map the precipitation isotope ratios across New Zealand, three years of integrated monthly precipitation samples were acquired from >50 stations. Conventional mean-annual precipitation δ(2)H and δ(18)O maps were produced by regressions using geographic and annual climate variables. Incomplete data and short-term variation in climate and precipitation sources limited the utility of this approach. We overcome these difficulties by calculating precipitation-weighted monthly climate parameters using national 5-km-gridded daily climate data. This data plus geographic variables were regressed to predict δ(2)H, δ(18)O, and d-excess at all sites. The procedure yields statistically-valid predictions of the isotope composition of precipitation (long-term average root mean square error (RMSE) for δ(18)O = 0.6 ‰; δ(2)H = 5.5 ‰); and monthly RMSE δ(18)O = 1.9 ‰, δ(2)H = 16 ‰. This approach has substantial benefits for studies that require the isotope composition of precipitation during specific time intervals, and may be further improved by comparison to daily and event-based precipitation samples as well as the use of back-trajectory calculations.

Energetic electron precipitation associated with pulsating aurora: EISCAT and Van Allen Probe observations

DOE PAGES

Miyoshi, Y.; Oyama, S.; Saito, S.; ...

2015-04-21

Pulsating auroras show quasi-periodic intensity modulations caused by the precipitation of energetic electrons of the order of tens of keV. It is expected theoretically that not only these electrons but also subrelativistic/relativistic electrons precipitate simultaneously into the ionosphere owing to whistler mode wave-particle interactions. The height-resolved electron density profile was observed with the European Incoherent Scatter (EISCAT) Tromsø VHF radar on 17 November 2012. Electron density enhancements were clearly identified at altitudes >68 km in association with the pulsating aurora, suggesting precipitation of electrons with a broadband energy range from ~10 keV up to at least 200 keV. The riometermore » and network of subionospheric radio wave observations also showed the energetic electron precipitations during this period. During this period, the footprint of the Van Allen Probe-A satellite was very close to Tromsø and the satellite observed rising tone emissions of the lower band chorus (LBC) waves near the equatorial plane. Considering the observed LBC waves and electrons, we conducted a computer simulation of the wave-particle interactions. This showed simultaneous precipitation of electrons at both tens of keV and a few hundred keV, which is consistent with the energy spectrum estimated by the inversion method using the EISCAT observations. This result revealed that electrons with a wide energy range simultaneously precipitate into the ionosphere in association with the pulsating aurora, providing the evidence that pulsating auroras are caused by whistler chorus waves. We suggest that scattering by propagating whistler simultaneously causes both the precipitations of subrelativistic electrons and the pulsating aurora.« less

Energetic electron precipitation associated with pulsating aurora: EISCAT and Van Allen Probe observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miyoshi, Y.; Oyama, S.; Saito, S.

Pulsating auroras show quasi-periodic intensity modulations caused by the precipitation of energetic electrons of the order of tens of keV. It is expected theoretically that not only these electrons but also subrelativistic/relativistic electrons precipitate simultaneously into the ionosphere owing to whistler mode wave-particle interactions. The height-resolved electron density profile was observed with the European Incoherent Scatter (EISCAT) Tromsø VHF radar on 17 November 2012. Electron density enhancements were clearly identified at altitudes >68 km in association with the pulsating aurora, suggesting precipitation of electrons with a broadband energy range from ~10 keV up to at least 200 keV. The riometermore » and network of subionospheric radio wave observations also showed the energetic electron precipitations during this period. During this period, the footprint of the Van Allen Probe-A satellite was very close to Tromsø and the satellite observed rising tone emissions of the lower band chorus (LBC) waves near the equatorial plane. Considering the observed LBC waves and electrons, we conducted a computer simulation of the wave-particle interactions. This showed simultaneous precipitation of electrons at both tens of keV and a few hundred keV, which is consistent with the energy spectrum estimated by the inversion method using the EISCAT observations. This result revealed that electrons with a wide energy range simultaneously precipitate into the ionosphere in association with the pulsating aurora, providing the evidence that pulsating auroras are caused by whistler chorus waves. We suggest that scattering by propagating whistler simultaneously causes both the precipitations of subrelativistic electrons and the pulsating aurora.« less

A 3056-year tree-ring based annual precipitation reconstruction from southern Qaidam Basin, Qinghai, China

NASA Astrophysics Data System (ADS)

Wang, H.; Xuemei, S.; Yin, Z. Y.; LI, M.

2017-12-01

Past climate is desired for understanding the forcing of climatic changes, for evaluating present conditions in the long-term context of the past, and for the basis of projecting future climate scenarios. By using tree-ring data, temperature, precipitation, streamflow, and drought history have been reconstructed back to hundreds or even thousands of years. In China, many dendroclimatological studies have focused on west China, particularly in the environmental sensitive Tibetan Plateau. For example, several millennial-long climatic reconstructions for northeast and east Qaidam basin have been published, and got many new achievements. Whereas, there are few samples collected from the dry area in the south. In this study, we developed a new tree ring-width chronology (from 1403 BC to AD 2015) using samples from eight stands in the southeast of Qaidam basin near Nuomuhong. Response analysis showed significant positive correlations with monthly precipitation in July and September of the previous year, May and June of the current year. Statistically, the chronology was appropriate for reconstructing the annual precipitation of July-June from 1040 BC to AD 2015, and explains 45.5% of variance contained in the instrumental date for the calibration periods 1957-2015. In the past 3056 years of reconstruction, the precipitation has experienced 14 wetter periods and 13 drier ones, and the precipitation increased obviously in 20th century. Meanwhile, wavelet analysis shows that there are 2-3, 3-8 and 11 year cycles of variability, which may be associated with ENSO and solar activity. We expect that our reconstruction will improve the understanding of precipitation variation in millennial scale on the southern Qaidam basin.

Characterizing Seasonal Drought, Water Supply Pattern and Their Impact on Vegetation Growth Using Satellite Soil Moisture Data, GRACE Water Storage and Precipitation Observations

NASA Astrophysics Data System (ADS)

A, G.; Velicogna, I.; Kimball, J. S.; Du, J.; Kim, Y.; Njoku, E. G.; Colliander, A.

2016-12-01

We combine soil moisture (SM) data from AMSR-E, AMSR-2 and SMAP, terrestrial water storage (TWS) changes from GRACE and precipitation measurements from GPCP to delineate and characterize drought and water supply pattern and its impact on vegetation growth. GRACE TWS provides spatially continuous observations of total terrestrial water storage changes and regional drought extent, persistence and severity, while satellite derived soil moisture estimates provide enhanced delineation of plant-available soil moisture. Together these data provide complementary metrics quantifying available plant water supply and have important implications for water resource management. We use these data to investigate the supply changes from different water components in relation to satellite based vegetation productivity metrics from MODIS, before, during and following the major drought events observed in the continental US during the past 13 years. We observe consistent trends and significant correlations between monthly time series of TWS, SM, and vegetation productivity. In Texas and surrounding semi-arid areas, we find that the spatial pattern of the vegetation-moisture relation follows the gradient in mean annual precipitation. In Texas, GRACE TWS and surface SM show strong coupling and similar characteristic time scale in relatively normal years, while during the 2011 onward hydrological drought, GRACE TWS manifests a longer time scale than that of surface SM, implying stronger drought persistence in deeper water storage. In the Missouri watershed, we find a spatially varying vegetation-moisture relationship where in the drier northwestern portion of the basin, the inter-annual variability in summer vegetation productivity is closely associated with changes in carry-on GRACE TWS from spring, whereas in the moist southeastern portion of the basin, summer precipitation is the dominant controlling factor on vegetation growth.

Regional precipitation-frequency analysis and spatial mapping of 24-hour precipitation for Oregon.

DOT National Transportation Integrated Search

2008-01-01

For this study regional frequency analyses were conducted for precipitation annual maxima in the state of Oregon for the : 24-hour duration. A total of 693 precipitation gages in Oregon, southern Washington, western Idaho, northern California : and n...

Recent and future extreme precipitation over Ukraine

NASA Astrophysics Data System (ADS)

Vyshkvarkova, Olena; Voskresenskaya, Elena

2014-05-01

The aim of study is to analyze the parameters of precipitation extremes and inequality over Ukraine in recent climate epoch and their possible changes in the future. Data of observations from 28 hydrometeorological stations over Ukraine and output of GFDL-CM3 model (CMIP5) for XXI century were used in the study. The methods of concentration index (J. Martin-Vide, 2004) for the study of precipitation inequality while the extreme precipitation indices recommended by the ETCCDI - for the frequency of events. Results. Precipitation inequality on the annual and seasonal scales was studied using estimated CI series for 1951-2005. It was found that annual CI ranges vary from 0.58 to 0.64. They increase southward from the north-west (forest zone) and the north-east (forest steppe zone) of Ukraine. CI maxima are located in the coastal regions of the Black Sea and the Sea of Azov. Annual CI spatial distribution indicates that the contribution of extreme precipitation into annual totals is most significant at the boundary zone between steppe and marine regions. At the same time precipitation pattern at the foothill of Carpathian Mountains is more homogenous. The CI minima (0.54) are typical for the winter season in foothill of Ukrainian Carpathians. The CI maxima reach 0.71 in spring at the steppe zone closed to the Black Sea coast. It should be noted that the greatest ranges of CI maximum and CI minimum deviation are typical for spring. It is associated with patterns of cyclone trajectories in that season. The most territory is characterized by tendency to decrease the contribution of extreme precipitation into the total amount (CI linear trends are predominantly negative in all seasons). Decadal and interdecadal variability of precipitation inequality associated with global processes in ocean-atmosphere system are also studied. It was shown that precipitation inequality over Ukraine on 10 - 15 % stronger in negative phase of Pacific Decadal Oscillation and in positive phase

Precipitation characteristics in tropical Africa using satellite and in situ observations

NASA Astrophysics Data System (ADS)

Dezfuli, A. K.; Ichoku, I.; Huffman, G. J.; Mohr, K. I.

2017-12-01

Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region have not been well-understood, despite their crucial role in regional and global circulation. This is mainly due to the lack of in situ observations. Here, we have used precipitation records from the Trans-African Hydro-Meteorological Observatory (TAHMO) ground-based gauge network to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product based on satellite observations from the Global Precipitation Measurement (GPM) constellation. The high temporal resolution of the gauge data has allowed us to identify three classes of rain events based on their duration and intensity. The contribution of each class to the total rainfall and the favorable surface atmospheric conditions for each class have been examined. As IMERG aims to continue the legacy of its predecessor, TRMM Multi-Satellite Precipitation Analysis (TMPA), and provide higher resolution data, continent-wide comparisons are made between these two products. Due to its improved temporal resolution, IMERG shows some advantages over TMPA in capturing the diurnal cycle and propagation of the meso-scale convective systems. However, the performance of the two satellite-based products varies by season, region and the evaluation statistics. The results of this study serve as a basis for our ongoing work on the impacts of biomass burning on precipitation processes in Africa.

Evaluation of precipitation trends from high-resolution satellite precipitation products over Mainland China

NASA Astrophysics Data System (ADS)

Chen, Fengrui; Gao, Yongqi

2018-01-01

Many studies have reported the excellent ability of high-resolution satellite precipitation products (0.25° or finer) to capture the spatial distribution of precipitation. However, it is not known whether the precipitation trends derived from them are reliable. For the first time, we have evaluated the annual and seasonal precipitation trends from two typical sources of high-resolution satellite-gauge products, TRMM 3B43 and PERSIANN-CDR, using rain gauge observations over China, and they were also compared with those from gauge-only products (0.25° and 0.5° precipitation products, hereafter called CN25 and CN50). The evaluation focused mainly on the magnitude, significance, sign, and relative order of the precipitation trends, and was conducted at gridded and regional scales. The following results were obtained: (1) at the gridded scale, neither satellite-gauge products precisely measure the magnitude of precipitation trends but they do reproduce their sign and relative order; regarding capturing the significance of trends, they exhibit relatively acceptable performance only over regions with a sufficient amount of significant precipitation trends; (2) at the regional scale, both satellite-gauge products generally provide reliable precipitation trends, although they do not reproduce the magnitude of trends in winter precipitation; and (3) overall, CN50 and TRMM 3B43 outperform others in reproducing all four aspects of the precipitation trends. Compared with CN25, PERSIANN-CDR performs better in determining the magnitude of precipitation trends but marginally worse in reproducing their sign and relative order; moreover, both of them are at a level in capturing the significance of precipitation trends.

Satellite and ground based observations of a large-scale electron precipitation event

NASA Astrophysics Data System (ADS)

Gamble, R. J.; Rodger, C. J.; Clilverd, M.; Thomson, N. R.; Ulich, T.; Parrot, M.; Sauvaud, J.; Berthelier, J.

2010-12-01

In order to describe how geomagnetic storms couple to the upper atmosphere, and hence to atmospheric chemistry and dynamics, measurements are required of energetic electron precipitation into the atmosphere. However, satellite observations are currently poorly suited to providing measurements of energetic and relativistic electron precipitation. The AARDDVARK network (Antarctic-Arctic Radiation-belt (Dynamic) Deposition - VLF Atmospheric Research Konsortium) provides continuous long-range observations of ionisation levels from ~30-85 km altitude, with the goal of increasing the understanding of energy coupling between the Earth's atmosphere, Sun, and Space. In this study we combine AARDDVARK subionospheric VLF measurements with DEMETER electron spectra using modelling techniques to study >100 keV energetic and relativistic electron precipitation into the atmosphere for the 24-hour period beginning 0600UT 19 January during the 17-21 January 2005 geomagnetic storms. The study augments large-scale regional observations using VLF measurements of multiple subionospheric paths to our receiver at Sodankylä, Finland (67.4°N, 26.6°E, L=5.31), combined with detailed in situ measurements from the DEMETER satellite to allow the spatial extent, flux, and energy distribution of the precipitation to be determined. In contrast to other satellites, DEMETER’s electron spectrometer has excellent energy resolution. The DEMETER-measured precipitation spectrum is used to infer an altered electron density profile, modelled using a simple ionospheric electron model. This altered electron profile is then used in a subionospheric VLF model and compared with AARDDVARK VLF results. Matching model results with subionospheric VLF measurements allows calculation of both the intensity and geographic extent (in L) of the precipitation region required to produce such an effect. We find that a flux of 7000 elec.cm-2s-1 >100 keV electrons precipitates into the atmosphere over an L range of 3

Regional hydrologic response of loblolly pine to air temperature and precipitation changes

Treesearch

Steven G. McNulty; James M. Vose; Wayne T. Swank

1997-01-01

Large deviations in average annual air temperatures and total annual precipitation were observed across the Southern United States during the last 50 years, and these fluctuations could become even larger during the next century. The authors used PnET-IIS, a monthly time-step forest process model that uses soil, vegetation, and climate inputs to assess the influence of...

Annual plants change in size over a century of observations.

PubMed

Leger, Elizabeth A

2013-07-01

Studies have documented changes in animal body sizes over the last century, but very little is known about changes in plant sizes, even though reduced plant productivity is potentially responsible for declines in size of other organisms. Here, I ask whether warming trends in the Great Basin have affected plant size by measuring specimens preserved on herbarium sheets collected between 1893 and 2011. I asked how maximum and minimum temperatures, precipitation, and the Pacific Decadal Oscillation (PDO) in the year of collection affected plant height, leaf size, and flower number, and asked whether changes in climate resulted in decreasing sizes for seven annual forbs. Species had contrasting responses to climate factors, and would not necessarily be expected to respond in parallel to climatic shifts. There were generally positive relationships between plant size and increased minimum and maximum temperatures, which would have been predicted to lead to small increases in plant sizes over the observation period. While one species increased in size and flower number over the observation period, five of the seven species decreased in plant height, four of these decreased in leaf size, and one species also decreased in flower production. One species showed no change. The mechanisms behind these size changes are unknown, and the limited data available on these species (germination timing, area of occupancy, relative abundance) did not explain why some species shrank while others grew or did not change in size over time. These results show that multiple annual forbs are decreasing in size, but that even within the same functional group, species may have contrasting responses to similar environmental stimuli. Changes in plant size could have cascading effects on other members of these communities, and differential responses to directional change may change the composition of plant communities over time. © 2013 Blackwell Publishing Ltd.

Observed and Projected Precipitation Changes over the Nine US Climate Regions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chylek, Petr; Dubey, Manvendra; Hengartner, Nicholas

Here, we analyze the past (1900–2015) temperature and precipitation changes in nine separate US climate regions. We find that the temperature increased in a statistically significant (95% confidence level equivalent to alpha level of 0.05) manner in all of these regions. However, the variability in the observed precipitation was much more complex. In the eastern US (east of Rocky Mountains), the precipitation increased in all five climate regions and the increase was statistically significant in three of them. In contract, in the western US, the precipitation increased in two regions and decreased in two with no statistical significance in anymore » region. The CMIP5 climate models (an ensemble mean) were not able to capture properly either the large precipitation differences between the eastern and the western US, or the changes of precipitation between 1900 and 2015 in eastern US. The statistical regression model explains the differences between the eastern and western US precipitation as results of different significant predictors. The anthropogenic greenhouse gases and aerosol (GHGA) are the major forcing of the precipitation in the eastern part of US, while the Pacific Decadal Oscillation (PDO) has the major influence on precipitation in the western part of the US. This analysis suggests that the precipitation over the eastern US increased at an approximate rate of 6.7%/K, in agreement with the Clausius-Clapeyron equation, while the precipitation of the western US was approximately constant, independent of the temperature. Future precipitation over the western part of the US will depend on the behavior of the PDO, and how it (PDO) may be affected by future warming. Low hydrological sensitivity (percent increase of precipitation per one K of warming) projected by the CMIP5 models for the eastern US suggests either an underestimate of future precipitation or an overestimate of future warming.« less

Observed and Projected Precipitation Changes over the Nine US Climate Regions

DOE PAGES

Chylek, Petr; Dubey, Manvendra; Hengartner, Nicholas; ...

2017-10-25

Here, we analyze the past (1900–2015) temperature and precipitation changes in nine separate US climate regions. We find that the temperature increased in a statistically significant (95% confidence level equivalent to alpha level of 0.05) manner in all of these regions. However, the variability in the observed precipitation was much more complex. In the eastern US (east of Rocky Mountains), the precipitation increased in all five climate regions and the increase was statistically significant in three of them. In contract, in the western US, the precipitation increased in two regions and decreased in two with no statistical significance in anymore » region. The CMIP5 climate models (an ensemble mean) were not able to capture properly either the large precipitation differences between the eastern and the western US, or the changes of precipitation between 1900 and 2015 in eastern US. The statistical regression model explains the differences between the eastern and western US precipitation as results of different significant predictors. The anthropogenic greenhouse gases and aerosol (GHGA) are the major forcing of the precipitation in the eastern part of US, while the Pacific Decadal Oscillation (PDO) has the major influence on precipitation in the western part of the US. This analysis suggests that the precipitation over the eastern US increased at an approximate rate of 6.7%/K, in agreement with the Clausius-Clapeyron equation, while the precipitation of the western US was approximately constant, independent of the temperature. Future precipitation over the western part of the US will depend on the behavior of the PDO, and how it (PDO) may be affected by future warming. Low hydrological sensitivity (percent increase of precipitation per one K of warming) projected by the CMIP5 models for the eastern US suggests either an underestimate of future precipitation or an overestimate of future warming.« less

Advanced Microwave Precipitation Radiometer (AMPR) for remote observation of precipitation

NASA Technical Reports Server (NTRS)

Galliano, J. A.; Platt, R. H.

1990-01-01

The design, development, and tests of the Advanced Microwave Precipitation Radiometer (AMPR) operating in the 10 to 85 GHz range specifically for precipitation retrieval and mesoscale storm system studies from a high altitude aircraft platform (i.e., ER-2) are described. The primary goals of AMPR are the exploitation of the scattering signal of precipitation at frequencies near 10, 19, 37, and 85 GHz together to unambiguously retrieve precipitation and storm structure and intensity information in support of proposed and planned space sensors in geostationary and low earth orbit, as well as storm-related field experiments. The development of AMPR will have an important impact on the interpretation of microwave radiances for rain retrievals over both land and ocean for the following reasons: (1) A scanning instrument, such as AMPR, will allow the unambiguous detection and analysis of features in two dimensional space, allowing an improved interpretation of signals in terms of cloud features, and microphysical and radiative processes; (2) AMPR will offer more accurate comparisons with ground-based radar data by feature matching since the navigation of the ER-2 platform can be expected to drift 3 to 4 km per hour of flight time; and (3) AMPR will allow underflights of the SSM/I satellite instrument with enough spatial coverage at the same frequencies to make meaningful comparisons of the data for precipitation studies.

Trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma, 1951–2011

USGS Publications Warehouse

Wagner, Daniel M.; Krieger, Joshua D.; Merriman, Katherine R.

2014-01-01

The U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers (USACE) conducted a statistical analysis of trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma for the period 1951–2011. The Mann-Kendall test was used to test for trends in annual and seasonal precipitation, annual and seasonal streamflows of 42 continuous-record USGS streamflow-gaging stations, annual pool elevations and releases from 16 USACE reservoirs, and annual releases from 11 dams on the Arkansas River. A statistically significant (p≤0.10) upward trend was observed in annual precipitation for the State, with a Sen slope of approximately 0.10 inch per year. Autumn and winter were the only seasons that had statistically significant trends in precipitation. Five of six physiographic sections and six of seven 4-digit hydrologic unit code (HUC) regions in Arkansas had statistically significant upward trends in autumn precipitation, with Sen slopes of approximately 0.06 to 0.10 inch per year. Sixteen sites had statistically significant upward trends in the annual mean daily streamflow and were located on streams that drained regions with statistically significant upward trends in annual precipitation. Expected annual rates of change corresponding to statistically significant trends in annual mean daily streamflows, which ranged from 0.32 to 0.88 percent, were greater than those corresponding to regions with statistically significant upward trends in annual precipitation, which ranged from 0.19 to 0.28 percent, suggesting that the observed trends in regional annual precipitation do not fully account for the observed trends in annual mean daily streamflows. Trends in annual maximum daily streamflows were similar to trends in the annual mean daily streamflows but were only statistically significant at seven sites. There were more statistically significant trends (28 of 42 sites) in the

Response of North American ecosystem models to multi-annual periodicities in temperature and precipitation

Treesearch

J. Alan Yeakley; Ron A. Moen; David D. Breshears; Martha K. Nungesser

1994-01-01

Ecosystem models typically use input temperature and precipitation data generated stochastically from weather station means and variances. Although the weather station data are based on measurements taken over a few decades, model simulations are usually on the order of centuries. Consequently, observed periodicities in temperature and precipitation at the continental...

Comparison between weather station data in south-eastern Italy and CRU precipitation datasets

NASA Astrophysics Data System (ADS)

Miglietta, D.

2009-04-01

Monthly precipitation data in south-eastern Italy from 1920 to 2005 have been extensively analyzed. Data were collected in almost 200 weather stations located 10-20km apart from each other and almost uniformly distributed in Puglia and Basilicata regions. Apart from few years around world war II, time series are mostly complete and allow a reliable reconstruction of climate variability in the considered region. Statistically significant trends have been studied by applying the Mann-Kendall test to annual, seasonal and monthly values. A comparison has been made between observations and precipitation data given by the Climate Research Unit (CRU), University of East Anglia, with both low (30') and high (10') space resolution grid. In particular, rainfall records, time series behaviors and annual cycles at each station have been compared to the corresponding CRU data. CRU time series show a large negative trend for winter since 1970. Trend is not significant if the whole 20th century is considered (both for the whole year and for winter only). This might be considered as an evidence of recent acceleration towards increasingly dry conditions. However correlation between CRU data and observations is not very high and large percent errors are present mainly in the mountains regions, where observations show a large annual cycle, with intense precipitation in winter, which is not present in CRU data. To identify trends, therefore observed data are needed, even at monthly scale. In particular observations confirm the overall trend, but also indicate large spatial variability, with locations where precipitation has even increased since 1970. Daily precipitation data coming from a subset of weather stations have also been studied for the same time period. The distributions of maximum annual rainfalls, wet spells and dry spells were analyzed for each station, together with their time series. The tools of statistical analysis of extremes have been used in order to evaluate

Rapid decadal convective precipitation increase over Eurasia during the last three decades of the 20th century.

PubMed

Ye, Hengchun; Fetzer, Eric J; Wong, Sun; Lambrigtsen, Bjorn H

2017-01-01

Convective precipitation-localized, short-lived, intense, and sometimes violent-is at the root of challenges associated with observation, simulation, and prediction of precipitation. The understanding of long-term changes in convective precipitation characteristics and their role in precipitation extremes and intensity over extratropical regions are imperative to future water resource management; however, they have been studied very little. We show that annual convective precipitation total has been increasing astonishingly fast, at a rate of 18.4%/°C, of which 16% is attributable to an increase in convective precipitation occurrence, and 2.4% is attributable to increased daily intensity based on the 35 years of two (combined) historical data sets of 3-hourly synoptic observations and daily precipitation. We also reveal that annual daily precipitation extreme has been increasing at a rate of about 7.4%/°C in convective events only. Concurrently, the overall increase in mean daily precipitation intensity is mostly due to increased convective precipitation, possibly at the expanse of nonconvective precipitation. As a result, transitional seasons are becoming more summer-like as convective becomes the dominant precipitation type that has accompanied higher daily extremes and intensity since the late 1980s. The data also demonstrate that increasing convective precipitation and daily extremes appear to be directly linearly associated with higher atmospheric water vapor accompanying a warming climate over northern Eurasia.

Comparison of GPCP Monthly and Daily Precipitation Estimates with High-Latitude Gauge Observations

NASA Technical Reports Server (NTRS)

Bolvin, David T.; Adler, Robert G.; Nelkin, Eric J.; Poutiainen, Jani

2008-01-01

It is very important to know how much rain and snow falls around the world for uses that range from crop forecasting to disaster response, drought monitoring to flood forecasting, and weather analysis to climate research. Precipitation is usually measured with rain gauges, but rain gauges don t exist in areas that are sparsely populated, which tends to be a good portion of the globe. To overcome this, meteorologists use satellite data to estimate global precipitation. However, it is difficult to estimate rain and especially snow in cold climates using most current satellites. The satellite sensors are often "confused" by a snowy or frozen surface and therefore cannot distinguish precipitation. One commonly used satellite-based precipitation data set, the Global Precipitation Climatology Project (GPCP) data, overcomes this frozen-surface problem through the innovative use of two sources of satellite data, the Television Infrared Observation Satellite Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). Though the GPCP estimates are generally considered a very reliable source of precipitation, it has been difficult to assess the quality of these estimates in cold climates due to the lack of gauges. Recently, the Finnish Meteorological Institute (FMI) has provided a 12-year span of high-quality daily rain gauge observations, covering all of Finland, that can be used to compare with the GPCP data to determine how well the satellites estimate cold-climate precipitation. Comparison of the monthly GPCP satellite-based estimates and the FMI gauge observations shows remarkably good agreement, with the GPCP estimates being 6% lower in the amount of precipitation than the FMI observations. Furthermore, the month-to-month correlation between the GPCP and FMI is very high at 0.95 (1.0 is perfect). The daily GPCP estimates replicate the FMI daily occurrences of precipitation with a correlation of 0.55 in the summer and 0.45 in the winter. The winter

Improving Reanalyses Using TRMM and SSM/I-Derived Precipitation and Total Precipitable Water Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.

1999-01-01

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of rainfall and total precipitable water (TPW) observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve these fields in reanalyses. The DAO has developed a "1+1"D procedure to assimilate 6-hr averaged rainfall and TPW into the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS. The "1+1" designation refers to one spatial dimension plus one temporal dimension. The scheme minimizes the least-square differences between the satellite-retrieved rain rates and those produced by the column model over the 6-hr analysis window. The control variables are analysis increments of moisture within the Incremental Analysis Update (IAU) framework of the GEOS DAS. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but differs in its choice of the control variable. Instead of estimating the initial condition at the beginning of the assimilation cycle, it estimates the constant IAU forcing applied over a 6-hr assimilation cycle. In doing so, it imposes the forecast model as a weak constraint in a manner similar to the variational continuous assimilation techniques. We present results from an experiment in which the observed rain rate and TPW are assumed to be "perfect". They show that assimilating the TMI and SSM/I-derived surface precipitation and TPW observations improves not only the precipitation and moisture fields but also key climate parameters directly linked to convective activities such as clouds, the

Impacts of precipitation seasonality and ecosystem types on evapotranspiration in the Yukon River Basin, Alaska

USGS Publications Warehouse

Yuan, W.; Liu, S.; Liu, H.; Randerson, J.T.; Yu, G.; Tieszen, L.L.

2010-01-01

Evapotranspiration (ET) is the largest component of water loss from terrestrial ecosystems; however, large uncertainties exist when estimating the temporal and spatial variations of ET because of concurrent shifts in the magnitude and seasonal distribution of precipitation as well as differences in the response of ecosystem ET to environmental variabilities. In this study, we examined the impacts of precipitation seasonality and ecosystem types on ET quantified by eddy covariance towers from 2002 to 2004 in three ecosystems (grassland, deciduous broadleaf forest, and evergreen needleleaf forest) in the Yukon River Basin, Alaska. The annual precipitation changed greatly in both magnitude and seasonal distribution through the three investigated years. Observations and model results showed that ET was more sensitive to precipitation scarcity in the early growing season than in the late growing season, which was the direct result of different responses of ET components to precipitation in different seasons. The results demonstrated the importance of seasonal variations of precipitation in regulating annual ET and overshadowing the function of annual precipitation. Comparison of ET among ecosystems over the growing season indicated that ET was largest in deciduous broadleaf, intermediate in evergreen needleleaf, and lowest in the grassland ecosystem. These ecosystem differences in ET were related to differences in successional stages and physiological responses.

Spatiotemporal patterns of precipitation inferred from streamflow observations across the Sierra Nevada mountain range

NASA Astrophysics Data System (ADS)

Henn, Brian; Clark, Martyn P.; Kavetski, Dmitri; Newman, Andrew J.; Hughes, Mimi; McGurk, Bruce; Lundquist, Jessica D.

2018-01-01

Given uncertainty in precipitation gauge-based gridded datasets over complex terrain, we use multiple streamflow observations as an additional source of information about precipitation, in order to identify spatial and temporal differences between a gridded precipitation dataset and precipitation inferred from streamflow. We test whether gridded datasets capture across-crest and regional spatial patterns of variability, as well as year-to-year variability and trends in precipitation, in comparison to precipitation inferred from streamflow. We use a Bayesian model calibration routine with multiple lumped hydrologic model structures to infer the most likely basin-mean, water-year total precipitation for 56 basins with long-term (>30 year) streamflow records in the Sierra Nevada mountain range of California. We compare basin-mean precipitation derived from this approach with basin-mean precipitation from a precipitation gauge-based, 1/16° gridded dataset that has been used to simulate and evaluate trends in Western United States streamflow and snowpack over the 20th century. We find that the long-term average spatial patterns differ: in particular, there is less precipitation in the gridded dataset in higher-elevation basins whose aspect faces prevailing cool-season winds, as compared to precipitation inferred from streamflow. In a few years and basins, there is less gridded precipitation than there is observed streamflow. Lower-elevation, southern, and east-of-crest basins show better agreement between gridded and inferred precipitation. Implied actual evapotranspiration (calculated as precipitation minus streamflow) then also varies between the streamflow-based estimates and the gridded dataset. Absolute uncertainty in precipitation inferred from streamflow is substantial, but the signal of basin-to-basin and year-to-year differences are likely more robust. The findings suggest that considering streamflow when spatially distributing precipitation in complex terrain

Changes in precipitation regime in the Baltic countries in 1966-2015

NASA Astrophysics Data System (ADS)

Jaagus, Jaak; Briede, Agrita; Rimkus, Egidijus; Sepp, Mait

2018-01-01

The aim of the study was to analyse trends and regime shifts in time series of monthly, seasonal and annual precipitation in the eastern Baltic countries (Lithuania, Latvia, Estonia) during 1966-2015. Data from 54 stations with nearly homogeneous series were used. The Mann-Kendall test was used for trend analysis and the Rodionov test for the analysis of regime shifts. Rather few statistically significant trends ( p < 0.05) and regime shifts were determined. The highest increase (by approximately 10 mm per decade) was observed in winter precipitation when a significant trend was found at the large majority of stations. For monthly precipitation, increasing trends were detected at many stations in January, February and June. Weak negative trends revealed at few stations in April and September. Annual precipitation has generally increased, but the trend is mostly insignificant. The analysis of regime shifts revealed some significant abrupt changes, the most important of which were upward shifts in winter, in January and February precipitation at many stations since 1990 or in some other years (1989, 1995). A return shift in the time series of February precipitation occurred since 2003. The most significant increase in precipitation was determined in Latvia and the weakest increase in Lithuania.

Urban and peri-urban precipitation and air temperature trends in mega cities of the world using multiple trend analysis methods

NASA Astrophysics Data System (ADS)

Ajaaj, Aws A.; Mishra, Ashok K.; Khan, Abdul A.

2018-04-01

Urbanization plays an important role in altering local to regional climate. In this study, the trends in precipitation and the air temperature were investigated for urban and peri-urban areas of 18 mega cities selected from six continents (representing a wide range of climatic patterns). Multiple statistical tests were used to examine long-term trends in annual and seasonal precipitation and air temperature for the selected cities. The urban and peri-urban areas were classified based on the percentage of land imperviousness. Through this study, it was evident that removal of the lag-k serial correlation caused a reduction of approximately 20 to 30% in significant trend observability for temperature and precipitation data. This observation suggests that appropriate trend analysis methodology for climate studies is necessary. Additionally, about 70% of the urban areas showed higher positive air temperature trends, compared with peri-urban areas. There were not clear trend signatures (i.e., mix of increase or decrease) when comparing urban vs peri-urban precipitation in each selected city. Overall, cities located in dry areas, for example, in Africa, southern parts of North America, and Eastern Asia, showed a decrease in annual and seasonal precipitation, while wetter conditions were favorable for cities located in wet regions such as, southeastern South America, eastern North America, and northern Europe. A positive relationship was observed between decadal trends of annual/seasonal air temperature and precipitation for all urban and peri-urban areas, with a higher rate being observed for urban areas.

Rapid decadal convective precipitation increase over Eurasia during the last three decades of the 20th century

PubMed Central

Ye, Hengchun; Fetzer, Eric J.; Wong, Sun; Lambrigtsen, Bjorn H.

2017-01-01

Convective precipitation—localized, short-lived, intense, and sometimes violent—is at the root of challenges associated with observation, simulation, and prediction of precipitation. The understanding of long-term changes in convective precipitation characteristics and their role in precipitation extremes and intensity over extratropical regions are imperative to future water resource management; however, they have been studied very little. We show that annual convective precipitation total has been increasing astonishingly fast, at a rate of 18.4%/°C, of which 16% is attributable to an increase in convective precipitation occurrence, and 2.4% is attributable to increased daily intensity based on the 35 years of two (combined) historical data sets of 3-hourly synoptic observations and daily precipitation. We also reveal that annual daily precipitation extreme has been increasing at a rate of about 7.4%/°C in convective events only. Concurrently, the overall increase in mean daily precipitation intensity is mostly due to increased convective precipitation, possibly at the expanse of nonconvective precipitation. As a result, transitional seasons are becoming more summer-like as convective becomes the dominant precipitation type that has accompanied higher daily extremes and intensity since the late 1980s. The data also demonstrate that increasing convective precipitation and daily extremes appear to be directly linearly associated with higher atmospheric water vapor accompanying a warming climate over northern Eurasia. PMID:28138545

Relationship between annual precipitation variability and ENSO in Southern California for the Common Era (last 2,000 years)

NASA Astrophysics Data System (ADS)

DU, X.; Hendy, I. L.; Hinnov, L.; Brown, E. T.; Schimmelmann, A.; Pak, D. K.

2017-12-01

The El Niño-Southern Oscillation (ENSO) has a major influence on Southern California's hydroclimate as demonstrated by both historical observations and model simulations. Santa Barbara Basin (SBB) off Southern California preserves a unique varved (i.e. annually laminated) marine sedimentary archive of modern and Holocene hydroclimate variability, notably including the transition from the regionally dry Medieval Climate Anomaly (MCA) to the wetter Little Ice Age (LIA). Here we present sub-annually resolved scanning XRF elemental counts for the last 2,000 years in SBB from core SPR0901-03KC. Titanium (associated with silicate minerals) is delivered more efficiently to SBB sediments during times of enhanced river flow and in the Mediterranean climate of Southern California, river flow only occurs after precipitation. The Ti record suggests that the precipitation frequency was reduced during the MCA except for a pluvial episode at CE 1075-1121, but increased during the LIA. Time series analysis of Ti counts indicates ENSO variability robustly increased during the intervals CE 450-520, 650-720, 980-1150, 1380-1550 and 1720-1750, and experienced relatively quiescent intervals between CE 50-150, 250-400, 550-650, 750-950, 1150-1280 and 1580-1620. Generally the LIA in Southern California is characterized by more active ENSO variability with long periodicities (4-7 yr) and multi-decadal variability (54 yr). MCA drought episodes were associated with less active ENSO. Active ENSO variability in Southern California during the last 2,000 years coincided with reconstructed southward migration of the Intertropical Convergence Zone (ITCZ) suggesting the ITCZ may play a role in the waxing and waning of ENSO teleconnections between the central Pacific and the west coast of North America.

The full annual carbon balance of a subtropical coniferous plantation is highly sensitive to autumn precipitation.

PubMed

Xu, Mingjie; Wang, Huimin; Wen, Xuefa; Zhang, Tao; Di, Yuebao; Wang, Yidong; Wang, Jianlei; Cheng, Chuanpeng; Zhang, Wenjiang

2017-08-30

Deep understanding of the effects of precipitation on carbon budgets is essential to assess the carbon balance accurately and can help predict potential variation within the global change context. Therefore, we addressed this issue by analyzing twelve years (2003-2014) of observations of carbon fluxes and their corresponding temperature and precipitation data in a subtropical coniferous plantation at the Qianyanzhou (QYZ) site, southern China. During the observation years, this coniferous ecosystem experienced four cold springs whose effects on the carbon budgets were relatively clear based on previous studies. To unravel the effects of temperature and precipitation, the effects of autumn precipitation were examined by grouping the data into two pools based on whether the years experienced cold springs. The results indicated that precipitation in autumn can accelerate the gross primary productivity (GPP) of the following year. Meanwhile, divergent effects of precipitation on ecosystem respiration (Re) were found. Autumn precipitation was found to enhance Re in normal years but the same regulation was not found in the cold-spring years. These results suggested that for long-term predictions of carbon balance in global climate change projections, the effects of precipitation must be considered to better constrain the uncertainties associated with the estimation.

Wide energy electron precipitations associated with chorus waves; Initial observations from Arase and ground-based observations

NASA Astrophysics Data System (ADS)

Miyoshi, Y.; Kurita, S.; Saito, S.; Shinohara, I.; Kasahara, Y.; Matsuda, S.; Kasaba, Y.; Yagitani, S.; Kojima, H.; Hikishima, M.; Tsuchiya, F.; Kumamoto, A.; Katoh, Y.; Matsuoka, A.; Higashio, N.; Mitani, T.; Takashima, T.; Kasahara, S.; Yokota, S.; Asamura, K.; Kazama, Y.; Wang, S. Y.; Shiokawa, K.; Oyama, S. I.; Ogawa, Y.; Hosokawa, K.; Kataoka, R.; Kero, A.; Hori, T.; Turunen, E. S.; Shoji, M.; Teramoto, M.; Chang, T. F.

2017-12-01

The pulsating aurora is caused by intermittent precipitations of a few - 10s keV electrons, and it is expected that the pitch angle scattering by chorus waves at the magnetosphere is a primary process to cause the pulsating aurora. The Arase satellite that was launched in December, 2016 has obtained comprehensive data sets for plasma/particles and fields/waves. In March and April, 2017, a series of campaign observation focused on the chorus-wave particle interactions from conjugate observations from Arase and ground-based observations, and the pulsating aurora as a manifest of chorus-wave particle ineteractions was the important observation subject. During the campaign observations, good conjugate observations were realized between Arase and ground-based observations in Scandinavia. Associated with the pulsating aurora, the EISCAT VHF incoherent scatter radar at Tromso, Norway observed strong ionization in lower ionosphere. During the period, the Arase satellite observed intense chorus waves near the magnetic equator for a few hours, suggesting that strong pitch angle scattering took place. From the conjugate observations from Arase and ground-based observations, we discuss how chorus waves cause strong precipitation of electrons from plasma sheet and radiation belts.

Mean annual precipitation predicts primary production resistance and resilience to extreme drought

DOE PAGES

Stuart-Haëntjens, Ellen; De Boeck, Hans J.; Lemoine, Nathan P.; ...

2018-09-01

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitationmore » (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought – a vulnerability that is expected to compound as extreme drought frequency increases in the future.« less

Mean annual precipitation predicts primary production resistance and resilience to extreme drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stuart-Haëntjens, Ellen; De Boeck, Hans J.; Lemoine, Nathan P.

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitationmore » (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought – a vulnerability that is expected to compound as extreme drought frequency increases in the future.« less

Trends in monthly precipitation over the northwest of Iran (NWI)

NASA Astrophysics Data System (ADS)

Asakereh, Hossein

2017-10-01

Increasing global temperatures during the last century have had their own effects on other climatic conditions, particularly on precipitation characteristics. This study was meant to investigate the spatial and temporal monthly trends of precipitation using the least square error (LSE) approach for the northwest of Iran (NWI). To this end, a database was obtained from 250 measuring stations uniformly scattered all over NWI from 1961 to 2010. The spatial average of annual precipitation in NWI during the period of study was approximately 220.9-726.7 mm. The annual precipitation decreased from southwest to northeast, while the large amount of precipitation was concentrated in the south-west and in the mountainous areas. All over NWI, the maximum and minimum precipitation records occurred from March to May and July to September, respectively. The coefficient of variation (CV) is greater than 44 % in all of NWI and may reach over 76 % in many places. The greatest range of CV, for instance, occurred during July. The spatial variability of precipitation was consistent with a tempo-spatial pattern of precipitation trends. There was a considerable difference between the amounts of change during the months, and the negative trends were mainly attributed to areas concentrated in eastern and southern parts of NWI far from the western mountain ranges. Moreover, limited areas with positive precipitation trends can be found in very small and isolated regions. This is observable particularly in the eastern half of NWI, which is mostly located far from Westerlies. On the other hand, seasonal precipitation trends indicated a slight decrease during winter and spring and a slight increase during summer and autumn. Consequently, there were major changes in average precipitation that occurred negatively in the area under study during the observation period. This finding is in agreement with those findings by recent studies which revealed a decreasing trend of around 2 mm/year over NWI

An intercomparison of observational precipitation data sets over Northwest India during winter

NASA Astrophysics Data System (ADS)

Nageswararao, M. M.; Mohanty, U. C.; Ramakrishna, S. S. V. S.; Dimri, A. P.

2018-04-01

Winter (DJF) precipitation over Northwest India (NWI) is very important for the cultivation of Rabi crops. Thus, an accurate estimation of high-resolution observations, evaluation of high-resolution numerical models, and understanding the local variability trends are essential. The objective of this study is to verify the quality of a new high spatial resolution (0.25° × 0.25°) gridded daily precipitation data set of India Meteorological Department (IMD1) over NWI during winter. An intercomparison with four existing precipitation data sets at 0.5° × 0.5° of IMD (IMD2), 1° × 1° of IMD (IMD3), 0.25° × 0.25° of APHRODITE (APRD1), and 0.5° × 0.5° of APHRODITE (APRD1) resolution during a common period of 1971-2003 is done. The evaluation of data quality of these five data sets against available 26 station observations is carried out, and the results clearly indicate that all the five data sets reasonably agreed with the station observation. However, the errors are relatively more in all the five data sets over Jammu and Kashmir-related four stations (Srinagar, Drass, Banihal top, and Dawar), while these errors are less in the other stations. It may be due to the lack of station observations over the region. The quality of IMD1 data set over NWI for winter precipitation is reasonably well than the other data sets. The intercomparison analysis suggests that the climatological mean, interannual variability, and coefficient of variation from IMD1 are similar with other data sets. Further, the analysis extended to the India meteorological subdivisions over the region. This analysis indicates overestimation in IMD3 and underestimation in APRD1 and APRD2 over Jammu and Kashmir, Himachal Pradesh, and NWI as a whole, whereas IMD2 is closer to IMD1. Moreover, all the five data sets are highly correlated (>0.5) among them at 99.9% confidence level for all subdivisions. It is remarkably noticed that multicategorical (light precipitation, moderate precipitation, heavy

Co-variation of Temperature and Precipitation in CMIP5 Models and Satellite Observations

NASA Technical Reports Server (NTRS)

Liu, Chunlei; Allan, Richard P.; Huffman, George J.

2013-01-01

Current variability of precipitation (P) and its response to surface temperature (T) are analysed using coupled (CMIP5) and atmosphere-only (AMIP5) climate model simulations and compared with observational estimates.There is striking agreement between Global Precipitation Climatology Project (GPCP) observed and AMIP5)simulated P anomalies over land both globally and in the tropics suggesting that prescribed sea surface temperature and realistic radiative forcings are sufficient for simulating the interannual variability in continental P. Differences between the observed and simulated P variability over the ocean, originate primarily from the wet tropical regions, in particular the western Pacific, but are reduced slightly after 1995. All datasets show positive responses of P to T globally of around 2 % K for simulations and 3-4 % K in GPCP observations but model responses over the tropical oceans are around 3 times smaller than GPCP over the period 1988-2005. The observed anticorrelation between land and ocean P, linked with El Nio Southern Oscillation, is captured by the simulations. All data sets over the tropical ocean show a tendency for wet regions to become wetter and dry regions drier with warming. Over the wet region (greater than or equal to 75 precipitation percentile), the precipitation response is 13-15%K for GPCP and 5%K for models while trends in P are 2.4% decade for GPCP, 0.6% decade for CMIP5 and 0.9decade for AMIP5 suggesting that models are underestimating the precipitation responses or a deficiency exists in the satellite datasets.

Observations and simulations of the interactions between clouds, radiation, and precipitation

NASA Astrophysics Data System (ADS)

Naegele, Alexandra Claire

The first part of this study focuses on the radiative constraint on the hydrologic cycle as seen in observations. In the global energy budget, the atmospheric radiative cooling (ARC) is approximately balanced by latent heating, but on regional scales, the ARC and precipitation are inversely related. We use precipitation data from the Global Precipitation Climatology Project and radiative flux data from the Clouds and the Earth's Radiant Energy System (CERES) project to investigate the radiative constraint on the hydrologic cycle and how it changes in both space and time. We find that the effect of clouds is to decrease the ARC in the tropics, and to increase the ARC in middle and higher latitudes. We find that, spatially, precipitation and the ARC are negatively correlated in the tropics, and positively correlated in middle and higher latitudes. In terms of the global mean, the precipitation rate and the ARC are temporally out-of-phase during the Northern Hemisphere winter. In the second part of this study, we use a cloud-resolving model to gain a deeper understanding of the relationship between precipitation and the ARC. In particular, we explore how the relationship between precipitation and the ARC is affected by convective aggregation, in which the convective activity is confined to a small portion of the domain that is surrounded by a much larger region of dry, subsiding air. We investigate the responses of the ARC and precipitation rate to changes in the sea surface temperature (SST), domain size, and microphysics parameterization. Both fields increase with increasing SST and the use of 2-moment microphysics. The precipitation and ARC show evidence of convective aggregation, and in the domain average, both fields increase as a result. While running these sensitivity tests, we observed a pulsation in the convective precipitation rate, once aggregation had occurred. The period of the pulsation is on the order of ten simulated hours for a domain size of 768 km

Quantifying Precipitation Variability on Titan Using a GCM and Implications for Observed Geomorphology

NASA Astrophysics Data System (ADS)

Faulk, Sean P.; Mitchell, Jonathan L.; Moon, Seulgi; Lora, Juan Manuel

2016-10-01

Titan's zonal-mean precipitation behavior has been widely investigated using general circulation models (GCMs), but the spatial and temporal variability of rainfall in Titan's active hydrologic cycle is less well understood. We conduct statistical analyses of rainfall, diagnosed from GCM simulations of Titan's atmosphere, to determine storm intensity and frequency. Intense storms of methane have been proposed to be critical for enabling mechanical erosion of Titan's surface, as indicated by observations of dendritic valley networks. Using precipitation outputs from the Titan Atmospheric Model (TAM), a GCM shown to realistically simulate many features of Titan's atmosphere, we quantify the precipitation variability within eight separate latitude bins for a variety of initial surface liquid distributions. We find that while the overall wettest regions are indeed the poles, the most intense rainfall generally occurs in the high mid-latitudes, between 45-67.5 degrees, consistent with recent geomorphological observations of alluvial fans concentrated at those latitudes. We also find that precipitation rates necessary for surface erosion, as estimated by Perron et al. (2006) J. Geophys. Res. 111, E11001, frequently occur at all latitudes, with recurrence intervals of less than one Titan year. Such analysis is crucial towards understanding the complex interaction between Titan's atmosphere and surface and defining the influence of precipitation on observed geomorphology.

Estimating Precipitation Input to a Watershed by Combining Gauge and Radar Derived Observations

NASA Astrophysics Data System (ADS)

Ercan, M. B.; Goodall, J. L.

2011-12-01

One challenge in creating an accurate watershed model is obtaining estimates of precipitation intensity over the watershed area. While precipitation measurements are generally available from gauging stations and radar instruments, both of these approaches for measuring precipitation have strengths and weakness. A typical way of addressing this challenge is to use gauged precipitation estimates to calibrate radar based estimates, however this study proposes a slightly different approach in which the optimal daily precipitation value is selected from either the gauged or the radar estimates based on the observed streamflow for that day. Our proposed approach is perhaps most relevant for cases of modeling watersheds that do not have a nearby precipitation gauge, or for regions that experience convective storms that are often highly spatially variable. Using the Eno River watershed located in Orange County, NC, three different precipitation datasets were created to predict streamflow at the watershed outlet for the time period 2005-2010 using the Soil and Water Assessment Tool (SWAT): (1) estimates based on only precipitation gauging stations, (2) estimates based only on gauged-corrected radar observations, and (3) the combination of precipitation estimates from the gauge and radar data determined using our proposed approach. The results show that the combined precipitation approach significantly improves streamflow predictions (Nash-Sutcliffe Coefficient, E = 0.66) when compared to the gauged estimates alone (E = 0.47) and the radar based estimates alone (E = 0.45). Our study was limited to one watershed, therefore additional studies are needed to control for factors such as climate, ecology, and hydrogeology that will likely influence the results of the analysis.

Can thermal instabilities drive galactic precipitation and explain observed circumgalactic structure?

NASA Astrophysics Data System (ADS)

Silvia, Devin

2015-10-01

Understanding the complex nature of the circumgalactic medium (CGM) has been a target of numerous research efforts, both observationally and theoretically. While significant progress has been made in probing the structure and thermodynamic state of the CGM through the detection of metal line absorption systems using the Hubble Space Telescope (HST), a complete picture of the physical mechanisms that produce the observed properties does not yet exist. Recent theoretical work has suggested that a delicate balance between radiative cooling and thermal feedback detemines whether or not the CGM is capable of sustaining a stable, multiphase medium that would allow cool clouds to precipitate out of the galactic halo. This new theoretical framework may provide the explanation for many observational results. In this project, we will detemine whether or not this elegant and simple precipitation model can be supported by physics-rich numerical simulations of isolated galaxies. We will use our simulations to gain a deeper understanding of the precipitation model and explore the ionization and temperature stucture of the CGM. Our analysis will include the comparison of realistic synthetic spectra to those produced by HST, using the newly-developed Trident software package.

Carbon economics of LAI drive photosynthesis patterns across an Amazonian precipitation gradient

NASA Astrophysics Data System (ADS)

Flack, Sophie; Williams, Mathew; Meir, Patrick; Malhi, Yadvinder

2017-04-01

The Amazon rainforest is an integral part of the terrestrial carbon cycle, yet whilst the physiological response of its plants to water availability is increasingly well quantified, constraints to photosynthesis through adaptive response to precipitation regime have received little attention. We use the Soil Plant Atmosphere model to apportion variation in photosynthesis to individual drivers for plots with detailed measurements of carbon cycling, leaf traits and canopy properties, along an Amazonian mean annual precipitation (MAP) gradient. We hypothesised that leaf area index (LAI) would be the principal driver of variation in photosynthesis. Differences in LAI are predicted to result from economic factors; plants balance the carbon cost of leaf construction and maintenance with assimilation potential, to maximise canopy carbon export. Model analysis showed that LAI was the primary driver of differences in GPP along the precipitation gradient, accounting for 49% of observed variation. Meteorology accounted for 19%, whilst plant traits accounted for only 5%. To explain the observed spatial trends in LAI we undertook model experiments. For each plot the carbon budget was quantified iteratively using the field measured LAI time-series of the other plots, keeping meteorology, soil and plant traits constant. The mean annual LAI achieving maximum photosynthesis and net canopy carbon export increased with MAP, reflecting observed LAI trends. At the driest site, alternative, higher LAI strategies were unsustainable. The carbon cost of leaf construction and maintenance was disproportional to GPP achieved. At high MAP, increased foliar carbon costs were remunerative and GPP was maximised by high LAI. Our evidence therefore suggests that observed LAI trends across the precipitation gradient are driven by carbon economics. Forests LAI response to temporal changes in precipitation reflects trends observed across spatial gradients, identifying LAI as a key mechanism for plant

Videosonde observations of tropical precipitating clouds developed over the Sumatera Island, Indonesia

NASA Astrophysics Data System (ADS)

Suzuki, Kenji; Nakagawa, Katsuhiro; Kawano, Tetsuya; Mori, Shuichi; Katsumata, Masaki; Yoneyama, Kunio

2017-04-01

During November-December 2015, as a pilot study of the Years of the Maritime and Continent (YMC), a campaign observation over the southwestern coastal land and adjacent sea of Sumatera Island, Indonesia was carried out to examine land-ocean coupling processes in mechanisms of coastal heavy rain. Our videosonde observations were conducted as a part of this campaign for the better understandings of microphysical features in tropical precipitating clouds developed over the Sumatera Island. Videosonde is one of strong tools to measure hydrometeors in clouds directly. It is a balloon-borne radiosonde that acquires images of precipitation particles via a CCD camera. The system has a stroboscopic illumination that provides information on particle size and shape. One of the advantages for the videosonde is to capture images of precipitation particles as they are in the air because the videosonde can obtain particle images without contact. Recorded precipitation particles are classified as raindrops, frozen drops (hail), graupel, ice crystals, or snowflakes on the basis of transparency and shape. Videosondes were launched from BMKG Bengkulu weather station (3.86°S，102.3°E). After the launch of a videosonde, the Range Height Indicator (RHI) scans by a C-band dual-polarimetric radar installed on R/V Mirai, which was approximately 50 km off Sumatera Island, were continuously performed, targeting the videosonde in the precipitating cloud. Eighteen videosondes were launched into various types of tropical precipitating clouds during the Pre-YMC campaign.

Assessment of Observational Uncertainty in Extreme Precipitation Events over the Continental United States

NASA Astrophysics Data System (ADS)

Slinskey, E. A.; Loikith, P. C.; Waliser, D. E.; Goodman, A.

2017-12-01

Extreme precipitation events are associated with numerous societal and environmental impacts. Furthermore, anthropogenic climate change is projected to alter precipitation intensity across portions of the Continental United States (CONUS). Therefore, a spatial understanding and intuitive means of monitoring extreme precipitation over time is critical. Towards this end, we apply an event-based indicator, developed as a part of NASA's support of the ongoing efforts of the US National Climate Assessment, which assigns categories to extreme precipitation events based on 3-day storm totals as a basis for dataset intercomparison. To assess observational uncertainty across a wide range of historical precipitation measurement approaches, we intercompare in situ station data from the Global Historical Climatology Network (GHCN), satellite-derived precipitation data from NASA's Tropical Rainfall Measuring Mission (TRMM), gridded in situ station data from the Parameter-elevation Regressions on Independent Slopes Model (PRISM), global reanalysis from NASA's Modern Era Retrospective-Analysis version 2 (MERRA 2), and regional reanalysis with gauge data assimilation from NCEP's North American Regional Reanalysis (NARR). Results suggest considerable variability across the five-dataset suite in the frequency, spatial extent, and magnitude of extreme precipitation events. Consistent with expectations, higher resolution datasets were found to resemble station data best and capture a greater frequency of high-end extreme events relative to lower spatial resolution datasets. The degree of dataset agreement varies regionally, however all datasets successfully capture the seasonal cycle of precipitation extremes across the CONUS. These intercomparison results provide additional insight about observational uncertainty and the ability of a range of precipitation measurement and analysis products to capture extreme precipitation event climatology. While the event category threshold is fixed

On the relationship between Indian Ocean Dipole events and the precipitation of Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Mian Sabir; Kim, Sunyoung; Lee, Seungho

2017-10-01

This study investigated the relationship between the Indian Ocean Dipole (IOD) and the precipitation of Pakistan using data for the period of 1958-2010. The long-term evolution of the IOD index did not show interannual patterns similar to those of the annual precipitation of Pakistan. No linkage between the co-occurring trends of the IOD and the precipitation was traced during the period of investigation. The correlation between the IOD and the precipitation of Pakistan indicated a noteworthy impact over the monsoonal regions, especially the coastal area and the western region of Pakistan, which showed a significant positive correlation between the IOD index and annual and summer precipitation. A significant positive relationship was also revealed between the precipitation of the Balochistan Plateau and the IOD index for the summer monsoon season. No connection was observed between the IOD and the precipitation of the northern regions and the upper Indus Plain of Pakistan. Positive phases of the IOD have been noted to occur along with surplus precipitation during active monsoon conditions. The southeasterly wind moves from the Arabian Sea and transports additional moisture from the Arabian Sea to the coastal and southwestern parts of Pakistan during positive phases of the IOD.

Variations of annual and seasonal runoff in Guangdong Province, south China: spatiotemporal patterns and possible causes

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Xiao, Mingzhong; Singh, Vijay P.; Xu, Chong-Yu; Li, Jianfeng

2015-06-01

In this study, we thoroughly analyzed spatial and temporal distributions of runoff and their relation with precipitation changes based on monthly runoff dataset at 25 hydrological stations and monthly precipitation at 127 stations in Guangdong Province, south China. Trends of the runoff and precipitation are detected using Mann-Kendall trend test technique. Correlations between runoff and precipitation are tested using Spearman's and Pearson's correlation coefficients. The results indicate that: (1) annual maximum monthly runoff is mainly in decreasing tendency and significant increasing annual minimum monthly runoff is observed in the northern and eastern Guangdong Province. In addition, annual mean runoff is observed to be increasing at the stations located in the West and North Rivers and the coastal region; (2) analysis of seasonal runoff variations indicates increasing runoff in spring, autumn and winter. Wherein, significant increase of runoff is found at 8 stations and only 3 stations are dominated by decreasing runoff in winter; (3) runoff changes of the Guangdong Province are mainly the results of precipitation changes. The Guangdong Province is wetter in winter, spring and autumn. Summer is coming to be drier as reflected by decreasing runoff in the season; (4) both precipitation change and water reservoirs also play important roles in the increasing of annual minimum monthly streamflow. Seasonal shifts of runoff variations may pose new challenges for the water resources management under the influences of climate changes and intensifying human activities.

Are weather models better than gridded observations for precipitation in the mountains? (Invited)

NASA Astrophysics Data System (ADS)

Gutmann, E. D.; Rasmussen, R.; Liu, C.; Ikeda, K.; Clark, M. P.; Brekke, L. D.; Arnold, J.; Raff, D. A.

2013-12-01

Mountain snowpack is a critical storage component in the water cycle, and it provides drinking water for tens of millions of people in the Western US alone. This water store is susceptible to climate change both because warming temperatures are likely to lead to earlier melt and a temporal shift of the hydrograph, and because changing atmospheric conditions are likely to change the precipitation patterns that produce the snowpack. Current measurements of snowfall in complex terrain are limited in number due in part to the logistics of installing equipment in complex terrain. We show that this limitation leads to statistical artifacts in gridded observations of current climate including errors in precipitation season totals of a factor of two or more, increases in wet day fraction, and decreases in storm intensity. In contrast, a high-resolution numerical weather model (WRF) is able to reproduce observed precipitation patterns, leading to confidence in its predictions for areas without measurements and new observations support this. Running WRF for a future climate scenario shows substantial changes in the spatial patterns of precipitation in the mountains related to the physics of hydrometeor production and detrainment that are not captured by statistical downscaling products. The stationarity in statistical downscaling products is likely to lead to important errors in our estimation of future precipitation in complex terrain.

Should we care about diurnal temperatures when calculating the precipitation isotope thermometer?

NASA Astrophysics Data System (ADS)

Vachon, R.; Kloeckner, D.

2008-12-01

Long records of the concentrations of stable isotopes of precipitation (SIPs) have long been used as proxies for regional and global climates for periods when meteorological measurements were not made. SIPs' longstanding correlation to local surface temperatures (in many locations) and molecular thermal dynamics have lead to many interpretations of variability in SIPs to be changes in local temperatures. In order to create accurate temperature-SIP transfer functions one needs to link modern SIP concentrations to temperatures of when precipitation happened. A well-sited example of complexities in the temperature-SIP relationships - For simplicity one may assume that annual precipitation occurred at the same time of year throughout a long SIP archive, however, it is possible that the timing of precipitation actually shifted from summer to winter months. If the temperature difference between the seasons is large the SIP archive could be wrongly interpreted as a several degree cooling in average annual temperatures. Temperature changes similar in magnitude to seasonal fluctuations are also observed throughout a given day. What would happen if precipitation shifted from mid-afternoon to nighttime events? This line of thinking implies that diurnal effects plausibly should be considered when calculating SIP-transfer functions. This is particularly convincing when precipitation for a region is powered by middle of the day (summer) heat causing convective precipitation or evening cooling increasing relative humidities near the land's surface. This study examines both theoretical and observed (5 locations within North America) surface temperatures at the time of precipitation throughout a day and estimates diurnal effects on SIP-transfer functions. Ultimately, one must ask, how high does condensation form, and what are daily temperature patterns at those heights?

Long-term variability and changes of the precipitation regime in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Mian Sabir; Lee, Seungho

2014-05-01

This paper presents an examination of precipitation amounts in Pakistan. For this purpose, the annual precipitation and the annual number of precipitation days have been calculated, and a study aimed at investigating precipitation intensity and decadal changes was conducted. Precipitation trends have been calculated using a simple linear regression method and Kendall's tau-based test. To assess stability and differences, a 10-year span was determined for each precipitation region for the period of 1951-2010. This study focused on the three CLINO (Climatological Normal) periods, namely 1961-1990, 1971-2000, and 1981-2010 (the latest global standard normal period). Results confirm the gradual increase of annual precipitation in southwestern coastal areas of Pakistan and Cholistan desert. With regard to annual number of precipitation days, in the central part of the country negative trends were evident for wet days (with precipitation ≧ 0.1 mm), while the number of rainy days (with precipitation ≧ 1 mm) displayed a prominent positive trend. The series of the precipitation intensity gives evidence of a minor decrease in the Baluchistan Plateau, sub-Himalayas, and Potwar Plateau during the study period. Examination of secular trends evidenced that the Murree hills, the upper Indus plain, and the northwestern Baluchistan plateau have had shifts in their precipitation regime towards drier conditions, while the central plain, the northwestern mountains, and the southern part of the country are shifting in their precipitation regime towards wetter conditions. Description among the means of precipitation amounts suggests that "normal" precipitation data for various national projects should be calculated for the last 30 years.

Uncertainty Analysis of Downscaled CMIP5 Precipitation Data for Louisiana, USA

NASA Astrophysics Data System (ADS)

Sumi, S. J.; Tamanna, M.; Chivoiu, B.; Habib, E. H.

2014-12-01

The downscaled CMIP3 and CMIP5 Climate and Hydrology Projections dataset contains fine spatial resolution translations of climate projections over the contiguous United States developed using two downscaling techniques (monthly Bias Correction Spatial Disaggregation (BCSD) and daily Bias Correction Constructed Analogs (BCCA)). The objective of this study is to assess the uncertainty of the CMIP5 downscaled general circulation models (GCM). We performed an analysis of the daily, monthly, seasonal and annual variability of precipitation downloaded from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections website for the state of Louisiana, USA at 0.125° x 0.125° resolution. A data set of daily gridded observations of precipitation of a rectangular boundary covering Louisiana is used to assess the validity of 21 downscaled GCMs for the 1950-1999 period. The following statistics are computed using the CMIP5 observed dataset with respect to the 21 models: the correlation coefficient, the bias, the normalized bias, the mean absolute error (MAE), the mean absolute percentage error (MAPE), and the root mean square error (RMSE). A measure of variability simulated by each model is computed as the ratio of its standard deviation, in both space and time, to the corresponding standard deviation of the observation. The correlation and MAPE statistics are also computed for each of the nine climate divisions of Louisiana. Some of the patterns that we observed are: 1) Average annual precipitation rate shows similar spatial distribution for all the models within a range of 3.27 to 4.75 mm/day from Northwest to Southeast. 2) Standard deviation of summer (JJA) precipitation (mm/day) for the models maintains lower value than the observation whereas they have similar spatial patterns and range of values in winter (NDJ). 3) Correlation coefficients of annual precipitation of models against observation have a range of -0.48 to 0.36 with variable spatial distribution by model

Observed changes in extreme precipitation in Poland: 1991-2015 versus 1961-1990

NASA Astrophysics Data System (ADS)

Pińskwar, Iwona; Choryński, Adam; Graczyk, Dariusz; Kundzewicz, Zbigniew W.

2018-01-01

Several episodes of extreme precipitation excess and extreme precipitation deficit, with considerable economic and social impacts, have occurred in Europe and in Poland in the last decades. However, the changes of related indices exhibit complex variability. This paper analyses changes in indices related to observed abundance and deficit of precipitated water in Poland. Among studied indices are maximum seasonal 24-h precipitation for the winter half-year (Oct.-March) and the summer half-year (Apr.-Sept.), maximum 5-day precipitation, maximum monthly precipitation and number of days with intense or very intense precipitation (respectively, in excess of 10 mm or 20 mm per day). Also, the warm-seasonal maximum number of consecutive dry days (longest period with daily precipitation below 1 mm) was examined. Analysis of precipitation extremes showed that daily maximum precipitation for the summer half-year increased for many stations, and increases during the summer half-year are more numerous than those in the winter half-year. Also, analysis of 5-day and monthly precipitation sums show increases for many stations. Number of days with intense precipitation increases especially in the north-western part of Poland. The number of consecutive dry days is getting higher for many stations in the summer half-year. Comparison of these two periods: colder 1961-1990 and warmer 1991-2015, revealed that during last 25 years most of statistical indices, such as 25th and 75th percentiles, median, mean and maximum are higher. However, many changes discussed in this paper are weak and statistically insignificant. The findings reported in this paper challenge results based on earlier data that do not include 2007-2015.

A perturbation approach for assessing trends in precipitation extremes across Iran

NASA Astrophysics Data System (ADS)

Tabari, Hossein; AghaKouchak, Amir; Willems, Patrick

2014-11-01

Extreme precipitation events have attracted a great deal of attention among the scientific community because of their devastating consequences on human livelihood and socio-economic development. To assess changes in precipitation extremes in a given region, it is essential to analyze decadal oscillations in precipitation extremes. This study examines temporal oscillations in precipitation data in several sub-regions of Iran using a novel quantile perturbation method during 1980-2010. Precipitation data from NASA's Modern-Era Retrospective Analysis for Research and Applications-Land (MERRA-Land) are used in this study. The results indicate significant anomalies in precipitation extremes in the northwest and southeast regions of Iran. Analysis of extreme precipitation perturbations reveals that perturbations for the monthly aggregation level are generally lower than the annual perturbations. Furthermore, high-oscillation and low-oscillation periods are found in extreme precipitation quantiles across different seasons. In all selected regions, a significant anomaly (i.e., extreme wet/dry conditions) in precipitation extremes is observed during spring.

Spatial downscaling algorithm of TRMM precipitation based on multiple high-resolution satellite data for Inner Mongolia, China

NASA Astrophysics Data System (ADS)

Duan, Limin; Fan, Keke; Li, Wei; Liu, Tingxi

2017-12-01

Daily precipitation data from 42 stations in Inner Mongolia, China for the 10 years period from 1 January 2001 to 31 December 2010 was utilized along with downscaled data from the Tropical Rainfall Measuring Mission (TRMM) with a spatial resolution of 0.25° × 0.25° for the same period based on the statistical relationships between the normalized difference vegetation index (NDVI), meteorological variables, and digital elevation models (https://en.wikipedia.org/wiki/Digital_elevation_model) (DEM) using the leave-one-out (LOO) cross validation method and multivariate step regression. The results indicate that (1) TRMM data can indeed be used to estimate annual precipitation in Inner Mongolia and there is a linear relationship between annual TRMM and observed precipitation; (2) there is a significant relationship between TRMM-based precipitation and predicted precipitation, with a spatial resolution of 0.50° × 0.50°; (3) NDVI and temperature are important factors influencing the downscaling of TRMM precipitation data for DEM and the slope is not the most significant factor affecting the downscaled TRMM data; and (4) the downscaled TRMM data reflects spatial patterns in annual precipitation reasonably well, showing less precipitation falling in west Inner Mongolia and more in the south and southeast. The new approach proposed here provides a useful alternative for evaluating spatial patterns in precipitation and can thus be applied to generate a more accurate precipitation dataset to support both irrigation management and the conservation of this fragile grassland ecosystem.

Large-Scale Covariability Between Aerosol and Precipitation Over the 7-SEAS Region: Observations and Simulations

NASA Technical Reports Server (NTRS)

Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;

Observations and modeling of wave-induced microburst electron precipitation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosenberg, T.J.; Wei, R.; Detrick, D.L.

1990-05-01

Energy-time features of X ray microbursts are examined and compared with the predictions of a test particle simulation model of wave-induced electron precipitation resulting from gyroresonant wave-particle interactions in the magnetosphere. An algorithm designed to search the E > 25 keV counting rate data for single isolated microbursts identified 651 events in a 3-hr interval. The distribution of burst durations ranged from 0.2 to 1.2 s. Approximately two-thirds of the distribution were narrow bursts (0.2 - 0.6 s), the rest wide (0.6 - 1.2 s), with the average burst durations equal to {minus}0.4 s and {minus}0.7 s, respectively, for themore » two classes. The precipitation was characterized by exponential electron spectra with e-folding energies Eo of 25-50 keV. Individual and superposed microburst profiles show that the X ray energy spectrum is softest near the peak of the energy influx. Computer simulations of the flux- and energy-time profiles of direct and mirrored electron precipitation induced by a whistler-mode wave pulse of 0.2-s duration and linear frequency increase from 2 to 4 kHz were performed for plasma, energetic particle and wave parameters appropriate for the location and geophysical conditions of the observations. In general, the results provide further support for the guroresonant test particle simulation model, and for the belief that the observed type of microbursts originates in the vicinity of the magnetic equator in a gyroresonant process involving discrete chorus emissions.« less

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System

NASA Technical Reports Server (NTRS)

Chambon, Philippe; Zhang, Sara Q.; Hou, Arthur Y.; Zupanski, Milija; Cheung, Samson

2013-01-01

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability.

Summary of types of radiation belt electron precipitation observed by BARREL

NASA Astrophysics Data System (ADS)

Halford, Alexa

2016-07-01

The Balloon Array for Relativistic Radiation belt Electron Loss (BARREL) was able to infer precipitation of radiation belt electrons on multiple time scales and due to multiple loss mechanisms. One storm will be specifically highlighted which occurred on 26 January 2013 when a solar wind shock hit the Earth. Although MeV electrons were observed to be lost due to an EMIC wave event [Zhang et al in prep], and multiple periods of electron loss during substorms were observed [Rae et al submitted JGR, Mann et al in prep], we will consider an event period where loss associated with multiple time scales, and thus possibly different loss mechanisms was observed from 1000 - 1200 UT on 26 January 2013. At about 1005 UT on 26 January 2013 an injection of radiation belt electrons followed by drift echoes for energies of ˜80 - 400 keV. BARREL observed X-rays with energies less than 180 keV associated with multiple temporal structures during the drift echo event period. The Van Allen Probes were at similar L-values but upwards of 2 hours away in MLT. Upper band chorus and ULF waves were observed during the event period. Throughout the beginning of the event period, microbursts were clearly observed. During this time lower band chorus waves as well as time domain structures were observed at Van Allen Probe A located upwards of 2 hours away in MLT. This large difference in MLT meant that neither potential loss mechanism was able to be clearly associated with the microbursts. As the lower band chorus and time domain structures were observed to recede, the microbursts were also observed to subside. ULF time scale modulation of the X-rays was also observed throughout most of the event period. We will examine if the ULF waves are the cause of the precipitation themselves, or are modulating the loss of particles from a secondary loss mechanism [Brito et al 2015 JGR, Rae et al Submitted JGR]. Although the 100s ms and ULF time scales are clearly observed, there is an ˜20 minute

Spatial and temporal variability of precipitation in Serbia for the period 1961-2010

NASA Astrophysics Data System (ADS)

Milovanović, Boško; Schuster, Phillip; Radovanović, Milan; Vakanjac, Vesna Ristić; Schneider, Christoph

2017-10-01

Monthly, seasonal and annual sums of precipitation in Serbia were analysed in this paper for the period 1961-2010. Latitude, longitude and altitude of 421 precipitation stations and terrain features in their close environment (slope and aspect of terrain within a radius of 10 km around the station) were used to develop a regression model on which spatial distribution of precipitation was calculated. The spatial distribution of annual, June (maximum values for almost all of the stations) and February (minimum values for almost all of the stations) precipitation is presented. Annual precipitation amounts ranged from 500 to 600 mm to over 1100 mm. June precipitation ranged from 60 to 140 mm and February precipitation from 30 to 100 mm. The validation results expressed as root mean square error (RMSE) for monthly sums ranged from 3.9 mm in October (7.5% of the average precipitation for this month) to 6.2 mm in April (10.4%). For seasonal sums, RMSE ranged from 10.4 mm during autumn (6.1% of the average precipitation for this season) to 20.5 mm during winter (13.4%). On the annual scale, RMSE was 68 mm (9.5% of the average amount of precipitation). We further analysed precipitation trends using Sen's estimation, while the Mann-Kendall test was used for testing the statistical significance of the trends. For most parts of Serbia, the mean annual precipitation trends fell between -5 and +5 and +5 and +15 mm/decade. June precipitation trends were mainly between -8 and +8 mm/decade. February precipitation trends generally ranged from -3 to +3 mm/decade.

Spatial correlation in precipitation trends in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Buarque, Diogo Costa; Clarke, Robin T.; Mendes, Carlos Andre Bulhoes

2010-06-01

A geostatistical analysis of variables derived from Amazon daily precipitation records (trends in annual precipitation totals, trends in annual maximum precipitation accumulated over 1-5 days, trend in length of dry spell, trend in number of wet days per year) gave results that are consistent with those previously reported. Averaged over the Brazilian Amazon region as a whole, trends in annual maximum precipitations were slightly negative, the trend in the length of dry spell was slightly positive, and the trend in the number of wet days in the year was slightly negative. For trends in annual maximum precipitation accumulated over 1-5 days, spatial correlation between trends was found to extend up to a distance equivalent to at least half a degree of latitude or longitude, with some evidence of anisotropic correlation. Time trends in annual precipitation were found to be spatially correlated up to at least ten degrees of separation, in both W-E and S-N directions. Anisotropic spatial correlation was strongly evident in time trends in length of dry spell with much stronger evidence of spatial correlation in the W-E direction, extending up to at least five degrees of separation, than in the S-N. Because the time trends analyzed are shown to be spatially correlated, it is argued that methods at present widely used to test the statistical significance of climate trends over time lead to erroneous conclusions if spatial correlation is ignored, because records from different sites are assumed to be statistically independent.

Nutrient content of precipitation over Iowa

Treesearch

M. A. Tabatabai; J. M. Laflen

1976-01-01

Nutrient content and pH of precipitation samples collected at six sites during 1971-1973 were studied to determine the reaction of rainfall and snowmelt and the amounts of N, S, and P added by precipitation over Iowa. The amount of NH4-N added by precipitation per hectare annually at each site was about equal to that added as NO3...

Modeling Precipitation Dependent Forest Resilience in India

NASA Astrophysics Data System (ADS)

Das, P.; Behera, M. D.; Roy, P. S.

2018-04-01

The impact of long term climate change that imparts stress on forest could be perceived by studying the regime shift of forest ecosystem. With the change of significant precipitation, forest may go through density change around globe at different spatial and temporal scale. The 100 class high resolution (60 meter spatial resolution) Indian vegetation type map was used in this study recoded into four broad categories depending on phrenology as (i) forest, (ii) scrubland, (iii) grassland and (iv) treeless area. The percentage occupancy of forest, scrub, grass and treeless were observed as 19.9 %, 5.05 %, 1.89 % and 7.79 % respectively. Rest of the 65.37 % land area was occupied by the cropland, built-up, water body and snow covers. The majority forest cover were appended into a 5 km × 5 km grid, along with the mean annual precipitation taken from Bioclim data. The binary presence and absence of different vegetation categories in relates to the annual precipitation was analyzed to calculate their resilience expressed in probability values ranging from 0 to 1. Forest cover observed having resilience probability (Pr) < 0.3 in only 0.3 % (200 km2) of total forest cover in India, which was 4.3 % < 0.5 Pr. Majority of the scrubs and grass (64.92 % Pr < 0.5) from North East India which were the shifting cultivation lands showing low resilience, having their high tendency to be transform to forest. These results have spatial explicitness to highlight the resilient and non-resilient distribution of forest, scrub and grass, and treeless areas in India.

Validation of satellite based precipitation over diverse topography of Pakistan

NASA Astrophysics Data System (ADS)

Iqbal, Muhammad Farooq; Athar, H.

2018-03-01

This study evaluates the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product data with 0.25° × 0.25° spatial and post-real-time 3 h temporal resolution using point-based Surface Precipitation Gauge (SPG) data from 40 stations, for the period 1998-2013, and using gridded Asian Precipitation ˗ Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) data abbreviated as APH data with 0.25° × 0.25° spatial and daily temporal resolution for the period 1998-2007, over vulnerable and data sparse regions of Pakistan (24-37° N and 62-75° E). To evaluate the performance of TMPA relative to SPG and APH, four commonly used statistical indicator metrics including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC) are employed on daily, monthly, seasonal as well as on annual timescales. The TMPA slightly overestimated both SPG and APH at daily, monthly, and annual timescales, however close results were obtained between TMPA and SPG as compared to those between TMPA and APH, on the same timescale. The TMPA overestimated both SPG and APH during the Pre-Monsoon and Monsoon seasons, whereas it underestimated during the Post-Monsoon and Winter seasons, with different magnitudes. Agreement between TMPA and SPG was good in plain and medium elevation regions, whereas TMPA overestimated APH in 31 stations. The magnitudes of MAE and RMSE were high at daily timescale as compared to monthly and annual timescales. Relatively large MAE was observed in stations located over high elevation regions, whereas minor MAE was recorded in plain area stations at daily, monthly, and annual timescales. A strong positive linear relationship between TMPA and SPG was established at monthly (0.98), seasonal (0.93 to 0.98) and annual (0.97) timescales. Precipitation increased with the increase of elevation, and not only elevation but latitude also affected the

Self-organizing map network-based precipitation regionalization for the Tibetan Plateau and regional precipitation variability

NASA Astrophysics Data System (ADS)

Wang, Nini; Yin, Jianchuan

2017-12-01

A precipitation-based regionalization for the Tibetan Plateau (TP) was investigated for regional precipitation trend analysis and frequency analysis using data from 1113 grid points covering the period 1900-2014. The results utilizing self-organizing map (SOM) network suggest that four clusters of precipitation coherent zones can be identified, including the southwestern edge, the southern edge, the southeastern region, and the north central region. Regionalization results of the SOM network satisfactorily represent the influences of the atmospheric circulation systems such as the East Asian summer monsoon, the south Asian summer monsoon, and the mid-latitude westerlies. Regionalization results also well display the direct impacts of physical geographical features of the TP such as orography, topography, and land-sea distribution. Regional-scale annual precipitation trend as well as regional differences of annual and seasonal total precipitation were investigated by precipitation index such as precipitation concentration index (PCI) and Standardized Anomaly Index (SAI). Results demonstrate significant negative long-term linear trends in southeastern TP and the north central part of the TP, indicating arid and semi-arid regions in the TP are getting drier. The empirical mode decomposition (EMD) method shows an evolution of the main cycle with 4 and 12 months for all the representative grids of four sub-regions. The cross-wavelet analysis suggests that predominant and effective period of Indian Ocean Dipole (IOD) on monthly precipitation is around ˜12 months, except for the representative grid of the northwestern region.

Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

NASA Astrophysics Data System (ADS)

Beranová, Romana; Kyselý, Jan; Hanel, Martin

2018-04-01

The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May-September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.

Recent Observations of Clouds and Precipitation by the Airborne Precipitation Radar 2nd Generation in Support of the GPM and ACE Missions

NASA Technical Reports Server (NTRS)

Durden, Stephen L.; Tanelli, Simone; Im, Eastwood

2012-01-01

In this paper we illustrate the unique dataset collected during the Global Precipitation Measurement Cold-season Precipitation Experiment (GCPEx, US/Canada Jan/Feb 2012). We will focus on the significance of these observations for the development of algorithms for GPM and ACE, with particular attention to classification and retrievals of frozen and mixed phase hydrometeors.

The Impacts of Atmospheric Rivers on California's Extreme Precipitation

NASA Astrophysics Data System (ADS)

Asgari Lamjiri, M.; Dettinger, M. D.; Ralph, M.

2017-12-01

Atmospheric rivers (ARs) are long, narrow corridors of enhanced water vapor transport that are typically associated with extratropical cyclones. ARs can be beneficial and replenish water resources, be hazardous and cause damaging floods, or have a combination of hazardous and beneficial impacts. Thus, understanding hydrologic impacts of ARs can help to improve water reservoir management and enhance flood risk mitigation, especially in California where there is extremely large year-to-year variability in annual precipitation accumulations. At the continental scale, gridded hourly precipitation observations are used in this study to identify unique characteristics of precipitation events impacting the US west coast compared to other regions in the US; precipitation events are defined here as continuous periods of precipitation with at least 5 mm of accumulated precipitation. It is shown that on average, the US west coast receives the largest precipitation totals across the US; these extreme precipitation events are largely associated with the most persistent ARs. Within California, hourly precipitation observations from 200 sites are being analyzed to better understand distinct categories of ARs that dictate extreme precipitation in different regions of California. It is found that, on average, the north coast, northern Sierra, and the Transverse Ranges experience the largest precipitation events; north coast and northern Sierra precipitation events tend to be longer, whereas the Transverse Ranges generally experience higher maximum and event-averaged intensities. ARs contribute significantly to extreme precipitation events in all regions of California, particularly the north coast, northern Sierra, and the Transverse Ranges. ARs associated with extreme precipitation events across California are significantly more persistent and have higher integrated vapor transport intensities than those associated with non-extreme events. Composites of characteristics of ARs which

The Centennial Trends Greater Horn of Africa precipitation dataset.

PubMed

Funk, Chris; Nicholson, Sharon E; Landsfeld, Martin; Klotter, Douglas; Peterson, Pete; Harrison, Laura

2015-01-01

East Africa is a drought prone, food and water insecure region with a highly variable climate. This complexity makes rainfall estimation challenging, and this challenge is compounded by low rain gauge densities and inhomogeneous monitoring networks. The dearth of observations is particularly problematic over the past decade, since the number of records in globally accessible archives has fallen precipitously. This lack of data coincides with an increasing scientific and humanitarian need to place recent seasonal and multi-annual East African precipitation extremes in a deep historic context. To serve this need, scientists from the UC Santa Barbara Climate Hazards Group and Florida State University have pooled their station archives and expertise to produce a high quality gridded 'Centennial Trends' precipitation dataset. Additional observations have been acquired from the national meteorological agencies and augmented with data provided by other universities. Extensive quality control of the data was carried out and seasonal anomalies interpolated using kriging. This paper documents the CenTrends methodology and data.

The Centennial Trends Greater Horn of Africa precipitation dataset

USGS Publications Warehouse

Funk, Chris; Nicholson, Sharon E.; Landsfeld, Martin F.; Klotter, Douglas; Peterson, Pete J.; Harrison, Laura

2015-01-01

East Africa is a drought prone, food and water insecure region with a highly variable climate. This complexity makes rainfall estimation challenging, and this challenge is compounded by low rain gauge densities and inhomogeneous monitoring networks. The dearth of observations is particularly problematic over the past decade, since the number of records in globally accessible archives has fallen precipitously. This lack of data coincides with an increasing scientific and humanitarian need to place recent seasonal and multi-annual East African precipitation extremes in a deep historic context. To serve this need, scientists from the UC Santa Barbara Climate Hazards Group and Florida State University have pooled their station archives and expertise to produce a high quality gridded ‘Centennial Trends’ precipitation dataset. Additional observations have been acquired from the national meteorological agencies and augmented with data provided by other universities. Extensive quality control of the data was carried out and seasonal anomalies interpolated using kriging. This paper documents the CenTrends methodology and data.

A Global-Scale Examination of Monsoon-Related Precipitation.

NASA Astrophysics Data System (ADS)

Janowiak, John E.; Xie, Pingping

2003-12-01

A pentad version of the Global Precipitation Climatology Project global precipitation dataset is used to document the annual and interannual variations in precipitation over monsoon regions around the globe. An algorithm is described that determines objectively wet season onset and withdrawal for individual years, and this tool is used to examine the behavior of various characteristics of the major monsoon systems. The definition of onset and withdrawal are determined by examining the ramp-up and diminution of rainfall within the context of the climatological rainfall at each location. Also examined are interannual variations in onset and withdrawal and their relationship to rainy season precipitation accumulations. Changes in the distribution of “heavy” and “light” precipitation events are examined for years in which “abundant” and “poor” wet seasons are observed, and associations with variations in large-scale atmospheric general circulation features are also examined. In particular, some regions of the world have strong associations between wet season rainfall and global-scale patterns of 200-hPa streamfunction anomalies.

A multiple wavelet coherency method for temporal streamflow-precipitation-temperature relationships in 17 small catchments on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Yang, Y.; Liu, B.

2017-12-01

Climate change and human activities are two critical factors causing the dramatical variations of streamflow in the Yellow River Basin of China during the last several decades. More and more attention has been paid to the temporal relationships of streamflow with precipitation and temperature recently. The objective of the current study was to explore the contributions of precipitation and temperature to the temporal variations of streamflow on the Loess Plateau using a multiple wavelet coherency method. Annual streamflow during 1961-2013 for 17 small catchments were collected from the Yellow River Conservancy Commission and annual precipitation and temperature for each catchment were derived from the meteorological data at the national weather stations across the Loess Plateau through the China Meteorological Data Sharing Service System. An abrupt decrease was observed in the annual streamflow around year 2000 for any of the 17 catchments investigated, which was believed to be related with the extensive Grain for Green Project. According to bivariate wavelet coherences, however, annual streamflow showed strong temporal variations with annual precipitation at 8 out of the 17 catchments, where the percentage area of significant coherency (PASC) exceeded 50%. Especially in Weihe and Yiluohe catchments, the corresponding PASC were close to 100%, suggesting that annual precipitation change accounted for almost all the temporal streamflow variations. Compared to annual precipitation, the temporal correlation of temperature with streamflow was relatively small, as implied in the lower mean wavelet coherence (MWC) and PASC. Moreover, including temperature in addition to precipitation in the multiple wavelet coherency analysis failed to increase either MWC or PASC in any of the 17 catchments except for Qingjianhe and Qiushuihe catchments. It was indicated that for most catchments on the Loess Plateau, annual temperature was not significantly different from the red noise in

Local biomass burning is a dominant cause of the observed precipitation reduction in southern Africa

PubMed Central

Hodnebrog, Øivind; Myhre, Gunnar; Forster, Piers M.; Sillmann, Jana; Samset, Bjørn H.

2016-01-01

Observations indicate a precipitation decline over large parts of southern Africa since the 1950s. Concurrently, atmospheric concentrations of greenhouse gases and aerosols have increased due to anthropogenic activities. Here we show that local black carbon and organic carbon aerosol emissions from biomass burning activities are a main cause of the observed decline in southern African dry season precipitation over the last century. Near the main biomass burning regions, global and regional modelling indicates precipitation decreases of 20–30%, with large spatial variability. Increasing global CO2 concentrations further contribute to precipitation reductions, somewhat less in magnitude but covering a larger area. Whereas precipitation changes from increased CO2 are driven by large-scale circulation changes, the increase in biomass burning aerosols causes local drying of the atmosphere. This study illustrates that reducing local biomass burning aerosol emissions may be a useful way to mitigate reduced rainfall in the region. PMID:27068129

Time scales of biogeochemical and organismal responses to individual precipitation events

NASA Astrophysics Data System (ADS)

von Fischer, J. C.; Angert, A. L.; Augustine, D. J.; Brown, C.; Dijkstra, F. A.; Derner, J. D.; Hufbauer, R. A.; Fierer, N.; Milchunas, D. G.; Moore, J. C.; Steltzer, H.; Wallenstein, M. D.

2010-12-01

In temperate grasslands, spatial and intra-annual variability in the activity of plants and microbes are structured by patterns in the precipitation regime. While the effects of total annual precipitation have been well-explored, the ecological dynamics associated with individual precipitation events have not. Rainfall events induce a short-term pulse of soil respiration that may or may not be followed by stimulation of plant photosynthetic activity and growth. Because the underlying heterotrophic and autotrophic responses are interactive, respond over unique timescales and are sensitive to precipitation magnitude, it remains difficult to predict the hydrologic effects on net CO2 exchange. To develop a better mechanistic understanding of these processes, we conducted a synthetic, multi-investigator experiment to characterize the ecosystem responses to rainfall events of different sizes. Our work was conducted on the Shortgrass Steppe (SGS) LTER site over 7 days in June 2009, using 1cm and 2cm rainfall events, with controls and each treatment replicated 5 times in 2m x 2m plots. Our observations revealed both expected responses of plant activity and soil respiration, and surprising patterns in microbial enzyme activity and soil fauna population densities. Coupled with observed dynamics in 15N partitioning and kinetics, our findings provide empirical timescales for the complex ecological interactions that underlie the ecosystem responses to rainfall events. These results can be used to inform a new generation of ecosystem simulation models to more explicitly consider the time lags and interactions of different functional groups.

Changes in temperature and precipitation extremes observed in Modena, Italy

NASA Astrophysics Data System (ADS)

Boccolari, M.; Malmusi, S.

2013-03-01

Climate changes has become one of the most analysed subjects from researchers community, mainly because of the numerous extreme events that hit the globe. To have a better view of climate changes and trends, long observations time series are needed. During last decade a lot of Italian time series, concerning several surface meteorological variables, have been analysed and published. No one of them includes one of the longest record in Italy, the time series of the Geophysical Observatory of the University of Modena and Reggio Emilia. Measurements, collected since early 19th century, always in the same position, except for some months during the second world war, embrace daily temperature, precipitation amount, relative humidity, pressure, cloudiness and other variables. In this work we concentrated on the analysis of yearly and seasonal trends and climate extremes of temperature, both minimum and maximum, and precipitation time series, for the periods 1861-2010 and 1831-2010 respectively, in which continuous measurements are available. In general, our results confirm quite well those reported by IPCC and in many other studies over Mediterranean area. In particular, we found that minimum temperature has a non significant positive trend of + 0.1 °C per decade considering all the period, the value increases to 0.9 °C per decade for 1981-2010. For maximum temperature we observed a non significant + 0.1 °C trend for all the period, while + 0.8 °C for the last thirty years. On the other hand precipitation is decreasing, -6.3 mm per decade, considering all the analysed period, while the last thirty years are characterised by a great increment of 74.8 mm per decade. For both variables several climate indices have been analysed and they confirm what has been found for minimum and maximum temperatures and precipitation. In particular, during last 30 years frost days and ice days are decreasing, whereas summer days are increasing. During the last 30-year tropical nights

An assessment of mean annual precipitation in Rajasthan, India needed to maintain Mid-Holocene lakes

NASA Astrophysics Data System (ADS)

Gill, E.; Rajagopalan, B.; Molnar, P. H.

2013-12-01

Paleo-climate literature reports evidence of freshwater lakes over Rajasthan, a region of northwestern India, during the mid-Holocene (~6ka), where desert conditions prevail in present time. It's suggested that mid-Holocene temperatures were warmer, precipitation was nearly double current levels, and there was an enhanced La Niña-like state. While previous analyses infer the lakes were sustained by generally high precipitation and low evaporation, we provide a systematic analysis on the relevant energy budget quantities and the dynamic relationships between them. We have built a hydrological lake model to reconstruct lake levels throughout the Holocene. Model output is evaporation from the lake. Inputs are precipitation over the lake and catchment runoff, determined using precipitation, Preistley-Taylor evapotranspiration, interception and infiltration. Initial tests of the model have been completed with current climate conditions to ensure accurate behavior. Contemporary runs used station precipitation and temperature data [Rajeevan et al., 2006] for the region surrounding Lake Didwana (27°N 74°E). Digital elevation maps were used to compile lake bathymetry for Lake Didwana. Under current climate conditions, a full Lake Didwana (~ 9 m) empties over the first several years. While lake depth varies yearly, increasing with each monsoon season, variations following the initial decline are minimal (~ × 1.0 m). We ran the model with a 2000-year sequence of precipitation and temperature generated by resampling the observed weather sequences, with a suite of base line fractions of vegetation cover and increased precipitation, with solar insolation appropriate during the mid-Holocene period. Initial runs revealed that precipitation amount and percent of vegetated catchment area influence lake levels, but insolation alone does not. Incrementally changing precipitation (between current levels and a 75% increase) and percent of vegetated area (between 10-90%) reveals that

Extreme Precipitation and Emergency Room Visits for Influenza in Massachusetts: A Case-Crossover Analysis

EPA Science Inventory

BACKGROUND: Influenza peaks during the wintertime in temperate regions and during the annual rainy season in tropical regions – however reasons for the observed differences in disease ecology are poorly understood. We hypothesize that episodes of extreme precipitation also result...

Hydrological modelling of the Mabengnong catchment in the southeast Tibet with support of short term intensive precipitation observation

NASA Astrophysics Data System (ADS)

Wang, L.; Zhang, F.; Zhang, H.; Scott, C. A.; Zeng, C.; SHI, X.

2017-12-01

Precipitation is one of the crucial inputs for models used to better understand hydrological processes. In high mountain areas, it is a difficult task to obtain a reliable precipitation data set describing the spatial and temporal characteristic due to the limited meteorological observations and high variability of precipitation. This study carries out intensive observation of precipitation in a high mountain catchment in the southeast of the Tibet during July to August 2013. According to the rain gauges set up at different altitudes, it is found that precipitation is greatly influenced by altitude. The observed precipitation is used to depict the precipitation gradient (PG) and hourly distribution (HD), showing that the average duration is around 0.1, 0.8 and 6.0 hours and the average PG is 0.10, 0.28 and 0.26 mm/d/100m for trace, light and moderate rain, respectively. Based on the gridded precipitation derived from the PG and HD and the nearby Linzhi meteorological station at lower altitude, a distributed biosphere hydrological model based on water and energy budgets (WEB-DHM) is applied to simulate the hydrological processes. Beside the observed runoff, MODIS/Terra snow cover area (SCA) data, and MODIS/Terra land surface temperature (LST) data are also used for model calibration and validation. The resulting runoff, SCA and LST simulations are all reasonable. Sensitivity analyses indicate that runoff is greatly underestimated without considering PG, illustrating that short-term intensive precipitation observation contributes to improving hydrological modelling of poorly gauged high mountain catchments.

Precipitation estimates and comparison of satellite rainfall data to in situ rain gauge observations to further develop the watershed-modeling capabilities for the Lower Mekong River Basin

NASA Astrophysics Data System (ADS)

Dandridge, C.; Lakshmi, V.; Sutton, J. R. P.; Bolten, J. D.

2017-12-01

This study focuses on the lower region of the Mekong River Basin (MRB), an area including Burma, Cambodia, Vietnam, Laos, and Thailand. This region is home to expansive agriculture that relies heavily on annual precipitation over the basin for its prosperity. Annual precipitation amounts are regulated by the global monsoon system and therefore vary throughout the year. This research will lead to improved prediction of floods and management of floodwaters for the MRB. We compare different satellite estimates of precipitation to each other and to in-situ precipitation estimates for the Mekong River Basin. These comparisons will help us determine which satellite precipitation estimates are better at predicting precipitation in the MRB and will help further our understanding of watershed-modeling capabilities for the basin. In this study we use: 1) NOAA's PERSIANN daily 0.25° precipitation estimate Climate Data Record (CDR), 2) NASA's Tropical Rainfall Measuring Mission (TRMM) daily 0.25° estimate, and 3) NASA's Global Precipitation Measurement (GPM) daily 0.1 estimate and 4) 488 in-situ stations located in the lower MRB provide daily precipitation estimates. The PERSIANN CDR precipitation estimate was able to provide the longest data record because it is available from 1983 to present. The TRMM precipitation estimate is available from 2000 to present and the GPM precipitation estimates are available from 2015 to present. It is for this reason that we provide several comparisons between our precipitation estimates. Comparisons were done between each satellite product and the in-situ precipitation estimates based on geographical location and date using the entire available data record for each satellite product for daily, monthly, and yearly precipitation estimates. We found that monthly PERSIANN precipitation estimates were able to explain up to 90% of the variability in station precipitation depending on station location.

Lightning and Precipitation: Observational Analysis of LIS and PR

NASA Technical Reports Server (NTRS)

Adamo, C.; Solomon, R.; Goodman, S.; Dietrich, S.; Mugnai, A.

2003-01-01

Lightning flash rate can identify areas of convective rainfall when the storms are dominated by ice-phase precipitation. Modeling and observational studies indicate that cloud electrification and microphysics are very closely related and it is of great interest to understand the relationship between lightning and cloud microphysical quantities. Analyzing data from the Lightning Image Sensor (LIS) and the Precipitation Radar (PR), we show a quantitative relationship between microphysical characteristics of thunderclouds and lightning flash rate. We have performed a complete analysis of all data available over the Mediterranean during the TRMM mission and show a range of reflective profiles as a function of lightning activity for both convective and stratiform regimes as well as seasonal variations. Due to the increasing global coverage of lightning detection networks, this kind of study can used to extend the knowledge about thunderstorms and discriminate between different regimes in regions where radar measurements are readilly available.

Comparison of methods for non-stationary hydrologic frequency analysis: Case study using annual maximum daily precipitation in Taiwan

NASA Astrophysics Data System (ADS)

Chen, Po-Chun; Wang, Yuan-Heng; You, Gene Jiing-Yun; Wei, Chih-Chiang

2017-02-01

Future climatic conditions likely will not satisfy stationarity assumption. To address this concern, this study applied three methods to analyze non-stationarity in hydrologic conditions. Based on the principle of identifying distribution and trends (IDT) with time-varying moments, we employed the parametric weighted least squares (WLS) estimation in conjunction with the non-parametric discrete wavelet transform (DWT) and ensemble empirical mode decomposition (EEMD). Our aim was to evaluate the applicability of non-parameter approaches, compared with traditional parameter-based methods. In contrast to most previous studies, which analyzed the non-stationarity of first moments, we incorporated second-moment analysis. Through the estimation of long-term risk, we were able to examine the behavior of return periods under two different definitions: the reciprocal of the exceedance probability of occurrence and the expected recurrence time. The proposed framework represents an improvement over stationary frequency analysis for the design of hydraulic systems. A case study was performed using precipitation data from major climate stations in Taiwan to evaluate the non-stationarity of annual maximum daily precipitation. The results demonstrate the applicability of these three methods in the identification of non-stationarity. For most cases, no significant differences were observed with regard to the trends identified using WLS, DWT, and EEMD. According to the results, a linear model should be able to capture time-variance in either the first or second moment while parabolic trends should be used with caution due to their characteristic rapid increases. It is also observed that local variations in precipitation tend to be overemphasized by DWT and EEMD. The two definitions provided for the concept of return period allows for ambiguous interpretation. With the consideration of non-stationarity, the return period is relatively small under the definition of expected

Evaluation of NASA GISS post-CMIP5 single column model simulated clouds and precipitation using ARM Southern Great Plains observations

NASA Astrophysics Data System (ADS)

Zhang, Lei; Dong, Xiquan; Kennedy, Aaron; Xi, Baike; Li, Zhanqing

2017-03-01

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies (GISS) Model E2 atmospheric general circulation model (GCM; post-CMIP5, hereafter P5). In this study, single column model (SCM P5) simulated cloud fractions (CFs), cloud liquid water paths (LWPs) and precipitation were compared with Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) groundbased observations made during the period 2002-08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase (10%-20%) but precipitation increased significantly (56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.

Precipitation regimes over central Greenland inferred from 5 years of ICECAPS observations

NASA Astrophysics Data System (ADS)

Pettersen, Claire; Bennartz, Ralf; Merrelli, Aronne J.; Shupe, Matthew D.; Turner, David D.; Walden, Von P.

2018-04-01

A novel method for classifying Arctic precipitation using ground based remote sensors is presented. Using differences in the spectral variation of microwave absorption and scattering properties of cloud liquid water and ice, this method can distinguish between different types of snowfall events depending on the presence or absence of condensed liquid water in the clouds that generate the precipitation. The classification reveals two distinct, primary regimes of precipitation over the Greenland Ice Sheet (GIS): one originating from fully glaciated ice clouds and the other from mixed-phase clouds. Five years of co-located, multi-instrument data from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit (ICECAPS) are used to examine cloud and meteorological properties and patterns associated with each precipitation regime. The occurrence and accumulation of the precipitation regimes are identified and quantified. Cloud and precipitation observations from additional ICECAPS instruments illustrate distinct characteristics for each regime. Additionally, reanalysis products and back-trajectory analysis show different synoptic-scale forcings associated with each regime. Precipitation over the central GIS exhibits unique microphysical characteristics due to the high surface elevations as well as connections to specific large-scale flow patterns. Snowfall originating from the ice clouds is coupled to deep, frontal cloud systems advecting up and over the southeast Greenland coast to the central GIS. These events appear to be associated with individual storm systems generated by low pressure over Baffin Bay and Greenland lee cyclogenesis. Snowfall originating from mixed-phase clouds is shallower and has characteristics typical of supercooled cloud liquid water layers, and slowly propagates from the south and southwest of Greenland along a quiescent flow above the GIS.

An Update on Oceanic Precipitation Rate and its Zonal Distribution in Light of Advanced Observations from Space

NASA Technical Reports Server (NTRS)

Behrangi, Ali; Stephens, Graeme; Adler, Robert F.; Huffman, George J.; Lambrigsten, Bjorn; Lebstock, Matthew

2014-01-01

This study contributes to the estimation of the global mean and zonal distribution of oceanic precipitation rate using complementary information from advanced precipitation measuring sensors and provides an independent reference to assess current precipitation products. Precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and CloudSat cloud profiling radar (CPR) were merged, as the two complementary sensors yield an unprecedented range of sensitivity to quantify rainfall from drizzle through the most intense rates. At higher latitudes, where TRMM PR does not exist, precipitation estimates from Aqua's Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) complemented CloudSat CPR to capture intense precipitation rates. The high sensitivity of CPR allows estimation of snow rate, an important type of precipitation at high latitudes, not directly observed in current merged precipitation products. Using the merged precipitation estimate from the CloudSat, TRMM, and Aqua platforms (this estimate is abbreviated to MCTA), the authors' estimate for 3-yr (2007-09) nearglobal (80degS-80degN) oceanic mean precipitation rate is approx. 2.94mm/day. This new estimate of mean global ocean precipitation is about 9% higher than that of the corresponding Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) value (2.68mm/day) and about 4% higher than that of the Global Precipitation Climatology Project (GPCP; 2.82mm/day). Furthermore, MCTA suggests distinct differences in the zonal distribution of precipitation rate from that depicted in GPCPand CMAP, especially in the Southern Hemisphere.

Evaluation of CMIP5 models for projection of future precipitation change in Bornean tropical rainforests

NASA Astrophysics Data System (ADS)

Hussain, Mubasher; Yusof, Khamaruzaman Wan; Mustafa, Muhammad Raza Ul; Mahmood, Rashid; Jia, Shaofeng

2017-10-01

We present the climate change impact on the annual and seasonal precipitation over Rajang River Basin (RRB) in Sarawak by employing a set of models from Coupled Model Intercomparison Project Phase 5 (CMIP5). Based on the capability to simulate the historical precipitation, we selected the three most suitable GCMs (i.e. ACCESS1.0, ACCESS1.3, and GFDL-ESM2M) and their mean ensemble (B3MMM) was used to project the future precipitation over the RRB. Historical (1976-2005) and future (2011-2100) precipitation ensembles of B3MMM were used to perturb the stochastically generated future precipitation over 25 rainfall stations in the river basin. The B3MMM exhibited a significant increase in precipitation during 2080s, up to 12 and 8% increase in annual precipitation over upper and lower RRB, respectively, under RCP8.5, and up to 7% increase in annual precipitation under RCP4.5. On the seasonal scale, Mann-Kendal trend test estimated statistically significant positive trend in the future precipitation during all seasons; except September to November when we only noted significant positive trend for the lower RRB under RCP4.5. Overall, at the end of the twenty-first century, an increase in annual precipitation is noteworthy in the whole RRB, with 7 and 10% increase in annual precipitation under the RCP4.5 and the RCP8.5, respectively.

Spatiotemporal variability of temperature and precipitation in Gansu Province (Northwest China) during 1951-2015

NASA Astrophysics Data System (ADS)

Wen, Xiaohu; Wu, Xiaoqing; Gao, Meng

2017-11-01

Climate change is potentially challenging the sustainable development in many parts of the world, especially the semi-arid and arid regions on the earth. Northwest China (NWC) is one of the most arid areas in East Asia, and Gansu Province is located at the important climate transition zone in NWC. Spatiotemporal variability of both temperature and precipitation were analyzed based on the daily observation dataset at 29 meteorological stations over Gansu during 1951-2015. The Mann-Kendall trend test was utilized to detect monotonic trends in extreme climate indices, mean temperature, and total precipitation. The results revealed that the warming trends were statistically significant at most stations in Gansu, especially at the high altitude stations; however, the change trends in annual and seasonal precipitation over Gansu were not significant as expected. Furthermore, the 29 stations were spatially grouped using hierarchical clustering method. The regional-averaged temperature anomalies also showed a significant warming trend beginning at the end of 1970s. Spatial variations were also observed in the annual and seasonal precipitation over Gansu. In general, precipitation increased in the western part of Gansu while decreased in the eastern part. Additionally, the wavelet analyses revealed that the teleconnection between large scale circulation and summer precipitation varied not only from region to region, but also was different at different time scale and different time periods. Analysis of large-scale atmospheric circulation changes showed that a strengthening anticyclonic circulation, increasing geopotential height and rapid warming over the Eurasian continent were considered to be attributable to climate change in Gansu and even in NWC.

Reassessing the role of temperature in precipitation oxygen isotopes across the eastern and central United States through weekly precipitation-day data

NASA Astrophysics Data System (ADS)

Akers, Pete D.; Welker, Jeffrey M.; Brook, George A.

2017-09-01

Air temperature is correlated with precipitation oxygen isotope (δ18Oprcp) variability for much of the eastern and central United States, but the nature of this δ18Oprcp-temperature relationship is largely based on data coarsely aggregated at a monthly resolution. We constructed a database of 6177 weeks of isotope and precipitation-day air temperature data from 25 sites to determine how more precise data change our understanding of this classic relationship. Because the δ18Oprcp-temperature relationship is not perfectly linear, trends in the regression residuals suggest the influence of additional environmental factors such as moisture recycling and extratropical cyclone interactions. Additionally, the temporal relationships between δ18Oprcp and temperature observed in the weekly data at individual sites can explain broader spatial patterns observed across the study region. For 20 of 25 sites, the δ18Oprcp-temperature relationship slope is higher for colder precipitation than for warmer precipitation. Accordingly, northern and western sites with relatively more cold precipitation events have steeper overall relationships with higher slope values than southeastern sites that have more warm precipitation events. Although the magnitude of δ18Oprcp variability increases to the north and west, the fraction of δ18Oprcp variability explained by temperature increases due to wider annual temperature ranges, producing stronger relationships in these regions. When our δ18Oprcp-temperature data are grouped by month, we observe significant variations in the relationship from month to month. This argues against a principal causative role for temperature and suggests the existence of an alternative environmental control on δ18Oprcp values that simply covaries seasonally with temperature.

Evaluating Precipitation Observed in Complex Terrain During GPM Field Campaigns with the SIMBA Data-Fusion Tool

NASA Astrophysics Data System (ADS)

Wingo, S. M.; Petersen, W. A.; Gatlin, P. N.; Marks, D. A.; Wolff, D. B.; Pabla, C. S.

2017-12-01

The versatile SIMBA (System for Integrating Multi-platform data to Build the Atmospheric column) precipitation data-fusion framework produces an atmospheric column data product with multi-platform observations set into a common 3-D grid, affording an efficient starting point for multi-sensor comparisons and analysis that can be applied to any region. Supported data sources include: ground-based scanning and profiling radars (S-, X-, Ku-, K-, and Ka-band), multiple types of disdrometers and rain gauges, the GPM Core Observatory's Microwave Imager (GMI, 10-183 GHz) and Dual-frequency Precipitation Radar (DPR, Ka/Ku-band), as well as thermodynamic soundings and the Multi-Radar/Multi-Sensor QPE product. SIMBA column data files provide a unique way to evaluate the complete vertical profile of precipitation. Two post-launch (GPM Core in orbit) field campaigns focused on different facets of the GPM mission: the Olympic Mountains Experiment (OLYMPEX) was geared toward winter season (November-February) precipitation in Pacific frontal systems and their transition from the coastal to mountainous terrain of northwest Washington, while the Integrated Precipitation and Hydrology Experiment (IPHEx) sampled warm season (April-June) precipitation and supported hydrologic applications in the southern Appalachians and eastern North Carolina. Both campaigns included multiple orographic precipitation enhancement episodes. SIMBA column products generated for select OLYMPEX and IPHEx events will be used to evaluate spatial variability and vertical profiles of precipitation and drop size distribution parameters derived and/or observed by space- and ground-based sensors. Results will provide a cursory view of how well the space-based measurements represent what is observed from the ground below and an indication to how the terrain in both regions impacts the characteristics of precipitation within the column and reaching the ground.

Evaluating Precipitation Observed in Complex Terrain During GPM Field Campaigns with the SIMBA Data-Fusion Tool

NASA Astrophysics Data System (ADS)

Wingo, S. M.; Petersen, W. A.; Gatlin, P. N.; Marks, D. A.; Wolff, D. B.; Pabla, C. S.

2016-12-01

The versatile SIMBA (System for Integrating Multi-platform data to Build the Atmospheric column) precipitation data-fusion framework produces an atmospheric column data product with multi-platform observations set into a common 3-D grid, affording an efficient starting point for multi-sensor comparisons and analysis that can be applied to any region. Supported data sources include: ground-based scanning and profiling radars (S-, X-, Ku-, K-, and Ka-band), multiple types of disdrometers and rain gauges, the GPM Core Observatory's Microwave Imager (GMI, 10-183 GHz) and Dual-frequency Precipitation Radar (DPR, Ka/Ku-band), as well as thermodynamic soundings and the Multi-Radar/Multi-Sensor QPE product. SIMBA column data files provide a unique way to evaluate the complete vertical profile of precipitation. Two post-launch (GPM Core in orbit) field campaigns focused on different facets of the GPM mission: the Olympic Mountains Experiment (OLYMPEX) was geared toward winter season (November-February) precipitation in Pacific frontal systems and their transition from the coastal to mountainous terrain of northwest Washington, while the Integrated Precipitation and Hydrology Experiment (IPHEx) sampled warm season (April-June) precipitation and supported hydrologic applications in the southern Appalachians and eastern North Carolina. Both campaigns included multiple orographic precipitation enhancement episodes. SIMBA column products generated for select OLYMPEX and IPHEx events will be used to evaluate spatial variability and vertical profiles of precipitation and drop size distribution parameters derived and/or observed by space- and ground-based sensors. Results will provide a cursory view of how well the space-based measurements represent what is observed from the ground below and an indication to how the terrain in both regions impacts the characteristics of precipitation within the column and reaching the ground.

[Responses of normalized difference vegetation index (NDVI) to precipitation changes on the grassland of Tibetan Plateau from 2000 to 2015.

PubMed

Wang, Zhi Peng; Zhang, Xian Zhou; He, Yong Tao; Li, Meng; Shi, Pei Li; Zu, Jia Xing; Niu, Ben

2018-01-01

Precipitation change is an important factor in the inter-annual variation of grassland growth on the Tibetan Plateau. The total amount, distribution pattern and concentration time are three basic characteristics of precipitation change. The temporal and spatial characteristics of precipitation change were analyzed based on climate data of 145 meteorological stations on the Tibetan Plateau and nearby areas from 2000 to 2015. The total precipitation amount was characterized by annual precipitation, distribution pattern of precipitation during the year was characterized by improved precipitation concentration index (PCI), and precipitation centroid (PC) was defined to indicate the change in precipitation concentrated time. To better illustrate the response of grassland to precipitation change, vegetation growth status was characterized by the maximum value of normalized difference vegetation index (NDVI max ). Results indicated that the annual precipitation and PCI had an apparent gradient across the whole plateau and the latest PC occurred in the southern plateau. NDVI max of alpine shrub grassland was significantly correlated with the change of PCI,increased with even distribution of precipitation during growth period, and limited by the total annual precipitation. Alpine meadow did not show significantly correlations with these three indices. The inter-annual variability of NDVI max of steppe was controlled by both PCI and PC. NDVI max of alpine desert grassland was mainly controlled by annual precipitation. In addition to annual total amount of precipitation, the distribution characteristics of precipitation should be further considered when the influence of precipitation change on different types of vegetation on the Qinghai Tibet Plateau was studied.

Status of NASA Satellite, Field Observations, and Numerical Modeling Addressing the Impact of Urbanization on Short and Long Term Precipitation Variability

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Manyin, Michael; Burian, Steve; Garza, Carlos

2003-01-01

There is renewed interest in the impacts of urbanization on global change as witnessed by special sessions at the Fall AGU and Annual AMS meeting. A comprehensive satellite, modeling, and field campaign program is underway to assess the impact of urbanization on precipitation.

Global Precipitation Estimates from Cross-Track Passive Microwave Observations Using a Physically-Based Retrieval Scheme

NASA Technical Reports Server (NTRS)

Kidd, Chris; Matsui, Toshi; Chern, Jiundar; Mohr, Karen; Kummerow, Christian; Randel, Dave

2015-01-01

The estimation of precipitation across the globe from satellite sensors provides a key resource in the observation and understanding of our climate system. Estimates from all pertinent satellite observations are critical in providing the necessary temporal sampling. However, consistency in these estimates from instruments with different frequencies and resolutions is critical. This paper details the physically based retrieval scheme to estimate precipitation from cross-track (XT) passive microwave (PM) sensors on board the constellation satellites of the Global Precipitation Measurement (GPM) mission. Here the Goddard profiling algorithm (GPROF), a physically based Bayesian scheme developed for conically scanning (CS) sensors, is adapted for use with XT PM sensors. The present XT GPROF scheme utilizes a model-generated database to overcome issues encountered with an observational database as used by the CS scheme. The model database ensures greater consistency across meteorological regimes and surface types by providing a more comprehensive set of precipitation profiles. The database is corrected for bias against the CS database to ensure consistency in the final product. Statistical comparisons over western Europe and the United States show that the XT GPROF estimates are comparable with those from the CS scheme. Indeed, the XT estimates have higher correlations against surface radar data, while maintaining similar root-mean-square errors. Latitudinal profiles of precipitation show the XT estimates are generally comparable with the CS estimates, although in the southern midlatitudes the peak precipitation is shifted equatorward while over the Arctic large differences are seen between the XT and the CS retrievals.

Sub-annual paleoenvironmental information evaluated from intensity variations of fluorescent annual layers in a stalagmite from Ryuo-do Cave, Nagasaki Prefecture, western Japan

NASA Astrophysics Data System (ADS)

Sasaki, Hana; Onishi, Yuri; Ishihara, Yoshiro; Yoshimura, Kazuhisa

2017-04-01

vary stratigraphically, and multiple types of fluorescence intensity pattern are observed in the stalagmite. When the co-precipitation of FA is governed by the hiatus model, it is suggested that a gradual increase in the annual layers will result from a large accumulation of calcite after the annual peak in the FA concentration, whereas there will be a gradual decrease if the main growth occurs before the annual peak in FA concentration. However, in the case of the PC model, a gradually increasing type of pattern is formed if the main growth occurs before the annual peak in FA concentration, and a gradually decreasing type is formed if the main growth occurs afterwards. If the annual peak of FA concentration occurs several months after high summer, it is suggested that intervals showing a gradually increasing type were formed in winter, and intervals showing a gradually decreasing type were formed in the early summer, in the case of the hiatus model. In the case of PC model, the seasons are reversed. In the climatic environment around the Ryuo-do Cave, the growth rates of stalagmites are affected by cave air circulation in winter and by rainfall (rainy season) in early summer.

Arctic daily temperature and precipitation extremes: Observed and simulated physical behavior

NASA Astrophysics Data System (ADS)

Glisan, Justin Michael

Simulations using a six-member ensemble of Pan-Arctic WRF (PAW) were produced on two Arctic domains with 50-km resolution to analyze precipitation and temperature extremes for various periods. The first study used a domain developed for the Regional Arctic Climate Model (RACM). Initial simulations revealed deep atmospheric circulation biases over the northern Pacific Ocean, manifested in pressure, geopotential height, and temperature fields. Possible remedies to correct these large biases, such as modifying the physical domain or using different initial/boundary conditions, were unsuccessful. Spectral (interior) nudging was introduced as a way of constraining the model to be more consistent with observed behavior. However, such control over numerical model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events, since the nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes---what is the minimum spectral nudging needed to correct biases while not limiting the simulation of extreme events? To determine this, we use varying degrees of spectral nudging, using WRF's standard nudging as a reference point during January and July 2007. Results suggest that there is a marked lack of sensitivity to varying degrees of nudging. Moreover, given that nudging is an artificial forcing applied in the model, an important outcome of this work is that nudging strength apparently can be considerably smaller than WRF's standard strength and still produce reliable simulations. In the remaining studies, we used the same PAW setup to analyze daily precipitation extremes simulated over a 19-year period on the CORDEX Arctic domain for winter and summer. We defined these seasons as the three-month period leading up to and including the climatological sea ice maximum and minimum, respectively. Analysis focused on four North American regions defined using

Climatic driving forces in inter-annual variation of global FPAR

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Liu, Liangyun; Yang, Xiaohua; Zhou, Bin

2012-09-01

Fraction of Absorbed Photosynthetically Active Radiation (FPAR) characterizes vegetation canopy functioning and its energy absorption capacity. In this paper, we focus on climatic driving forces in inter-annual variation of global FPAR from 1982 to 2006 by Global Historical Climatology Network (GHCN-Monthly) data. Using FPAR-Simple Ratio Vegetation Index (SR) relationship, Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) was used to estimate FPAR at the global scale. The correlation between inter-annual variation of FPAR and temperature, precipitation derived from GHCN-Monthly was examined, during the periods of March-May (MAM), June-August (JJA), September-November (SON), and December-February (DJF) over from 1982 to 2006. The analysis of climatic influence on global FPAR revealed the significant correlation with temperature and precipitation in some meteorological stations area, and a more significant correlation with precipitation was found than which with temperature. Some stations in the regions between 30° N and 60° N and around 30° S in South America, where the annual FPAR variation showed a significant positive correlation with temperature (P < 0.01 or P < 0.05) during MAM, SON, and DJF, as well as in Europe during MAM and SON period. A negative correlation for more stations was observed during JJA. For precipitation, there were many stations showed a significant positive correlation with inter-annual variation of global FPAR (P < 0.01 or P < 0.05), especially for the tropical rainfall forest of Africa and Amazon during the dry season of JJA and SON.

Evaluation of multiple forcing data sets for precipitation and shortwave radiation over major land areas of China

NASA Astrophysics Data System (ADS)

Yang, Fan; Lu, Hui; Yang, Kun; He, Jie; Wang, Wei; Wright, Jonathon S.; Li, Chengwei; Han, Menglei; Li, Yishan

2017-11-01

Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Several global and regional forcing data sets currently provide historical estimates of these two variables over China, including the Global Land Data Assimilation System (GLDAS), the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the China Meteorological Forcing Dataset (CMFD). The CN05.1 precipitation data set, a gridded analysis based on CMA gauge observations, also provides high-resolution historical precipitation data for China. In this study, we present an intercomparison of precipitation and shortwave radiation data from CN05.1, CMFD, CLDAS and GLDAS during 2008-2014. We also validate all four data sets against independent ground station observations. All four forcing data sets capture the spatial distribution of precipitation over major land areas of China, although CLDAS indicates smaller annual-mean precipitation amounts than CN05.1, CMFD or GLDAS. Time series of precipitation anomalies are largely consistent among the data sets, except for a sudden decrease in CMFD after August 2014. All forcing data indicate greater temporal variations relative to the mean in dry regions than in wet regions. Validation against independent precipitation observations provided by the Ministry of Water Resources (MWR) in the middle and lower reaches of the Yangtze River indicates that CLDAS provides the most realistic estimates of spatiotemporal variability in precipitation in this region. CMFD also performs well with respect to annual mean precipitation, while GLDAS fails to accurately capture much of the spatiotemporal variability and CN05.1 contains significant high biases relative to the MWR observations. Estimates of shortwave radiation from CMFD are largely consistent with station observations, while CLDAS and GLDAS greatly overestimate shortwave radiation. All three forcing data sets capture the key features of the

Ionospheric footprint of magnetosheathlike particle precipitation observed by an incoherent scatter radar

NASA Technical Reports Server (NTRS)

Watermann, Jurgen; Lummerzheim, Dirk; De La Beaujardiere, Odile; Newell, Patrick T.; Rich, Frederic J.

1994-01-01

We have examined Sondrestrom incoherent scatter radar observations of ionospheric plasma density and temperature distributions and measurements of F region ion drifts that were made during a prenoon pass of the Defense Meteorological Satellite Program (DMSP)-F7 satellite through the radar field of view. The spacecraft traversed a region of intense electron precipitation with a characteristic energy below approximately 200 eV. Particles with such low characteristic energies are believed to be directly or indirectly of magnetosheath origin. The precipitation region had a width about 2 deg invariant latitude and covered the low-latitude boundary layer (LLBL), the cusp, and the equatorward section of the plasma mantle (PM). The corotating radar observed a patch of enhanced electron density and elevated electron temperature in the F2 region between about 10.5 and 12 magnetic local time in the same invariant latitude range where DMSP-F7 detected the soft-electron flux. The ion drift pattern, also obtained by radar, shows that it is unlikely that the plasma patch was produced by solar radiation and advected into the radar field of view. We suggest that the radar observed modifications of the ionospheric plasma distribution, which resulted from direct entry of magnetosheath electrons into the magnetosphere and down to ionospheric altitudes. Model calculations of the ionospheric response to the observed electron precipitation support our interpretation. The spectral characteristics of the electron flux in the LLBL, cusp, and equatorward section of the PM were in this case too similar to allow to distinguish between them by using incoherent scatter radar measurements only.

Application of Observed Precipitation in NCEP Global and Regional Data Assimilation Systems, Including Reanalysis and Land Data Assimilation

NASA Astrophysics Data System (ADS)

Mitchell, K. E.

2006-12-01

The Environmental Modeling Center (EMC) of the National Centers for Environmental Prediction (NCEP) applies several different analyses of observed precipitation in both the data assimilation and validation components of NCEP's global and regional numerical weather and climate prediction/analysis systems (including in NCEP global and regional reanalysis). This invited talk will survey these data assimilation and validation applications and methodologies, as well as the temporal frequency, spatial domains, spatial resolution, data sources, data density and data quality control in the precipitation analyses that are applied. Some of the precipitation analyses applied by EMC are produced by NCEP's Climate Prediction Center (CPC), while others are produced by the River Forecast Centers (RFCs) of the National Weather Service (NWS), or by automated algorithms of the NWS WSR-88D Radar Product Generator (RPG). Depending on the specific type of application in data assimilation or model forecast validation, the temporal resolution of the precipitation analyses may be hourly, daily, or pentad (5-day) and the domain may be global, continental U.S. (CONUS), or Mexico. The data sources for precipitation include ground-based gauge observations, radar-based estimates, and satellite-based estimates. The precipitation analyses over the CONUS are analyses of either hourly, daily or monthly totals of precipitation, and they are of two distinct types: gauge-only or primarily radar-estimated. The gauge-only CONUS analysis of daily precipitation utilizes an orographic-adjustment technique (based on the well-known PRISM precipitation climatology of Oregon State University) developed by the NWS Office of Hydrologic Development (OHD). The primary NCEP global precipitation analysis is the pentad CPC Merged Analysis of Precipitation (CMAP), which blends both gauge observations and satellite estimates. The presentation will include a brief comparison between the CMAP analysis and other global

Annual nitrate drawdown observed by SOCCOM profiling floats and the relationship to annual net community production

NASA Astrophysics Data System (ADS)

Johnson, Kenneth S.; Plant, Joshua N.; Dunne, John P.; Talley, Lynne D.; Sarmiento, Jorge L.

2017-08-01

Annual nitrate cycles have been measured throughout the pelagic waters of the Southern Ocean, including regions with seasonal ice cover and southern hemisphere subtropical zones. Vertically resolved nitrate measurements were made using in situ ultraviolet spectrophotometer (ISUS) and submersible ultraviolet nitrate analyzer (SUNA) optical nitrate sensors deployed on profiling floats. Thirty-one floats returned 40 complete annual cycles. The mean nitrate profile from the month with the highest winter nitrate minus the mean profile from the month with the lowest nitrate yields the annual nitrate drawdown. This quantity was integrated to 200 m depth and converted to carbon using the Redfield ratio to estimate annual net community production (ANCP) throughout the Southern Ocean south of 30°S. A well-defined, zonal mean distribution is found with highest values (3-4 mol C m-2 yr-1) from 40 to 50°S. Lowest values are found in the subtropics and in the seasonal ice zone. The area weighted mean was 2.9 mol C m-2 yr-1 for all regions south of 40°S. Cumulative ANCP south of 50°S is 1.3 Pg C yr-1. This represents about 13% of global ANCP in about 14% of the global ocean area.