Comparison of Precipitation from Gauge and Tropical Rainfall Measurement Mission (TRMM) for River Basins of India

NASA Astrophysics Data System (ADS)

Mondal, A.; Chandniha, S. K.; Lakshmi, V.; Kundu, S.; Hashemi, H.

2017-12-01

This study compares the monthly precipitation from the gridded rain gauge data collected by India Meteorological Department (IMD) and the retrievals from the Tropical Rainfall Measurement Mission (TRMM) for the river basins of India using the TRMM Multisatellite Precipitation Analysis (TMPA) version 7 (V7). The IMD and TMPA datasets have the same spatial resolution (0.25°×0.25°) and extend from 1998 to 2013. The TRMM data accuracy for the river basins is assessed by comparison with IMD using root mean square error (RMSE), normalized mean square error (NMSE), Nash-Sutcliffe coefficient (NASH) and correlation coefficient (CC) methods. The Mann-Kendall (MK) and modified Mann-Kendall (MMK) tests have been applied for analyzing the data trend, and the change has been detected by Sen's Slope using both data sets for annual and seasonal time periods. The change in intensity of precipitation is estimated by percentage for comparing actual differences in various river basins. Variation in precipitation is high (>100 mm represents >15% of average annual precipitation) in Brahmaputra, rivers draining into Myanmar (RDM), rivers draining into Bangladesh (RDB), east flowing rivers between Mahanadi and Godavari (EMG), east flowing rivers between Pennar and Cauvery (EPC), Cauvery and Tapi. The NASH and CC values vary between 0.80 to 0.98 and 0.87 to 0.99 in all river basins except area of north Ladakh not draining into Indus (NLI) and east flowing rivers south of Cauvery (ESC), while RMSE and NMSE vary from 15.95 to 101.68 mm and 2.66 to 58.38 mm, respectively. The trends for TMPA and IMD datasets from 1998 to 2013 are quite similar in MK (except 4 river basins) and MMK (except 3 river basins). The estimated results imply that the TMPA precipitation show good agreement and can be used in climate studies and hydrological simulations in locations/river basins where the number of rain gauge stations is not adequate to quantify the spatial variability of precipitation. Keywords: Precipitation data comparison, IMD, TRMM, river basins, Mann-Kendall test

Development of Sub-Daily Intensity Duration Frequency (IDF) Curves for Major Urban Areas in India

NASA Astrophysics Data System (ADS)

Ali, H.; Mishra, V.

2014-12-01

Extreme precipitation events disrupt urban transportation and cause enormous damage to infrastructure. Urban areas are fast responding catchments due to significant impervious surface. Stormwater designs based on daily rainfall data provide inadequate information. We, therefore, develop intensity-duration-frequency curves using sub-daily (1 hour to 12 hour) rainfall data for 57 major urban areas in India. While rain gage stations data from urban areas are most suitable, but stations are unevenly distributed and their data have gaps and inconsistencies. Therefore, we used hourly rainfall data from the Modern Era Retrospective-analysis for Research and Applications (MERRA), which provides a long term data (1979 onwards). Since reanalysis products have uncertainty associated with them we need to enhance their accuracy before their application. We compared daily rain gage station data obtained from Global Surface Summary of Day Data (GSOD) available for 65 stations for the period of 2000-2010 with gridded daily rainfall data provided by Indian Meteorological Department (IMD). 3-hourly data from NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) were aggregated to daily for comparison with GSOD station data . TMPA is found to be best correlated with GSOD data. We used TMPA data to correct MERRA's hourly precipitation, which were applied to develop IDF curves. We compared results with IDF curves from empirical methods and found substantial disparities in the existing stormwater designs in India.

Assessment of satellite rainfall products over the Andean plateau

NASA Astrophysics Data System (ADS)

Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

2016-01-01

Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a negative bias becomes positive for GSMaP. TMPA-3B42 Adjusted (Adj) version 7 demonstrates the best overall agreement with gauges in terms of correlation, rain rate distribution and bias. However, PERSIANN-Adj's bias in the southern part of the domain is very low.

A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis K.; AghaKouchak, Amir; Liu, Zhong; Norouzi, Hamidreza; Pai, D. S.

2018-01-01

Following the launch of the Global Precipitation Measurement (GPM) Core Observatory, two advanced high resolution multi-satellite precipitation products namely, Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) version 6 are released. A critical evaluation of these newly released precipitation data sets is very important for both the end users and data developers. This study provides a comprehensive assessment of IMERG research product and GSMaP estimates over India at a daily scale for the southwest monsoon season (June to September 2014). The GPM-based precipitation products are inter-compared with widely used TRMM Multi-satellite Precipitation Analysis (TMPA), and gauge-based observations over India. Results show that the IMERG estimates represent the mean monsoon rainfall and its variability more realistically than the gauge-adjusted TMPA and GSMaP data. However, GSMaP has relatively smaller root-mean-square error than IMERG and TMPA, especially over the low mean rainfall regimes and along the west coast of India. An entropy-based approach is employed to evaluate the distributions of the selected precipitation products. The results indicate that the distribution of precipitation in IMERG and GSMaP has been improved markedly, especially for low precipitation rates. IMERG shows a clear improvement in missed and false precipitation bias over India. However, all the three satellite-based rainfall estimates show exceptionally smaller correlation coefficient, larger RMSE, larger negative total bias and hit bias over the northeast India where precipitation is dominated by orographic effects. Similarly, the three satellite-based estimates show larger false precipitation over the southeast peninsular India which is a rain-shadow region. The categorical verification confirms that these satellite-based rainfall estimates have difficulties in detection of rain over the southeast peninsula and northeast India. These preliminary results need to be confirmed in other monsoon seasons in future studies when the fully GPM-based IMERG retrospectively processed data prior to 2014 are available.

Comparison of Diurnal Characteristics of GPM-IMERG Precipitation Products with Hourly Rain Gauge Observations and TRMM-TMPA Products over Mainland China

NASA Astrophysics Data System (ADS)

Li, R.; Wang, K.; QI, D.

2017-12-01

The next generation global high resolutions precipitation products, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) provide new insights into the global hydrometeorology studies. Although there are some previous works to evaluate it on daily scale or above, its performance on sub-daily scale is still limited. This study evaluates the diurnal characteristics of the half-hourly IMERG product with the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) data and the hourly rain gauge data from approximately 50000 automatic weather station (AWS) in China during 2014-2016. The results show that IMERG can roughly capture the diurnal cycle of precipitation amount with serial correlation for eight sub-regions ranging from 0.63 to 0.97, but less agreed in frequency (from 0.21 to 0.90) and intensity (from -0.22 to 0.83). IMERG can generally capture the nocturnal and early morning peak of amount, frequency and intensity, which it's a known issue unsolved by TMPA, partly due to the better detection of light rain in the morning. However as for the afternoon precipitation, overestimation of amount and frequency and underestimation of intensity still exist in IMERG product, which probably result from the overestimation of light and moderate rain. IMERG shows large bias in late morning (0900-1100 Beijing Time) and mid evening (2000-2200 Beijing Time). All these results highlight the cautions when using the IMERG sub-daily product and indicate the necessity of improved retrieval algorithm in the future.

Precipitation Characteristics of ISCCP Cloud Regimes for Improving Model Hydrological Budgets

NASA Technical Reports Server (NTRS)

Lee, D.; Oreopoulos, L.

2011-01-01

The key in unraveling relationships between precipitation and atmospheric circulations is their common linkage to clouds. Clouds can be described in a variety of ways and several approaches can be adopted to examine their connections to precipitation. We claim that when cloud regimes (aka weather states) from the International Satellite Cloud Climatology Project (ISCCP) are used to conditionally sample/sort and average precipitation data, useful insight and GCM-appropriate diagnostics on the origins and distribution of precipitation can be obtained. The ISCCP cloud regimes are mesoscale (2.5 ) cloud mixtures determined by cluster analysis on joint histograms of cloud optical thickness and cloud top pressure inferred from geostationary and polar orbiter satellite passive retrievals. The ISCCP cloud regime data are combined with GPCP IDD merged surface precipitation data and/or higher temporal and spatial resolution TRMM Multi-Satellite Precipitation Analysis (TMPA) data. The analysis is performed separately for three geographical zones, tropics, and northern/southern midlatitudes (for GPCP; only the tropics can be examined with TMPA data). Our presentation aspires to provide answers to the following questions: (l) What is the mean and variability of surface precipitation produced by each cloud regime at the time of regime occurrence? (2) What is the relative contribution of each cloud regime to the total precipitation within its geographical zone? (3) What is the geographical distribution of precipitation corresponding to particular cloud regime? (4) To what extent are the cloud regimes distinct in terms of their precipitation characteristics and is the regime ordering in terms of convective strength consistent with the observed precipitation intensity?

Validation Of TRMM For Hazard Assessment In The Remote Context Of Tropical Africa

NASA Astrophysics Data System (ADS)

Monsieurs, E.; Kirschbaum, D.; Tan, J.; Jacobs, L.; Kervyn, M.; Demoulin, A.; Dewitte, O.

2017-12-01

Accurate rainfall data is fundamental for understanding and mitigating the disastrous effects of many rainfall-triggered hazards, especially when one considers the challenges arising from climate change and rainfall variability. In tropical Africa in particular, the sparse operational rainfall gauging network hampers the ability to understand these hazards. Satellite rainfall estimates (SRE) can therefore be of great value. Yet, rigorous validation is required to identify the uncertainties when using SRE for hazard applications. We evaluated the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 Research Derived Daily Product from 1998 to 2017, at 0.25° x 0.25° spatial and 24 h temporal resolution. The validation was done over the western branch of the East African Rift, with the perspective of regional landslide hazard assessment in mind. Even though we collected an unprecedented dataset of 47 gauges with a minimum temporal resolution of 24 h, the sparse and heterogeneous temporal coverage in a region with high rainfall variability poses challenges for validation. In addition, the discrepancy between local-scale gauge data and spatially averaged ( 775 km²) TMPA data in the context of local convective storms and orographic rainfall is a crucial source of uncertainty. We adopted a flexible framework for SRE validation that fosters explorative research in a remote context. Results show that TMPA performs reasonably well during the rainy seasons for rainfall intensities <20 mm/day. TMPA systematically underestimates rainfall, but most problematic is the decreasing probability of detection of high intensity rainfalls. We suggest that landslide hazard might be efficiently assessed if we take account of the systematic biases in TMPA data and determine rainfall thresholds modulated by controls on, and uncertainties of, TMPA revealed in this study. Moreover, it is found relevant in mapping regional-scale rainfall-triggered hazards that are in any case poorly covered by the sparse available gauges. We anticipate validation of TMPA's successor (Integrated Multi-satellitE Retrievals for Global Precipitation Measurement; 10 km × 10 km, half-hourly) using the proposed framework, as soon as this product will be available in early 2018 for the 1998-present period.

First Evaluation of the Climatological Calibration Algorithm in the Real-time TMPA Precipitation Estimates over Two Basins at High and Low Latitudes

NASA Technical Reports Server (NTRS)

Yong, Bin; Ren, Liliang; Hong, Yang; Gourley, Jonathan; Tian, Yudong; Huffman, George J.; Chen, Xi; Wang, Weiguang; Wen, Yixin

2013-01-01

The TRMM Multi-satellite Precipitation Analysis (TMPA) system underwent a crucial upgrade in early 2009 to include a climatological calibration algorithm (CCA) to its realtime product 3B42RT, and this algorithm will continue to be applied in the future Global Precipitation Measurement era constellation precipitation products. In this study, efforts are focused on the comparison and validation of the Version 6 3B42RT estimates before and after the climatological calibration is applied. The evaluation is accomplished using independent rain gauge networks located within the high-latitude Laohahe basin and the low-latitude Mishui basin, both in China. The analyses indicate the CCA can effectively reduce the systematic errors over the low-latitude Mishui basin but misrepresent the intensity distribution pattern of medium-high rain rates. This behavior could adversely affect TMPA's hydrological applications, especially for extreme events (e.g., floods and landslides). Results also show that the CCA tends to perform slightly worse, in particular, during summer and winter, over the high-latitude Laohahe basin. This is possibly due to the simplified calibration-processing scheme in the CCA that directly applies the climatological calibrators developed within 40 degrees latitude to the latitude belts of 40 degrees N-50 degrees N. Caution should therefore be exercised when using the calibrated 3B42RT for heavy rainfall-related flood forecasting (or landslide warning) over high-latitude regions, as the employment of the smooth-fill scheme in the CCA bias correction could homogenize the varying rainstorm characteristics. Finally, this study highlights that accurate detection and estimation of snow at high latitudes is still a challenging task for the future development of satellite precipitation retrievals.

The Evolution of Remotely Sensed Precipitation Products for Hydrological Applications with a Focus on the Tropical Rainfall Measurement Mission (TRMM)

NASA Astrophysics Data System (ADS)

Tobin, K. J.; Bennett, M.

2012-12-01

This study examines the evolution of how remotely sensed precipitation products have impacted hydrologic modeling from six basins across the continental United States. Precipitation products include both ground-based (Multisensor Precipitation Estimator - MPE) and space-based products. Two space-based products are from the Tropical Rainfall Measurement Mission (TRMM) and include the real-time TRMM Multi-Satellite Precipitation Analysis (TMPA-RT) and TRMM 3B42 Research product. Precipitation products are compared between early (2004-2008) and late (2008-2010) periods. Additionally, version 6 and the new version 7 of these TRMM products are examined. Watersheds examined were moderately large (1000 to 1,000 square kilometers) and included the San Pedro (Arizona), Cimarron (Oklahoma); Alapaha (Georgia), mid-Nueces (Texas), San Casimiro (Texas), and the mid-Rio Grande basins, which is a bi-national basin that spans the Texas-Mexico border. Precipitation products are used to drive streamflow simulations using the Soil Water Assessment Tool (SWAT). The main results of this study concludes that MPE is a mature remote sensing product that generally supports superior hydrologic simulations based on standard performance metrics such as mass balance error, Nash-Sutcliffe efficiency coefficient, and coefficient of persistence. TRMM products support acceptable simulations and have improved in performance between early and late periods for TMPA-RT (both versions) and version 6 of TRMM 3B42 Research in five out of the six basins examined. This improvement is related to modification of TRMM in January 2009 with the addition of more satellite data and a climatologic bias correction, which greatly improves the real-time TMPA-RT product. Conversely, version 7 of the TRMM 3B42 Research has a positive bias compared to version 6, which is translated into poorer hydrological simulations of streamflow. Future research is urgently needed to determine if the issues observed in this study are indicative of a broader problem associated with the most recent version of TRMM.

Potential Applications of Remote Sensing Precipitation Data on Urban Stormwater Modeling

NASA Astrophysics Data System (ADS)

Maggioni, V.; Tarantola, R.; Ferreira, C.

2014-12-01

Although stormwater modeling is widely used to plan, manage and operate stormwater systems in the urban environment, accuracy in model development and calibration is still problematic. Precipitation is the major forcing of stormwater modeling and one of the most important variables for accurate representation of the water cycle in urban areas. However, rainfall data availability in both temporal and spatial adequate scales is scarce. Here we investigate the potential to apply satellite precipitation products to small-scale urban watersheds with a focus on real-time data for operational use and historical data for model calibration and planning. We present a study case in Northern Virginia, part of the Washington, D.C. metropolitan region. We compare several rainfall datasets from satellites, radar and rain gauges during 2002-2008, using two multi-satellite precipitation products. The first one is the NASA TRMM TMPA at daily/0.25° time/space resolution, which is available in two forms: 3B42-Real Time and 3B42-Version 7, where the latter is a post-processed product, corrected with ground-based observations. The second one is the NOAA CMORPH at 3hrs/0.25° time/space resolution. The NOAA Climate Prediction Center (CPC) data and NCEP Stage IV radar-based product are used as reference datasets for TMPA and CMORPH, respectively. Statistical analyses are conducted to compare these datasets: correlation coefficient, RMSE, bias, probability of correct no-rain detection and of false alarm were computed with a focus on Fairfax, VA county. Preliminary results show that the TMPA products outperform CMORPH, when compared to rain gauges and radar data over the county. Moreover, no appreciable difference is detected between TMPA-V7 and TMPA-RT, which demonstrates that real-time data could be used over the urban watershed with results that are comparable to the adjusted product. Analyses are undergoing to investigate higher temporal resolution and to include a comparison with the Fairfax county rain gages data. Future work will also evaluate the impacts of different precipitation datasets on stormwater runoff for Fairfax county, using the EPA-SWMM5 storm water model.

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

NASA Astrophysics Data System (ADS)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches has the potential to improve the quality of near-real-time rainfall estimates from remote sensing in the near future.

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.

First evaluation of the utility of GPM precipitation in global flood monitoring

NASA Astrophysics Data System (ADS)

Wu, H.; Yan, Y.; Gao, Z.

2017-12-01

The Global Flood Monitoring System (GFMS) has been developed and used to provide real-time flood detection and streamflow estimates over the last few years with significant success shown by validation against global flood event data sets and observed streamflow variations (Wu et al., 2014). It has become a tool for various national and international organizations to appraise flood conditions in various areas, including where rainfall and hydrology information is limited. The GFMS has been using the TRMM Multi-satellite Precipitation Analysis (TMPA) as its main rainfall input. Now, with the advent of the Global Precipitation Measurement (GPM) mission there is an opportunity to significantly improve global flood monitoring and forecasting. GPM's Integrated Multi-satellitE Retrievals for GPM (IMERG) multi-satellite product is designed to take advantage of various technical advances in the field and combine that with an efficient processing system producing "early" (4 hrs) and "late" (12 hrs) products for operational use. Specifically, this study is focused on (1) understanding the difference between the new IMERG products and other existing satellite precipitation products, e.g., TMPA, CMORPH, and ground observations; (2) addressing the challenge in the usage of the IMERG for flood monitoring through hydrologic models, given that only a short period of precipitation data record has been accumulated since the lunch of GPM in 2014; and (3) comparing the statistics of flood simulation based on the DRIVE model with IMERG, TMPA, CMORPH etc. as precipitation inputs respectively. Derivation of a global threshold map is a necessary step to define flood events out of modelling results, which requires a relatively longer historic information. A set of sensitivity tests are conducted by adjusting IMERG's light, moderate, heavy rain to existing precipitation products with long-term records separately, to optimize the strategy of PDF matching. Other aspects are also examined, including higher latitude events, where GPM precipitation algorithms should also provide improvements. This study provides a first evaluating the utility of the new IMERG products in flood monitoring through hydrologic modeling at a global scale.

Satellite-Based Precipitation Datasets

NASA Astrophysics Data System (ADS)

Munchak, S. J.; Huffman, G. J.

2017-12-01

Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

Evaluation of the Potential of NASA Multi-satellite Precipitation Analysis in Global Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.

2007-01-01

Landslides are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage every year. In the U.S. alone landslides occur in every state, causing an estimated $2 billion in damage and 25- 50 deaths each year. Annual average loss of life from landslide hazards in Japan is 170. The situation is much worse in developing countries and remote mountainous regions due to lack of financial resources and inadequate disaster management ability. Recently, a landslide buried an entire village on the Philippines Island of Leyte on Feb 17,2006, with at least 1800 reported deaths and only 3 houses left standing of the original 300. Intense storms with high-intensity , long-duration rainfall have great potential to trigger rapidly moving landslides, resulting in casualties and property damage across the world. In recent years, through the availability of remotely sensed datasets, it has become possible to conduct global-scale landslide hazard assessment. This paper evaluates the potential of the real-time NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA) system to advance our understanding of and predictive ability for rainfall-triggered landslides. Early results show that the landslide occurrences are closely associated with the spatial patterns and temporal distribution of rainfall characteristics. Particularly, the number of landslide occurrences and the relative importance of rainfall in triggering landslides rely on the influence of rainfall attributes [e.g. rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms). TMPA precipitation data are available in both real-time and post-real-time versions, which are useful to assess the location and timing of rainfall-triggered landslide hazards by monitoring landslide-prone areas while receiving heavy rainfall. For the purpose of identifying rainfall-triggered landslides, an empirical global rainfall intensity-duration threshold is developed by examining a number of landslide occurrences and their corresponding TMPA precipitation characteristics across the world. These early results , in combination with TRMM real-time precipitation estimation system, may form a starting point for developing an operational early warning system for rainfall-triggered landslides around the globe.

Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan

NASA Astrophysics Data System (ADS)

Anjum, Muhammad Naveed; Ding, Yongjian; Shangguan, Donghui; Ahmad, Ijaz; Ijaz, Muhammad Wajid; Farid, Hafiz Umar; Yagoub, Yousif Elnour; Zaman, Muhammad; Adnan, Muhammad

2018-06-01

Recently, the Global Precipitation Measurement (GPM) mission has released the Integrated Multi-satellite Retrievals for GPM (IMERG) at a fine spatial (0.1° × 0.1°) and temporal (half hourly) resolutions. A comprehensive evaluation of this newly launched precipitation product is very important for satellite-based precipitation data users as well as for algorithm developers. The objective of this study was to provide a preliminary and timely performance evaluation of the IMERG product over the northern high lands of Pakistan. For comparison reference, the real-time and post real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products were also evaluated parallel to the IMERG. All of the selected precipitation products were evaluated at annual, monthly, seasonal and daily time scales using reference gauges data from April 2014 to December 2016. The results showed that: (1) the precipitation estimates from IMERG, 3B42V7 and 3B42RT products correlated well with the reference gauges observations at monthly time scale (CC = 0.93, 0.91, 0.88, respectively), whereas moderately at the daily time scale (CC = 0.67, 0.61, and 0.58, respectively); (2) Compared to the 3B42V7 and 3B42RT, the precipitation estimates from IMERG were more reliable in all seasons particularly in the winter season with lowest relative bias (2.61%) and highest CC (0.87); (3) IMERG showed a clear superiority over 3B42V7 and 3B42RT products in order to capture spatial distribution of precipitation over the northern Pakistan; (4) Relative to the 3B42V7 and 3B42RT, daily precipitation estimates from IMEREG showed lowest relative bias (9.20% vs. 21.40% and 26.10%, respectively) and RMSE (2.05 mm/day vs. 2.49 mm/day and 2.88 mm/day, respectively); and (5) Light precipitation events (0-1 mm/day) were usually overestimated by all said satellite-based precipitation products. In contrast moderate (1-20 mm/day) to heavy (>20 mm/day) precipitation events were underestimated by both TMPA products while IMERG was found capable to detect moderate to heavy precipitation events more precisely. Overall, the performance of IMERG was better than that of TMPA products. This preliminary evaluation of new generation of satellite-based precipitation estimates might be a useful feedback for sensor and algorithm developers as well as data users.

Ground and satellite based assessment of meteorological droughts: The Coello river basin case study

NASA Astrophysics Data System (ADS)

Cruz-Roa, A. F.; Olaya-Marín, E. J.; Barrios, M. I.

2017-10-01

The spatial distribution of droughts is a key factor for designing water management policies at basin scale in arid and semi-arid regions. Ground hydro-meteorological data in neo-tropical areas are scarce; therefore, the merging of ground and satellite datasets is a promissory approach for improving our understanding of water distribution. This paper compares three monthly rainfall interpolation methods for drought evaluation. The ordinary kriging technique based on ground data, and cokriging with elevation as auxiliary variable were compared against cokriging using the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA). Twenty rain gauge stations and the 3B42V7 version of the TMPA research dataset were considered. Comparisons were made over the Coello river basin (Colombia) at 3″ spatial resolution covering a period of eight years (1998-2005). The best spatial rainfall estimation was found for cokriging using ground data and elevation. The spatial support of TMPA dataset is very coarse for a merged interpolation with ground data, this spatial scales discrepancy highlight the need to consider scaling rules in the interpolation process.

Application of a medium-range global hydrologic probabilistic forecast scheme to the Ohio River Basin

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

Voisin, Nathalie; Pappenberger, Florian; Lettenmaier, D. P.

2011-08-15

A 10-day globally applicable flood prediction scheme was evaluated using the Ohio River basin as a test site for the period 2003-2007. The Variable Infiltration Capacity (VIC) hydrology model was initialized with the European Centre for Medium Range Weather Forecasts (ECMWF) analysis temperatures and wind, and Tropical Rainfall Monitoring Mission Multi Satellite Precipitation Analysis (TMPA) precipitation up to the day of forecast. In forecast mode, the VIC model was then forced with a calibrated and statistically downscaled ECMWF ensemble prediction system (EPS) 10-day ensemble forecast. A parallel set up was used where ECMWF EPS forecasts were interpolated to the spatialmore » scale of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions. The 15-day spatially distributed ensemble runoff forecasts were then routed to four locations in the basin, each with different drainage areas. Surrogates for observed daily runoff and flow were provided by the reference run, specifically VIC simulation forced with ECMWF analysis fields and TMPA precipitation fields. The flood prediction scheme using the calibrated and downscaled ECMWF EPS forecasts was shown to be more accurate and reliable than interpolated forecasts for both daily distributed runoff forecasts and daily flow forecasts. Initial and antecedent conditions dominated the flow forecasts for lead times shorter than the time of concentration depending on the flow forecast amounts and the drainage area sizes. The flood prediction scheme had useful skill for the 10 following days at all sites.« less

Initial Results in Global Flood Monitoring System (GFMS) Using GPM Data

NASA Astrophysics Data System (ADS)

Wu, H.; Adler, R. F.; Kirschbaum, D.; Huffman, G. J.; Tian, Y.

2016-12-01

The Global Flood Monitoring System (GFMS) (http://flood.umd.edu) has been developed and used to provide real-time flood detection and streamflow estimates over the last few years with significant success shown by validation against global flood event data sets and observed streamflow variations. It has become a tool for various national and international organizations to appraise flood conditions in various areas, including where rainfall and hydrology information is limited. The GFMS has been using the TRMM Multi-satellite Precipitation Analysis (TMPA) as its main rainfall input. Now, with the advent of NASA's Global Precipitation Measurement (GPM) mission there is an opportunity to significantly improve global flood monitoring and forecasting. GPM's Integrated Multi-satellitE Retrievals for GPM (IMERG) multi-satellite product is designed to take advantage of various technical advances in the field and combine that with an efficient processing system producing "early" (4 hrs) and "late" (12 hrs) products for operational use. The products are also more uniform in results than TMPA among the various satellites going into the analysis and available at finer time and space resolutions. On the road to replacing TMPA with the IMERG in the operational version of the GFMS parallel systems were run for periods to understand the impact of the new type of data on the streamflow and flood estimates. Results of this comparison are the basis for this presentation. It is expected that an improvement will be noted both in the accuracy of the precipitation estimates and a smoother transition in and out of heavy rain events, helping to reduce "shock" in the hydrology model. The finer spatial resolution should also help in this regard. The GFMS will be initially run at its primary resolution of 1/8th degree latitude/longitude with both data sets to isolate the impact of the rain information change. Other aspects will also be examined, including higher latitude events, where GPM precipitation algorithms should also provide improvements. This initial work will help focus full implementation of the IMERG into GFMS and the retrospective calculations to be done for the full TRMM/GPM era.

Statistical Evaluation of Combined Daily Gauge Observations and Rainfall Satellite Estimations over Continental South America

NASA Technical Reports Server (NTRS)

Vila, Daniel; deGoncalves, Luis Gustavo; Toll, David L.; Rozante, Jose Roberto

2008-01-01

This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.

Utilizing Satellite-derived Precipitation Products in Hydrometeorological Applications

NASA Astrophysics Data System (ADS)

Liu, Z.; Ostrenga, D.; Teng, W. L.; Kempler, S. J.; Huffman, G. J.

2012-12-01

Each year droughts and floods happen around the world and can cause severe property damages and human casualties. Accurate measurement and forecast are important for preparedness and mitigation efforts. Through multi-satellite blended techniques, significant progress has been made over the past decade in satellite-based precipitation product development, such as, products' spatial and temporal resolutions as well as timely availability. These new products are widely used in various research and applications. In particular, the TRMM Multi-satellite Precipitation Analysis (TMPA) products archived and distributed by the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) provide 3-hourly, daily and monthly near-global (50° N - 50° S) precipitation datasets for research and applications. Two versions of TMPA products are available, research (3B42, 3B43, rain gauge adjusted) and near-real-time (3B42RT). At GES DISC, we have developed precipitation data services to support hydrometeorological applications in order to maximize the TRMM mission's societal benefits. In this presentation, we will present examples of utilizing TMPA precipitation products in hydrometeorological applications including: 1) monitoring global floods and droughts; 2) providing data services to support the USDA Crop Explorer; 3) support hurricane monitoring activities and research; and 4) retrospective analog year analyses to improve USDA's world agricultural supply and demand estimates. We will also present precipitation data services that can be used to support hydrometeorological applications including: 1) User friendly TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/); 2) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at GES DISC; 3) Simple Subset Wizard (http://disc.sci.gsfc.nasa.gov/SSW/ ) for data subsetting and format conversion; 4) Data via OPeNDAP (http://disc.sci.gsfc.nasa.gov/services/opendap/) that can be used for remote access to individual variables within datasets in a form usable by many tools, such as IDV, McIDAS-V, Panoply, Ferret and GrADS; 4) GrADS-DODS Data Server or GDS (http://disc2.nascom.nasa.gov/dods/); 5) The Open Geospatial Consortium (OGC) Web Map Service (WMS) (http://disc.sci.gsfc.nasa.gov/services/wxs_ogc.shtml) that allows the use of data and enables clients to build customized maps with data coming from a different network; and 6) Providing NASA gridded hydrological data access through CUAHSI HIS (Consortium of Universities for the Advancement of Hydrologic Science, Inc. - Hydrologic Information Systems).

Comparison of GPM IMERG, TMPA 3B42 and PERSIANN-CDR satellite precipitation products over Malaysia

NASA Astrophysics Data System (ADS)

Tan, Mou Leong; Santo, Harrif

2018-04-01

The launch of the Global Precipitation Measurement (GPM) mission has prompted the assessment of the newly released satellite precipitation products (SPPs) in different parts of the world. This study performed an initial comparison of three GPM IMERG products (IMERG_E, IMERG_L and IMERG_F) with its predecessor, the TMPA 3B42 and 3B42RT products, and a long-term PERSIANN-CDR product over Malaysia. The performance of six SPPs was evaluated using 501 precipitation gauges from 12 March 2014 to 29 February 2016. The annual, seasonal, monthly and daily precipitation measurements were validated using three widely used statistical metrics (CC, RMSE and RB). The precipitation detection capability (POD, FAR and CSI), probability density function (PDF) and the 2014-2015 flood event analysis were also considered in this assessment. The results show that all the SPPs perform well in annual and monthly precipitation measurements. The spatial variability of the total annual precipitation in 2015 is well captured by all six SPPs, with high precipitation amount in southern East Malaysia, and low precipitation amount in the middle part of Peninsular Malaysia. In contrast, all the SPPs show moderate correlation at daily precipitation estimations, with better performance during the northeast monsoon season. The performance of all the SPPs is better in eastern Peninsular Malaysia, but poorer in northern Peninsular Malaysia. All the SPPs have good precipitation detection ability, except the PERSIANN-CDR. All the SPPs underestimate the light (0-1 mm/day) and violent (> 50 mm/day) precipitation classes, but overestimate moderate and heavy (1-50 mm/day) precipitation classes. The IMERG is shown to have a better capability in detecting light precipitation (0-1 mm/day) compared to the other SPPs. The PERSIANN-CDR has the worst performance in capturing all the precipitation classes, with significant underestimation of light precipitation (0-1 mm/day) class and overestimation of moderate and heavy precipitation classes. The IMERG near-real time products with finer temporal and spatial resolutions can be regarded as a reliable precipitation source in studying the 2014-2015 flood event in Malaysia.

Heading Toward Launch with the Integrated Multi-Satellite Retrievals for GPM (IMERG)

NASA Technical Reports Server (NTRS)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric J.; Adler, Robert F.

2012-01-01

The Day-l algorithm for computing combined precipitation estimates in GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). We plan for the period of record to encompass both the TRMM and GPM eras, and the coverage to extend to fully global as experience is gained in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following cloud motion; and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures. In this talk we summarize the major building blocks and important design issues driven by user needs and practical data issues. One concept being pioneered by the IMERG team is that the code system should produce estimates for the same time period but at different latencies to support the requirements of different groups of users. Another user requirement is that all these runs must be reprocessed as new IMERG versions are introduced. IMERG's status at meeting time will be summarized, and the processing scenario in the transition from TRMM to GPM will be laid out. Initially, IMERG will be run with TRMM-based calibration, and then a conversion to a GPM-based calibration will be employed after the GPM sensor products are validated. A complete reprocessing will be computed, which will complete the transition from TMPA.

Evaluation of high resolution global satellite precipitation products using daily raingauge data over the Upper Blue Nile Basin

NASA Astrophysics Data System (ADS)

Sahlu, Dejene; Moges, Semu; Anagnostou, Emmanouil; Nikolopoulos, Efthymios; Hailu, Dereje; Mei, Yiwen

2017-04-01

Water resources assessment, planning and management in Africa is often constrained by the lack of reliable spatio-temporal rainfall data. Satellite products are steadily growing and offering useful alternative datasets of rainfall globally. The aim of this paper is to examine the error characteristics of the main available global satellite precipitation products with the view of improving the reliability of wet season (June to September) and small rainy season rainfall datasets over the Upper Blue Nile Basin. The study utilized six satellite derived precipitation datasets at 0.25-deg spatial grid size and daily temporal resolution:1) the near real-time (3B42_RT) and gauge adjusted (3B42_V7) products of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), 2) gauge adjusted and unadjusted Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products and 3) the gauge adjusted and un-adjusted product of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center Morphing technique (CMORPH) over the period of 2000 to 2013.The error analysis utilized statistical techniques using bias ratio (Bias), correlation coefficient (CC) and root-mean-square-error (RMSE). Mean relative error (MRE), CC and RMSE metrics are further examined for six categories of 10th, 25th, 50th, 75th, 90thand 95th percentile rainfall thresholds. The skill of the satellite estimates is evaluated using categorical error metrics of missed rainfall volume fraction (MRV), falsely detected rainfall volume fraction (FRV), probability of detection (POD) and False Alarm Ratio (FAR). Results showed that six satellite based rainfall products underestimated wet season (June to September) gauge precipitation, with the exception of non-adjusted PERSIANN that overestimated the initial part of the rainy season (March to May). During the wet season, adjusted CMORPH has relatively better bias ratio (89 %) followed by 3B42_V7 (88%), adjusted-PERSIANN (81%), and non-adjusted products have relatively lower bias ratio. The results from CC statistic range from 0.34 to 0.43 for the wet season with adjusted products having slightly higher values. The initial rainy season has relatively higher CC than the wet season. Results from the categorical error metrics showed that CMORPH products have higher POD (91%), which are better in avoiding detecting false rainfall events in the wet season. For the initial rainy season PERSIANN (<50%), TMPA and CMORPH products are nearly equivalent (63-67%). On the other hand, FAR is below 0.1% for all products while in the wet season is higher (10-25%). In terms of rainfall volume of missed and false detected rainfall, CMORPH exhibited lower MRV ( 4.5%) than the TMPA and PERSIANN products (11-19%.) in the wet season. MRV for the initial rainy season was 20% for TMPA and CMORPH products and above 30% for PERSIANN products. All products are nearly equivalent in the wet season in terms of FRV (< 0.2%). The magnitude of MRE increases with gauge rainfall threshold categories with 3B42-V7 and adjusted CMORPH having lower magnitude, showing that underestimation of rainfall increases with increasing rainfall magnitude. CC also decreases with gauge rainfall threshold categories with CMORPH products having slightly higher values. Overall, all satellite products underestimated (overestimated) lower (higher) quantiles quantiles. We have observed that among the six satellite rainfall products the adjusted CMORPH has relatively better potential to improve wet season rainfall estimate and 3B42-V7 that initial rainy season in the Upper Blue Nile Basin.

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Hong, Yang; Huffman, George J.

2006-01-01

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Precipitation Characteristics in Tropical Africa Using Satellite and In-Situ Observations

NASA Technical Reports Server (NTRS)

Dezfuli, Amin; Ichoku, Charles; Huffman, George; Mohr, Karen

2017-01-01

Tropical Africa receives nearly all its precipitation as a result of convection. The characteristics of rain-producing systems in this region, despite their crucial role in regional and global circulation, have not been well-understood. 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) to improve our knowledge about the rainfall systems in the region, and to validate the recently-released IMERG precipitation product. 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, TMPA, and provide higher resolution data, continent-wide comparisons are made between these two products. IMERG, due to its improved temporal resolution, 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.

Combining Hydrological Modeling and Remote Sensing Observations to Enable Data-Driven Decision Making for Devils Lake Flood Mitigation in a Changing Climate

NASA Technical Reports Server (NTRS)

Zhang, Xiaodong; Kirilenko, Andrei; Lim, Howe; Teng, Williams

2010-01-01

This slide presentation reviews work to combine the hydrological models and remote sensing observations to monitor Devils Lake in North Dakota, to assist in flood damage mitigation. This reports on the use of a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model.

Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

NASA Technical Reports Server (NTRS)

Adler, Robert; Hong, Yang; Huffman, George

2007-01-01

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences.

Explore GPM IMERG and Other Global Precipitation Products with GES DISC GIOVANNI

NASA Technical Reports Server (NTRS)

Liu, Zhong; Ostrenga, Dana M.; Vollmer, Bruce; MacRitchie, Kyle; Kempler, Steven

2015-01-01

New features and capabilities in the newly released GIOVANNI allow exploring GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) Early, Late and Final Run global half-hourly and monthly precipitation products as well as other precipitation products distributed by the GES DISC such as TRMM Multi-Satellite Precipitation Analysis (TMPA), MERRA (Modern Era Retrospective-Analysis for Research and Applications), NLDAS (North American Land Data Assimilation Systems), GLDAS (Global Land Data Assimilation Systems), etc. GIOVANNI is a web-based tool developed by the GES DISC (Goddard Earth Sciences and Data Information Services Center) to visualize and analyze Earth science data without having to download data and software. The new interface in GIOVANNI allows searching and filtering precipitation products from different NASA missions and projects and expands the capabilities to inter-compare different precipitation products in one interface. Knowing differences in precipitation products is important to identify issues in retrieval algorithms, biases, uncertainties, etc. Due to different formats, data structures, units and so on, it is not easy to inter-compare precipitation products. Newly added features and capabilities (unit conversion, regridding, etc.) in GIOVANNI make inter-comparisons possible. In this presentation, we will describe these new features and capabilities along with examples.

Precipitation Characteristics in West and East Africa from Satellite and in Situ Observations

NASA Technical Reports Server (NTRS)

Dezfuli, Amin K.; Ichoku, Charles M.; Mohr, Karen I.; Huffman, George J.

2017-01-01

Using in situ data, three precipitation classes are identified for rainy seasons of West and East Africa: weak convective rainfall (WCR), strong convective rainfall (SCR), and mesoscale convective systems (MCSs).Nearly 75% of the total seasonal precipitation is produced by the SCR and MCSs, even though they represent only 8% of the rain events. Rain events in East Africa tend to have a longer duration and lower intensity than in West Africa, reflecting different characteristics of the SCR and MCS events in these two regions. Surface heating seems to be the primary convection trigger for the SCR, particularly in East Africa, whereas the WCR requires a dynamical trigger such as low-level convergence. The data are used to evaluate the performance of the recently launched Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG)project. The IMERG-based precipitation shows significant improvement over its predecessor, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), particularly in capturing the MCSs, due to its improved temporal resolution.

Understanding moisture recycling for atmospheric river management in Amazonian communities

NASA Astrophysics Data System (ADS)

Weng, Wei; Luedeke, Matthias; Zemp, Delphine-Clara; Lakes, Tobia; Pradhan, Prajal; Kropp, Juergen

2017-04-01

The invisible atmospheric transports of moisture have recently attracted more research efforts into understanding their structures, processes involved and their function as an ecosystem service. Current attention has been focused on larger scale analysis such as studying global or continental level moisture recycling. Here we applied a water balance model to backtrack the flying river that sustains two local communities in the Colombian and Peruvian Amazon where vulnerable communities rely highly on the rainfall for agricultural practices. By utilising global precipitation (TRMM Multisatillite Precipitation Analysis; TMPA) and evapotranspiration products (Moderate Resolution Imaging Spectroradiometer MODIS, MOD16ET) as input data in the present modelling experiments to compensate the sparse ground observation data in these regions, the moisture recycling process targeting the two amazonian communities which has not yet been explored quantitatively has been shown. The TMPA was selected because of its proved comparativeness with observation data in its precipitation estimations over Amazon regions while the MOD16ET data was chosen for being validated by previous studies in the Amazon basin and for reported good performance. In average, 45.5 % of the precipitation occurring to Caquetá region in Colombia is of terrestrial origin from the South American continent while 48.2% of the total rainfall received by Peruvian Yurimaguas is also from the South American land sources. The spatial distribution of the precipitationsheds (defined previously as the upwind contribution of evapotranspiration to a specific location's precipitation) shows transboundary and transnational shares in the moisture contributors of the precipitation for both regions. An interesting reversed upstream-downstream roles can be observed when the upstream regions in traditional watershed thinking become downstream areas considering precipitationsheds and flying rivers. Strong seasonal variations are also detected by our results. Since undergoing rapid land cultivation expansion in the precipitationsheds of these study areas can potentially alter the moisture recycling process which sustains ecosystem and communities, the tele-connection linking the contributors and recipients presented in this study has highlighted that region-wise collaboration and communication will be essential for an adaptive Amazonia facing environmental change, especially in regards to its vulnerable communities.

The utility of satellite precipitation products for hydrologic prediction in topographically complex regions: The Chehalis River Basin, WA as a case study

NASA Astrophysics Data System (ADS)

Cao, Q.; Mehran, A.; Lettenmaier, D. P.; Mass, C.; Johnson, N.

2015-12-01

Accurate measurements of precipitation are of great importance in hydrologic predictions especially for floods, which are a pervasive natural hazard. One of the primary objectives of Global Precipitation Measurement (GPM) mission is to provide a basis for hydrologic predictions using satellite sensors. A major advance in GPM relative to the Tropical Rainfall Measuring Mission (TRMM) is that it observes atmospheric river (AR) events, most of which have landfall too far north to be tracked by TRMM. These events are responsible for most major floods along the U.S. West Coast. We address the question of whether, for hydrologic modeling purposes, it is better to use precipitation products derived directly from GPM and/or other precipitation fields from weather models that have assimilated satellite data. Our overall strategy is to compare different methods for prediction of flood and/or high flow events by different forcings on the hydrologic model. We examine four different configurations of the Distroibute Hydrology Soil Vegetation Model (DHSVM) over the Chehalis River Basin that use a) precipitation forcings based on gridded station data; b) precipitation forcings based on NWS WSR-88D data, c) forcings based from short-term precipitation forecasts using the Weather Research and Forecasting (WRF) mesoscale atmospheric model, and d) satellite-based precipitation estimates (TMPA and IMERG). We find that in general, biases in the radar and satellite products result in much larger errors than with either gridded station data or WRF forcings, but if these biases are removed, comparable performance in flood predictions can be achieved by Satellite-based precipitation estimates (TMPA and IMERG).

Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China

NASA Astrophysics Data System (ADS)

Guo, Hao; Chen, Sheng; Bao, Anming; Behrangi, Ali; Hong, Yang; Ndayisaba, Felix; Hu, Junjun; Stepanian, Phillip M.

2016-07-01

Two post-real time precipitation products from the Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) are systematically evaluated over China with China daily Precipitation Analysis Product (CPAP) as reference. The IMERG products include the gauge-corrected IMERG product (IMERG_Cal) and the version of IMERG without direct gauge correction (IMERG_Uncal). The post-research TRMM Multisatellite Precipitation Analysis version 7 (TMPA-3B42V7) is also evaluated concurrently with IMERG for better perspective. In order to be consistent with CPAP, the evaluation and comparison of selected products are performed at 0.25° and daily resolutions from 12 March 2014 through 28 February 2015. The results show that: Both IMERG and 3B42V7 show similar performances. Compared to IMERG_Uncal, IMERG_Cal shows significant improvement in overall and conditional bias and in the correlation coefficient. Both IMERG_Cal and IMERG_Uncal perform relatively poor in winter and over-detect slight precipitation events in northwestern China. As an early validation of the GPM-era IMERG products that inherit the TRMM-era global satellite precipitation products, these findings will provide useful feedbacks and insights for algorithm developers and data users over China and beyond.

Online tools for uncovering data quality issues in satellite-based global precipitation products

NASA Astrophysics Data System (ADS)

Liu, Z.; Heo, G.

2015-12-01

Accurate and timely available global precipitation products are important to many applications such as flood forecasting, hydrological modeling, vector-borne disease research, crop yield estimates, etc. However, data quality issues such as biases and uncertainties are common in satellite-based precipitation products and it is important to understand these issues in applications. In recent years, algorithms using multi-satellites and multi-sensors for satellite-based precipitation estimates have become popular, such as the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA) and the latest Integrated Multi-satellitE Retrievals for GPM (IMERG). Studies show that data quality issues for multi-satellite and multi-sensor products can vary with space and time and can be difficult to summarize. Online tools can provide customized results for a given area of interest, allowing customized investigation or comparison on several precipitation products. Because downloading data and software is not required, online tools can facilitate precipitation product evaluation and comparison. In this presentation, we will present online tools to uncover data quality issues in satellite-based global precipitation products. Examples will be presented as well.

Decadal Seasonal Shifts of Precipitation and Temperature in TRMM and AIRS Data

NASA Technical Reports Server (NTRS)

Savtchenko, Andrey; Huffman, George; Meyer, David; Vollmer, Bruce

2018-01-01

We present results from an analysis of seasonal phase shifts in the global precipitation and surface temperatures. We use data from the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Algorithm (TMPA), and the Atmospheric Infrared Sounder (AIRS) on Aqua satellite, all hosted at NASA Goddard Earth Science Data and Information Services Center (GES DISC). We explore the information content and data usability by first aggregating daily grids from the entire records of both missions to pentad (5-day) series which are then processed using Singular Value Decomposition approach. A strength of this approach is the normalized principal components that can then be easily converted from real to complex time series. Thus, we can separate the most informative, the seasonal, components and analyze unambiguously for potential seasonal phase drifts. TMPA and AIRS records represent correspondingly 20 and 15 years of data, which allows us to run simple “phase learning†from the first 5 years of records and use it as reference. The most recent 5 years are then phase-compared with the reference. We demonstrate that the seasonal phase of global precipitation and surface temperatures has been stable in the past two decades. However, a small global trend of delayed precipitation, and earlier arrival of surface temperatures seasons, are detectable at 95% confidence level. Larger phase shifts are detectable at regional level, in regions recognizable from the Eigen vectors to having strong seasonal patterns. For instance, in Central North America, including the North American Monsoon region, confident phase shifts of 1-2 days per decade are detected at 95% confidence level. While seemingly symbolic, these shifts are indicative of larger changes in the Earth Climate System. We thus also demonstrate a potential usability scenario of Earth Science Data Records curated at the NASA GES DISC in partnership with Earth Science Missions.

Integrating NASA Satellite Data Into USDA World Agricultural Outlook Board Decision Making Environment To Improve Agricultural Estimates

NASA Technical Reports Server (NTRS)

Teng, William; Shannon, Harlan; deJeu, Richard; Kempler, Steve

2012-01-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. The goal of the current project is to improve WAOB estimates by integrating NASA satellite precipitation and soil moisture observations into WAOB's decision making environment. Precipitation (Level 3 gridded) is from the TRMM Multi-satellite Precipitation Analysis (TMPA). Soil moisture (Level 2 swath and Level 3 gridded) is generated by the Land Parameter Retrieval Model (LPRM) and operationally produced by the NASA Goddard Earth Sciences Data and Information Services Center (GBS DISC). A root zone soil moisture (RZSM) product is also generated, via assimilation of the Level 3 LPRM data by a land surface model (part of a related project). Data services to be available for these products include GeoTIFF, GDS (GrADS Data Server), WMS (Web Map Service), WCS (Web Coverage Service), and NASA Giovanni. Project benchmarking is based on retrospective analyses of WAOB analog year comparisons. The latter are between a given year and historical years with similar weather patterns and estimated crop yields. An analog index (AI) was developed to introduce a more rigorous, statistical approach for identifying analog years. Results thus far show that crop yield estimates derived from TMPA precipitation data are closer to measured yields than are estimates derived from surface-based precipitation measurements. Work is continuing to include LPRM surface soil moisture data and model-assimilated RZSM.

Large-scale assessment of soil erosion in Africa: satellites help to jointly account for dynamic rainfall and vegetation cover

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Hoedjes, Joost C. B.; van der Velde, Marijn

2015-04-01

Efforts to map and monitor soil erosion need to account for the erratic nature of the soil erosion process. Soil erosion by water occurs on sloped terrain when erosive rainfall and consequent surface runoff impact soils that are not well-protected by vegetation or other soil protective measures. Both rainfall erosivity and vegetation cover are highly variable through space and time. Due to data paucity and the relative ease of spatially overlaying geographical data layers into existing models like USLE (Universal Soil Loss Equation), many studies and mapping efforts merely use average annual values for erosivity and vegetation cover as input. We first show that rainfall erosivity can be estimated from satellite precipitation data. We obtained average annual erosivity estimates from 15 yr of 3-hourly TRMM Multi-satellite Precipitation Analysis (TMPA) data (1998-2012) using intensity-erosivity relationships. Our estimates showed a positive correlation (r = 0.84) with long-term annual erosivity values of 37 stations obtained from literature. Using these TMPA erosivity retrievals, we demonstrate the large interannual variability, with maximum annual erosivity often exceeding two to three times the mean value, especially in semi-arid areas. We then calculate erosivity at a 10-daily time-step and combine this with vegetation cover development for selected locations in Africa using NDVI - normalized difference vegetation index - time series from SPOT VEGETATION. Although we do not integrate the data at this point, the joint analysis of both variables stresses the need for joint accounting for erosivity and vegetation cover for large-scale erosion assessment and monitoring.

33 Years of Near-Global Daily Precipitation from Multisatellite Observations and its Application to Drought Monitoring

NASA Astrophysics Data System (ADS)

Ashouri, H.; Hsu, K.; Sorooshian, S.; Braithwaite, D.; Knapp, K. R.; Cecil, L. D.

2013-12-01

PERSIANN Climate Data Record (PERSIANN-CDR) is a new retrospective satellite-based precipitation data set that is constructed for long-term hydrological and climate studies. The PERSIANN-CDR is a near-global (60°S-60°N) long-term (1980-2012), multi-satellite, high-resolution precipitation product that provides rain rate estimates at 0.25° and daily spatiotemporal resolution. PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high resolution precipitation data set for studying the spatial and temporal variations and changes of precipitation patterns, particularly in a scale relevant to climate extremes at the global scale. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data from the International Satellite Cloud Climatology Project (ISCCP). PERSIANN-CDR is adjusted using the Global Precipitation Climatology Project (GPCP) monthly precipitation to maintain consistency of two data sets at 2.5° monthly scale throughout the entire reconstruction period. PERSIANN-CDR daily precipitation data demonstrates considerable consistency with both GPCP monthly and GPCP 1DD precipitation products. Verification studies over Hurricane Katrina show that PERSIANN-CDR has a good agreement with NCEP Stage IV radar data, noting that PERSIANN-CDR has better spatial coverage. In addition, the Probability Density Function (PDF) of PERSIANN-CDR over the contiguous United States was compared with the PDFs extracted from CPC gauge data and the TMPA precipitation product. The experiment also shows good agreement of the PDF of PERSIANN-CDR with the PDFs of TMPA and CPC gauge data. The application of PERSIANN-CDR in regional and global drought monitoring is investigated. Consisting of more than three decades of high-resolution precipitation data, PERSIANN-CDR makes us capable of long-term assessment of droughts at a higher resolution (0.25°) than previously possible. The results will be presented at the meeting.

Evaluation of multiple precipitation products across Mainland China using the triple collocation method without ground truth

NASA Astrophysics Data System (ADS)

Tang, G.; Li, C.; Hong, Y.; Long, D.

2017-12-01

Proliferation of satellite and reanalysis precipitation products underscores the need to evaluate their reliability, particularly over ungauged or poorly gauged regions. However, it is really challenging to perform such evaluations over regions lacking ground truth data. Here, using the triple collocation (TC) method that is capable of evaluating relative uncertainties in different products without ground truth, we evaluate five satellite-based precipitation products and comparatively assess uncertainties in three types of independent precipitation products, e.g., satellite-based, ground-observed, and model reanalysis over Mainland China, including a ground-based precipitation dataset (the gauge based daily precipitation analysis, CGDPA), the latest version of the European reanalysis agency reanalysis (ERA-interim) product, and five satellite-based products (i.e., 3B42V7, 3B42RT of TMPA, IMERG, CMORPH-CRT, PERSIANN-CDR) on a regular 0.25° grid at the daily timescale from 2013 to 2015. First, the effectiveness of the TC method is evaluated by comparison with traditional methods based on ground observations in a densely gauged region. Results show that the TC method is reliable because the correlation coefficient (CC) and root mean square error (RMSE) are close to those based on the traditional method with a maximum difference only up to 0.08 and 0.71 (mm/day) for CC and RMSE, respectively. Then, the TC method is applied to Mainland China and the Tibetan Plateau (TP). Results indicate that: (1) the overall performance of IMERG is better than the other satellite products over Mainland China; (2) over grid cells without rain gauges in the TP, IMERG and ERA show better performance than CGDPA, indicating the potential of remote sensing and reanalysis data over these regions and the inherent uncertainty of CGDPA due to interpolation using sparsely gauged data; (3) both TMPA-3B42 and CMORPH-CRT have some unexpected CC values over certain grid cells that contain water bodies, reaffirming the overestimation of precipitation over inland water bodies. Overall, the TC method provides not only reliable cross-validation results of precipitation estimates over Mainland China but also a new perspective as to compressively assess multi-source precipitation products, particularly over poorly gauged regions.

Cloud Regimes as a Tool for Systematic Study of Various Aerosol-Cloud-Precipitation Interactions

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

2016-01-01

Systematic changes of clouds and precipitation are notoriously difficult to ascribe to aerosols. This presentation will showcase yet one more attempt to at least credibly detect the signal of aerosol-cloud-precipitation interactions. We surmise that the concept of cloud regimes (CRs) is appropriate to conduct such an investigation. Previous studies focused on what we call here dynamical CRs, and while we continue to adopt those too for our analysis, we have found that a different way of organizing cloud systems, namely via microphysical regimes is also promising. Our analysis relies on MODIS Collection 6 Level-3 data for clouds and aerosols, and TRMM-TMPA data for precipitation. The regimes are derived by applying clustering analysis on MODIS joint histograms, and once each grid cell is assigned a regime, aerosol and precipitation data can be spatiotemporally matched and composited by regime. The composites of various cloud and precipitation variables for high (upper quartile of distribution) and low (lower quartile) aerosol loadings can then be contrasted. We seek evidence of aerosol effects both in regimes with large fractions of deep ice-rich clouds, as well as regimes where low liquid phase clouds dominate. Signals can be seen, especially when the analysis is broken by land-ocean and when additional filters are applied, but there are of course caveats which will be discussed.

Connecting Satellite-Based Precipitation Estimates to Users

NASA Technical Reports Server (NTRS)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric

2018-01-01

Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

Application of Multi-Satellite Precipitation Analysis to Floods and Landslides

NASA Technical Reports Server (NTRS)

Adler, Robert; Hong, Yang; Huffman, George

2007-01-01

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences. However, difficulties in comparing landslide event information (mostly from news reports) with the satellite-based forecasts are analyzed.

Access NASA Satellite Global Precipitation Data Visualization on YouTube

NASA Astrophysics Data System (ADS)

Liu, Z.; Su, J.; Acker, J. G.; Huffman, G. J.; Vollmer, B.; Wei, J.; Meyer, D. J.

2017-12-01

Since the satellite era began, NASA has collected a large volume of Earth science observations for research and applications around the world. Satellite data at 12 NASA data centers can also be used for STEM activities such as disaster events, climate change, etc. However, accessing satellite data can be a daunting task for non-professional users such as teachers and students because of unfamiliarity of terminology, disciplines, data formats, data structures, computing resources, processing software, programing languages, etc. Over the years, many efforts have been developed to improve satellite data access, but barriers still exist for non-professionals. In this presentation, we will present our latest activity that uses the popular online video sharing web site, YouTube, to access visualization of global precipitation datasets at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). With YouTube, users can access and visualize a large volume of satellite data without necessity to learn new software or download data. The dataset in this activity is the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA). The video consists of over 50,000 data files collected since 1998 onwards, covering a zone between 50°N-S. The YouTube video will last 36 minutes for the entire dataset record (over 19 years). Since the time stamp is on each frame of the video, users can begin at any time by dragging the time progress bar. This precipitation animation will allow viewing precipitation events and processes (e.g., hurricanes, fronts, atmospheric rivers, etc.) on a global scale. The next plan is to develop a similar animation for the GPM (Global Precipitation Measurement) Integrated Multi-satellitE Retrievals for GPM (IMERG). The IMERG provides precipitation on a near-global (60°N-S) coverage at half-hourly time interval, showing more details on precipitation processes and development, compared to the 3-hourly TMPA product. The entire video will contain more than 330,000 files and will last 3.6 hours. Future plans include development of fly-over videos for orbital data for an entire satellite mission or project. All videos will be uploaded and available at the GES DISC site on YouTube (https://www.youtube.com/user/NASAGESDISC).

Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

NASA Astrophysics Data System (ADS)

Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye

2016-10-01

Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30 years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and evaluate their applicability for agricultural drought evaluation when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in-situ rainfall measurements across Chile were initially compared to the satellite-based precipitation estimates. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite-based estimates. Nine statistics were used to evaluate the performance of satellite products to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze these datasets to better understand their similarities and differences in characterizing rainfall patterns across Chile. Monthly analysis showed that all satellite products highly overestimated precipitation in the arid North zone. However, there were no major difference between all three products from North to South-Central zones. Though, in the South zone, PERSIANN-CDR shows the lowest fit with high underestimation, further CHIRPS 2.0 and TMPA 3B43 v7 had better agreement with in-situ measurements. The accuracy of satellite products were highly dependent on the amount of monthly rainfall with the best results found during winter seasons and in zones (Central to South) with higher amounts of precipitation. PERSIANN-CDR and CHIRPS 2.0 were used to derive SPI at time-scale of 1, 3 and 6 months, both satellite products presented similar results when it was compared in-situ against satellite SPI's. Because of its higher spatial resolution that allows better characterizing of spatial variation in precipitation pattern, the CHIRPS 2.0 was used to mapping the SPI-3 over Chile. The results of this study show that in order to use the CHIRPS 2.0 and PERSIANN-CDR data sets in Chile to monitor spatial patterns in the rainfall and drought intensity conditions, these products should be calibrated to adjust for the overestimation/underestimation of precipitation geographically specially in the North zone and seasonally during the summer and spring months in the other zones.

Preparing Precipitation Data Access, Value-added Services and Scientific Exploration Tools for the Integrated Multi-satellitE Retrievals for GPM (IMERG)

NASA Astrophysics Data System (ADS)

Ostrenga, D.; Liu, Z.; Kempler, S. J.; Vollmer, B.; Teng, W. L.

2013-12-01

The Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google: NASA PDISC), located at the NASA Goddard Space Flight Center (GSFC) Earth Sciences (GES) Data and Information Services Center (DISC), is home of the Tropical Rainfall Measuring Mission (TRMM) data archive. For over 15 years, the GES DISC has served not only TRMM, but also other space-based, airborne-based, field campaign and ground-based precipitation data products to the precipitation community and other disciplinary communities as well. The TRMM Multi-Satellite Precipitation Analysis (TMPA) products are the most popular products in the TRMM product family in terms of data download and access through Mirador, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) and other services. The next generation of TMPA, the Integrated Multi-satellitE Retrievals for GPM (IMERG) to be released in 2014 after the launch of GPM, will be significantly improved in terms of spatial and temporal resolutions. To better serve the user community, we are preparing data services and samples are listed below. To enable scientific exploration of Earth science data products without going through complicated and often time consuming processes, such as data downloading, data processing, etc., the GES DISC has developed Giovanni in consultation with members of the user community, requesting quick search, subset, analysis and display capabilities for their specific data of interest. For example, the TRMM Online Visualization and Analysis System (TOVAS, http://disc2.nascom.nasa.gov/Giovanni/tovas/) has proven extremely popular, especially as additional datasets have been added upon request. Giovanni will continue to evolve to accommodate GPM data and the multi-sensor data inter-comparisons that will be sure to follow. Additional PDISC tool and service capabilities being adapted for GPM data include: An on-line PDISC Portal (includes user guide, etc.); Data ingest, processing, distribution from on-line archive; Google-like Mirador data search and access engine; electronic distribution, Subscriptions; Uses semantic technology to help manage large amounts of multi-sensor data and their relationships; Data drill down and search capabilities; Data access through various web services, i.e., OPeNDAP, GDS, WMS, WCS; Conversion into various formats, e.g., netCDF, HDF, KML (for Google Earth), ascii; Exploration, visualization and statistical online analysis through Giovanni; Visualization and analysis of L2 data profiles and maps; Generation of derived products, such as, daily products; Parameter and spatial subsetting; Time and temporal aggregation; Regridding; Data version control and provenance; Data Stewardship - Continuous archive verification; Documentation; Science support for proper data usage, help desk; Monitoring services for applications; Expertise in data related standards and interoperability. This presentation will further describe the data services at the PDISC that are currently being utilized by precipitation science and application researchers, and the preparation plan for IMERG. Comments and feedback are welcome.

TMPA Products 3B42RT & 3B42V6: Evaluation and Application in Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

Hao, Z.; Sun, L.; Wang, J.

2012-04-01

Hydrological researchers in Qinghai-Tibet Plateau tend to be haunted by deficiency of station gauged precipitation data for the sparse and uneven distribution of local meteorological stations. Fortunately, alternative data can be obtained from TRMM (Tropic Rainfall Measurement Mission) satellite. Preliminary evaluation and necessary correction of TRMM satellite rainfall products is required for the sake of reliability and suitability considering that TRMM precipitation is unconventional and natural condition in Qinghai-Tibet Plateau is unusually complicated. 3B42RT and 3B42V6 products from TRMM Multisatellite Precipitation Analysis(TMPA) are evaluated in northeast Qinghai-Tibet Plateau with 50 stations quality-controlled gauged daily precipitation as the benchmark precipitation set. It is found that the RT data overestimates the actual precipitation greatly while V6 only overestimates it slightly. RT data shows different seasonal and inter-annual accuracies. Summer and autumn see better accuracies than winter and spring and wet years see higher accuracies than dry years. Latitude is believed to be an important factor that influences the accuracy of satellite precipitation. Both RT and V6 can reflect the general pattern of the spatial distribution of precipitation even though RT overestimates the quantity greatly. A new parameter, accumulated precipitation weight point (APWP), was introduced to describe the temporal-spatial pattern evolution of precipitation. The APWP of both RT and V6 were moving from south to north in the past decade, but they are all in the west of station gauged precipitation APWP(s).V6 APWP track fit gauged precipitation perfectly while RT APWP track has over-exaggerated legs, indicating that spatial distribution of RT precipitation experienced unreasonable sharp changes. A practical and operational procedure to correct satellite precipitation data is developed. For RT, there are two steps. Step 1, the downscaling, original daily precipitation was multiplied by a ratio of its monthly satellite/station precipitation gauged precipitation. Step2, objective analysis, Barnes/Cressman successive correction as well as Optimal Interpolation was applied to refine the processed daily results. Step 1 is unnecessary for V6 correction. The accuracy of RT can be improved significantly and the spatial details of satellite precipitation can be obtained as much as possible while quite little improvement showed in V6 correction. Besides, the iteration of successive correction should not be more than twice and the ideal influence radius for Optimal Interpolation is R=5. The original/corrected RT and V6 data sets were used as precipitation inputs to drive a newly developed hydrological model DHM-SP in the headwater region of the Yellow river so as to assess their applicability in simulating the daily runoff. V6 simulation result is qualified even though it is uncorrected. The bias in RT is too much to make use of RT as model input directly while quite satisfied results can be derived from corrected RT input. The simulation results of corrected RT are even better than that of station gauged and V6.

Statistical and Hydrological Evaluation of TRMM-Based Multi-Satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the Latest Satellite Precipitation Products 3B42V7 Ready for Use in Ungauged Basins?

NASA Technical Reports Server (NTRS)

Xue, Xianwu; Hong, Yang; Limaye, Ashutosh S.; Gourley, Jonathan; Huffman, George J.; Khan, Sadiq Ibrahim; Dorji, Chhimi; Chen, Sheng

2013-01-01

The objective of this study is to quantitatively evaluate the successive Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products and further to explore the improvements and error propagation of the latest 3B42V7 algorithm relative to its predecessor 3B42V6 using the Coupled Routing and Excess Storage (CREST) hydrologic model in the mountainous Wangchu Basin of Bhutan. First, the comparison to a decade-long (2001-2010) daily rain gauge dataset reveals that: 1) 3B42V7 generally improves upon 3B42V6s underestimation both for the whole basin (bias from -41.15 to -8.38) and for a 0.250.25 grid cell with high-density gauges (bias from -40.25 to 0.04), though with modest enhancement of correlation coefficients (CC) (from 0.36 to 0.40 for basin-wide and from 0.37 to 0.41 for grid); and 2) 3B42V7 also improves its occurrence frequency across the rain intensity spectrum. Using the CREST model that has been calibrated with rain gauge inputs, the 3B42V6-based simulation shows limited hydrologic prediction NSCE skill (0.23 in daily scale and 0.25 in monthly scale) while 3B42V7 performs fairly well (0.66 in daily scale and 0.77 in monthly scale), a comparable skill score with the gauge rainfall simulations. After recalibrating the model with the respective TMPA data, significant improvements are observed for 3B42V6 across all categories, but not as much enhancement for the already well-performing 3B42V7 except for a reduction in bias (from -26.98 to -4.81). In summary, the latest 3B42V7 algorithm reveals a significant upgrade from 3B42V6 both in precipitation accuracy (i.e., correcting the underestimation) thus improving its potential hydrological utility. Forcing the model with 3B42V7 rainfall yields comparable skill scores with in-situ gauges even without recalibration of the hydrological model by the satellite precipitation, a compensating approach often used but not favored by the hydrology community, particularly in ungauged basins.

Early Examples from the Integrated Multi-Satellite Retrievals for GPM (IMERG)

NASA Astrophysics Data System (ADS)

Huffman, George; Bolvin, David; Braithwaite, Daniel; Hsu, Kuolin; Joyce, Robert; Kidd, Christopher; Sorooshian, Soroosh; Xie, Pingping

2014-05-01

The U.S. GPM Science Team's Day-1 algorithm for computing combined precipitation estimates as part of GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). The goal is to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG is being developed as a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design and development, plans for testing, and current status. Some of the lessons learned in running and reprocessing the previous data sets include the importance of quality-controlling input data sets, strategies for coping with transitions in the various input data sets, and practical approaches to retrospective analysis of multiple output products (namely the real- and post-real-time data streams). IMERG output will be illustrated using early test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. We end by considering recent changes in input data specifications, the transition from TRMM-based calibration to GPM-based, and further "Day 2" development.

Comprehensive evaluation of multisatellite precipitation estimates over India using gridded rainfall data

NASA Astrophysics Data System (ADS)

Sunilkumar, K.; Narayana Rao, T.; Saikranthi, K.; Purnachandra Rao, M.

2015-09-01

This study presents a comprehensive evaluation of five widely used multisatellite precipitation estimates (MPEs) against 1° × 1° gridded rain gauge data set as ground truth over India. One decade observations are used to assess the performance of various MPEs (Climate Prediction Center (CPC)-South Asia data set, CPC Morphing Technique (CMORPH), Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks, Tropical Rainfall Measuring Mission's Multisatellite Precipitation Analysis (TMPA-3B42), and Global Precipitation Climatology Project). All MPEs have high detection skills of rain with larger probability of detection (POD) and smaller "missing" values. However, the detection sensitivity differs from one product (and also one region) to the other. While the CMORPH has the lowest sensitivity of detecting rain, CPC shows highest sensitivity and often overdetects rain, as evidenced by large POD and false alarm ratio and small missing values. All MPEs show higher rain sensitivity over eastern India than western India. These differential sensitivities are found to alter the biases in rain amount differently. All MPEs show similar spatial patterns of seasonal rain bias and root-mean-square error, but their spatial variability across India is complex and pronounced. The MPEs overestimate the rainfall over the dry regions (northwest and southeast India) and severely underestimate over mountainous regions (west coast and northeast India), whereas the bias is relatively small over the core monsoon zone. Higher occurrence of virga rain due to subcloud evaporation and possible missing of small-scale convective events by gauges over the dry regions are the main reasons for the observed overestimation of rain by MPEs. The decomposed components of total bias show that the major part of overestimation is due to false precipitation. The severe underestimation of rain along the west coast is attributed to the predominant occurrence of shallow rain and underestimation of moderate to heavy rain by MPEs. The decomposed components suggest that the missed precipitation and hit bias are the leading error sources for the total bias along the west coast. All evaluation metrics are found to be nearly equal in two contrasting monsoon seasons (southwest and northeast), indicating that the performance of MPEs does not change with the season, at least over southeast India. Among various MPEs, the performance of TMPA is found to be better than others, as it reproduced most of the spatial variability exhibited by the reference.

Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

NASA Technical Reports Server (NTRS)

Liu, Zhong; Heo, Gil

2015-01-01

Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

NASA Astrophysics Data System (ADS)

Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

2017-04-01

Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze these datasets to better understand their similarities and differences in characterizing rainfall patterns across Chile. Monthly analysis showed that all satellite products highly overestimated rainfall in the arid North zone. However, there were no major difference between all three products from North to South-Central zones. Though, in the South zone, PERSIANN-CDR shows the lowest fit with high underestimation, while CHIRPS 2.0 and TMPA 3B43 v7 had better agreement with in situ measurements. The accuracy of satellite products were highly dependent on the amount of monthly rainfall with the best results found during winter seasons and in zones (Central to South) with higher amounts of precipitation. PERSIANN-CDR and CHIRPS 2.0 were used to derive SPI at time-scale of 1, 3 and 6 months, both satellite products presented similar results when it was compared in situ against satellite SPI's. Because of its higher spatial resolution that allows better characterizing of spatial variation in precipitation pattern, the CHIRPS 2.0 was used to mapping the SPI-3 over Chile. The results of this study show that in order to use the CHIRPS 2.0 and PERSIANN-CDR datasets in Chile to monitor spatial patterns in the rainfall and drought intensity conditions, these products should be calibrated to adjust for the overestimation/underestimation of rainfall geographically specially in the North zone and seasonally during the summer and spring months in the other zones.

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.

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.

Comprehensive Evaluation of GPM and TRMM: A Case Study of the Winter 2015-2016 over California

NASA Astrophysics Data System (ADS)

Li, J.; Liu, H.

2016-12-01

The Global Precipitation Measurement (GPM) has been established to provide the next-generation observations of precipitation globally. It gives the opportunities to measure the snow and lighter rainfall rates, which are relatively difficult to be retrieved by the previous missions. Recently, the state of California experienced with El Nino in the winter of 2015-2016, which brought more-than-average rainfall and snow to the much of areas in the state. This study focused on the state of California to examine how well GPM can capture the winter precipitation compared to the Tropical Rainfall Measuring Mission (TRMM). The Integrated Multi-satellitE Retrievals for GPM (IMERG) final-run and TRMM Multi-satellite Precipitation Analysis (TMPA) version 7 were evaluated against the ground reference of NOAA stage IV multi-sensor composite rain analysis. This study employed both the pixel-based and object-based verification measures to conduct a comprehensive evaluation for GPM and TRMM in the winter season. Probability of Detection, False Alarm Ratio, Bias Ratio, Taylor Diagram, Object-based Missing Ratio, Object-based False Alarm Ratio and Overall Interest Score were used as evaluation metrics. We found the IMERG-final has a better overall performance. We anticipate that the IMERG will benefit the applications of satellite remote-sensed precipitation, such as, hydrological flood modeling, watershed management and climate studies.

Contrasting the co-variability of daytime cloud and precipitation over tropical land and ocean

NASA Astrophysics Data System (ADS)

Jin, Daeho; Oreopoulos, Lazaros; Lee, Dongmin; Cho, Nayeong; Tan, Jackson

2018-03-01

The co-variability of cloud and precipitation in the extended tropics (35° N-35° S) is investigated using contemporaneous data sets for a 13-year period. The goal is to quantify potential relationships between cloud type fractions and precipitation events of particular strength. Particular attention is paid to whether the relationships exhibit different characteristics over tropical land and ocean. A primary analysis metric is the correlation coefficient between fractions of individual cloud types and frequencies within precipitation histogram bins that have been matched in time and space. The cloud type fractions are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) joint histograms of cloud top pressure and cloud optical thickness in 1° grid cells, and the precipitation frequencies come from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) data set aggregated to the same grid.

It is found that the strongest coupling (positive correlation) between clouds and precipitation occurs over ocean for cumulonimbus clouds and the heaviest rainfall. While the same cloud type and rainfall bin are also best correlated over land compared to other combinations, the correlation magnitude is weaker than over ocean. The difference is attributed to the greater size of convective systems over ocean. It is also found that both over ocean and land the anti-correlation of strong precipitation with weak (i.e., thin and/or low) cloud types is of greater absolute strength than positive correlations between weak cloud types and weak precipitation. Cloud type co-occurrence relationships explain some of the cloud-precipitation anti-correlations. Weak correlations between weaker rainfall and clouds indicate poor predictability for precipitation when cloud types are known, and this is even more true over land than over ocean.

TRMM Applications for Rainfall-Induced Landslide Early Warning

NASA Astrophysics Data System (ADS)

Dok, A.; Fukuoka, H.; Hong, Y.

2012-04-01

Early warning system (EWS) is the most effective method in saving lives and reducing property damages resulted from the catastrophic landslides if properly implemented in populated areas of landslide-prone nations. For predicting the occurrence of landslides, it requires examination of empirical relationship between rainfall characteristics and past landslide occurrence. In developed countries like Japan and the US, precipitation is monitored by rain radars and ground-based rain gauge matrix. However, in developing regions like Southeast Asian countries, very limited number of rain gauges is available, and there is no implemented methodology for issuing effective warming of landslides yet. Correspondingly, satellite precipitation monitoring could be therefore a possible and promising solution for launching landslide quasi-real-time early warning system in those countries. It is due to the fact that TMPA (TRMM Multi-satellite Precipitation Analysis) can provides a globally calibration-based sequential scheme for combining precipitation estimates from multiple satellites, and gauge analyses where feasible, at fine scales (3-hourly with 0.25°x0.25° spatial resolution). It is available both after and in quasi-real time, calibrated by TRMM Combined Instrument and TRMM Microwave Imager precipitation product. However, validation of ground based rain gauge and TRMM satellite data in the vulnerable regions is still not yet operative. Snake-line/Critical-line and Soil Water Index (SWI) are used for issuing warning of landslide occurrence in Japan; whereas, Caine criterion is preferable in Europe and western nations. Herewith, it presents rainfall behavior which took place in Beichuan city (located on the 2008 Chinese Wenchuan earthquake fault), Hofu and Shobara cities in Japan where localized heavy rainfall attacked in 2009 and 2010, respectively, from TRMM 3B42RT correlated with ground based rain gauge data. The 1-day rainfall intensity and 15-day cumulative rainfall (snake line) were independently plotted to investigate the impact of short-term rainfall intensity and accumulated effective rainfall volume respectively for obtaining some probabilistic threshold. Japanese SWI was also tested to distribute threshold regarding to highly nonlinear rainfall patterns in predicting the landslide occurrence through the plot of total water of 3 serial tank models and daily precipitation. As a result, the snake line plots using TMPA work well for landslide warning in the selected cities; while SWI plots shows unusual peak value on the day of the debris flow occurrence. Graph of daily precipitation vs SWI implies possible zone of critical line, and second peak appearance 1 day before, indicating possibility of early warning.

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.

Assessing the performance of satellite-based precipitation products over the Mediterranean region

NASA Astrophysics Data System (ADS)

Xaver, Angelika; Dorigo, Wouter; Brocca, Luca; Ciabatta, Luca

2017-04-01

Detailed knowledge about the spatial and temporal patterns and quantities of precipitation is of high importance. This applies especially in the Mediterranean region, where water demand for agricultural, industrial and touristic needs is growing and climate projections foresee a decrease of precipitation amounts and an increase in variability. In this region, ground-based rain gauges are available only limited in number, particularly in northern Africa and the Middle East and lack to capture the high spatio-temporal character of precipitation over large areas. This has motivated the development of a large number of remote sensing products for monitoring rainfall. Satellite-based precipitation products are based on various observation principles and retrieval approaches, i.e. from thermal infra-red and microwaves. Although, many individual validation studies on the performance of these precipitation datasets exist, they mostly examine only one or a few of these rainfall products at the same time and are not targeted at the Mediterranean basin as a whole. Here, we present an extensive comparative study of seven different satellite-based precipitation products, namely CMORPH 30-minutes, CMORPH 3-hourly, GPCP, PERSIANN, SM2Rain CCI, TRMM TMPA 3B42, and TRMM TMPA 3B42RT, focusing on the whole Mediterranean region and on individual Mediterranean catchments. The time frame of investigation is restricted by the common availability of all precipitation products and covers the period 2000-2013. We assess the skill of the satellite products against gridded gauge-based data provided by GPCC and E-OBS. Apart from common characteristics like biases and temporal correlations we evaluate several sophisticated dataset properties that are of particular interest for Mediterranean hydrology, including the capability of the remotely sensed products to capture extreme events and trends. A clear seasonal dependency of the correlation results can be observed for the whole Mediterranean basin as well as for the individual catchments. While high correlation values are achieved for basins north of the Mediterranean Sea, the African Nile catchment is showing the lowest correlation values. When examining the climate indices, e.g. number of (very) heavy precipitation days, the maximum precipitation amount of five consecutive wet days, maximum number of consecutive wet days, it becomes clear that the satellite-based precipitation products are having difficulties in capturing consecutive rainfall events. More promising results are obtained when calculating the total annual amount of precipitation or the number of heavy precipitation days.

Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42 over Far-East Asia

NASA Astrophysics Data System (ADS)

Kim, Kiyoung; Park, Jongmin; Baik, Jongjin; Choi, Minha

2017-05-01

The acquisition of accurate precipitation data is essential for analyzing various hydrological phenomena and climate change. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing global precipitation characteristics. The main objective in this study is to assess precipitation products from GPM, especially the Integrated Multi-satellitE Retrievals (GPM-3IMERGHH) and the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), using gauge-based precipitation data from Far-East Asia during the pre-monsoon and monsoon seasons. Evaluation was performed by focusing on three different factors: geographical aspects, seasonal factors, and spatial distributions. In both mountainous and coastal regions, the GPM-3IMERGHH product showed better performance than the TRMM 3B42 V7, although both rainfall products showed uncertainties caused by orographic convection and the land-ocean classification algorithm. GPM-3IMERGHH performed about 8% better than TRMM 3B42 V7 during the pre-monsoon and monsoon seasons due to the improvement of loaded sensor and reinforcement in capturing convective rainfall, respectively. In depicting the spatial distribution of precipitation, GPM-3IMERGHH was more accurate than TRMM 3B42 V7 because of its enhanced spatial and temporal resolutions of 10 km and 30 min, respectively. Based on these results, GPM-3IMERGHH would be helpful for not only understanding the characteristics of precipitation with high spatial and temporal resolution, but also for estimating near-real-time runoff patterns.

Upper Blue Nile basin water budget from a multi-model perspective

NASA Astrophysics Data System (ADS)

Jung, Hahn Chul; Getirana, Augusto; Policelli, Frederick; McNally, Amy; Arsenault, Kristi R.; Kumar, Sujay; Tadesse, Tsegaye; Peters-Lidard, Christa D.

2017-12-01

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.

Evaluation of TRMM 3B42V7 product on extreme precipitation measurements over peninsular Malaysia

NASA Astrophysics Data System (ADS)

Paska, Jacquoelyne; Lau, Alvin M. S.; Tan, Mou Leong; Tan, Kok Chooi

2017-10-01

Climate variability has become a matter worth our attention as this issue has unveiled to the extreme water-related disasters such as flood and drought. Increments in heavy precipitation have happened over the past century and future climate scenarios show that it may alter the recurrence, timing, force, and length of these occasions. Satellite precipitation products (SPPs) could be used as representation of precipitation over a large region. This could be useful for the monitoring of the precipitation pattern as well as extreme events. Nevertheless, application of these products in monitoring extreme precipitation is still limited because insufficiency of quality assessment. This study aims to evaluate the performance of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42V7 product in capturing the behavior of extreme precipitation events over Peninsular Malaysia from 2000 to 2015. Four extreme precipitation indices, in two general categories of absolute threshold (R10mm, R20mm and R50mm) and maximum (Rx1d) indices that recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) were used. General evaluation has shown that the TRMM 3B42V7 product performed good on the measurements of monthly and annual precipitation. In the respect of extreme precipitation measurements, weak to moderate positive correlations were found between the TRMM 3B42 product and rain gauges over Peninsular Malaysia. The TRMM 3B42V7 product overestimated the R10mm and R20mm indices, while an underestimation was found for the R50mm and Rx1d indices.

Marker retention in the cochlea following injections through the round window membrane

PubMed Central

Salt, Alec N.; Sirjani, Davud B.; Hartsock, Jared J.; Gill, Ruth M.; Plontke, Stefan K.

2007-01-01

Local delivery of drugs to the inner ear is increasingly being used in both clinical and experimental studies. Although direct injection of drugs into perilymph appears to be the most promising way of administering drugs quantitatively, no studies have yet demonstrated the pharmacokinetics in perilymph following direct injections. In this study, we have investigated the retention of substance in perilymph following a single injection into the basal turn of scala tympani (ST). The substance injected was a marker, trimethylphenylammonium (TMPA) that can be detected in low concentrations with ion-selective microelectrodes. Perilymph pharmacokinetics of TMPA was assessed using sequential apical sampling to obtain perilymph for analysis. The amount of TMPA retained in perilymph was compared for different injection and sampling protocols. TMPA concentrations measured in fluid samples were close to those predicted by simulations when the injection pipette was sealed into the bony wall of ST but were systematically lower when the injection pipette was inserted through the round window membrane (RWM). In the latter condition it was estimated that over 60% of the injected TMPA was lost due to leakage of perilymph around the injection pipette at a rate estimated to be 0.09 μL/min. The effects of leakage during and after injections through the RWM were dramatically reduced when the round window niche was filled with 1% sodium hyaluronate gel before penetrating the RWM with the injection pipette. The findings demonstrate that in order to perform quantitative drug injections into perilymph, even small rates of fluid leakage at the injection site must be controlled. PMID:17662546

Evaluation of Integrated Multi-satellitE Retrievals for GPM with All Weather Gauge Observations over CONUS

NASA Astrophysics Data System (ADS)

Chen, S.; Qi, Y.; Hu, B.; Hu, J.; Hong, Y.

2015-12-01

The Global Precipitation Measurement (GPM) mission is composed of an international network of satellites that provide the next-generation global observations of rain and snow. Integrated Multi-satellitE Retrievals for GPM (IMERG) is the state-of-art precipitation products with high spatio-temporal resolution of 0.1°/30min. IMERG unifies precipitation measurements from a constellation of research and operational satellites with the core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI) on board a "Core" satellite. Additionally, IMERG blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. In this study, the final run post real-time IMERG is evaluated with all-weather manual gauge observations over CONUS from June 2014 through May 2015. Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) are used to quantify the performance of IMERG. The performance of IMERG in estimating snowfall precipitation is highlighted in the study. This timely evaluation with all-weather gauge observations is expected to offer insights into performance of IMERG and thus provide useful feedback to the algorithm developers as well as the GPM data users.

Influence of cochleostomy and cochlear implant insertion on drug gradients following intratympanic application in guinea pigs

PubMed Central

King, EB; Hartsock, JJ; O'Leary, SJ; Salt, AN

2013-01-01

Locally-applied drugs can protect residual hearing following cochlear implantation. The influence of cochlear implantation on drug levels in scala tympani (ST) after round window application was investigated in guinea pigs using the marker trimethylphenlyammonium (TMPA) measured in real-time with TMPA-selective microelectrodes. TMPA concentration in the upper basal turn of ST rapidly increased during implantation and then declined due to cerebrospinal fluid entering ST at the cochlear aqueduct and exiting at the cochleostomy. The TMPA increase was found to be caused by the cochleostomy drilling, if the burr tip partially entered ST. TMPA distribution in the second turn was less affected by implantation procedures. These findings show that basal turn drug levels may be changed during implantation and the changes may need to be considered in the interpretation of therapeutic effects of drugs in conjunction with implantation. PMID:24008355

Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Ma, Yingzhao; Hong, Yang; Chen, Yang; Yang, Yuan; Tang, Guoqiang; Yao, Yunjun; Long, Di; Li, Changmin; Han, Zhongying; Liu, Ronghua

2018-01-01

Accurate estimation of precipitation from satellites at high spatiotemporal scales over the Tibetan Plateau (TP) remains a challenge. In this study, we proposed a general framework for blending multiple satellite precipitation data using the dynamic Bayesian model averaging (BMA) algorithm. The blended experiment was performed at a daily 0.25° grid scale for 2007-2012 among Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT and 3B42V7, Climate Prediction Center MORPHing technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). First, the BMA weights were optimized using the expectation-maximization (EM) method for each member on each day at 200 calibrated sites and then interpolated to the entire plateau using the ordinary kriging (OK) approach. Thus, the merging data were produced by weighted sums of the individuals over the plateau. The dynamic BMA approach showed better performance with a smaller root-mean-square error (RMSE) of 6.77 mm/day, higher correlation coefficient of 0.592, and closer Euclid value of 0.833, compared to the individuals at 15 validated sites. Moreover, BMA has proven to be more robust in terms of seasonality, topography, and other parameters than traditional ensemble methods including simple model averaging (SMA) and one-outlier removed (OOR). Error analysis between BMA and the state-of-the-art IMERG in the summer of 2014 further proved that the performance of BMA was superior with respect to multisatellite precipitation data merging. This study demonstrates that BMA provides a new solution for blending multiple satellite data in regions with limited gauges.

Hydrologic Evaluation of Integrated Multi-satellite Retrivals for GPM over Nanliu River Basin in Southern China

NASA Astrophysics Data System (ADS)

Zhenqing, L.; Sheng, C.; Chaoying, H.

2017-12-01

The core satellite of Global Precipitation Measurement (GPM) mission was launched on 27 February2014 with two core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI). The algorithm of Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH) ADDIN EN.CITE ADDIN EN.CITE.DATA , Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS).Therefore, IMERG is deemed to be the state-of-art precipitation product with high spatio-temporal resolution of 0.1°/30min. The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. Early studies about assessment of IMERG with gauge observations or analysis products show that the current version GPM Day-1 product IMERG demonstrates promising performance over China [1], Europe [2], and United States [3]. However, few studies are found to study the IMERG' potentials of hydrologic utility.In this study, the real-time and final run post real-time IMERG products are hydrologically evaluated with gauge analysis product as reference over Nanliu River basin (Fig.1) in Southern China since March 2014 to February 2017 with Xinanjiang model. Statistics metrics Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), and Nash-Sutcliffe (NSCE) index will be used to compare the stream flow simulated with IMERG to the observed stream flow. This timely hydrologic evaluation is expected to offer insights into IMERG' potentials in hydrologic utility and thus provide useful feedback to the IMERG algorithm developers and the hydrologic users.

How reliable are satellite precipitation estimates for driving hydrological models: a verification study over the Mediterranean area

NASA Astrophysics Data System (ADS)

Camici, Stefania; Ciabatta, Luca; Massari, Christian; Brocca, Luca

2017-04-01

Floods are one of the most common and dangerous natural hazards, causing every year thousands of casualties and damages worldwide. The main tool for assessing flood risk and reducing damages is represented by hydrologic early warning systems that allow to forecast flood events by using real time data obtained through ground monitoring networks (e.g., raingauges and radars). However, the use of such data, mainly rainfall, presents some issues firstly related to the network density and to the limited spatial representativeness of local measurements. A way to overcome these issues may be the use of satellite-based rainfall products (SRPs) that nowadays are available on a global scale at ever increasing spatial/temporal resolution and accuracy. However, despite the large availability and increased accuracy of SRPs (e.g., the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA); the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF); and the recent Global Precipitation Measurement (GPM) mission), remotely sensed rainfall data are scarcely used in hydrological modeling and only a small number of studies have been carried out to outline some guidelines for using satellite data as input for hydrological modelling. Reasons may be related to: 1) the large bias characterizing satellite precipitation estimates, which is dependent on rainfall intensity and season, 2) the spatial/temporal resolution, 3) the timeliness, which is often insufficient for operational purposes, and 4) a general (often not justified) skepticism of the hydrological community in the use of satellite products for land applications. The objective of this study is to explore the feasibility of using SRPs in a lumped hydrologic model (MISDc, "Modello Idrologico Semi-Distribuito in continuo", Masseroni et al., 2017) over 10 basins in the Mediterranean area with different sizes and physiographic characteristics. Specifically, TMPA 3B42-RT, CMORPH, PERSIANN and a new soil moisture-derived rainfall datasets obtained through the application of SM2RAIN algorithm (Brocca et al., 2014) to ASCAT (Advanced SCATterometer) soil moisture product are used in the analysis. The performances obtained with SRPs are compared with those obtained by using ground data during the 6-year period from 2010 to 2015. In addition, the performance obtained by an integration of the above mentioned SRPs is also investigated to see whether merged rainfall observations are able to improve flood simulation. Preliminary analysis were also carried out by using the IMERG early run product of GPM mission. The results highlight that SRPs should be used with caution for rainfall-runoff modelling in the Mediterranean region. Bias correction and model recalibration are necessary steps, even though not always sufficient to achieve satisfactory performances. Indeed, some of the products provide unreliable outcomes, mainly in smaller basins (<500 km2) that, however, represent the main target for flood modelling in the Mediterranean area. The better performances are obtained by integrating different SRPs, and particularly by merging TMPA 3B42-RT and SM2RAIN-ASCAT products. The promising results of the integrated product are expected to increase the confidence on the use of SRPs in hydrological modeling, even in challenging areas as the Mediterranean. REFERENCES Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., Levizzani, V. (2014). Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data. Journal of Geophysical Research, 119(9), 5128-5141, doi:10.1002/2014JD021489. Masseroni, D., Cislaghi, A., Camici, S., Massari, C., Brocca, L. (2017). A reliable rainfall-runoff model for flood forecasting: review and application to a semiurbanized watershed at high flood risk in Italy. Hydrology Research, in press, doi:10.2166/nh.2016.037.

Assesing the temporal and spatial performance of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

NASA Astrophysics Data System (ADS)

Zambrano-Bigiarini, Mauricio; Nauditt, Alexandra; Birkel, Christian; Verbist, Koen; Ribbe, Lars

2017-04-01

Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SRE) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods. This study attempts to exhaustively evaluate -for the first time- the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-adj, MSWEPv1.1 and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25° grid if necessary). The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities. Results revealed that most SRE products performed better for the humid South (36.4-43.7°S) and Central Chile (32.18-36.4°S), in particular at low- and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons autumn and winter (MAM-JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all time scales, which can be clearly attributed to its bias-correction procedure using 217 stations from Chile. Good results were also obtained by the research products CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR and the real-time PERSIANN-CCS-adj were less skillful in representing observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resources assessments. We finally conclude that despite improvements of most SRE products, a site-specific assessment is still needed before any use in catchment-scale hydrological studies.

Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile

NASA Astrophysics Data System (ADS)

Zambrano-Bigiarini, Mauricio; Nauditt, Alexandra; Birkel, Christian; Verbist, Koen; Ribbe, Lars

2017-03-01

Accurate representation of the real spatio-temporal variability of catchment rainfall inputs is currently severely limited. Moreover, spatially interpolated catchment precipitation is subject to large uncertainties, particularly in developing countries and regions which are difficult to access. Recently, satellite-based rainfall estimates (SREs) provide an unprecedented opportunity for a wide range of hydrological applications, from water resources modelling to monitoring of extreme events such as droughts and floods.This study attempts to exhaustively evaluate - for the first time - the suitability of seven state-of-the-art SRE products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-Adj, MSWEPv1.1, and PGFv3) over the complex topography and diverse climatic gradients of Chile. Different temporal scales (daily, monthly, seasonal, annual) are used in a point-to-pixel comparison between precipitation time series measured at 366 stations (from sea level to 4600 m a.s.l. in the Andean Plateau) and the corresponding grid cell of each SRE (rescaled to a 0.25° grid if necessary). The modified Kling-Gupta efficiency was used to identify possible sources of systematic errors in each SRE. In addition, five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities.Results revealed that most SRE products performed better for the humid South (36.4-43.7° S) and Central Chile (32.18-36.4° S), in particular at low- and mid-elevation zones (0-1000 m a.s.l.) compared to the arid northern regions and the Far South. Seasonally, all products performed best during the wet seasons (autumn and winter; MAM-JJA) compared to summer (DJF) and spring (SON). In addition, all SREs were able to correctly identify the occurrence of no-rain events, but they presented a low skill in classifying precipitation intensities during rainy days. Overall, PGFv3 exhibited the best performance everywhere and for all timescales, which can be clearly attributed to its bias-correction procedure using 217 stations from Chile. Good results were also obtained by the research products CHIRPSv2, TMPA 3B42v7 and MSWEPv1.1, while CMORPH, PERSIANN-CDR, and the real-time PERSIANN-CCS-Adj were less skillful in representing observed rainfall. While PGFv3 (currently available up to 2010) might be used in Chile for historical analyses and calibration of hydrological models, the high spatial resolution, low latency and long data records of CHIRPS and TMPA 3B42v7 (in transition to IMERG) show promising potential to be used in meteorological studies and water resource assessments. We finally conclude that despite improvements of most SRE products, a site-specific assessment is still needed before any use in catchment-scale hydrological studies.

Amazon river basin evapotranspiration and its influence on the rainfall in southern Brazil

NASA Astrophysics Data System (ADS)

Folegatti, M. V.; Wolff, W.

2017-12-01

Amazon river basin (ARB) presents a positive water balance, i.e. the precipitation is higher than evapotranspiration. Regarding the regional circulation, ARB evapotranspiration represents an important source of humidity for the South of Brazil. Thus, the aim of this work is to answer the question: how much is the correlation between ARB evapotranspiration and rainfall in South of Brazil? The shapefiles data of ARB and countries/states boundary were obtained through the Oak Ridge National Laboratory (ORNL) and Instituto Brasileiro de Geografia e Estatística (IBGE), respectively. According to rasters data, the precipitation was obtained from study of Numerical Terradynamic Simulation Group (NTSG) for images of Moderate Resolution Imaging Spectroradiometer (MODIS), under code MOD16A2, whereas rasters data for evapotranspiration were obtained from National Aeronautics and Space Administration (NASA) by Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA), under code 3B43_V7. The products MOD16A2 and 3B43_V7 have a respective spatial resolution of 0.5º and 0.25º, and a monthly temporal resolution from January/2000 to December/2014. For ARB and South region of Brazil was calculated the mean evapotranspiration and mean precipitation through the pixels within of the respective polygons. To answer the question of this work was performed the cross-correlation analysis between these time series. We observed the highest value for the lag that corresponds the begin of spring (October), being 0.3 approximately. As a result, the mean precipitation on South region of Brazil during spring and summer was in the order of 15% to 30 %, explained by ARB evapotranspiration. For this reason, the maintenance of ARB is extremely important for water resource grant in South of Brazil.

The Day-1 GPM Combined Precipitation Algorithm: IMERG

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

2012-12-01

The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) algorithm will provide the at-launch combined-sensor precipitation dataset being produced by the U.S. GPM Science Team. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in three current U.S. algorithms: - the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; - the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following storm motion; and - the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures, and filters out some non-raining cold clouds. The goal is to provide a long-term, fine-scale record of global precipitation from the entire constellation of precipitation-relevant satellite sensors, with input from surface precipitation gauges. The record will begin January 1998 at the start of the Tropical Rainfall Measuring Mission (TRMM) and extend as GPM records additional data. Although homogeneity is considered desirable, the use of diverse and evolving data sources works against the strict long-term homogeneity that characterizes a Climate Data Record (CDR). This talk will briefly review the design requirements for IMERG, including multiple runs at different latencies (most likely around 4 hours, 12 hours, and 2 months after observation time), various intermediate data fields as part of the IMERG data file, and the plans to bring up IMERG with calibration by TRMM initially, transitioning to GPM when its individual-sensor precipitation algorithms are fully functional. Then we will present some early examples of IMERG data products and compare them with existing products to illustrate how the design of IMERG affects the overall performance of the algorithm.

Satellite precipitation estimation over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Porcu, F.; Gjoka, U.

2012-04-01

Precipitation characteristics over the Tibetan Plateau are very little known, given the scarcity of reliable and widely distributed ground observation, thus the satellite approach is a valuable choice for large scale precipitation analysis and hydrological cycle studies. However,the satellite perspective undergoes various shortcomings at the different wavelengths used in atmospheric remote sensing. In the microwave spectrum often the high soil emissivity masks or hides the atmospheric signal upwelling from light-moderate precipitation layers, while low and relatively thin precipitating clouds are not well detected in the visible-infrared, because of their low contrast with cold and bright (if snow covered) background. In this work an IR-based, statistical rainfall estimation technique is trained and applied over the Tibetan Plateau hydrological basin to retrive precipitation intensity at different spatial and temporal scales. The technique is based on a simple artificial neural network scheme trained with two supervised training sets assembled for monsoon season and for the rest of the year. For the monsoon season (estimated from June to September), the ground radar precipitation data for few case studies are used to build the training set: four days in summer 2009 are considered. For the rest of the year, CloudSat-CPR derived snowfall rate has been used as reference precipitation data, following the Kulie and Bennartz (2009) algorithm. METEOSAT-7 infrared channels radiance (at 6.7 and 11 micometers) and derived local variability features (such as local standard deviation and local average) are used as input and the actual rainrate is obtained as output for each satellite slot, every 30 minutes on the satellite grid. The satellite rainrate maps for three years (2008-2010) are computed and compared with available global precipitation products (such as C-MORPH and TMPA products) and with other techniques applied to the Plateau area: similarities and differences are discussed. Relevant characteristics of precipitation fields are derived and analyzed, such as diurnal cycle, precipitation frequency, maximum rainrate distribution and dry areas detection. Interannual variability of precipitation pattern and intensity is also discussed.

Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup

2013-04-01

Errors in the forcing data are sometimes overlooked in hydrological studies even when they could be the most important source of uncertainty. The latter particularly holds true in tropical countries with short historical records of rainfall monitoring and remote areas with sparse rain gauge network. In such instances, alternative data such as the remotely sensed precipitation from the TRMM (Tropical Rainfall Measuring Mission) satellite have been used. These provide a good spatial representation of rainfall processes but have been established in the literature to contain volumetric biases that may impair the results of hydrological modelling or worse, are compensated during model calibration. In this study, we analysed precipitation time series from the TMPA (TRMM Multiple Precipitation Algorithm, version 6) against measurements from over 300 gauges in the Andes and Amazon regions of Peru and Ecuador. We found moderately good monthly correlation between the pixel and gauge pairs but a severe underestimation of rainfall amounts and wet days. The discrepancy between the time series pairs is particularly visible over the east side of the Andes and may be attributed to localized and orographic-driven high intensity rainfall, which the satellite product may have limited skills at capturing due to technical and scale issues. This consequently results in a low bias in the simulated streamflow volumes further downstream. In comparison, with the recently released TMPA, version 7, the biases reduce. This work further explores several approaches to merge the two sources of rainfall measurements, each of a different spatial and temporal support, with the objective of improving the representation of rainfall in hydrological simulations. The methods used are (1) mean bias correction (2) data assimilation using Kalman filter Bayesian updating. The results are evaluated by means of (1) a comparison of runoff ratios (the ratio of the total runoff and the total precipitation over an extended period) in multiple basins, and (2) a comparison of the outcome of hydrological modelling using the distributed JULES (Joint-UK Land Environment Simulator) land surface model. First results indicate an improvement in the water balance that directly translates into an increased hydrological performance. The more interesting aspect of the study, however, will be the insights into the nature of satellite precipitation errors in this extreme environment and the optimal means of improving the data to generate increased confidence in hydrological predictions.

Evaluation of Satellite and Model Precipitation Products Over Turkey

NASA Astrophysics Data System (ADS)

Yilmaz, M. T.; Amjad, M.

2017-12-01

Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14.72 mm/month and 10.75 mm/month, respectively) compared to gauges IWD error (21.58 mm/month). These results show that, on average, ECMWF forecast data have higher skill than TRMM observations. Overall, both ECMWF forecast data and TRMM observations show good potential for catchment scale hydrological analysis.

Sorption and desorption of carbamazepine from water by smectite clays.

PubMed

Zhang, Weihao; Ding, Yunjie; Boyd, Stephen A; Teppen, Brian J; Li, Hui

2010-11-01

Carbamazepine is a prescription anticonvulsant and mood stabilizing pharmaceutical administered to humans. Carbamazepine is persistent in the environment and frequently detected in water systems. In this study, sorption and desorption of carbamazepine from water was measured for smectite clays with the surface negative charges compensated with K+, Ca2+, NH4+, tetramethylammonium (TMA), trimethylphenylammonium (TMPA) and hexadecyltrimethylammonium (HDTMA) cations. The magnitude of sorption followed the order: TMPA-smectite≥HDTMA-smectite>NH4-smectite>K-smectite>Ca-smectite⩾TMA-smectite. The greatest sorption of carbamazepine by TMPA-smectite is attributed to the interaction of conjugate aromatic moiety in carbamazepine with the phenyl ring in TMPA through π-π interaction. Partitioning process is the primary mechanism for carbamazepine uptake by HDTMA-smectite. For NH4-smectite the urea moiety in carbamazepine interacts with exchanged cation NH4+ by H-bonding hence demonstrating relatively higher adsorption. Sorption by K-, Ca- and TMA-smectites from water occurs on aluminosilicate mineral surfaces. These results implicate that carbamazepine sorption by soils occurs primarily in soil organic matter, and soil mineral fractions play a secondary role. Desorption of carbamazepine from the sorbents manifested an apparent hysteresis. Increasing irreversibility of desorption vs. sorption was observed for K-, Ca-, TMA-, TMPA- and HDTMA-clays as aqueous carbamazepine concentrations increased. Desorption hysteresis of carbamazepine from K-, Ca-, NH4-smectites was greater than that from TMPA- and HDTMA-clays, suggesting that the sequestrated carbamazepine molecules in smectite interlayers are more resistant to desorption compared to those sorbed by organic phases in smectite clays. Copyright © 2010 Elsevier Ltd. All rights reserved.

On the Characterization of Rainfall Associated with U.S. Landfalling North Atlantic Tropical Cyclones Based on Satellite Data and Numerical Weather Prediction Outputs

NASA Astrophysics Data System (ADS)

Luitel, B. N.; Villarini, G.; Vecchi, G. A.

2014-12-01

When we talk about tropical cyclones (TCs), the first things that come to mind are strong winds and storm surge affecting the coastal areas. However, according to the Federal Emergency Management Agency (FEMA) 59% of the deaths caused by TCs since 1970 is due to fresh water flooding. Heavy rainfall associated with TCs accounts for 13% of heavy rainfall events nationwide for the June-October months, with this percentage being much higher if the focus is on the eastern and southern United States. This study focuses on the evaluation of precipitation associated with the North Atlantic TCs that affected the continental United States over the period 2007 - 2012. We evaluate the rainfall associated with these TCs using four satellite based rainfall products: Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA; both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); Climate Prediction Center (CPC) MORPHing technique (CMORPH). As a reference data we use gridded rainfall provided by CPC (Daily US Unified Gauge-Based Analysis of Precipitation). Rainfall fields from each of these satellite products are compared to the reference data, providing valuable information about the realism of these products in reproducing the rainfall associated with TCs affecting the continental United States. In addition to the satellite products, we evaluate the forecasted rainfall produced by five state-of-the-art numerical weather prediction (NWP) models: European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC). The skill of these models in reproducing TC rainfall is quantified for different lead times, and discussed in light of the performance of the satellite products.

Evaluation and intercomparison of GPM-IMERG and TRMM 3B42 daily precipitation products over Greece

NASA Astrophysics Data System (ADS)

Kazamias, A. P.; Sapountzis, M.; Lagouvardos, K.

2017-09-01

Accurate precipitation data at high temporal and spatial resolutions are needed for numerous applications in hydrology, water resources management and flood risk management. Satellite-based precipitation estimations/products offer a potential alternative source of rainfall data for regions with sparse rain gauge network. The recently launched Global Precipitation Measurement (GPM) mission is the successor of Tropical Rainfall Measuring Mission (TRMM) providing global precipitation estimates at spatial resolution of 0.1 degree x 0.1 degree and half-hourly temporal resolution. This study aims at evaluating the accuracy of the Integrated Multi-satellite Retrievals for GPM (IMERG) near-real-time daily product (GPM-3IMERGDL) against rain gauge observations from a network of stations distributed across Greece for the year 2016. Moreover, the GPM-IMERG product is also compared with its predecessor, the Version-7 near-real-time (3B42RT) daily product of TRMM Multisatellite Precipitation Analysis (TMPA). Several statistical metrics are used to quantitatively evaluate the performance of the satellite-based precipitation estimates against rain gauge observations. In addition, categorical statistical indices are used to assess rain detection capabilities of the two satellite products. The GPM-IMERG daily product shows reasonable agreement (CC=0.60) against rain gauge observations, with the exception of coastal areas in which low correlations are achieved. The GPM-IMERG daily precipitation product tends to overestimate rainfall, especially in complex terrain areas with high annual precipitation. In particular, rainfall estimates in western Greece have a strong positive bias. On the other hand, the TRMM 3B42 product shows low correlation (CC=0.45) against rain gauge observations and slightly underestimates rainfall. This study is a first attempt to evaluate and compare the newly introduced GPM-IMERG and the TRMM 3B42 rainfall products at daily timescale over Greece.

Alluvial groundwater recharge estimation in semi-arid environment using remotely sensed data

NASA Astrophysics Data System (ADS)

Coelho, Victor Hugo R.; Montenegro, Suzana; Almeida, Cristiano N.; Silva, Bernardo B.; Oliveira, Leidjane M.; Gusmão, Ana Cláudia V.; Freitas, Emerson S.; Montenegro, Abelardo A. A.

2017-05-01

Data limitations on groundwater (GW) recharge over large areas are still a challenge for efficient water resource management, especially in semi-arid regions. Thus, this study seeks to integrate hydrological cycle variables from satellite imagery to estimate the spatial distribution of GW recharge in the Ipanema river basin (IRB), which is located in the State of Pernambuco in Northeast Brazil. Remote sensing data, including monthly maps (2011-2012) of rainfall, runoff and evapotranspiration, are used as input for the water balance method within Geographic Information Systems (GIS). Rainfall data are derived from the TRMM Multi-satellite Precipitation Analysis (TMPA) Version 7 (3B43V7) product and present the same monthly average temporal distributions from 15 rain gauges that are distributed over the study area (r = 0.93 and MAE = 12.7 mm), with annual average estimates of 894.3 (2011) and 300.7 mm (2012). The runoff from the Natural Resources Conservation Service (NRCS) method, which is based on regional soil information and Thematic Mapper (TM) sensor image, represents 29% of the TMPA rainfall that was observed across two years of study. Actual evapotranspiration data, which were provided by the SEBAL application of MODIS images, present annual averages of 1213 (2011) and 1067 (2012) mm. The water balance results reveal a large inter-annual difference in the IRB GW recharge, which is characterized by different rainfall regimes, with averages of 30.4 (2011) and 4.7 (2012) mm year-1. These recharges were mainly observed between January and July in regions with alluvial sediments and highly permeable soils. The GW recharge approach with remote sensing is compared to the WTF (Water Table Fluctuation) method, which is used in an area of alluvium in the IRB. The estimates from these two methods exhibit reliable annual agreement, with average values of 154.6 (WTF) and 124.6 (water balance) mm in 2011. These values correspond to 14.89 and 13.53% of the rainfall that was recorded at the rain gauges and the TMPA, respectively. Only the WTF method indicates a very low recharge of 15.9 mm for the second year. The values in this paper provide reliable insight regarding the use of remotely sensed data to evaluate the rates of alluvial GW recharge in regions where the potential runoff cannot be disregarded from WB equation and must be calculated spatially.

An improved procedure for the validation of satellite-based precipitation estimates

NASA Astrophysics Data System (ADS)

Tang, Ling; Tian, Yudong; Yan, Fang; Habib, Emad

2015-09-01

The objective of this study is to propose and test a new procedure to improve the validation of remote-sensing, high-resolution precipitation estimates. Our recent studies show that many conventional validation measures do not accurately capture the unique error characteristics in precipitation estimates to better inform both data producers and users. The proposed new validation procedure has two steps: 1) an error decomposition approach to separate the total retrieval error into three independent components: hit error, false precipitation and missed precipitation; and 2) the hit error is further analyzed based on a multiplicative error model. In the multiplicative error model, the error features are captured by three model parameters. In this way, the multiplicative error model separates systematic and random errors, leading to more accurate quantification of the uncertainties. The proposed procedure is used to quantitatively evaluate the recent two versions (Version 6 and 7) of TRMM's Multi-sensor Precipitation Analysis (TMPA) real-time and research product suite (3B42 and 3B42RT) for seven years (2005-2011) over the continental United States (CONUS). The gauge-based National Centers for Environmental Prediction (NCEP) Climate Prediction Center (CPC) near-real-time daily precipitation analysis is used as the reference. In addition, the radar-based NCEP Stage IV precipitation data are also model-fitted to verify the effectiveness of the multiplicative error model. The results show that winter total bias is dominated by the missed precipitation over the west coastal areas and the Rocky Mountains, and the false precipitation over large areas in Midwest. The summer total bias is largely coming from the hit bias in Central US. Meanwhile, the new version (V7) tends to produce more rainfall in the higher rain rates, which moderates the significant underestimation exhibited in the previous V6 products. Moreover, the error analysis from the multiplicative error model provides a clear and concise picture of the systematic and random errors, with both versions of 3B42RT have higher errors in varying degrees than their research (post-real-time) counterparts. The new V7 algorithm shows obvious improvements in reducing random errors in both winter and summer seasons, compared to its predecessors V6. Stage IV, as expected, surpasses the satellite-based datasets in all the metrics over CONUS. Based on the results, we recommend the new procedure be adopted for routine validation of satellite-based precipitation datasets, and we expect the procedure will work effectively for higher resolution data to be produced in the Global Precipitation Measurement (GPM) era.

Design of a 15N Molecular Unit to Achieve Long Retention of Hyperpolarized Spin State

NASA Astrophysics Data System (ADS)

Nonaka, Hiroshi; Hirano, Masashi; Imakura, Yuki; Takakusagi, Yoichi; Ichikawa, Kazuhiro; Sando, Shinsuke

2017-01-01

Nuclear hyperpolarization is a phenomenon that can be used to improve the sensitivity of magnetic resonance molecular sensors. However, such sensors typically suffer from short hyperpolarization lifetime. Herein we report that [15N, D14]trimethylphenylammonium (TMPA) has a remarkably long spin-lattice relaxation time (1128 s, 14.1 T, 30 °C, D2O) on its 15N nuclei and achieves a long retention of the hyperpolarized state. [15N, D14]TMPA-based hyperpolarized sensor for carboxylesterase allowed the highly sensitive analysis of enzymatic reaction by 15N NMR for over 40 min in phophate-buffered saline (H2O, pH 7.4, 37 °C).

High-resolution Monthly Satellite Precipitation Product over the Conterminous United States

NASA Astrophysics Data System (ADS)

Hashemi, H.; Fayne, J.; Knight, R. J.; Lakshmi, V.

2017-12-01

We present a data set that enhanced the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) monthly product 3B43 in its accuracy and spatial resolution. For this, we developed a correction function to improve the accuracy of TRMM 3B43, spatial resolution of 25 km, by estimating and removing the bias in the satellite data using a ground-based precipitation data set. We observed a strong relationship between the bias and land surface elevation; TRMM 3B43 tends to underestimate the ground-based product at elevations above 1500 m above mean sea level (m.amsl) over the conterminous United States. A relationship was developed between satellite bias and elevation. We then resampled TRMM 3B43 to the Digital Elevation Model (DEM) data set at a spatial resolution of 30 arc second ( 1 km on the ground). The produced high-resolution satellite-based data set was corrected using the developed correction function based on the bias-elevation relationship. Assuming that each rain gauge represents an area of 1 km2, we verified our product against 9,200 rain gauges across the conterminous United States. The new product was compared with the gauges, which have 50, 60, 70, 80, 90, and 100% temporal coverage within the TRMM period of 1998 to 2015. Comparisons between the high-resolution corrected satellite-based data and gauges showed an excellent agreement. The new product captured more detail in the changes in precipitation over the mountainous region than the original TRMM 3B43.

Variations/Changes in Daily Precipitation Extremes Derived from Satellite-Based Products

NASA Astrophysics Data System (ADS)

Gu, G.; Adler, R. F.

2017-12-01

Interannual/decadal-scale variations/changes in daily precipitation extremes are investigated by means of satellite-based high-spatiotemporal resolution precipitation products, including TRMM-TMPA, PERSIANN-CDR-Daily, GPCP 1DD, etc. Extreme precipitation indices at grids are first defined, including the maximum daily precipitation amount (Rx1day), the simple precipitation intensity index (SDII), the conditional (Rcond) daily precipitation rate (Pr>0 mm day-1), and monthly frequencies of rainy (FOCc) and wet (FOCw) days. Other two precipitation intensity indices, i.e., mean daily precipitation rates for Pr ≥10 mm day-1 (Pr10II) and for Pr ≥ 20 mm day-1 (Pr20II), are also constructed. Consistency analyses of daily extreme indices among these data sets are then performed by comparing corresponding averages over large domains such as tropical (30oN-30oS) land, ocean, land+ocean, for their common period (post-1997). This can provide a preliminary uncertainty analysis of these data sets in describing daily extreme precipitation events. Discrepancies can readily be found among these products regarding the magnitudes of area-averaged extreme indices. However, generally consistent temporal variations can be found among the indices derived from different satellite products. Interannual variability in daily precipitation extremes are then examined and compared at grids by exploring their relations with the El Nino-Southern Oscillation (ENSO). Linear correlation and composite analyses are used to examine the impact of ENSO on these extreme indices at grids and over large domains during the post-1997 period. Decadal-scale variability/change in daily extreme events is further examined by using the PERSIANN-CDR-Daily that can cover the entire post-1983 period, based on its general consistency with other two products during the post-1979 period. We specifically focus on exploring and discriminating the effects of decadal-scale internal variability such as the Pacific Decadal Oscillation (PDO) and anthropogenic forcings including the greenhouse-gases (GHG) related warming. Comparisons are also made over global land with the results from two gridded daily rain-gauge products, GPCC Full-record daily (1988-2013) and NOAA/CPC Unified daily (1979-present).

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, 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), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme precipitation events is also provided. Furthermore, this work is part of a broader effort to evaluate long-term multi-sensor QPEs in the perspective of developing Climate Data Records (CDRs) for precipitation.

Application of satellite precipitation data to analyse and model arbovirus activity in the tropics

PubMed Central

2011-01-01

Background Murray Valley encephalitis virus (MVEV) is a mosquito-borne Flavivirus (Flaviviridae: Flavivirus) which is closely related to Japanese encephalitis virus, West Nile virus and St. Louis encephalitis virus. MVEV is enzootic in northern Australia and Papua New Guinea and epizootic in other parts of Australia. Activity of MVEV in Western Australia (WA) is monitored by detection of seroconversions in flocks of sentinel chickens at selected sample sites throughout WA. Rainfall is a major environmental factor influencing MVEV activity. Utilising data on rainfall and seroconversions, statistical relationships between MVEV occurrence and rainfall can be determined. These relationships can be used to predict MVEV activity which, in turn, provides the general public with important information about disease transmission risk. Since ground measurements of rainfall are sparse and irregularly distributed, especially in north WA where rainfall is spatially and temporally highly variable, alternative data sources such as remote sensing (RS) data represent an attractive alternative to ground measurements. However, a number of competing alternatives are available and careful evaluation is essential to determine the most appropriate product for a given problem. Results The Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 product was chosen from a range of RS rainfall products to develop rainfall-based predictor variables and build logistic regression models for the prediction of MVEV activity in the Kimberley and Pilbara regions of WA. Two models employing monthly time-lagged rainfall variables showed the strongest discriminatory ability of 0.74 and 0.80 as measured by the Receiver Operating Characteristics area under the curve (ROC AUC). Conclusions TMPA data provide a state-of-the-art data source for the development of rainfall-based predictive models for Flavivirus activity in tropical WA. Compared to ground measurements these data have the advantage of being collected spatially regularly, irrespective of remoteness. We found that increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Pilbara at a time-lag of two months. Increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Kimberley at a lag of three months. PMID:21255449

Utilizing Satellite Precipitation Products to Understand the Link Between Climate Variability and Malaria

NASA Astrophysics Data System (ADS)

Maggioni, V.; Mousam, A.; Delamater, P. L.; Cash, B. A.; Quispe, A.

2015-12-01

Malaria is a public health threat to people globally leading to 198 million cases and 584,000 deaths annually. Outbreaks of vector borne diseases such as malaria can be significantly impacted by climate variables such as precipitation. For example, an increase in rainfall has the potential to create pools of water that can serve as breeding locations for mosquitos. Peru is a country that is currently controlling malaria, but has not been able to completely eliminate the disease. Despite the various initiatives in order to control malaria - including regional efforts to improve surveillance, early detection, prompt treatment, and vector management - malaria cases in Peru have risen between 2011 and 2014. The purpose of this study is to test the hypothesis that climate variability plays a fundamental role in malaria occurrence over a 12-year period (2003-2014) in Peru. When analyzing climate variability, it is important to obtain high-quality, high-resolution data for a time series long enough to draw conclusion about how climate variables have been and are changing. Remote sensing is a powerful tool for measuring and monitoring climate variables continuously in time and space. A widely used satellite-based precipitation product, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), available globally since 1998, was used to obtain 3-hourly data with a spatial resolution of 0.25° x 0.25°. The precipitation data was linked to weekly (2003-2014) malaria cases collected by health centers and available at a district level all over Peru to investigate the relationship between precipitation and the seasonal and annual variations in malaria incidence. Further studies will incorporate additional climate variables such as temperature, humidity, soil moisture, and surface pressure from remote sensing data products and climate models. Ultimately, this research will help us to understand if climate variability impacts malaria incidence rates and to determine which regions of the country are most affected.

Access NASA Satellite Global Precipitation Data Visualization on YouTube

NASA Technical Reports Server (NTRS)

Liu, Z.; Su, J.; Acker, J.; Huffman, G.; Vollmer, B.; Wei, J.; Meyer, D.

2017-01-01

Since the satellite era began, NASA has collected a large volume of Earth science observations for research and applications around the world. The collected and archived satellite data at 12 NASA data centers can also be used for STEM education and activities such as disaster events, climate change, etc. However, accessing satellite data can be a daunting task for non-professional users such as teachers and students because of unfamiliarity of terminology, disciplines, data formats, data structures, computing resources, processing software, programming languages, etc. Over the years, many efforts including tools, training classes, and tutorials have been developed to improve satellite data access for users, but barriers still exist for non-professionals. In this presentation, we will present our latest activity that uses a very popular online video sharing Web site, YouTube (https://www.youtube.com/), for accessing visualizations of our global precipitation datasets at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). With YouTube, users can access and visualize a large volume of satellite data without the necessity to learn new software or download data. The dataset in this activity is a one-month animation for the GPM (Global Precipitation Measurement) Integrated Multi-satellite Retrievals for GPM (IMERG). IMERG provides precipitation on a near-global (60 deg. N-S) coverage at half-hourly time interval, providing more details on precipitation processes and development compared to the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multisatellite Precipitation Analysis (TMPA, 3B42) product. When the retro-processing of IMERG during the TRMM era is finished in 2018, the entire video will contain more than 330,000 files and will last 3.6 hours. Future plans include development of flyover videos for orbital data for an entire satellite mission or project. All videos, including the one-month animation, will be uploaded and available at the GES DISC site on YouTube (https://www.youtube.com/user/NASAGESDISC).

Day 1 for the Integrated Multi-Satellite Retrievals for GPM (IMERG) Data Sets

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K. L.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

2014-12-01

The Integrated Multi-satellitE Retrievals for GPM (IMERG) is designed to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG was developed to use GPM Core Observatory data as a reference for the international constellation of satellites of opportunity that constitute the GPM virtual constellation. Computationally, IMERG is a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design, development, testing, and current status. IMERG provides 0.1°x0.1° half-hourly data, and will be run at multiple times, providing successively more accurate estimates: 4 hours, 8 hours, and 2 months after observation time. In Day 1 the spatial extent is 60°N-S, for the period March 2014 to the present. In subsequent reprocessing the data will extend to fully global, covering the period 1998 to the present. Both the set of input data set retrievals and the IMERG system are substantially different than those used in previous U.S. products. The input passive microwave data are all being produced with GPROF2014, which is substantially upgraded compared to previous versions. For the first time, this includes microwave sounders. Accordingly, there is a strong need to carefully check the initial test data sets for performance. IMERG output will be illustrated using pre-operational test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. Finally, we will summarize the expected release of various output products, and the subsequent reprocessing sequence.

Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia

NASA Astrophysics Data System (ADS)

Tekeli, Ahmet Emre; Fouli, Hesham

2016-10-01

Floods are among the most common disasters harming humanity. In particular, flash floods cause hazards to life, property and any type of structures. Arid and semi-arid regions are equally prone to flash floods like regions with abundant rainfall. Despite rareness of intensive and frequent rainfall events over Kingdom of Saudi Arabia (KSA); an arid/semi-arid region, occasional flash floods occur and result in large amounts of damaging surface runoff. The flooding of 16 November, 2013 in Riyadh; the capital city of KSA, resulted in killing some people and led to much property damage. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) Real Time (RT) data (3B42RT) are used herein for flash flood forecasting. 3B42RT detected high-intensity rainfall events matching with the distribution of observed floods over KSA. A flood early warning system based on exceedance of threshold limits on 3B42RT data is proposed for Riyadh. Three different indexes: Constant Threshold (CT), Cumulative Distribution Functions (CDF) and Riyadh Flood Precipitation Index (RFPI) are developed using 14-year 3B42RT data from 2000 to 2013. RFPI and CDF with 90% captured the three major flooding events that occurred in February 2005, May 2010 and November 2013 in Riyadh. CT with 3 mm/h intensity indicated the 2013 flooding, but missed those of 2005 and 2010. The methodology implemented herein is a first-step simple and accurate way for flash flood forecasting over Riyadh. The simplicity of the methodology enables its applicability for the TRMM follow-on missions like Global Precipitation Measurement (GPM) mission.

Remote sensing-based characterization of rainfall during atmospheric rivers over the central United States

NASA Astrophysics Data System (ADS)

Nayak, Munir A.; Villarini, Gabriele

2018-01-01

Atmospheric rivers (ARs) play a central role in the hydrology and hydroclimatology of the central United States. More than 25% of the annual rainfall is associated with ARs over much of this region, with many large flood events tied to their occurrence. Despite the relevance of these storms for flood hydrology and water budget, the characteristics of rainfall associated with ARs over the central United has not been investigated thus far. This study fills this major scientific gap by describing the rainfall during ARs over the central United States using five remote sensing-based precipitation products over a 12-year study period. The products we consider are: Stage IV, Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH). As part of the study, we evaluate these products against a rain gauge-based dataset using both graphical- and metrics-based diagnostics. Based on our analyses, Stage IV is found to better reproduce the reference data. Hence, we use it for the characterization of rainfall in ARs. Most of the AR-rainfall is located in a narrow region within ∼150 km on both sides of the AR major axis. In this region, rainfall has a pronounced positive relationship with the magnitude of the water vapor transport. Moreover, we have also identified a consistent increase in rainfall intensity with duration (or persistence) of AR conditions. However, there is not a strong indication of diurnal variability in AR rainfall. These results can be directly used in developing flood protection strategies during ARs. Further, weather prediction agencies can benefit from the results of this study to achieve higher skill of resolving precipitation processes in their models.

Demonstration of a longitudinal concentration gradient along scala tympani by sequential sampling of perilymph from the cochlear apex.

PubMed

Mynatt, Robert; Hale, Shane A; Gill, Ruth M; Plontke, Stefan K; Salt, Alec N

2006-06-01

Local applications of drugs to the inner ear are increasingly being used to treat patients' inner ear disorders. Knowledge of the pharmacokinetics of drugs in the inner ear fluids is essential for a scientific basis for such treatments. When auditory function is of primary interest, the drug's kinetics in scala tympani (ST) must be established. Measurement of drug levels in ST is technically difficult because of the known contamination of perilymph samples taken from the basal cochlear turn with cerebrospinal fluid (CSF). Recently, we reported a technique in which perilymph was sampled from the cochlear apex to minimize the influence of CSF contamination (J. Neurosci. Methods, doi: 10.1016/j.jneumeth.2005.10.008 ). This technique has now been extended by taking smaller fluid samples sequentially from the cochlear apex, which can be used to quantify drug gradients along ST. The sampling and analysis methods were evaluated using an ionic marker, trimethylphenylammonium (TMPA), that was applied to the round window membrane. After loading perilymph with TMPA, 10 1-muL samples were taken from the cochlear apex. The TMPA content of the samples was consistent with the first sample containing perilymph from apical regions and the fourth or fifth sample containing perilymph from the basal turn. TMPA concentration decreased in subsequent samples, as they increasingly contained CSF that had passed through ST. Sample concentration curves were interpreted quantitatively by simulation of the experiment with a finite element model and by an automated curve-fitting method by which the apical-basal gradient was estimated. The study demonstrates that sequential apical sampling provides drug gradient data for ST perilymph while avoiding the major distortions of sample composition associated with basal turn sampling. The method can be used for any substance for which a sensitive assay is available and is therefore of high relevance for the development of preclinical and clinical strategies for local drug delivery to the inner ear.

Demonstration of a Longitudinal Concentration Gradient Along Scala Tympani by Sequential Sampling of Perilymph from the Cochlear Apex

PubMed Central

Mynatt, Robert; Hale, Shane A.; Gill, Ruth M.; Plontke, Stefan K.

2006-01-01

ABSTRACT Local applications of drugs to the inner ear are increasingly being used to treat patients' inner ear disorders. Knowledge of the pharmacokinetics of drugs in the inner ear fluids is essential for a scientific basis for such treatments. When auditory function is of primary interest, the drug's kinetics in scala tympani (ST) must be established. Measurement of drug levels in ST is technically difficult because of the known contamination of perilymph samples taken from the basal cochlear turn with cerebrospinal fluid (CSF). Recently, we reported a technique in which perilymph was sampled from the cochlear apex to minimize the influence of CSF contamination (J. Neurosci. Methods, doi: http://10.1016/j.jneumeth.2005.10.008). This technique has now been extended by taking smaller fluid samples sequentially from the cochlear apex, which can be used to quantify drug gradients along ST. The sampling and analysis methods were evaluated using an ionic marker, trimethylphenylammonium (TMPA), that was applied to the round window membrane. After loading perilymph with TMPA, 10 1-μL samples were taken from the cochlear apex. The TMPA content of the samples was consistent with the first sample containing perilymph from apical regions and the fourth or fifth sample containing perilymph from the basal turn. TMPA concentration decreased in subsequent samples, as they increasingly contained CSF that had passed through ST. Sample concentration curves were interpreted quantitatively by simulation of the experiment with a finite element model and by an automated curve-fitting method by which the apical–basal gradient was estimated. The study demonstrates that sequential apical sampling provides drug gradient data for ST perilymph while avoiding the major distortions of sample composition associated with basal turn sampling. The method can be used for any substance for which a sensitive assay is available and is therefore of high relevance for the development of preclinical and clinical strategies for local drug delivery to the inner ear. PMID:16718612

Transfer of Satellite Rainfall Uncertainty from Gauged to Ungauged Regions at Regional and Seasonal Timescales

NASA Technical Reports Server (NTRS)

Tang, Ling; Hossain, Faisal; Huffman, George J.

2010-01-01

Hydrologists and other users need to know the uncertainty of the satellite rainfall data sets across the range of time/space scales over the whole domain of the data set. Here, uncertainty' refers to the general concept of the deviation' of an estimate from the reference (or ground truth) where the deviation may be defined in multiple ways. This uncertainty information can provide insight to the user on the realistic limits of utility, such as hydrologic predictability, that can be achieved with these satellite rainfall data sets. However, satellite rainfall uncertainty estimation requires ground validation (GV) precipitation data. On the other hand, satellite data will be most useful over regions that lack GV data, for example developing countries. This paper addresses the open issues for developing an appropriate uncertainty transfer scheme that can routinely estimate various uncertainty metrics across the globe by leveraging a combination of spatially-dense GV data and temporally sparse surrogate (or proxy) GV data, such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar and the Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar. The TRMM Multi-satellite Precipitation Analysis (TMPA) products over the US spanning a record of 6 years are used as a representative example of satellite rainfall. It is shown that there exists a quantifiable spatial structure in the uncertainty of satellite data for spatial interpolation. Probabilistic analysis of sampling offered by the existing constellation of passive microwave sensors indicate that transfer of uncertainty for hydrologic applications may be effective at daily time scales or higher during the GPM era. Finally, a commonly used spatial interpolation technique (kriging), that leverages the spatial correlation of estimation uncertainty, is assessed at climatologic, seasonal, monthly and weekly timescales. It is found that the effectiveness of kriging is sensitive to the type of uncertainty metric, time scale of transfer and the density of GV data within the transfer domain. Transfer accuracy is lowest at weekly timescales with the error doubling from monthly to weekly.However, at very low GV data density (<20% of the domain), the transfer accuracy is too low to show any distinction as a function of the timescale of transfer.

Satellite-based Flood Modeling Using TRMM-based Rainfall Products.

PubMed

Harris, Amanda; Rahman, Sayma; Hossain, Faisal; Yarborough, Lance; Bagtzoglou, Amvrossios C; Easson, Greg

2007-12-20

Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25 o to 0.50 o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km² Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA's Tropical Rainfall Measuring Mission (TRMM) Multi-satellitePrecipitation Analysis (TMPA) product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

Quantification of solute entry into cochlear perilymph through the round window membrane.

PubMed

Salt, A N; Ma, Y

2001-04-01

The administration of drugs to the inner ear via the round window membrane is becoming more widely used for both clinical and experimental purposes. The actual drug levels achieved in different regions of the inner ear by this method have not been established. The present study has made use of simulations of solute movements in the cochlear fluids to describe the distribution of a marker solute in the guinea pig cochlear fluid spaces. Simulation parameters were derived from experimental measurements using a marker ion, trimethylphenylammonium (TMPA). The distribution of this ion in the cochlea was monitored without volume disturbance using TMPA-selective microelectrodes sealed into the first and second turns of scala tympani (ST). TMPA was applied to perilymph by irrigation of the intact round window membrane with 2 mM solution. At the end of a 90 min application period, TMPA in the first turn, 1.4 mm from the base of ST, reached an average concentration of 330 microM (standard deviation (S.D.) 147 microM, n = 8). TMPA in the second turn, 7.5 mm from the base of ST reached a concentration of 15 microM (S.D. 33 microM, n = 5). The measured time courses of TMPA concentration change were interpreted using the Washington University Cochlear Fluids Simulator (V 1.4), a public-domain program available on the internet at http ://oto.wustl.edu/cochlea/. Simulations with parameters producing concentration time courses comparable to those measured were: (1) round window permeability: 1.9 x 10(-80 cm/s; (2) ST clearance half-time: 60 min; (3) longitudinal perilymph flow rate: 4.4 nl/min, directed from base to apex. Solute concentrations in apical regions of the cochlea were found to be determined primarily by the rate at which the solute diffuses, balanced by the rate of clearance of the solute from perilymph. Longitudinal perilymph flow was not an important factor in solute distribution unless the bony otic capsule was perforated, which rapidly caused substantial changes to solute distribution. This study demonstrates the basic processes by which substances are distributed in the cochlea and provides a foundation to understand how other applied substances will be distributed in the ear.

Temporal and spatial evaluation of satellite rainfall estimates over different regions in Latin-America.

NASA Astrophysics Data System (ADS)

Villanueva, O. M. B.; Zambrano-Bigiarini, M.; Ribbe, L.; Nauditt, A.; Rebolledo Coy, M. A.; Xuan Thinh, N.; Bartz-Beielstein, T.

2017-12-01

In developing countries an accurate representation of the spatio-temporal variability of catchment rainfall inputs is currently severely limited. This issue can be overcame with the use of satellite rainfall estimates (SREs), which provide rainfall data in such environments for a wide range of hydrological applications, such as extreme events analysis and water accounting. Three different basins in Latin-America (Imperial Basin in Chile, Paraiba do Sul in Brazil and Magdalena in Colombia) were evaluated with a point-to-pixel analysis to determine the best SRE for further hydrological modelling. For this purpose, daily values of six state-of-the-art SRE products (TMPA 3B42v7, TMPA 3B42RT, CHIRPSv2, CMORPH, PERSIANN-CDR and MSWEPv1.2) were evaluated at annual and seasonal scales. The modified Kling-Gupta Efficiency (KGE') was used to evaluate the linear correlation, variability and bias relationship between satellite data and observations. Also, two categorical indices (POD and fBias) were used to assess product performance for different rainfall intensities. The results showed that for the southern Imperial River Basin PERSIANN-CDR presented the best performance at the annual scale, while TRMM 3B42v7 and PERSIANN-CDR had the best performance in a seasonal basis. In the Brazilian Paraiba do Sul, MSWEP performed the best in annual and seasonal basis. For the Magdalena Basin, CHIRPS and TRMM 3B42RT presented the highest performance in the seasonal analysis, while CHIRPS showed the best annual performance. When the bias term of the modified KGE' was removed from KGE', it was observed that the best evaluated SRE was not necessarily the one that have the highest linear correlation and variability relation with the observed data. In the categorical indices, all SREs showed a good detection in no-rain events, but low skill classifying days with precipitation. Nevertheless, all SREs performed relatively well identifying moderate rain events in all regions. We finally conclude that there is not a best performing SRE over all, a specific assessment is required to determine which SRE is the most suitable for each region. However, SREs show promising potential to be used for hydrological studies, and they must be taken in to account in order to derive better rainfall estimates.

Applications of TRMM-based Multi-Satellite Precipitation Estimation for Global Runoff Simulation: Prototyping a Global Flood Monitoring System

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.; Pierce, Harold

2008-01-01

Advances in flood monitoring/forecasting have been constrained by the difficulty in estimating rainfall continuously over space (catchment-, national-, continental-, or even global-scale areas) and flood-relevant time scale. With the recent availability of satellite rainfall estimates at fine time and space resolution, this paper describes a prototype research framework for global flood monitoring by combining real-time satellite observations with a database of global terrestrial characteristics through a hydrologically relevant modeling scheme. Four major components included in the framework are (1) real-time precipitation input from NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA); (2) a central geospatial database to preprocess the land surface characteristics: water divides, slopes, soils, land use, flow directions, flow accumulation, drainage network etc.; (3) a modified distributed hydrological model to convert rainfall to runoff and route the flow through the stream network in order to predict the timing and severity of the flood wave, and (4) an open-access web interface to quickly disseminate flood alerts for potential decision-making. Retrospective simulations for 1998-2006 demonstrate that the Global Flood Monitor (GFM) system performs consistently at both station and catchment levels. The GFM website (experimental version) has been running at near real-time in an effort to offer a cost-effective solution to the ultimate challenge of building natural disaster early warning systems for the data-sparse regions of the world. The interactive GFM website shows close-up maps of the flood risks overlaid on topography/population or integrated with the Google-Earth visualization tool. One additional capability, which extends forecast lead-time by assimilating QPF into the GFM, also will be implemented in the future.

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

NASA Astrophysics Data System (ADS)

Beck, H.; Vergopolan, N.; Pan, M.; Levizzani, V.; van Dijk, A.; Weedon, G. P.; Brocca, L.; Huffman, G. J.; Wood, E. F.; William, L.

2017-12-01

We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000-2016. Twelve non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76,086 gauges worldwide. Another ten gauge-corrected ones were evaluated using hydrological modeling, by calibrating the conceptual model HBV against streamflow records for each of 9053 small to medium-sized (<50,000 km2) catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR), the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and JRA-55) unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified and MSWEP V1.2 and V2.0) generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed those indirectly incorporating gauge data through other multi-source datasets (PERSIANN-CDR V1R1 and PGF). Our results highlight large differences in estimation accuracy, and hence, the importance of P dataset selection in both research and operational applications. The good performance of MSWEP emphasizes that careful data merging can exploit the complementary strengths of gauge-, satellite- and reanalysis-based P estimates.

SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

NASA Astrophysics Data System (ADS)

Ciabatta, Luca; Massari, Christian; Brocca, Luca; Gruber, Alexander; Reimer, Christoph; Hahn, Sebastian; Paulik, Christoph; Dorigo, Wouter; Kidd, Richard; Wagner, Wolfgang

2018-02-01

Accurate and long-term rainfall estimates are the main inputs for several applications, from crop modeling to climate analysis. In this study, we present a new rainfall data set (SM2RAIN-CCI) obtained from the inversion of the satellite soil moisture (SM) observations derived from the ESA Climate Change Initiative (CCI) via SM2RAIN (Brocca et al., 2014). Daily rainfall estimates are generated for an 18-year long period (1998-2015), with a spatial sampling of 0.25° on a global scale, and are based on the integration of the ACTIVE and the PASSIVE ESA CCI SM data sets.The quality of the SM2RAIN-CCI rainfall data set is evaluated by comparing it with two state-of-the-art rainfall satellite products, i.e. the Tropical Measurement Mission Multi-satellite Precipitation Analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH), and one modeled data set (ERA-Interim). A quality check is carried out on a global scale at 1° of spatial sampling and 5 days of temporal sampling by comparing these products with the gauge-based Global Precipitation Climatology Centre Full Data Daily (GPCC-FDD) product. SM2RAIN-CCI shows relatively good results in terms of correlation coefficient (median value > 0.56), root mean square difference (RMSD, median value < 10.34 mm over 5 days) and bias (median value < -14.44 %) during the evaluation period. The validation has been carried out at original resolution (0.25°) over Europe, Australia and five other areas worldwide to test the capabilities of the data set to correctly identify rainfall events under different climate and precipitation regimes.The SM2RAIN-CCI rainfall data set is freely available at https://doi.org/10.5281/zenodo.846259.

MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data

NASA Astrophysics Data System (ADS)

Beck, Hylke E.; van Dijk, Albert I. J. M.; Levizzani, Vincenzo; Schellekens, Jaap; Miralles, Diego G.; Martens, Brecht; de Roo, Ad

2017-01-01

Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979-2015 with a 3-hourly temporal and 0.25° spatial resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite- and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0 % of the stations and a median R of 0.67 vs. 0.44-0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments (< 50 000 km2) across the globe. Specifically, we calibrated the simple conceptual hydrological model HBV (Hydrologiska Byråns Vattenbalansavdelning) against daily Q observations with P from each of the different datasets. For the 1058 sparsely gauged catchments, representative of 83.9 % of the global land surface (excluding Antarctica), MSWEP obtained a median calibration NSE of 0.52 vs. 0.29-0.39 for the other P datasets. MSWEP is available via http://www.gloh2o.org.

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

PubMed Central

Harris, Amanda; Rahman, Sayma; Hossain, Faisal; Yarborough, Lance; Bagtzoglou, Amvrossios C.; Easson, Greg

2007-01-01

Increasingly available and a virtually uninterrupted supply of satellite-estimated rainfall data is gradually becoming a cost-effective source of input for flood prediction under a variety of circumstances. However, most real-time and quasi-global satellite rainfall products are currently available at spatial scales ranging from 0.25° to 0.50° and hence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scale flood events. This study assesses the question: what are the hydrologic implications of uncertainty of satellite rainfall data at the coarse scale? We investigated this question on the 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall product assessed was NASA's Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product called 3B41RT that is available in pseudo real time with a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data can improve application in flood prediction to some extent with the trade-off of more false alarms in peak flow. However, a more rational and regime-based adjustment procedure needs to be identified before the use of satellite data can be institutionalized among flood modelers. PMID:28903302

Entry of substances into perilymph through the bone of the otic capsule following intratympanic applicatons in guinea pigs: Implications for local drug delivery in humans

PubMed Central

Mikulec, Anthony A; Plontke, Stefan K.; Hartsock, Jared J.; Salt, Alec N.

2008-01-01

Introduction Drugs applied intratympanically in humans are believed to enter the cochlea primarily through the round window membrane (RWM). Local drug treatments of the ear are commonly evaluated in rodent models. The otic capsule is much thinner at the cochlear apex in rodents than in humans. We therefore investigated whether drugs applied to the middle ear could enter perilymph through the otic capsule as well as through the RWM. Methods The distribution of gentamicin and the marker trimethylphenylammonium (TMPA) along the guinea pig cochlea was assessed with sequential apical perilymph sampling following two delivery paradigms that included i) completely filling the tympanic bulla with solution, and ii) applying the solution to the RWM only. In addition, TMPA entry into perilymph of the third turn was measured with ion-selective electrodes while the bulla was filled with TMPA solution. Results In application protocols that allowed drug to contact the otic capsule (by completely filling the bulla) markedly higher drug concentrations were found in the apical, low-frequency regions of the cochlea compared with drug applications to the RWM only. Conclusions Gentamicin and TMPA can enter perilymph of guinea pigs through the RWM and simultaneously through the bony otic capsule. Drug distribution along the cochlea following intratympanic applications will therefore be dramatically different in rodents and humans. Results obtained from intratympanic drug treatments of animals, in which the bulla is filled with solution and contacts the bony capsule of the cochlea, do not provide a good model for the human situation. PMID:19180674

Merging Satellite Precipitation Products for Improved Streamflow Simulations

NASA Astrophysics Data System (ADS)

Maggioni, V.; Massari, C.; Barbetta, S.; Camici, S.; Brocca, L.

2017-12-01

Accurate quantitative precipitation estimation is of great importance for water resources management, agricultural planning and forecasting and monitoring of natural hazards such as flash floods and landslides. In situ observations are limited around the Earth, especially in remote areas (e.g., complex terrain, dense vegetation), but currently available satellite precipitation products are able to provide global precipitation estimates with an accuracy that depends upon many factors (e.g., type of storms, temporal sampling, season, etc.). The recent SM2RAIN approach proposes to estimate rainfall by using satellite soil moisture observations. As opposed to traditional satellite precipitation methods, which sense cloud properties to retrieve instantaneous estimates, this new bottom-up approach makes use of two consecutive soil moisture measurements for obtaining an estimate of the fallen precipitation within the interval between two satellite overpasses. As a result, the nature of the measurement is different and complementary to the one of classical precipitation products and could provide a different valid perspective to substitute or improve current rainfall estimates. Therefore, we propose to merge SM2RAIN and the widely used TMPA 3B42RT product across Italy for a 6-year period (2010-2015) at daily/0.25deg temporal/spatial scale. Two conceptually different merging techniques are compared to each other and evaluated in terms of different statistical metrics, including hit bias, threat score, false alarm rates, and missed rainfall volumes. The first is based on the maximization of the temporal correlation with a reference dataset, while the second is based on a Bayesian approach, which provides a probabilistic satellite precipitation estimate derived from the joint probability distribution of observations and satellite estimates. The merged precipitation products show a better performance with respect to the parental satellite-based products in terms of categorical statistics, as well as bias reduction and correlation coefficient, with the Bayesian approach being superior to other methods. A study case in the Tiber river basin is also presented to discuss the performance of forcing a hydrological model with the merged satellite precipitation product to simulate streamflow time series.

Bias Correction of Satellite Precipitation Products (SPPs) using a User-friendly Tool: A Step in Enhancing Technical Capacity

NASA Astrophysics Data System (ADS)

Rushi, B. R.; Ellenburg, W. L.; Adams, E. C.; Flores, A.; Limaye, A. S.; Valdés-Pineda, R.; Roy, T.; Valdés, J. B.; Mithieu, F.; Omondi, S.

2017-12-01

SERVIR, a joint NASA-USAID initiative, works to build capacity in Earth observation technologies in developing countries for improved environmental decision making in the arena of: weather and climate, water and disasters, food security and land use/land cover. SERVIR partners with leading regional organizations in Eastern and Southern Africa, Hindu Kush-Himalaya, Mekong region, and West Africa to achieve its objectives. SERVIR develops hydrological applications to address specific needs articulated by key stakeholders and daily rainfall estimates are a vital input for these applications. Satellite-derived rainfall is subjected to systemic biases which need to be corrected before it can be used for any hydrologic application such as real-time or seasonal forecasting. SERVIR and the SWAAT team at the University of Arizona, have co-developed an open-source and user friendly tool of rainfall bias correction approaches for SPPs. Bias correction tools were developed based on Linear Scaling and Quantile Mapping techniques. A set of SPPs, such as PERSIANN-CCS, TMPA-RT, and CMORPH, are bias corrected using Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data which incorporates ground based precipitation observations. This bias correction tools also contains a component, which is included to improve monthly mean of CHIRPS using precipitation products of the Global Surface Summary of the Day (GSOD) database developed by the National Climatic Data Center (NCDC). This tool takes input from command-line which makes it user-friendly and applicable in any operating platform without prior programming skills. This presentation will focus on this bias-correction tool for SPPs, including application scenarios.

Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling

NASA Astrophysics Data System (ADS)

Beck, Hylke E.; Vergopolan, Noemi; Pan, Ming; Levizzani, Vincenzo; van Dijk, Albert I. J. M.; Weedon, Graham P.; Brocca, Luca; Pappenberger, Florian; Huffman, George J.; Wood, Eric F.

2017-12-01

We undertook a comprehensive evaluation of 22 gridded (quasi-)global (sub-)daily precipitation (P) datasets for the period 2000-2016. Thirteen non-gauge-corrected P datasets were evaluated using daily P gauge observations from 76 086 gauges worldwide. Another nine gauge-corrected datasets were evaluated using hydrological modeling, by calibrating the HBV conceptual model against streamflow records for each of 9053 small to medium-sized ( < 50 000 km2) catchments worldwide, and comparing the resulting performance. Marked differences in spatio-temporal patterns and accuracy were found among the datasets. Among the uncorrected P datasets, the satellite- and reanalysis-based MSWEP-ng V1.2 and V2.0 datasets generally showed the best temporal correlations with the gauge observations, followed by the reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR) and the satellite- and reanalysis-based CHIRP V2.0 dataset, the estimates based primarily on passive microwave remote sensing of rainfall (CMORPH V1.0, GSMaP V5/6, and TMPA 3B42RT V7) or near-surface soil moisture (SM2RAIN-ASCAT), and finally, estimates based primarily on thermal infrared imagery (GridSat V1.0, PERSIANN, and PERSIANN-CCS). Two of the three reanalyses (ERA-Interim and JRA-55) unexpectedly obtained lower trend errors than the satellite datasets. Among the corrected P datasets, the ones directly incorporating daily gauge data (CPC Unified, and MSWEP V1.2 and V2.0) generally provided the best calibration scores, although the good performance of the fully gauge-based CPC Unified is unlikely to translate to sparsely or ungauged regions. Next best results were obtained with P estimates directly incorporating temporally coarser gauge data (CHIRPS V2.0, GPCP-1DD V1.2, TMPA 3B42 V7, and WFDEI-CRU), which in turn outperformed the one indirectly incorporating gauge data through another multi-source dataset (PERSIANN-CDR V1R1). Our results highlight large differences in estimation accuracy, and hence the importance of P dataset selection in both research and operational applications. The good performance of MSWEP emphasizes that careful data merging can exploit the complementary strengths of gauge-, satellite-, and reanalysis-based P estimates.

TRMM- and GPM-based precipitation analysis and modelling in the Tropical Andes

NASA Astrophysics Data System (ADS)

Manz, Bastian; Buytaert, Wouter; Zulkafli, Zed; Onof, Christian

2016-04-01

Despite wide-spread applications of satellite-based precipitation products (SPPs) throughout the TRMM-era, the scarcity of ground-based in-situ data (high density gauge networks, rainfall radar) in many hydro-meteorologically important regions, such as tropical mountain environments, has limited our ability to evaluate both SPPs and individual satellite-based sensors as well as accurately model or merge rainfall at high spatial resolutions, particularly with respect to extremes. This has restricted both the understanding of sensor behaviour and performance controls in such regions as well as the accuracy of precipitation estimates and respective hydrological applications ranging from water resources management to early warning systems. Here we report on our recent research into precipitation analysis and modelling using various TRMM and GPM products (2A25, 3B42 and IMERG) in the tropical Andes. In an initial study, 78 high-frequency (10-min) recording gauges in Colombia and Ecuador are used to generate a ground-based validation dataset for evaluation of instantaneous TRMM Precipitation Radar (TPR) overpasses from the 2A25 product. Detection ability, precipitation time-series, empirical distributions and statistical moments are evaluated with respect to regional climatological differences, seasonal behaviour, rainfall types and detection thresholds. Results confirmed previous findings from extra-tropical regions of over-estimation of low rainfall intensities and under-estimation of the highest 10% of rainfall intensities by the TPR. However, in spite of evident regionalised performance differences as a function of local climatological regimes, the TPR provides an accurate estimate of climatological annual and seasonal rainfall means. On this basis, high-resolution (5 km) climatological maps are derived for the entire tropical Andes. The second objective of this work is to improve the local precipitation estimation accuracy and representation of spatial patterns of extreme rainfall probabilities over the region. For this purpose, an ensemble of high-resolution rainfall fields is generated by stochastic simulation using space-time averaged, coarse-scale (daily, 0.25°) satellite-based rainfall inputs (TRMM 3B42/ -RT) and the high-resolution climatological information derived from the TPR as spatial disaggregation proxies. For evaluation and merging, gridded ground-based rainfall fields are generated from gauge data using sequential simulation. Satellite and ground-based ensembles are subsequently merged using an inverse error weighting scheme. The model was tested over a case study in the Colombian Andes with optional coarse-scale bias correction prior to disaggregation and merging. The resulting outputs were assessed in the context of Generalized Extreme Value theory and showed improved estimation of extreme rainfall probabilities compared to the original TMPA inputs. Initial findings using GPM-IMERG inputs are also presented.

Lewis Acid-Induced Change from Four- to Two-Electron Reduction of Dioxygen Catalyzed by Copper Complexes Using Scandium Triflate

PubMed Central

Kakuda, Saya; Rolle, Clarence; Ohkubo, Kei; Siegler, Maxime A.; Karlin, Kenneth D.; Fukuzumi, Shunichi

2015-01-01

Mononuclear copper complexes, [(tmpa)CuII(CH3CN)](ClO4)2 (1, tmpa = tris(2-pyridylmethyl)amine) and [(BzQ)CuII(H2O)2](ClO4)2 (2, BzQ = bis(2-quinolinylmethyl)benzylamine)], act as efficient catalysts for the selective two-electron reduction of O2 by ferrocene derivatives in the presence of scandium triflate (Sc(OTf)3), in acetone, whereas 1 catalyzes the four-electron reduction of O2 by the same reductant in the presence of Brønsted acids such as triflic acid. Following formation of the peroxo-bridged dicopper(II) complex [(tmpa)CuII(O2)CuII(tmpa)]2+, the two-electron reduced product of O2 with Sc3+ is observed to be scandium peroxide ([Sc3+(O22−)]+). In the presence of three equiv of hexamethylphosphoric triamide (HMPA), [Sc3+(O22−)]+ was oxidized by [Fe(bpy)3]3+ (bpy = 2,2′-bipyridine) to the known superoxide species [(HMPA)3Sc3+(O2•−)]2+ as detected by EPR spectroscopy. A kinetic study revealed that the rate-determining step of the catalytic cycle for the two-electron reduction of O2 with 1 is electron transfer from Fc* to 1 to give a cuprous complex which is highly reactive toward O2, whereas the rate-determining step with 2 is changed to the reaction of the cuprous complex with O2 following electron transfer from ferrocene derivatives to 2. The explanation for the change in catalytic O2-reaction stoichiometry from four-electron with Brønsted acids to two-electron reduction in the presence of Sc3+ and also for the change in the rate-determining step is clarified based on a kinetics interrogation of the overall catalytic cycle as well as each step of the catalytic cycle with study of the observed effects of Sc3+ on copper-oxygen intermediates. PMID:25659416

Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

NASA Astrophysics Data System (ADS)

Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

2018-01-01

The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

Synthesis and spectroscopy of micro-oxo (O(2)(-))-bridged heme/non-heme diiron complexes: models for the active site of nitric oxide reductase.

PubMed

Wasser, Ian M; Martens, Constantinus F; Verani, Claudio N; Rentschler, Eva; Huang, Hong-Wei; Moënne-Loccoz, Pierre; Zakharov, Lev N; Rheingold, Arnold L; Karlin, Kenneth D

2004-01-26

In this paper, we describe the synthesis and study of a series of heme/non-heme Fe-O-Fe' complexes supported by a porphyrin and the tripodal nitrogen ligand TMPA [TMPA = tris(2-pyridylmethyl)amine]. The complete synthesis of [((6)L)Fe-O-Fe(X)](+) (1) (X = OMe(-) or Cl(-), 69:31 ratio), where (6)L is the dianion of 5-(o-O-[(N,N-bis(2-pyridylmethyl)-2-(6-methoxyl)pyridinemethanamine)phenyl]-10,15,20-tris(2,6-difluorophenyl)porphine, is reported. The crystal structure for 1.PF(6) reveals an intramolecular heme/non-heme diferric complex bridged by an Fe-O-Fe' moiety; 90 degree angle (Fe-O-Fe') = 166.7(3) degrees, and d(Fe.Fe') = 3.556 A. Crystal data for C(70)H(57)ClF(12)Fe(2)N(8)O(3)P (1.PF(6)): triclinic, Ponemacr;, a = 13.185(3) A, b = 14.590 (3) A, c = 16.885(4) A, alpha = 104.219(4) degrees, beta = 91.572(4) degrees, gamma = 107.907(4) degrees, V = 2977.3(11) A(3), Z = 2, T = 150(2) K. Complex 1 (where X = Cl(-)) is further characterized by UV-vis (lambda(max) = 328, 416 (Soret), 569 nm), (1)H NMR (delta 27-24 [TMPA -CH(2)-], 16.1 [pyrrole-H], 15.2-10.5 [PY-3H, PY-5H], 7.9-7.2 [m- and p-phenyl-H], 6.9-5.8 [PY-4H] ppm), resonance Raman (nu(as)(Fe-O-Fe') 844 cm(-)(1)), and Mössbauer (delta(Fe) = 0.47, 0.41 mm/s; deltaE(A) = 1.59, 0.55 mm/s; 80 K) spectroscopies, MALDI-TOF mass spectrometry (m/z 1202), and SQUID susceptometry (J = - 114.82 cm(-)(1), S = 0). We have also synthesized a series of 3-, 4-, and 5-methyl-substituted as well as selectively deuterated TMPA(Fe') complexes and condensed these with the hydroxo complex (F(8))FeOH or (F(8)-d(8))FeOH to yield "untethered" Fe-O-Fe' analogues. Along with selective deuteration of the methylene hydrogens in TMPA, complete (1)H NMR spectroscopic assignments for 1 have been accomplished. The magnetic properties of several of the untethered complexes and a comparison to those of 1 are also presented. Complex 1 and related species represent good structural and spectroscopic models for the heme/non-heme diiron active site in the enzyme nitric oxide reductase.

Analysing the origin of rain- and subsurface water in seasonal wetlands of north-central Namibia

NASA Astrophysics Data System (ADS)

Hiyama, Tetsuya; Kanamori, Hironari; Kambatuku, Jack R.; Kotani, Ayumi; Asai, Kazuyoshi; Mizuochi, Hiroki; Fujioka, Yuichiro; Iijima, Morio

2017-03-01

We investigated the origins of rain- and subsurface waters of north-central Namibia’s seasonal wetlands, which are critical to the region’s water and food security. The region includes the southern part of the Cuvelai system seasonal wetlands (CSSWs) of the Cuvelai Basin, a transboundary river basin covering southern Angola and northern Namibia. We analysed stable water isotopes (SWIs) of hydrogen (HDO) and oxygen (H2 18O) in rainwater, surface water and shallow groundwater. Rainwater samples were collected during every rainfall event of the rainy season from October 2013 to April 2014. The isotopic ratios of HDO (δD) and oxygen H2 18O (δ 18O) were analysed in each rainwater sample and then used to derive the annual mean value of (δD, δ 18O) in precipitation weighted by each rainfall volume. Using delta diagrams (plotting δD vs. δ 18O), we showed that the annual mean value was a good indicator for determining the origins of subsurface waters in the CSSWs. To confirm the origins of rainwater and to explain the variations in isotopic ratios, we conducted atmospheric water budget analysis using Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA) data and ERA-Interim atmospheric reanalysis data. The results showed that around three-fourths of rainwater was derived from recycled water at local-regional scales. Satellite-observed outgoing longwave radiation (OLR) and complementary satellite data from MODerate-resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer (AMSR) series implied that the isotopic ratios in rainwater were affected by evaporation of raindrops falling from convective clouds. Consequently, integrated SWI analysis of rain-, surface and subsurface waters, together with the atmospheric water budget analysis, revealed that shallow groundwater of small wetlands in this region was very likely to be recharged from surface waters originating from local rainfall, which was temporarily pooled in small wetlands. This was also supported by tritium (3H) counting of the current rain- and subsurface waters in the region. We highly recommend that shallow groundwater not be pumped intensively to conserve surface and subsurface waters, both of which are important water resources in the region.

Transferring Error Characteristics of Satellite Rainfall Data from Ground Validation (gauged) into Non-ground Validation (ungauged)

NASA Astrophysics Data System (ADS)

Tang, L.; Hossain, F.

2009-12-01

Understanding the error characteristics of satellite rainfall data at different spatial/temporal scales is critical, especially when the scheduled Global Precipitation Mission (GPM) plans to provide High Resolution Precipitation Products (HRPPs) at global scales. Satellite rainfall data contain errors which need ground validation (GV) data for characterization, while satellite rainfall data will be most useful in the regions that are lacking in GV. Therefore, a critical step is to develop a spatial interpolation scheme for transferring the error characteristics of satellite rainfall data from GV regions to Non-GV regions. As a prelude to GPM, The TRMM Multi-satellite Precipitation Analysis (TMPA) products of 3B41RT and 3B42RT (Huffman et al., 2007) over the US spanning a record of 6 years are used as a representative example of satellite rainfall data. Next Generation Radar (NEXRAD) Stage IV rainfall data are used as the reference for GV data. Initial work by the authors (Tang et al., 2009, GRL) has shown promise in transferring error from GV to Non-GV regions, based on a six-year climatologic average of satellite rainfall data assuming only 50% of GV coverage. However, this transfer of error characteristics needs to be investigated for a range of GV data coverage. In addition, it is also important to investigate if proxy-GV data from an accurate space-borne sensor, such as the TRMM PR (or the GPM DPR), can be leveraged for the transfer of error at sparsely gauged regions. The specific question we ask in this study is, “what is the minimum coverage of GV data required for error transfer scheme to be implemented at acceptable accuracy in hydrological relevant scale?” Three geostatistical interpolation methods are compared: ordinary kriging, indicator kriging and disjunctive kriging. Various error metrics are assessed for transfer such as, Probability of Detection for rain and no rain, False Alarm Ratio, Frequency Bias, Critical Success Index, RMSE etc. Understanding the proper space-time scales at which these metrics can be reasonably transferred is also explored in this study. Keyword: Satellite rainfall, error transfer, spatial interpolation, kriging methods.

Perilymph sampling from the cochlear apex: a reliable method to obtain higher purity perilymph samples from scala tympani.

PubMed

Salt, Alec N; Hale, Shane A; Plonkte, Stefan K R

2006-05-15

Measurements of drug levels in the fluids of the inner ear are required to establish kinetic parameters and to determine the influence of specific local delivery protocols. For most substances, this requires cochlear fluids samples to be obtained for analysis. When auditory function is of primary interest, the drug level in the perilymph of scala tympani (ST) is most relevant, since drug in this scala has ready access to the auditory sensory cells. In many prior studies, ST perilymph samples have been obtained from the basal turn, either by aspiration through the round window membrane (RWM) or through an opening in the bony wall. A number of studies have demonstrated that such samples are likely to be contaminated with cerebrospinal fluid (CSF). CSF enters the basal turn of ST through the cochlear aqueduct when the bony capsule is perforated or when fluid is aspirated. The degree of sample contamination has, however, not been widely appreciated. Recent studies have shown that perilymph samples taken through the round window membrane are highly contaminated with CSF, with samples greater than 2microL in volume containing more CSF than perilymph. In spite of this knowledge, many groups continue to sample from the base of the cochlea, as it is a well-established method. We have developed an alternative, technically simple method to increase the proportion of ST perilymph in a fluid sample. The sample is taken from the apex of the cochlea, a site that is distant from the cochlear aqueduct. A previous problem with sampling through a perforation in the bone was that the native perilymph rapidly leaked out driven by CSF pressure and was lost to the middle ear space. We therefore developed a procedure to collect all the fluid that emerged from the perforated apex after perforation. We evaluated the method using a marker ion trimethylphenylammonium (TMPA). TMPA was applied to the perilymph of guinea pigs either by RW irrigation or by microinjection into the apical turn. The TMPA concentration of the fluid sample was compared with that measured in perilymph prior to taking the sample using a TMPA-selective microelectrode sealed into ST. Data were interpreted with a finite element model of the cochlear fluids that was used to simulate each aspect of the experiment. The correction of sample concentration back to the perilymph concentration prior to sampling can be performed based on the known ST volume (4.7microL in the guinea pig) and the sample volume. A more precise correction requires some knowledge of the profile of drug distribution along the cochlear prior to sampling. This method of sampling from the apex is technically simple and provides a larger sample volume with a greater proportion of perilymph compared to sampling through the RW.

Perilymph Sampling from the Cochlear Apex: A Reliable Method to Obtain Higher Purity Perilymph Samples from Scala Tympani

PubMed Central

Salt, Alec N.; Hale, Shane A.; Plontke, Stefan K. R.

2006-01-01

Measurements of drug levels in the fluids of the inner ear are required to establish kinetic parameters and to determine the influence of specific local delivery protocols. For most substances, this requires cochlear fluids samples to be obtained for analysis. When auditory function is of primary interest, the drug level in the perilymph of scala tympani (ST) is most relevant, since drug in this scala has ready access to the auditory sensory cells. In many prior studies, ST perilymph samples have been obtained from the basal turn, either by aspiration through the round window membrane (RWM) or through an opening in the bony wall. A number of studies have demonstrated that such samples are likely to be contaminated with cerebrospinal fluid (CSF). CSF enters the basal turn of ST through the cochlear aqueduct when the bony capsule is perforated or when fluid is aspirated. The degree of sample contamination has, however, not been widely appreciated. Recent studies have shown that perilymph samples taken through the round window membrane are highly contaminated with CSF, with samples greater than 2 μL in volume containing more CSF than perilymph. In spite of this knowledge, many groups continue to sample from the base of the cochlea, as it is a well-established method. We have developed an alternative, technically simple method to increase the proportion of ST perilymph in a fluid sample. The sample is taken from the apex of the cochlea, a site that is distant from the cochlear aqueduct. A previous problem with sampling through a perforation in the bone was that the native perilymph rapidly leaked out driven by CSF pressure and was lost to the middle ear space. We therefore developed a procedure to collect all the fluid that emerged from the perforated apex after perforation. We evaluated the method using a marker ion trimethylphenylammonium (TMPA). TMPA was applied to the perilymph of guinea pigs either by RW irrigation or by microinjection into the apical turn. The TMPA concentration of the fluid sample was compared with that measured in perilymph prior to taking the sample using a TMPA-selective microelectrode sealed into ST. Data were interpreted with a finite element model of the cochlear fluids that was used to simulate each aspect of the experiment. The correction of sample concentration back to the perilymph concentration prior to sampling can be performed based on the known ST volume (4.7 μL in the guinea pig) and the sample volume. A more precise correction requires some knowledge of the profile of drug distribution along the cochlear prior to sampling. This method of sampling from the apex is technically simple and provides a larger sample volume with a greater proportion of perilymph compared to sampling through the RW. PMID:16310856

Long-Term Large-Scale Bias-Adjusted Precipitation Estimates at High Spatial and Temporal Resolution Derived from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Precipitation Reanalysis over CONUS

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Seo, D. J.; Kim, B.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over Continental United States (CONUS) is nearly completed for the period covering from 2000 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network - Daily (GHCN-D) are used to adjust for those biases and to merge with the radar only product to provide a multi-sensor estimate. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. After assessing the bias and applying reduction or elimination techniques, we are investigating the kriging method and its variants such as simple kriging (SK), ordinary kriging (OK), and conditional bias-penalized Kriging (CBPK) among others. In addition we hope to generate estimates of uncertainty for the gridded estimate. In this work the methodology is presented as well as a comparison between the radar-only product and the final multi-sensor QPE product. The comparison is performed at various time scales from the sub-hourly, to annual. In addition, comparisons over the same period with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) are provided in order to give a detailed picture of the improvements and remaining challenges.

The Impact of Spatial and Temporal Resolutions in Tropical Summer Rainfall Distribution: Preliminary Results

NASA Astrophysics Data System (ADS)

Liu, Q.; Chiu, L. S.; Hao, X.

2017-10-01

The abundance or lack of rainfall affects peoples' life and activities. As a major component of the global hydrological cycle (Chokngamwong & Chiu, 2007), accurate representations at various spatial and temporal scales are crucial for a lot of decision making processes. Climate models show a warmer and wetter climate due to increases of Greenhouse Gases (GHG). However, the models' resolutions are often too coarse to be directly applicable to local scales that are useful for mitigation purposes. Hence disaggregation (downscaling) procedures are needed to transfer the coarse scale products to higher spatial and temporal resolutions. The aim of this paper is to examine the changes in the statistical parameters of rainfall at various spatial and temporal resolutions. The TRMM Multi-satellite Precipitation Analysis (TMPA) at 0.25 degree, 3 hourly grid rainfall data for a summer is aggregated to 0.5,1.0, 2.0 and 2.5 degree and at 6, 12, 24 hourly, pentad (five days) and monthly resolutions. The probability distributions (PDF) and cumulative distribution functions(CDF) of rain amount at these resolutions are computed and modeled as a mixed distribution. Parameters of the PDFs are compared using the Kolmogrov-Smironov (KS) test, both for the mixed and the marginal distribution. These distributions are shown to be distinct. The marginal distributions are fitted with Lognormal and Gamma distributions and it is found that the Gamma distributions fit much better than the Lognormal.

Perilymph pharmacokinetics of markers and dexamethasone applied and sampled at the lateral semi-circular canal.

PubMed

Salt, Alec N; Hartsock, Jared J; Gill, Ruth M; Piu, Fabrice; Plontke, Stefan K

2012-12-01

Perilymph pharmacokinetics was investigated by a novel approach, in which solutions containing drug or marker were injected from a pipette sealed into the perilymphatic space of the lateral semi-circular canal (LSCC). The cochlear aqueduct provides the outlet for fluid flow so this procedure allows almost the entire perilymph to be exchanged. After wait times of up to 4 h the injection pipette was removed and multiple, sequential samples of perilymph were collected from the LSCC. Fluid efflux at this site results from cerebrospinal fluid (CSF) entry into the basal turn of scala tympani (ST) so the samples allow drug levels from different locations in the ear to be defined. This method allows the rate of elimination of substances from the inner ear to be determined more reliably than with other delivery methods in which drug may only be applied to part of the ear. Results were compared for the markers trimethylphenylammonium (TMPA) and fluorescein and for the drug dexamethasone (Dex). For each substance, the concentration in fluid samples showed a progressive decrease as the delay time between injection and sampling was increased. This is consistent with the elimination of substance from the ear with time. The decline with time was slowest for fluorescein, was fastest for Dex, with TMPA at an intermediate rate. Simulations of the experiments showed that elimination occurred more rapidly from scala tympani (ST) than from scala vestibuli (SV). Calculated elimination half-times from ST averaged 54.1, 24.5 and 22.5 min for fluorescein, TMPA and Dex respectively and from SV 1730, 229 and 111 min respectively. The elimination of Dex from ST occurred considerably faster than previously appreciated. These pharmacokinetic parameters provide an important foundation for understanding of drug treatments of the inner ear.

Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

NASA Astrophysics Data System (ADS)

Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

2015-04-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to adjust the radar-only QPE product via an Inverse Distance Weighting (IDW) approach. In addition, we also investigate alternate adjustment techniques such as the kriging method and its variants (Simple Kriging: SK; Ordinary Kriging: OK; Conditional Bias-Penalized Kriging: CBPK). From this approach, we also hope to generate estimates of uncertainty for the gridded bias-adjusted QPE. Further comparison with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) is also provided in order to give a detailed picture of the improvements and remaining challenges.

Validating Microwave-Based Satellite Rain Rate Retrievals Over TRMM Ground Validation Sites

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Wolff, D. B.

2008-12-01

Multi-channel, passive microwave instruments are commonly used today to probe the structure of rain systems and to estimate surface rainfall from space. Until the advent of meteorological satellites and the development of remote sensing techniques for measuring precipitation from space, there was no observational system capable of providing accurate estimates of surface precipitation on global scales. Since the early 1970s, microwave measurements from satellites have provided quantitative estimates of surface rainfall by observing the emission and scattering processes due to the existence of clouds and precipitation in the atmosphere. This study assesses the relative performance of microwave precipitation estimates from seven polar-orbiting satellites and the TRMM TMI using four years (2003-2006) of instantaneous radar rain estimates obtained from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The seven polar orbiters include three different sensor types: SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), and AMSR-E. The TMI aboard the TRMM satellite flies in a sun asynchronous orbit between 35 S and 35 N latitudes. The rain information from these satellites are combined and used to generate several multi-satellite rain products, namely the Goddard TRMM Multi-satellite Precipitation Analysis (TMPA), NOAA's CPC Morphing Technique (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Instantaneous rain rates derived from each sensor were matched to the GV estimates in time and space at a resolution of 0.25 degrees. The study evaluates the measurement and error characteristics of the various satellite estimates through inter-comparisons with GV radar estimates. The GV rain observations provided an empirical ground-based reference for assessing the relative performance of each sensor and sensor class. Because the relative performance of the rain algorithms depends on the underlying surface terrain, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Relative to GV, AMSR-E and the TMI exhibited the highest correlation and skill over the full dynamic range of observed rain rates at both validation sites. The AMSU sensors, on the other hand, exhibited the lowest correlation and skill, though all sensors performed reasonably well compared to GV. The general tendency was for the microwave sensors to overestimate rain rates below 1 mm/hr where the sampling was highest and to underestimate the high rain rates above 10 mm/hr where the sampling was lowest. Underestimation of the low rain rate regime is attributed to difficulties of detecting and measuring low rain rates, while overestimation over the oceans was attributed largely to saturation of the brightness temperatures at high rain rates. Overall biases depended on the relative differences in the total rainfall at the extremes and the performance of each sensor at the nominal rain rates.

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2010-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSRE over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products. 3

Assessing the Relative Performance of Microwave-Based Satellite Rain Rate Retrievals Using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2011-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecasts of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (Aqua) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparisons with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellite estimates is examined via comparisons with space- and time-coincident GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25deg terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSR-E over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm/hr. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products.

Assessing the Relative Performance of Microwave-based Satellite Rain Rate Retrievals using TRMM Ground Validation Data

NASA Technical Reports Server (NTRS)

Wolff, David B.; Fisher, Brad L.

2008-01-01

Space-borne microwave sensors provide critical rain information used in several global multi-satellite rain products, which in turn are used for a variety of important studies, including landslide forecasting, flash flood warning, data assimilation, climate studies, and validation of model forecast of precipitation. This study employs four years (2003-2006) of satellite data to assess the relative performance and skill of SSM/I (F13, F14 and F15), AMSU-B (N15, N16 and N17), AMSR-E (AQUA) and the TRMM Microwave Imager (TMI) in estimating surface rainfall based on direct instantaneous comparison with ground-based rain estimates from Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) sites at Kwajalein, Republic of the Marshall Islands (KWAJ) and Melbourne, Florida (MELB). The relative performance of each of these satellites is examined via comparisons with GV radar-based rain rate estimates. Because underlying surface terrain is known to affect the relative performance of the satellite algorithms, the data for MELB was further stratified into ocean, land and coast categories using a 0.25 terrain mask. Of all the satellite estimates compared in this study, TMI and AMSR-E exhibited considerably higher correlations and skills in estimating/observing surface precipitation. While SSM/I and AMSU-B exhibited lower correlations and skills for each of the different terrain categories, the SSM/I absolute biases trended slightly lower than AMSRE over ocean, where the observations from both emission and scattering channels were used in the retrievals. AMSU-B exhibited the least skill relative to GV in all of the relevant statistical categories, and an anomalous spike was observed in the probability distribution functions near 1.0 mm hr-1. This statistical artifact appears to be related to attempts by algorithm developers to include some lighter rain rates, not easily detectable by its scatter-only frequencies. AMSU-B, however, agreed well with GV when the matching data was analyzed on monthly scales. These results signal developers of global rainfall products, such as the TRMM Multi-Satellite Precipitation Analysis (TMPA), and the Climate Data Center s Morphing (CMORPH) technique, that care must be taken when incorporating data from these input satellite estimates in order to provide the highest quality estimates in their products.

Using R for analysing spatio-temporal datasets: a satellite-based precipitation case study

NASA Astrophysics Data System (ADS)

Zambrano-Bigiarini, Mauricio

2017-04-01

Increasing computer power and the availability of remote-sensing data measuring different environmental variables has led to unprecedented opportunities for Earth sciences in recent decades. However, dealing with hundred or thousands of files, usually in different vectorial and raster formats and measured with different temporal frequencies, impose high computation challenges to take full advantage of all the available data. R is a language and environment for statistical computing and graphics which includes several functions for data manipulation, calculation and graphical display, which are particularly well suited for Earth sciences. In this work I describe how R was used to exhaustively evaluate seven state-of-the-art satellite-based rainfall estimates (SRE) products (TMPA 3B42v7, CHIRPSv2, CMORPH, PERSIANN-CDR, PERSIAN-CCS-adj, MSWEPv1.1 and PGFv3) over the complex topography and diverse climatic gradients of Chile. First, built-in functions were used to automatically download the satellite-images in different raster formats and spatial resolutions and to clip them into the Chilean spatial extent if necessary. Second, the raster package was used to read, plot, and conduct an exploratory data analysis in selected files of each SRE product, in order to detect unexpected problems (rotated spatial domains, order or variables in NetCDF files, etc). Third, raster was used along with the hydroTSM package to aggregate SRE files into different temporal scales (daily, monthly, seasonal, annual). Finally, the hydroTSM and hydroGOF packages were used to carry out a point-to-pixel comparison between precipitation time series measured at 366 stations and the corresponding grid cell of each SRE. The modified Kling-Gupta index of model performance was used to identify possible sources of systematic errors in each SRE, while five categorical indices (PC, POD, FAR, ETS, fBIAS) were used to assess the ability of each SRE to correctly identify different precipitation intensities. In the end, R proved to be and efficient environment to deal with thousands of raster, vectorial and time series files, with different spatial and temporal resolutions and spatial reference systems. In addition, the use of well-documented R scripts made code readable and re-usable, facilitating reproducible research which is essential to build trust in stakeholders and scientific community.

MSWEP V2 global 3-hourly 0.1° precipitation: methodology and quantitative appraisal

NASA Astrophysics Data System (ADS)

Beck, H.; Yang, L.; Pan, M.; Wood, E. F.; William, L.

2017-12-01

Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) V2, the first fully global gridded precipitation (P) dataset with a 0.1° spatial resolution. The dataset covers the period 1979-2016, has a 3-hourly temporal resolution, and was derived by optimally merging a wide range of data sources based on gauges (WorldClim, GHCN-D, GSOD, and others), satellites (CMORPH, GridSat, GSMaP, and TMPA 3B42RT), and reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR). MSWEP V2 implements some major improvements over V1, such as (i) the correction of distributional P biases using cumulative distribution function matching, (ii) increasing the spatial resolution from 0.25° to 0.1°, (iii) the inclusion of ocean areas, (iv) the addition of NCEP-CFSR P estimates, (v) the addition of thermal infrared-based P estimates for the pre-TRMM era, (vi) the addition of 0.1° daily interpolated gauge data, (vii) the use of a daily gauge correction scheme that accounts for regional differences in the 24-hour accumulation period of gauges, and (viii) extension of the data record to 2016. The gauge-based assessment of the reanalysis and satellite P datasets, necessary for establishing the merging weights, revealed that the reanalysis datasets strongly overestimate the P frequency for the entire globe, and that the satellite (resp. reanalysis) datasets consistently performed better at low (high) latitudes. Compared to other state-of-the-art P datasets, MSWEP V2 exhibits more plausible global patterns in mean annual P, percentiles, and annual number of dry days, and better resolves the small-scale variability over topographically complex terrain. Other P datasets appear to consistently underestimate P amounts over mountainous regions. Long-term mean P estimates for the global, land, and ocean domains based on MSWEP V2 are 959, 796, and 1026 mm/yr, respectively, in close agreement with the best previous published estimates.

Optimal Access to NASA Water Cycle Data for Water Resources Management

NASA Astrophysics Data System (ADS)

Teng, W. L.; Arctur, D. K.; Espinoza, G. E.; Rui, H.; Strub, R. F.; Vollmer, B.

2016-12-01

A "Digital Divide" in data representation exists between the preferred way of data access by the hydrology community (i.e., as time series of discrete spatial objects) and the common way of data archival by earth science data centers (i.e., as continuous spatial fields, one file per time step). This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. Hydrologic Information System (CUAHSI HIS) and NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). An optimal approach to bridging the Divide, developed by the GES DISC, is to reorganize data from the way they are archived to some way that is optimal for the desired method of data access. Specifically for CUAHSI HIS, selected data sets were reorganized into time series files, one per geographical "point." These time series files, termed "data rods," are pre-generated or virtual (generated on-the-fly). Data sets available as data rods include North American Land Data Assimilation System (NLDAS), Global Land Data Assimilation System (GLDAS), TRMM Multi-satellite Precipitation Analysis (TMPA), Land Parameter Retrieval Model (LPRM), Modern-Era Retrospective Analysis for Research and Applications (MERRA)-Land, and Groundwater and Soil Moisture Conditions from Gravity Recovery and Climate Experiment (GRACE) Data Assimilation drought indicators for North America Drought Monitor (GRACE-DA-DM). In order to easily avail the operational water resources community the benefits of optimally reorganized data, we have developed multiple methods of making these data more easily accessible and usable. These include direct access via RESTful Web services, a browser-based Web map and statistical tool for selected NLDAS variables for the U.S. (CONUS), a HydroShare app (Data Rods Explorer, under development) on the Tethys Platform, and access via the GEOSS Portal. Examples of drought-related applications of these data and data access methods are provided.

Rapid conversion of sorbitol to isosorbide in hydrophobic ionic liquids under microwave irradiation.

PubMed

Kamimura, Akio; Murata, Kengo; Tanaka, Yoshiki; Okagawa, Tomoki; Matsumoto, Hiroshi; Kaiso, Kouji; Yoshimoto, Makoto

2014-12-01

Sorbitol was effectively converted to isosorbide by treatment with [TMPA][NTf2 ] in the presence of catalytic amounts of TsOH under microwave heating at 180 °C. The reaction completed within 10 min and isosorbide was isolated to about 60%. Ionic liquids were readily recovered by an extraction treatment and reused several times. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Combining hydrological modeling and remote sensing observations to enable data-driven decision making for Devils Lake flood mitigation in a changing climate

NASA Astrophysics Data System (ADS)

Zhang, X.; Lim, Y. H.; Teng, W. L.; Kirilenko, A.

2010-12-01

The water level of Devils Lake in North Dakota has been rising since 1993, reaching record highs in each of the past three years. Nearly $1 billion have already been spent in mitigating the flooding impacts. If the current wet cycle continues, Devils Lake, a terminal lake currently at 1452 ft, will likely overflow at 1458 ft and cause extensive downstream flooding, with devastating environmental and economic impacts at local, regional, and international levels. We have implemented a distributed rainfall-runoff model, HEC-HMS, to simulate the hydro-dynamics of the lake watershed, and used NASA's remote sensing data, including the TRMM Multi-Satellite Precipitation Analysis (TMPA) and AIRS surface air temperature, to drive the model. The entire watershed with an area of about 10,000 km2 was delineated into six sub-basins using 30 m DEM, with each sub-basin having several hundred thousand hydrological cells. We generated a fine-resolution weather data set, based on a combination of ground observations and remote sensing data, to drive the hydrological simulations. Compared with a very limited number of data series available from five meteorological stations located within the watershed (none belonging to the US Historical Climate Network), NASA data offer a uniform coverage and dense distribution. The satellite and ground observations of precipitation and temperature agreed well with each other. However, if only weather station data were used, the observed runoff was underestimated by at least 30%, regardless of the value of the snow melt-rate coefficient used. The inclusion of NASA data, on the other hand, greatly improved the accuracy of runoff estimates, to within 2% of observations. Better runoff estimates will enable better predictions of water levels. The watershed hydrological model is coupled with a reservoir model, HEC-ResSim. The calibration against the observed lake elevation and monthly evaporation estimates from 2001 to 2004 showed a lake seepage varying between 500 - 1300 cfs. The coupled models can reproduce water level of the lake at sub-feet accuracy, and will be driven by the downscaled CMIP-3 projections of future climate, to provide decision support for mitigation measures in response to the potential flooding.

Transfer of uncertainty of space-borne high resolution rainfall products at ungauged regions

NASA Astrophysics Data System (ADS)

Tang, Ling

Hydrologically relevant characteristics of high resolution (˜ 0.25 degree, 3 hourly) satellite rainfall uncertainty were derived as a function of season and location using a six year (2002-2007) archive of National Aeronautics and Space Administration (NASA)'s Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) precipitation data. The Next Generation Radar (NEXRAD) Stage IV rainfall data over the continental United States was used as ground validation (GV) data. A geostatistical mapping scheme was developed and tested for transfer (i.e., spatial interpolation) of uncertainty information from GV regions to the vast non-GV regions by leveraging the error characterization work carried out in the earlier step. The open question explored here was, "If 'error' is defined on the basis of independent ground validation (GV) data, how are error metrics estimated for a satellite rainfall data product without the need for much extensive GV data?" After a quantitative analysis of the spatial and temporal structure of the satellite rainfall uncertainty, a proof-of-concept geostatistical mapping scheme (based on the kriging method) was evaluated. The idea was to understand how realistic the idea of 'transfer' is for the GPM era. It was found that it was indeed technically possible to transfer error metrics from a gauged to an ungauged location for certain error metrics and that a regionalized error metric scheme for GPM may be possible. The uncertainty transfer scheme based on a commonly used kriging method (ordinary kriging) was then assessed further at various timescales (climatologic, seasonal, monthly and weekly), and as a function of the density of GV coverage. The results indicated that if a transfer scheme for estimating uncertainty metrics was finer than seasonal scale (ranging from 3-6 hourly to weekly-monthly), the effectiveness for uncertainty transfer worsened significantly. Next, a comprehensive assessment of different kriging methods for spatial transfer (interpolation) of error metrics was performed. Three kriging methods for spatial interpolation are compared, which are: ordinary kriging (OK), indicator kriging (IK) and disjunctive kriging (DK). Additional comparison with the simple inverse distance weighting (IDW) method was also performed to quantify the added benefit (if any) of using geostatistical methods. The overall performance ranking of the kriging methods was found to be as follows: OK=DK > IDW > IK. Lastly, various metrics of satellite rainfall uncertainty were identified for two large continental landmasses that share many similar Koppen climate zones, United States and Australia. The dependence of uncertainty as a function of gauge density was then investigated. The investigation revealed that only the first and second ordered moments of error are most amenable to a Koppen-type climate type classification in different continental landmasses.

Satellite altimetry and hydrologic modeling of poorly-gauged tropical watershed

NASA Astrophysics Data System (ADS)

Sulistioadi, Yohanes Budi

Fresh water resources are critical for daily human consumption. Therefore, a continuous monitoring effort over their quantity and quality is instrumental. One important model for water quantity monitoring is the rainfall-runoff model, which represents the response of a watershed to the variability of precipitation, thus estimating the discharge of a channel (Bedient and Huber, 2002, Beven, 2012). Remote sensing and satellite geodetic observations are capable to provide critical hydrological parameters, which can be used to support hydrologic modeling. For the case of satellite radar altimetry, limited temporal resolutions (e.g., satellite revisit period) prohibit the use of this method for a short (less than weekly) interval monitoring of water level or discharge. On the other hand, the current satellite radar altimeter footprints limit the water level measurement for rivers wider than 1 km (Birkett, 1998, Birkett et al., 2002). Some studies indeed reported successful retrieval of water level for small-size rivers as narrow as 80 m (Kuo and Kao, 2011, Michailovsky et al., 2012); however, the processing of current satellite altimetry signals for small water bodies to retrieve accurate water levels, remains challenging. To address this scientific challenge, this study poses two main objectives: (1) to monitor small (40--200 m width) and medium-sized (200--800 m width) rivers and lakes using satellite altimetry through identification and choice of the over-water radar waveforms corresponding to the appropriately waveform-retracked water level; and (2) to develop a rainfall-runoff hydrological model to represent the response of mesoscale watershed to the variability of precipitation. Both studies address the humid tropics of Southeast Asia, specifically in Indonesia, where similar studies do not yet exist. This study uses the Level 2 radar altimeter measurements generated by European Space Agency's (ESA's) Envisat (Environmental Satellite) mission. The first study proves that satellite altimetry provides a good alternative or the only means in some regions to measure the water level of medium-sized river (200--800 m width) and small lake (extent less than 1000 km 2) in Southeast Asia humid tropic with reasonable accuracy. In addition, the procedure to choose retracked Envisat altimetry water level heights via identification or selection of over water waveform shapes is reliable; therefore this study concluded that the use of waveform shape selection procedure should be a standard measure in determining qualified range measurements especially over small rivers and lakes. This study also found that Ice-1 is not necessarily the best retracker as reported by previous studies, among the four standard waveform retracking algorithms for Envisat altimetry observing hydrologic bodies. The second study modeled the response of the poorly-gauged watershed in the Southeast Asia's humid tropic through the application of Hydrologic Engineering Center -- Hydrologic Modeling System (HEC-HMS). The performance evaluation of HEC-HMS discharge estimation confirms a good match between the simulated discharges with the observed ones. As the result of precipitation data analysis, this study found that Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is the preferred input forcing for the model, given the thorough evaluation of its relationship with field-measured precipitation data prior to its use as primary climatic forcing. This research also proposes a novel approach to process the TRMM precipitation estimation spatially through Thiessen polygon and area average hybrid method, which model the spatial distribution of TRMM data to match the spatial location of field meteorological stations. Through a simultaneous validation that compares the water level anomaly transformed from HEC-HMS simulated discharge and satellite altimetry measurement, this study found that satellite altimetry measures water level anomaly closer to the true water level anomaly than the water level anomaly converted from HEC-HMS simulated discharge. Some critical recommendations for future studies include the use of waveform shape selection procedure in the satellite altimetry based water level measurement of small and medium-sized rivers and small lakes, as well as the exploration to implement data assimilation between satellite altimetry and the hydrologic model for better discharge and water level estimations.

The contribution of tropical cyclones to rainfall in Mexico

NASA Astrophysics Data System (ADS)

Agustín Breña-Naranjo, J.; Pedrozo-Acuña, Adrián; Pozos-Estrada, Oscar; Jiménez-López, Salma A.; López-López, Marco R.

Investigating the contribution of tropical cyclones to the terrestrial water cycle can help quantify the benefits and hazards caused by the rainfall generated from this type of hydro-meteorological event. Rainfall induced by tropical cyclones can enhance both flood risk and groundwater recharge, and it is therefore important to characterise its minimum, mean and maximum contributions to a region or country's water balance. This work evaluates the rainfall contribution of tropical depressions, storms and hurricanes across Mexico from 1998 to 2013 using the satellite-derived precipitation dataset TMPA 3B42. Additionally, the sensitivity of rainfall to other datasets was assessed: the national rain gauge observation network, real-time satellite rainfall and a merged product that combines rain gauges with non-calibrated space-borne rainfall measurements. The lower Baja California peninsula had the highest contribution from cyclonic rainfall in relative terms (∼40% of its total annual rainfall), whereas the contributions in the rest of the country showed a low-to-medium dependence on tropical cyclones, with mean values ranging from 0% to 20%. In quantitative terms, southern regions of Mexico can receive more than 2400 mm of cyclonic rainfall during years with significant TC activity. Moreover, (a) the number of tropical cyclones impacting Mexico has been significantly increasing since 1998, but cyclonic contributions in relative and quantitative terms have not been increasing, and (b) wind speed and rainfall intensity during cyclones are not highly correlated. Future work should evaluate the impacts of such contributions on surface and groundwater hydrological processes and connect the knowledge gaps between the magnitude of tropical cyclones, flood hazards, and economic losses.

Climate change impacts on North Dakota: agriculture and hydrology

NASA Astrophysics Data System (ADS)

Kirilenko, A.; Zhang, X.; Lim, Y.; Teng, W. L.

2011-12-01

North Dakota is one of the principal producers of agricultural commodities in the USA, including over half of the total spring wheat production. While the region includes some of the best agricultural lands in the world, the steep temperature and precipitation gradients also make it one of the most sensitive to climate change. Over the 20th century, both the temperature and the pattern of precipitation in the state have changed. One of the most dramatic examples of the consequences of this change is the Devils Lake flooding. Devils Lake is a terminal lake with a surface area of about 500 km2 in a 9,867 km2 closed watershed, located in the northeastern part of the state. The recent changes in climate interrupted the 5-7 year long wet/dry cycle, resulting in a persistently wet state. The change in the water balance has led to a substantial increase in the lake level from 427.0 m in 1940 to 434.6 m in 1993 to 443.2 m in 2011. The resulting flooding has threatened the local communities, costing $450 million in mitigation efforts thus far. If the elevation reaches 444.4 m, the saline, eutrophic lake will naturally spill into the Sheyenne River, eventually flowing into Lake Winnipeg. In two studies, we estimated the climate change impacts on crop yields and on the hydrology of the Devils Lake basin. The projections of six GCMs, driven by three SRES scenarios were statistically downscaled for eight different locations throughout the state, for the 2020s, 2050s, and 2080s climate. Averaged over all GCMs, there is a small increase in precipitation, by 0.6 - 1.1% in 2020s, 3.1 - 3.5% in 2050s, and 3.0 - 7.6% in 2080s. This change in precipitation varies with the seasons, with cold seasons becoming wetter and warm seasons not changing. For projections of climate change impacts on the hydrology of the Devils Lake basin, we additionally used the information on the spatial distribution of precipitation over the basin from the NASA TRMM TMPA 3B42-V6 product, which combines measurements from multiple satellites with rain gauge data and is available over a 0.25° × 0.25° grid. We used the DSSAT package to simulate the impact of climate change on wheat yields in eight locations in North Dakota, using the outputs of the six GCMs, as described above. For each time period, we ran the DSSAT 10 times, under different synthetic weather conditions, to adequately take into account climate variability. In general, averaged across the simulations and across all locations, the simulations demonstrate a decline in yields: -3.6% -4.0% in 2020s and still more substantial in 2050s and 2080s. However, the decline differs dramatically among the outputs from different GCMs and among the scenarios. In the Devils Lake basin, the simulations show increasing amount of winter precipitation, and also increasing potential evapotranspiration. Together with longer warm seasons, these changes in climate will likely reduce earlier estimates (Vecchia, 2008) of the risks of Devils Lake spillage. In the report, we provide details on the research of climate change impacts on the Devils Lake watershed, and on the agriculture of North Dakota.

Dispersion polymerization of L-lactide utilizing ionic liquids as reaction medium

NASA Astrophysics Data System (ADS)

Fahmiati, Sri; Minami, Hideto; Haryono, Agus; Adilina, Indri B.

2017-11-01

Dispersion polymerization of L-lactide was proceeded in various ionic liquids. Ionic liquids as 1-Hexyl-3-methylimidazolium bis (trifluormethylsulfonyl) imide, [HMIM] [TFSI], 1-Butyl-3-methylimidazolium bis (trifluoromethylsulfonyl) imide, [BMP] [TFSI], and N,N,N-Trimethyl-N-Propylammonium Bis (trifloromethanesulfonyl) imide, [TMPA] [TFSI], were employed as reaction medium that dissolved both of lactide and stabilizer (polyvinylprrolidone). Sn-supported on bentonite was used as a ring opening catalyst of L-lactide. Gel Permeation Chromatography result showed that poly-(L-lactic acid) were formed in ionic liquids [HMIM] [TFSI] and [BMP] [TFSI] with molecular weight as 19390 and 20844, respectively.

Performance of CMORPH, TMPA, and PERSIANN rainfall datasets over plain, mountainous, and glacial regions of Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Yawar; Satgé, Frédéric; Hussain, Muhammad Babar; Martinez-Carvajal, Hernan; Bonnet, Marie-Paule; Cárdenas-Soto, Martin; Roig, Henrique Llacer; Akhter, Gulraiz

2018-02-01

The present study aims at the assessment of six satellite rainfall estimates (SREs) in Pakistan. For each assessed products, both real-time (RT) and post adjusted (Adj) versions are considered to highlight their potential benefits in the rainfall estimation at annual, monthly, and daily temporal scales. Three geomorphological climatic zones, i.e., plain, mountainous, and glacial are taken under considerations for the determination of relative potentials of these SREs over Pakistan at global and regional scales. All SREs, in general, have well captured the annual north-south rainfall decreasing patterns and rainfall amounts over the typical arid regions of the country. Regarding the zonal approach, the performance of all SREs has remained good over mountainous region comparative to arid regions. This poor performance in accurate rainfall estimation of all the six SREs over arid regions has made their use questionable in these regions. Over glacier region, all SREs have highly overestimated the rainfall. One possible cause of this overestimation may be due to the low surface temperature and radiation absorption over snow and ice cover, resulting in their misidentification with rainy clouds as daily false alarm ratio has increased from mountainous to glacial regions. Among RT products, CMORPH-RT is the most biased product. The Bias was almost removed on CMORPH-Adj thanks to the gauge adjustment. On a general way, all Adj versions outperformed their respective RT versions at all considered temporal scales and have confirmed the positive effects of gauge adjustment. CMORPH-Adj and TMPA-Adj have shown the best agreement with in situ data in terms of Bias, RMSE, and CC over the entire study area.

Mechanistic Insights into the Oxidation of Substituted Phenols via Hydrogen Atom Abstraction by a Cupric–Superoxo Complex

PubMed Central

2015-01-01

To obtain mechanistic insights into the inherent reactivity patterns for copper(I)–O2 adducts, a new cupric–superoxo complex [(DMM-tmpa)CuII(O2•–)]+ (2) [DMM-tmpa = tris((4-methoxy-3,5-dimethylpyridin-2-yl)methyl)amine] has been synthesized and studied in phenol oxidation–oxygenation reactions. Compound 2 is characterized by UV–vis, resonance Raman, and EPR spectroscopies. Its reactions with a series of para-substituted 2,6-di-tert-butylphenols (p-X-DTBPs) afford 2,6-di-tert-butyl-1,4-benzoquinone (DTBQ) in up to 50% yields. Significant deuterium kinetic isotope effects and a positive correlation of second-order rate constants (k2) compared to rate constants for p-X-DTBPs plus cumylperoxyl radical reactions indicate a mechanism that involves rate-limiting hydrogen atom transfer (HAT). A weak correlation of (kBT/e) ln k2 versus Eox of p-X-DTBP indicates that the HAT reactions proceed via a partial transfer of charge rather than a complete transfer of charge in the electron transfer/proton transfer pathway. Product analyses, 18O-labeling experiments, and separate reactivity employing the 2,4,6-tri-tert-butylphenoxyl radical provide further mechanistic insights. After initial HAT, a second molar equiv of 2 couples to the phenoxyl radical initially formed, giving a CuII–OO–(ArO′) intermediate, which proceeds in the case of p-OR-DTBP substrates via a two-electron oxidation reaction involving hydrolysis steps which liberate H2O2 and the corresponding alcohol. By contrast, four-electron oxygenation (O–O cleavage) mainly occurs for p-R-DTBP which gives 18O-labeled DTBQ and elimination of the R group. PMID:24953129

The Version 2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979-Present)

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George J.; Chang, Alfred; Ferraro, Ralph; Xie, Ping-Ping; Janowiak, John; Rudolf, Bruno; Schneider, Udo; Curtis, Scott; Bolvin, David

2003-01-01

The Global Precipitation Climatology Project (GPCP) Version 2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5 degrees x 2.5 degrees latitude-longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The data set is extended back into the premicrowave era (before 1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the raingauge analysis. This monthly analysis is the foundation for the GPCP suite of products including those at finer temporal resolution, satellite estimate, and error estimates for each field. The 23-year GPCP climatology is characterized, along with time and space variations of precipitation.

Development of an Experimental African Drought Monitoring and Seasonal Forecasting System: A First Step towards a Global Drought Information System

NASA Astrophysics Data System (ADS)

Wood, E. F.; Chaney, N.; Sheffield, J.; Yuan, X.

2012-12-01

Extreme hydrologic events in the form of droughts are a significant source of social and economic damage. Internationally, organizations such as UNESCO, the Group on Earth Observations (GEO), and the World Climate Research Programme (WCRP) have recognized the need for drought monitoring, especially for the developing world where drought has had devastating impacts on local populations through food insecurity and famine. Having the capacity to monitor droughts in real-time, and to provide drought forecasts with sufficient warning will help developing countries and international programs move from the management of drought crises to the management of drought risk. While observation-based assessments, such as those produced by the US Drought Monitor, are effective for monitoring in countries with extensive observation networks (of precipitation in particular), their utility is lessened in areas (e.g., Africa) where observing networks are sparse. For countries with sparse networks and weak reporting systems, remote sensing observations can provide the real-time data for the monitoring of drought. More importantly, these datasets are now available for at least a decade, which allows for the construction of a climatology against which current conditions can be compared. In this presentation we discuss the development of our multi-lingual experimental African Drought Monitor (ADM) (see http://hydrology.princeton.edu/~nchaney/ADM_ML). At the request of UNESCO, the ADM system has been installed at AGRHYMET, a regional climate and agricultural center in Niamey, Niger and at the ICPAC climate center in Nairobi, Kenya. The ADM system leverages off our U.S. drought monitoring and forecasting system (http://hydrology.princeton.edu/forecasting) that uses the NLDAS data to force the VIC land surface model (LSM) at 1/8th degree spatial resolution for the estimation of our soil moisture drought index (Sheffield et al., 2004). For the seasonal forecast of drought, CFSv2 climate forecasts are bias corrected, downscaled and used as inputs to the VIC LSM as well as forecasts based on ESP and CPC official seasonal outlook. For Africa, data from a combination of remote sensing (TMPA-based precipitation, land cover characteristics) and GFS analysis fields (temperature and wind) are used to monitor drought using our soil moisture drought index as well as 1, 3 and and 6-month SPI. River discharge is also estimated at over 900 locations. Seasonal forecasts have been developed using CFSv2 climate forecasts following the approaches used over CONUS. We will discuss the performance of the system to evaluate the depiction of drought over various scales, from regional to the African continent, and over a number of years to capture multiple drought events. Furthermore, the hindcasts from the seasonal drought forecast system are analyzed to assess the ability of seasonal climate models to detect drought on-set and its recovery. Finally, we will discuss whether our ADM provides a pathway to a Global Drought Information System, a goal of the WCRP Drought Task Force.

Analysis of watershed topography effects on summer precipitation variability in the southwestern United States

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, Dagbegnon C.; Singh, Vijay P.; Frauenfeld, Oliver W.

2014-04-01

With climate change, precipitation variability is projected to increase. The present study investigates the potential interactions between watershed characteristics and precipitation variability. The watershed is considered as a functional unit that may impact seasonal precipitation. The study uses historical precipitation data from 370 meteorological stations over the last five decades, and digital elevation data from regional watersheds in the southwestern United States. This domain is part of the North American Monsoon region, and the summer period (June-July-August, JJA) was considered. Based on an initial analysis for 1895-2011, the JJA precipitation accounts, on average, for 22-43% of the total annual precipitation, with higher percentages in the arid part of the region. The unique contribution of this research is that entropy theory is used to address precipitation variability in time and space. An entropy-based disorder index was computed for each station's precipitation record. The JJA total precipitation and number of precipitation events were considered in the analysis. The precipitation variability potentially induced by watershed topography was investigated using spatial regionalization combining principal component and cluster analysis. It was found that the disorder in precipitation total and number of events tended to be higher in arid regions. The spatial pattern showed that the entropy-based variability in precipitation amount and number of events gradually increased from east to west in the southwestern United States. Regarding the watershed topography influence on summer precipitation patterns, hilly relief has a stabilizing effect on seasonal precipitation variability in time and space. The results show the necessity to include watershed topography in global and regional climate model parameterizations.

Development of an operational African Drought Monitor prototype

NASA Astrophysics Data System (ADS)

Chaney, N.; Sheffield, J.; Wood, E. F.; Lettenmaier, D. P.

2011-12-01

Droughts have severe economic, environmental, and social impacts. However, timely detection and monitoring can minimize these effects. Based on previous drought monitoring over the continental US, a drought monitor has been developed for Africa. Monitoring drought in data sparse regions such as Africa is difficult due to a lack of historical or real-time observational data at a high spatial and temporal resolution. As a result, a land surface model is used to estimate hydrologic variables, which are used as surrogate observations for monitoring drought. The drought monitoring system consists of two stages: the first is to create long-term historical background simulations against which current conditions can be compared. The second is the real-time estimation of current hydrological conditions that results in an estimated drought index value. For the first step, a hybrid meteorological forcing dataset was created that assimilates reanalysis and observational datasets from 1950 up to real-time. Furthermore, the land surface model (currently the VIC land surface model is being used) was recalibrated against spatially disaggregated runoff fields derived from over 500 GRDC stream gauge measurements over Africa. The final result includes a retrospective database from 1950 to real-time of soil moisture, evapotranspiration, river discharge at the GRDC gauged sites (etc.) at a 1/4 degree spatial resolution, and daily temporal resolution. These observation-forced simulations are analyzed to detect and track historical drought events according to a drought index that is calculated from the soil moisture fields and river discharge relative to their seasonal climatology. The real-time monitoring requires the use of remotely sensed and weather-model analysis estimates of hydrological model forcings. For the current system, NOAA's Global Forecast System (GFS) is used along with remotely sensed precipitation from the NASA TMPA system. The historical archive of these data is evaluated against the data set used to create the background simulations. Real-time adjustments are used to preserve consistency between the historical and real-time data. The drought monitor will be presented together with the web-interface that has been developed for the scientific community to access and retrieve the data products. This system will be deployed for operational use at AGRHYMET in Niamey, Niger before the end of 2011.

A Cascading Storm-Flood-Landslide Guidance System: Development and Application in China

NASA Astrophysics Data System (ADS)

Zeng, Ziyue; Tang, Guoqiang; Long, Di; Ma, Meihong; Hong, Yang

2016-04-01

Flash floods and landslides, triggered by storms, often interact and cause cascading effects on human lives and property. Satellite remote sensing data has significant potential use in analysis of these natural hazards. As one of the regions continuously affected by severe flash floods and landslides, Yunnan Province, located in Southwest China, has a complex mountainous hydrometeorology and suffers from frequent heavy rainfalls from May through to late September. Taking Yunnan as a test-bed, this study proposed a Cascading Storm-Flood-Landslide Guidance System to progressively analysis and evaluate the risk of the multi-hazards based on multisource satellite remote sensing data. First, three standardized rainfall amounts (average daily amount in flood seasons, maximum 1h and maximum 6h amount) from the products of Topical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) were used as rainfall indicators to derive the StorM Hazard Index (SMHI). In this process, an integrated approach of the Analytic Hierarchy Process (AHP) and the Information-Entropy theory was adopted to determine the weight of each indicator. Then, land cover and vegetation cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS) products, soil type from the Harmonized World Soil Database (HWSD) soil map, and slope from the Shuttle Radar Topography Mission (SRTM) data were add as semi-static geo-topographical indicators to derive the Flash Flood Hazard Index (FFHI). Furthermore, three more relevant landslide-controlling indicators, including elevation, slope angle and soil text were involved to derive the LandSlide Hazard Index (LSHI). Further inclusion of GDP, population and prevention measures as vulnerability indicators enabled to consecutively predict the risk of storm to flash flood and landslide, respectively. Consequently, the spatial patterns of the hazard indices show that the southeast of Yunnan has more possibility to encounter with storms than other parts, while the northeast of Yunnan are most susceptible to floods and landslides, which agrees with the distribution of observed flood and landslide events. Moreover, risks for the multi-hazards were classified into four categories. Results show a strong correlation between the distributions of flash flood prone and landslide-prone regions and also highlight the counties with high risk of storms (e.g., Funing and Malipo), flash floods (e.g., Gongshan and Yanjing) and landslides (e.g., Zhaotong and Luxi). Compared to other approaches, the Cascading Storm-Flood-Landslide Guidance System uses a straightforward yet useful indicator-based weighted linear combination method and could be a useful prototype in mapping characteristics of storm-triggered hazards for users at different administrative levels (e.g., catchment, town, county, province and even nation) in China.

Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

NASA Astrophysics Data System (ADS)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15-18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor-Yamada-Janjic PBL and Betts-Miller-Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios - (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) - are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.

Accounting for Effects of Orography in LDAS Precipitation Forcing Data

NASA Astrophysics Data System (ADS)

Schaake, J.; Higgins, W.; Cong, S.; Shi, W.; Duan, Q.; Yarosh, E.

2001-05-01

Precipitation analysis procedures that are widely used to make gridded precipitation estimates do not work well in mountainous areas because the gage density is too sparse relative to the spatacial frequency content of the actual precipitation field. Moreover, in the western U.S. most of the precipitation observations are low elevations and may not even detect occurrence of storms at high elevations. Although there are indeed significant limits to how accurately actual fields of orographic precipitation can be estimated from gage data alone, it is possible to make estimates for each time period that, over a period of time, have a climatology that should approximate the true climatology of the actual events. Analysis schemes that use the PRISM precipitation climatology to aid the precipitation analysis are being tested. The results of these tests will be presented.

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.

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

The Canadian Precipitation Analysis (CaPA): Evaluation of the statistical interpolation scheme

NASA Astrophysics Data System (ADS)

Evans, Andrea; Rasmussen, Peter; Fortin, Vincent

2013-04-01

CaPA (Canadian Precipitation Analysis) is a data assimilation system which employs statistical interpolation to combine observed precipitation with gridded precipitation fields produced by Environment Canada's Global Environmental Multiscale (GEM) climate model into a final gridded precipitation analysis. Precipitation is important in many fields and applications, including agricultural water management projects, flood control programs, and hydroelectric power generation planning. Precipitation is a key input to hydrological models, and there is a desire to have access to the best available information about precipitation in time and space. The principal goal of CaPA is to produce this type of information. In order to perform the necessary statistical interpolation, CaPA requires the estimation of a semi-variogram. This semi-variogram is used to describe the spatial correlations between precipitation innovations, defined as the observed precipitation amounts minus the GEM forecasted amounts predicted at the observation locations. Currently, CaPA uses a single isotropic variogram across the entire analysis domain. The present project investigates the implications of this choice by first conducting a basic variographic analysis of precipitation innovation data across the Canadian prairies, with specific interest in identifying and quantifying potential anisotropy within the domain. This focus is further expanded by identifying the effect of storm type on the variogram. The ultimate goal of the variographic analysis is to develop improved semi-variograms for CaPA that better capture the spatial complexities of precipitation over the Canadian prairies. CaPA presently applies a Box-Cox data transformation to both the observations and the GEM data, prior to the calculation of the innovations. The data transformation is necessary to satisfy the normal distribution assumption, but introduces a significant bias. The second part of the investigation aims at devising a bias correction scheme based on a moving-window averaging technique. For both the variogram and bias correction components of this investigation, a series of trial runs are conducted to evaluate the impact of these changes on the resulting CaPA precipitation analyses.

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 precipitation analyses by other institutions. Other global precipitation analyses produced by other methodologies are also used by EMC in certain applications, such as CPC's well-known satellite-IR based technique known as "GPI", and satellite-microwave based estimates from NESDIS or NASA. Finally, the presentation will cover the three assimilation methods used by EMC to assimilate precipitation data, including 1) 3D-VAR variational assimilation in NCEP's Global Data Assimilation System (GDAS), 2) direct insertion of precipitation-inferred vertical latent heating profiles in NCEP's N. American Data Assimilation System (NDAS) and its N. American Regional Reanalysis (NARR) counterpart, and 3) direct use of observed precipitation to drive the Noah land model component of NCEP's Global and N. American Land Data Assimilation Systems (GLDAS and NLDAS). In the applications of precipitation analyses in data assimilation at NCEP, the analyses are temporally disaggregated to hourly or less using time-weights calculated from A) either radar-based estimates or an analysis of hourly gauge-observations for the CONUS-domain daily precipitation analyses, or B) global model forecasts of 6-hourly precipitation (followed by linear interpolation to hourly or less) for the global CMAP precipitation analysis.

Short-range prediction of a heavy precipitation event by assimilating Chinese CINRAD-SA radar reflectivity data using complex cloud analysis

NASA Astrophysics Data System (ADS)

Sheng, C.; Gao, S.; Xue, M.

2006-11-01

With the ARPS (Advanced Regional Prediction System) Data Analysis System (ADAS) and its complex cloud analysis scheme, the reflectivity data from a Chinese CINRAD-SA Doppler radar are used to analyze 3D cloud and hydrometeor fields and in-cloud temperature and moisture. Forecast experiments starting from such initial conditions are performed for a northern China heavy rainfall event to examine the impact of the reflectivity data and other conventional observations on short-range precipitation forecast. The full 3D cloud analysis mitigates the commonly known spin-up problem with precipitation forecast, resulting a significant improvement in precipitation forecast in the first 4 to 5 hours. In such a case, the position, timing and amount of precipitation are all accurately predicted. When the cloud analysis is used without in-cloud temperature adjustment, only the forecast of light precipitation within the first hour is improved. Additional analysis of surface and upper-air observations on the native ARPS grid, using the 1 degree real-time NCEP AVN analysis as the background, helps improve the location and intensity of rainfall forecasting slightly. Hourly accumulated rainfall estimated from radar reflectivity data is found to be less accurate than the model predicted precipitation when full cloud analysis is used.

Projections of the Ganges-Brahmaputra precipitation: downscaled from GCM predictors

USGS Publications Warehouse

Pervez, Md Shahriar; Henebry, Geoffrey M.

2014-01-01

Downscaling Global Climate Model (GCM) projections of future climate is critical for impact studies. Downscaling enables use of GCM experiments for regional scale impact studies by generating regionally specific forecasts connecting global scale predictions and regional scale dynamics. We employed the Statistical Downscaling Model (SDSM) to downscale 21st century precipitation for two data-sparse hydrologically challenging river basins in South Asia—the Ganges and the Brahmaputra. We used CGCM3.1 by Canadian Center for Climate Modeling and Analysis version 3.1 predictors in downscaling the precipitation. Downscaling was performed on the basis of established relationships between historical Global Summary of Day observed precipitation records from 43 stations and National Center for Environmental Prediction re-analysis large scale atmospheric predictors. Although the selection of predictors was challenging during the set-up of SDSM, they were found to be indicative of important physical forcings in the basins. The precipitation of both basins was largely influenced by geopotential height: the Ganges precipitation was modulated by the U component of the wind and specific humidity at 500 and 1000 h Pa pressure levels; whereas, the Brahmaputra precipitation was modulated by the V component of the wind at 850 and 1000 h Pa pressure levels. The evaluation of the SDSM performance indicated that model accuracy for reproducing precipitation at the monthly scale was acceptable, but at the daily scale the model inadequately simulated some daily extreme precipitation events. Therefore, while the downscaled precipitation may not be the suitable input to analyze future extreme flooding or drought events, it could be adequate for analysis of future freshwater availability. Analysis of the CGCM3.1 downscaled precipitation projection with respect to observed precipitation reveals that the precipitation regime in each basin may be significantly impacted by climate change. Precipitation during and after the monsoon is likely to increase in both basins under the A1B and A2 emission scenarios; whereas, the pre-monsoon precipitation is likely to decrease. Peak monsoon precipitation is likely to shift from July to August, and may impact the livelihoods of large rural populations linked to subsistence agriculture in the basins. Uncertainty analysis of the downscaled precipitation indicated that the uncertainty in the downscaled precipitation was less than the uncertainty in the original CGCM3.1 precipitation; hence, the CGCM3.1 downscaled precipitation was a better input for the regional hydrological impact studies. However, downscaled precipitation from multiple GCMs is suggested for comprehensive impact studies.

North Atlantic Oscillation influence and weather types associated with winter total and extreme precipitation events in Spain

NASA Astrophysics Data System (ADS)

Queralt, S.; Hernández, E.; Barriopedro, D.; Gallego, D.; Ribera, P.; Casanova, C.

2009-12-01

An analysis of winter intensity and frequency of precipitation is presented, based on 102 daily precipitation stations over Spain and the Balearic Islands for the 1997-2006 decade. Precipitation stations have been merged in the eight different regions which compose the analyzed area by the use of an EOF analysis. NAO influence on the intensity and frequency of precipitation of each region is described in terms of mean precipitation, mean rain frequency, the number of extreme events, changes in the precipitation distribution and the prevalent synoptic configuration. Results indicate a non-stationary response; NAO signal being more evident in mid-late winter. Strong regional differences in the response to NAO are also found, which vary according to the specific character of the precipitation under analysis. Thus, NAO exerts a clear effect on the intensity of total and extreme precipitation rates in northern and westernmost Spanish regions, whereas the frequency of precipitation is clearly affected by NAO in central and southwestern areas. While the correlation between NAO and precipitation is negative for most of the analyzed area, two regions reveal positive responses to NAO in total precipitation occurrence and intensity for specific months. Further analyses reveal asymmetric responses to opposite phases of NAO in the precipitation distributions of some regions. The complex regional relationship between NAO and precipitation is also revealed through the modulation of the former in the preferred Circulation Weather Types associated to precipitation in each region. This spatially non-homogeneous NAO signal stresses the need of caution when employing Iberian precipitation as a proxy for NAO.

The spatiotemporal changes in precipitation extremes over Canada and their connections to large-scale climate patterns

NASA Astrophysics Data System (ADS)

Yang, Y.; Gan, T. Y.; Tan, X.

2017-12-01

In the past few decades, there have been more extreme climate events around the world, and Canada has also suffered from numerous extreme precipitation events. In this paper, trend analysis, change point analysis, probability distribution function, principal component analysis and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation in Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data from 164 gauging stations. Several large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Pacific-North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective Available Potential Energy (CAPE), specific humidity, and surface temperature were employed to investigate the potential causes of the trends.The results show statistically significant positive trends for most indices, which indicate increasing extreme precipitation. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominate in the central Canadian Prairies (CP). In addition, strong connections are found between the extreme precipitation and climate indices and the effects of climate pattern differ for each region. The seasonal CAPE, specific humidity, and temperature are found to be closely related to Canadian extreme precipitation.

Measurement of acid precipitation in Norway

Treesearch

Arne Semb

1976-01-01

Since January 1972, chemical analysis of daily precipitation samples from about 20 background stations in Norway has been carried out on a routine basis. Air monitoring is carried out at six stations. The chemical analysis programme is: sulphate, pH and acidity in precipitation, sulphates and sulphur dioxide in air. In addition, more detailed chemical analysis of...

HDSC/OWP

Science.gov Websites

Maximum Precipitation Documents Miscellaneous Publications Storm Analysis Record Precipitation Contact Us ; - Probability analysis for selected historical storm events learn more > - Record point precipitation for the Oceanic and Atmospheric Administration National Weather Service Office of Water Prediction (OWP) 1325 East

A precipitation organization climatology for North Carolina: Development and GIS-based analysis

NASA Astrophysics Data System (ADS)

Zarzar, Christopher M.

A climatology of precipitation organization is developed for the Southeast United States and is analyzed in a GIS framework. This climatology is created using four years (2009-2012) of daily-averaged data from the NOAA high-resolution multi-sensor precipitation estimation (MPE) dataset, specifically the radar-based quantitative precipitation estimation (QPE) product and the mosaic reflectivity. The analysis associates precipitation at each pixel with the spatial scale of precipitation organization, either a mesoscale precipitation feature (MPF) or isolated storm. While the long-term averaged precipitation totals of these systems may be similar, their hydrological and climatological impacts are very different, especially at a local scale. The classification of these modes of precipitation organization in the current precipitation climatology provides information beyond standard precipitation climatologies that will benefit a range of hydrological and climatological applications. This study focuses on North Carolina and takes advantage of a GIS framework to examine hydrological responses to different modes of precipitation organization. Specifically, the following questions are addressed: First, what are the discharge response characteristics to precipitation events in different watersheds across the state, from the mountains to the coastal plain? Second, what are the different impacts on watershed discharge between MPF precipitation and isolated precipitation? We first present seasonal and annual composites of precipitation and duration of MPF and isolated storms across three regions of North Carolina: the western mountains, the central Piedmont, and the eastern coastal plain. Further analysis in a GIS framework provides information about the impacts this seasonal and geographic variability in precipitation has on watershed discharge. This analysis defines five watersheds in North Carolina based on five North Carolina river basins using ArcGIS watershed delineation techniques. The amount of precipitation that comes from MPF and isolated convection in each watershed is estimated using ArcGIS and QPE data from a climatology of precipitation organization. Comparing these estimates to USGS streamflow data provides information about the impact different modes of precipitation organization have on watershed discharge in North Carolina. It was found that precipitation from MPF and isolated events had substantial spatial and temporal variability. While MPF average daily precipitation was greatest in the winter, isolated average daily precipitation was greatest in the summer. This resulted in seasonal and spatial variations in precipitation-discharge correlations. Precipitation originating from MPF events produced stronger precipitation-discharge correlations in the winter and fall than in the summer and spring, while most isolated precipitation-discharge correlations were relatively weak. Additionally, the watersheds in the western mountains experienced stronger correlations with a shorter time lag than coastal watersheds. It was determined that much of this spatial variability in precipitation-discharge correlations could be explained by watershed characteristics. Overall, it was found that MPF precipitation is the main mode of precipitation organization that drives daily watershed discharge, and differences in watershed precipitation-discharge lag times can be best explained by the watershed characteristics.

Analysis of the evolution of precipitation in the Haihe river basin of China under changing environment

NASA Astrophysics Data System (ADS)

Ding, Xiangyi; Liu, Jiahong; Gong, Jiaguo

2018-02-01

Precipitation is one of the important factors of water cycle and main sources of regional water resources. It is of great significance to analyze the evolution of precipitation under changing environment for identifying the evolution law of water resources, thus can provide a scientific reference for the sustainable utilization of water resources and the formulation of related policies and measures. Generally, analysis of the evolution of precipitation consists of three levels: analysis the observed precipitation change based on measured data, explore the possible factors responsible for the precipitation change, and estimate the change trend of precipitation under changing environment. As the political and cultural centre of China, the climatic conditions in the Haihe river basin have greatly changed in recent decades. This study analyses the evolution of precipitation in the basin under changing environment based on observed meteorological data, GCMs and statistical methods. Firstly, based on the observed precipitation data during 1961-2000 at 26 meteorological stations in the basin, the actual precipitation change in the basin is analyzed. Secondly, the observed precipitation change in the basin is attributed using the fingerprint-based attribution method, and the causes of the observed precipitation change is identified. Finally, the change trend of precipitation in the basin under climate change in the future is predicted based on GCMs and a statistical downscaling model. The results indicate that: 1) during 1961-2000, the precipitation in the basin showed a decreasing trend, and the possible mutation time was 1965; 2) natural variability may be the factor responsible for the observed precipitation change in the basin; 3) under climate change in the future, precipitation in the basin will slightly increase by 4.8% comparing with the average, and the extremes will not vary significantly.

Chemometric analysis of multisensor hyperspectral images of precipitated atmospheric particulate matter.

PubMed

Ofner, Johannes; Kamilli, Katharina A; Eitenberger, Elisabeth; Friedbacher, Gernot; Lendl, Bernhard; Held, Andreas; Lohninger, Hans

2015-09-15

The chemometric analysis of multisensor hyperspectral data allows a comprehensive image-based analysis of precipitated atmospheric particles. Atmospheric particulate matter was precipitated on aluminum foils and analyzed by Raman microspectroscopy and subsequently by electron microscopy and energy dispersive X-ray spectroscopy. All obtained images were of the same spot of an area of 100 × 100 μm(2). The two hyperspectral data sets and the high-resolution scanning electron microscope images were fused into a combined multisensor hyperspectral data set. This multisensor data cube was analyzed using principal component analysis, hierarchical cluster analysis, k-means clustering, and vertex component analysis. The detailed chemometric analysis of the multisensor data allowed an extensive chemical interpretation of the precipitated particles, and their structure and composition led to a comprehensive understanding of atmospheric particulate matter.

Three dimensional microstructural characterization of nanoscale precipitates in AA7075-T651 by focused ion beam (FIB) tomography

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

Singh, Sudhanshu S.; Loza, Jose J.

2016-08-15

The size and distribution of precipitates in Al 7075 alloys affects both the mechanical and corrosion behavior (including stress corrosion cracking and fatigue corrosion) of the alloy. Three dimensional (3D) quantitative microstructural analysis of Al 7075 in the peak aged condition (T651) allows for a better understanding of these behaviors. In this study, Focused ion beam (FIB) tomography was used to characterize the microstructure in three dimensions. Analysis of grains and precipitates was performed in terms of volume, size, and morphology. It was found that the precipitates at the grain boundaries are larger in size, higher in aspect ratios andmore » maximum Feret diameter compared to the precipitates inside the grains, due to earlier nucleation of the precipitates at the grain boundaries. Our data on the precipitates at the interface between grains and Mg{sub 2}Si inclusion show that the surfaces of inclusion (impurity) particles can serve as a location for heterogeneous nucleation of precipitates. - Highlights: •Focused ion beam (FIB) tomography was used to characterize the microstructure of Al 7075 in three dimensions. •Analysis of grains and precipitates was performed in terms of volume, size, and morphology. •Precipitates at the grain boundaries have larger size and aspect ratio compared to the precipitates inside the grains.« less

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.

Assessing and quantifying changes in precipitation patterns using event-driven analysis

USDA-ARS?s Scientific Manuscript database

Studies have claimed that climate change may adversely affect precipitation patterns by increasing the occurrence of extreme events. The effects of climate change on precipitation is expected to take place over a long period of time and will require long-term data to demonstrate. Frequency analysis ...

Recovery of nickel and cobalt as MHP from limonitic ore leaching solution: Kinetics analysis and precipitate characterization

NASA Astrophysics Data System (ADS)

Safitri, Nina; Mubarok, M. Zaki; Winarko, Ronny; Tanlega, Zela

2018-05-01

In the present study, precipitation of nickel and cobalt as mixed hydroxide precipitate (MHP) from pregnant leach solution of nickel limonite ore from Soroako after iron removal stage was carried out. A series of MHP precipitation experiments was conducted by using MgO slurry as neutralizing agent and the effects of pH, temperature, duration of precipitation and the addition of MHP seed on the precipitation behavior of nickel, cobalt, as well as iron and manganese was studied. Characterization of MHP product was performed by particle size analyzer (PSA) as well as X-Ray Fluorescence (XRF), X-Ray Diffractometer (XRD) and Scanning Electron Microscope (SEM) analyses. Kinetics analysis was made by using differential-integral method for the rate of homogenous reaction. Precipitation at pH 7, temperature 50°C for 30 minute, without seed addition resulted in nickel and cobalt recoveries of 82.8% and 92%, respectively with co-precipitated iron and manganese of 70% and 24.2%, respectively. The seed addition increases nickel and cobalt precipitations significantly to 99.9% and 99.1%, respectively. However, the addition of seed into led to a significant increase of manganese co-precipitation from 24.2% without seed addition to 39.5% at the addition of 1 g seed per 200 mL of PLS. Kinetics analysis revealed that Ni precipitation to form MHP follows the second-order reaction kinetics with activation energy of 94.6 kJ/mol.

Analysis of an ethanol precipitate from ileal digesta: evaluation of a method to determine mucin.

PubMed

Miner-Williams, Warren M; Moughan, Paul J; Fuller, Malcolm F

2013-11-06

The precipitation of mucin using high concentrations of ethanol has been used by many researchers while others have questioned the validity of the technique. In this study, analysis of an ethanol precipitate, from the soluble fraction of ileal digesta from pigs was undertaken using molecular weight profiling and polyacrylamide gel electrophoresis. The precipitate contained 201 mg·g⁻¹ protein, 87% of which had a molecular weight >20 KDa. Polyacrylamide gel electrophoresis stained with Coomassie blue and periodic acid/Schiff, revealed that most glycoprotein had a molecular weight between 37-100 KDa. The molecular weight of glycoprotein in the precipitate was therefore lower than that of intact mucin. These observations indicated that the glycoprotein in the ethanol precipitate was significantly degraded. The large amount of protein and carbohydrate in the supernatant from ethanol precipitation indicated that the precipitation of glycoprotein was incomplete. As a method for determining the concentration of mucin in digesta, ethanol precipitation is unreliable.

Harmonic analysis of the precipitation in Greece

NASA Astrophysics Data System (ADS)

Nastos, P. T.; Zerefos, C. S.

2009-04-01

Greece is a country with a big variety of climates due to its geographical position, to the many mountain ranges and also to the multifarious and long coastline. The mountainous volumes are of such orientation that influences the distribution of the precipitation, having as a result, Western Greece to present great differentiations from Central and Eastern Greece. The application of harmonic analysis to the annual variability of precipitation is the goal of this study, so that the components, which compose the annual variability, be elicited. For this purpose, the mean monthly precipitation data from 30 meteorological stations of National Meteorological Service were used for the time period 1950-2000. The initial target is to reduce the number of variables and to detect structure in the relationships between variables. The most commonly used technique for this purpose is the application of Factor Analysis to a table having as columns the meteorological stations-variables and rows the monthly mean precipitation, so that 2 main factors were calculated, which explain the 98% of total variability of precipitation in Greece. Factor 1, representing the so-called uniform field and interpreting the most of the total variance, refers in fact to the Mediterranean depressions, affecting mainly the West of Greece and also the East Aegean and the Asia Minor coasts. In the process, the Fourier Analysis was applied to the factor scores extracted from the Factor Analysis, so that 2 harmonic components are resulted, which explain above the 98% of the total variability of each main factor, and are due to different synoptic and thermodynamic processes associated with Greece's precipitation construction. Finally, the calculation of the time of occurrence of the maximum precipitation, for each harmonic component of each one of the two main factors, gives the spatial distribution of appearance of the maximum precipitation in the Hellenic region.

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.

Improving Precipitation Forcings for the National Water Model

NASA Astrophysics Data System (ADS)

Fall, G. M.; Zhang, Z.; Miller, D.; Kitzmiller, D.; Patrick, N.; Sparrow, K.; Olheiser, C.; Szeliga, T.

2017-12-01

The National Weather Service's Office of Water Prediction (NWS/OWP) produces operational hydrologic products, many of which are generated by the National Water Model (NWM). NWM analysis cycles (also known as "near-real-time" or "update" cycles) are of key importance, since the land surface states and fluxes they produce are used to initialize all forecast cycles. Among all forcing fields (which include precipitation, temperature, humidity, radiation, and wind), precipitation is particularly important. Currently, NWM precipitation forcings for analysis cycles are generated by combining hourly radar-derived precipitation products from the Multi-Radar, Multi-Sensor (MRMS) system with short-term quantitative precipitation forecasts (QPF) from the Rapid Refresh (RAP) and High Resolution Rapid Refresh (HRRR) systems. Short term QPF is used in analysis cycles to fill coverage gaps in MRMS products, and its inclusion is necessary due to the short latency associated with NWM analysis cycles relative to the availability of other operational precipitation analyses. This presentation will describe the methodology used to remove QPF bias and to spatially merge MRMS, HRRR, and RAP into hourly forcing inputs for NWM version 2.0, expected to enter into operations in late 2018. The accuracy of version 2.0 precipitation forcings relative to reference data sources, and the degree to which these forcings will represent an improvement over those used to drive the previous NWM version (1.2), will be described.

Simulating Streamflow Using Bias-corrected Multiple Satellite Rainfall Products in the Tekeze Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Abitew, T. A.; Roy, T.; Serrat-Capdevila, A.; van Griensven, A.; Bauwens, W.; Valdes, J. B.

2016-12-01

The Tekeze Basin supports one of Africans largest Arch Dam located in northern Ethiopian has vital role in hydropower generation. However, little has been done on the hydrology of the basin due to limited in situ hydroclimatological data. Therefore, the main objective of this research is to simulate streamflow upstream of the Tekeze Dam using Soil and Water Assessment Tool (SWAT) forced by bias-corrected multiple satellite rainfall products (CMORPH, TMPA and PERSIANN-CCS). This talk will present the potential as well as skills of bias-corrected satellite rainfall products for streamflow prediction in in Tropical Africa. Additionally, the SWAT model results will also be compared with previous conceptual Hydrological models (HyMOD and HBV) from SERVIR Streamflow forecasting in African Basin project (http://www.swaat.arizona.edu/index.html).

Investigation of Kelvin wave periods during Hai-Tang typhoon using Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Kishore, P.; Jayalakshmi, J.; Lin, Pay-Liam; Velicogna, Isabella; Sutterley, Tyler C.; Ciracì, Enrico; Mohajerani, Yara; Kumar, S. Balaji

2017-11-01

Equatorial Kelvin waves (KWs) are fundamental components of the tropical climate system. In this study, we investigate Kelvin waves (KWs) during the Hai-Tang typhoon of 2005 using Empirical Mode Decomposition (EMD) of regional precipitation, zonal and meridional winds. For the analysis, we use daily precipitation datasets from the Global Precipitation Climatology Project (GPCP) and wind datasets from the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-analysis (ERA-Interim). As an additional measurement, we use in-situ precipitation datasets from rain-gauges over the Taiwan region. The maximum accumulated precipitation was approximately 2400 mm during the period July 17-21, 2005 over the southwestern region of Taiwan. The spectral analysis using the wind speed at 950 hPa found in the 2nd, 3rd, and 4th intrinsic mode functions (IMFs) reveals prevailing Kelvin wave periods of ∼3 days, ∼4-6 days, and ∼6-10 days, respectively. From our analysis of precipitation datasets, we found the Kelvin waves oscillated with periods between ∼8 and 20 days.

Analysis of extreme precipitation characteristics in low mountain areas based on three-dimensional copulas—taking Kuandian County as an example

NASA Astrophysics Data System (ADS)

Wang, Cailin; Ren, Xuehui; Li, Ying

2017-04-01

We defined the threshold of extreme precipitation using detrended fluctuation analysis based on daily precipitation during 1955-2013 in Kuandian County, Liaoning Province. Three-dimensional copulas were introduced to analyze the characteristics of four extreme precipitation factors: the annual extreme precipitation day, extreme precipitation amount, annual average extreme precipitation intensity, and extreme precipitation rate of contribution. The results show that (1) the threshold is 95.0 mm, extreme precipitation events generally occur 1-2 times a year, the average extreme precipitation intensity is 100-150 mm, and the extreme precipitation amount is 100-270 mm accounting for 10 to 37 % of annual precipitation. (2) The generalized extreme value distribution, extreme value distribution, and generalized Pareto distribution are suitable for fitting the distribution function for each element of extreme precipitation. The Ali-Mikhail-Haq (AMH) copula function reflects the joint characteristics of extreme precipitation factors. (3) The return period of the three types has significant synchronicity, and the joint return period and co-occurrence return period have long delay when the return period of the single factor is long. This reflects the inalienability of extreme precipitation factors. The co-occurrence return period is longer than that of the single factor and joint return period. (4) The single factor fitting only reflects single factor information of extreme precipitation but is unrelated to the relationship between factors. Three-dimensional copulas represent the internal information of extreme precipitation factors and are closer to the actual. The copula function is potentially widely applicable for the multiple factors of extreme precipitation.

Qualitative analysis of precipitate formation on the surface and in the tubules of dentin irrigated with sodium hypochlorite and a final rinse of chlorhexidine or QMiX.

PubMed

Kolosowski, Kamil P; Sodhi, Rana N S; Kishen, Anil; Basrani, Bettina R

2014-12-01

Interaction of sodium hypochlorite (NaOCl) mixed with chlorhexidine (CHX) produces a brown precipitate containing para-chloroaniline (PCA). When QMiX is mixed with NaOCl, no precipitate forms, but color change occurs. The aim of this study was to qualitatively assess the formation of precipitate and PCA on the surface and in the tubules of dentin irrigated with NaOCl, followed either by EDTA, NaOCl, and CHX or by saline and QMiX by using time-of-flight secondary ion mass spectrometry (TOF-SIMS). Dentin blocks were obtained from human maxillary molars, embedded in resin, and cross-sectioned to expose dentin. Specimens in group 1 were immersed in 2.5% NaOCl, followed by 17% EDTA, 2.5% NaOCl, and 2% CHX. Specimens in group 2 were immersed in 2.5% NaOCl, followed by saline and QMiX. The dentin surfaces were subjected to TOF-SIMS spectra analysis. Longitudinal sections of dentin blocks were then exposed and subjected to TOF-SIMS analysis. All samples and analysis were performed in triplicate for confirmation. TOF-SIMS analysis of group 1 revealed an irregular precipitate, containing PCA and CHX breakdown products, on the dentin surfaces, occluding and extending into the tubules. In TOF-SIMS analysis of group 2, no precipitates, including PCA, were detected on the dentin surface or in the tubules. Within the limitations of this study, precipitate containing PCA was formed in the tubules of dentin irrigated with NaOCl followed by CHX. No precipitates or PCA were detected in the tubules of dentin irrigated with NaOCl followed by saline and QMiX. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

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...

Widespread, Very Heavy Precipitation Events in Contemporary and Scenario Summer Climates from NARCCAP Simulations

NASA Astrophysics Data System (ADS)

Kawazoe, S.; Gutowski, W. J., Jr.

2015-12-01

We analyze the ability of regional climate models (RCMs) to simulate very heavy daily precipitation and supporting processes for both contemporary and future-scenario simulations during summer (JJA). RCM output comes from North American Regional Climate Change Assessment Program (NARCCAP) simulations, which are all run at a spatial resolution of 50 km. Analysis focuses on the upper Mississippi basin for summer, between 1982-1998 for the contemporary climate, and 2052-2068 during the scenario climate. We also compare simulated precipitation and supporting processes with those obtained from observed precipitation and reanalysis atmospheric states. Precipitation observations are from the University of Washington (UW) and the Climate Prediction Center (CPC) gridded dataset. Utilizing two observational datasets helps determine if any uncertainties arise from differences in precipitation gridding schemes. Reanalysis fields come from the North American Regional Reanalysis. The NARCCAP models generally reproduce well the precipitation-vs.-intensity spectrum seen in observations, while producing overly strong precipitation at high intensity thresholds. In the future-scenario climate, there is a decrease in frequency for light to moderate precipitation intensities, while an increase in frequency is seen for the higher intensity events. Further analysis focuses on precipitation events exceeding the 99.5 percentile that occur simultaneously at several points in the region, yielding so-called "widespread events". For widespread events, we analyze local and large scale environmental parameters, such as 2-m temperature and specific humidity, 500-hPa geopotential heights, Convective Available Potential Energy (CAPE), vertically integrated moisture flux convergence, among others, to compare atmospheric states and processes leading to such events in the models and observations. The results suggest that an analysis of atmospheric states supporting very heavy precipitation events is a more fruitful path for understanding and detecting changes than simply looking at precipitation itself.

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.

Evaluation of Uncertainty in Precipitation Datasets for New Mexico, USA

NASA Astrophysics Data System (ADS)

Besha, A. A.; Steele, C. M.; Fernald, A.

2014-12-01

Climate change, population growth and other factors are endangering water availability and sustainability in semiarid/arid areas particularly in the southwestern United States. Wide coverage of spatial and temporal measurements of precipitation are key for regional water budget analysis and hydrological operations which themselves are valuable tool for water resource planning and management. Rain gauge measurements are usually reliable and accurate at a point. They measure rainfall continuously, but spatial sampling is limited. Ground based radar and satellite remotely sensed precipitation have wide spatial and temporal coverage. However, these measurements are indirect and subject to errors because of equipment, meteorological variability, the heterogeneity of the land surface itself and lack of regular recording. This study seeks to understand precipitation uncertainty and in doing so, lessen uncertainty propagation into hydrological applications and operations. We reviewed, compared and evaluated the TRMM (Tropical Rainfall Measuring Mission) precipitation products, NOAA's (National Oceanic and Atmospheric Administration) Global Precipitation Climatology Centre (GPCC) monthly precipitation dataset, PRISM (Parameter elevation Regression on Independent Slopes Model) data and data from individual climate stations including Cooperative Observer Program (COOP), Remote Automated Weather Stations (RAWS), Soil Climate Analysis Network (SCAN) and Snowpack Telemetry (SNOTEL) stations. Though not yet finalized, this study finds that the uncertainty within precipitation estimates datasets is influenced by regional topography, season, climate and precipitation rate. Ongoing work aims to further evaluate precipitation datasets based on the relative influence of these phenomena so that we can identify the optimum datasets for input to statewide water budget analysis.

The BlueSky Smoke Modeling Framework: Recent Developments

NASA Astrophysics Data System (ADS)

Sullivan, D. C.; Larkin, N.; Raffuse, S. M.; Strand, T.; ONeill, S. M.; Leung, F. T.; Qu, J. J.; Hao, X.

2012-12-01

BlueSky systems—a set of decision support tools including SmartFire and the BlueSky Framework—aid public policy decision makers and scientific researchers in evaluating the air quality impacts of fires. Smoke and fire managers use BlueSky systems in decisions about prescribed burns and wildland firefighting. Air quality agencies use BlueSky systems to support decisions related to air quality regulations. We will discuss a range of recent improvements to the BlueSky systems, as well as examples of applications and future plans. BlueSky systems have the flexibility to accept basic fire information from virtually any source and can reconcile multiple information sources so that duplication of fire records is eliminated. BlueSky systems currently apply information from (1) the National Oceanic and Atmospheric Administration's (NOAA) Hazard Mapping System (HMS), which represents remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR), and Geostationary Operational Environmental Satellites (GOES); (2) the Monitoring Trends in Burn Severity (MTBS) interagency project, which derives fire perimeters from Landsat 30-meter burn scars; (3) the Geospatial Multi-Agency Coordination Group (GeoMAC), which produces helicopter-flown burn perimeters; and (4) ground-based fire reports, such as the ICS-209 reports managed by the National Wildfire Coordinating Group. Efforts are currently underway to streamline the use of additional ground-based systems, such as states' prescribed burn databases. BlueSky systems were recently modified to address known uncertainties in smoke modeling associated with (1) estimates of biomass consumption derived from sparse fuel moisture data, and (2) models of plume injection heights. Additional sources of remotely sensed data are being applied to address these issues as follows: - The National Aeronautics and Space Administration's (NASA) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis Real-Time (TMPA-RT) data set is being used to improve dead fuel moisture estimates. - EastFire live fuel moisture estimates, which are derived from NASA's MODIS direct broadcast, are being used to improve live fuel moisture estimates. - NASA's Multi-angle Imaging Spectroradiometer (MISR) stereo heights are being used to improve estimates of plume injection heights. Further, the Fire Location and Modeling of Burning Emissions (FLAMBÉ) model was incorporated into the BlueSky Framework as an alternative means of calculating fire emissions. FLAMBÉ directly estimates emissions on the basis of fire detections and radiance measures from NASA's MODIS and NOAA's GOES satellites. (The authors gratefully acknowledge NASA's Applied Sciences Program [Grant Nos. NN506AB52A and NNX09AV76G)], the USDA Forest Service, and the Joint Fire Science Program for their support.)

Seasonal and annual precipitation time series trend analysis in North Carolina, United States

NASA Astrophysics Data System (ADS)

Sayemuzzaman, Mohammad; Jha, Manoj K.

2014-02-01

The present study performs the spatial and temporal trend analysis of the annual and seasonal time-series of a set of uniformly distributed 249 stations precipitation data across the state of North Carolina, United States over the period of 1950-2009. The Mann-Kendall (MK) test, the Theil-Sen approach (TSA) and the Sequential Mann-Kendall (SQMK) test were applied to quantify the significance of trend, magnitude of trend, and the trend shift, respectively. Regional (mountain, piedmont and coastal) precipitation trends were also analyzed using the above-mentioned tests. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation of precipitation data series. The application of the above-mentioned procedures has shown very notable statewide increasing trend for winter and decreasing trend for fall precipitation. Statewide mixed (increasing/decreasing) trend has been detected in annual, spring, and summer precipitation time series. Significant trends (confidence level ≥ 95%) were detected only in 8, 7, 4 and 10 nos. of stations (out of 249 stations) in winter, spring, summer, and fall, respectively. Magnitude of the highest increasing (decreasing) precipitation trend was found about 4 mm/season (- 4.50 mm/season) in fall (summer) season. Annual precipitation trend magnitude varied between - 5.50 mm/year and 9 mm/year. Regional trend analysis found increasing precipitation in mountain and coastal regions in general except during the winter. Piedmont region was found to have increasing trends in summer and fall, but decreasing trend in winter, spring and on an annual basis. The SQMK test on "trend shift analysis" identified a significant shift during 1960 - 70 in most parts of the state. Finally, the comparison between winter (summer) precipitations with the North Atlantic Oscillation (Southern Oscillation) indices concluded that the variability and trend of precipitation can be explained by the Oscillation indices for North Carolina.

Determine precipitation rates from visible and infrared satellite images of clouds by pattern recognition technique. Progress Report, 1 Jul. 1985 - 31 Mar. 1987 Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Weinman, James A.; Garan, Louis

1987-01-01

A more advanced cloud pattern analysis algorithm was subsequently developed to take the shape and brightness of the various clouds into account in a manner that is more consistent with the human analyst's perception of GOES cloud imagery. The results of that classification scheme were compared with precipitation probabilities observed from ships of opportunity off the U.S. east coast to derive empirical regressions between cloud types and precipitation probability. The cloud morphology was then quantitatively and objectively used to map precipitation probabilities during two winter months during which severe cold air outbreaks were observed over the northwest Atlantic. Precipitation probabilities associated with various cloud types are summarized. Maps of precipitation probability derived from the cloud morphology analysis program for two months and the precipitation probability derived from thirty years of ship observation were observed.

Associating extreme precipitation events to parent cyclones in gridded data

NASA Astrophysics Data System (ADS)

Rhodes, Ruari; Shaffrey, Len; Gray, Sue

2015-04-01

When analysing the relationship of regional precipitation to its parent cyclone, it is insufficient to consider the cyclone's region of influence as a fixed radius from the centre due to the irregular shape of rain bands. A new method is therefore presented which allows the use of objective feature tracking data in the analysis of regional precipitation. Utilising the spatial extent of precipitation in gridded datasets, the most appropriate cyclone(s) may be associated with regional precipitation events. This method is applied in the context of an analysis of the influence of clustering and stalling of extra-tropical cyclones in the North Atlantic on total precipitation accumulations over England and Wales. Cyclone counts and residence times are presented for historical records (ERA-Interim) and future projections (HadGEM2-ES) of extreme (> 98th percentile) precipitation accumulations over England and Wales, for accumulation periods ranging from one day to one month.

TOWARDS AN IMPROVED UNDERSTANDING OF SIMULATED AND OBSERVED CHANGES IN EXTREME PRECIPITATION

EPA Science Inventory

The evaluation of climate model precipitation is expected to reveal biases in simulated mean and extreme precipitation which may be a result of coarse model resolution or inefficiencies in the precipitation generating mechanisms in models. The analysis of future extreme precip...

Diagnosis of inconsistencies in multi-year gridded precipitation data over mountainous areas and related impacts on hydrologic simulations

NASA Astrophysics Data System (ADS)

Mizukami, N.; Smith, M. B.

2010-12-01

It is common for the error characteristics of long-term precipitation data to change over time due to various factors such as gauge relocation and changes in data processing methods. The temporal consistency of precipitation data error characteristics is as important as data accuracy itself for hydrologic model calibration and subsequent use of the calibrated model for streamflow prediction. In mountainous areas, the generation of precipitation grids relies on sparse gage networks, the makeup of which often varies over time. This causes a change in error characteristics of the long-term precipitation data record. We will discuss the diagnostic analysis of the consistency of gridded precipitation time series and illustrate the adverse effect of inconsistent precipitation data on a hydrologic model simulation. We used hourly 4 km gridded precipitation time series over a mountainous basin in the Sierra Nevada Mountains of California from October 1988 through September 2006. The basin is part of the broader study area that served as the focus of the second phase of the Distributed Model Intercomparison Project (DMIP-2), organized by the U.S. National Weather Service (NWS) of the National Oceanographic and Atmospheric Administration (NOAA). To check the consistency of the gridded precipitation time series, double mass analysis was performed using single pixel and basin mean areal precipitation (MAP) values derived from gridded DMIP-2 and Parameter-Elevation Regressions on Independent Slopes Model (PRISM) precipitation data. The analysis leads to the conclusion that over the entire study time period, a clear change in error characteristics in the DMIP-2 data occurred in the beginning of 2003. This matches the timing of one of the major gage network changes. The inconsistency of two MAP time series computed from the gridded precipitation fields over two elevation zones was corrected by adjusting hourly values based on the double mass analysis. We show that model simulations using the adjusted MAP data produce improved stream flow compared to simulations using the inconsistent MAP input data.

Global Precipitation Analyses at Time Scales of Monthly to 3-Hourly

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric; Einaudi, Franco (Technical Monitor)

2002-01-01

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the Goodyear data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the Goodyear period. Monthly anomalies of precipitation are related to ENRON variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 degree latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based Based analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous OR observations and merges the various calibrated observations into a final, Baehr resolution map. This TRMM standard product will be available for the entire TRMM period (January Represent). A real-time version of this merged product is being produced and is available at 0.25 degree latitude-longitude resolution over the latitude range from 50 deg. N -50 deg. S. Examples will be shown, including its use in monitoring flood conditions.

Multi-scale Quantitative Precipitation Forecasting Using ...

EPA Pesticide Factsheets

Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals difficult to be detected at a local scale as it could cause large uncertainties when using linear correlation analysis only. This paper explores the relationship between global SST and terrestrial precipitation with respect to long-term non-stationary teleconnection signals during 1981-2010 over three regions in North America and one in Central America. Empirical mode decomposition as well as wavelet analysis is utilized to extract the intrinsic trend and the dominant oscillation of the SST and precipitation time series in sequence. After finding possible associations between the dominant oscillation of seasonal precipitation and global SST through lagged correlation analysis, the statistically significant SST regions are extracted based on the correlation coefficient. With these characterized associations, individual contribution of these SST forcing regions linked to the related precipitation responses are further quantified through nonlinear modeling with the aid of extreme learning machine. Results indicate that the non-leading SST regions also contribute a salient portion to the terrestrial precipitation variability compared to some known leading SST regions. In some cases, these

Comparison of future and base precipitation anomalies by SimCLIM statistical projection through ensemble approach in Pakistan

NASA Astrophysics Data System (ADS)

Amin, Asad; Nasim, Wajid; Mubeen, Muhammad; Kazmi, Dildar Hussain; Lin, Zhaohui; Wahid, Abdul; Sultana, Syeda Refat; Gibbs, Jim; Fahad, Shah

2017-09-01

Unpredictable precipitation trends have largely influenced by climate change which prolonged droughts or floods in South Asia. Statistical analysis of monthly, seasonal, and annual precipitation trend carried out for different temporal (1996-2015 and 2041-2060) and spatial scale (39 meteorological stations) in Pakistan. Statistical downscaling model (SimCLIM) was used for future precipitation projection (2041-2060) and analyzed by statistical approach. Ensemble approach combined with representative concentration pathways (RCPs) at medium level used for future projections. The magnitude and slop of trends were derived by applying Mann-Kendal and Sen's slop statistical approaches. Geo-statistical application used to generate precipitation trend maps. Comparison of base and projected precipitation by statistical analysis represented by maps and graphical visualization which facilitate to detect trends. Results of this study projects that precipitation trend was increasing more than 70% of weather stations for February, March, April, August, and September represented as base years. Precipitation trend was decreased in February to April but increase in July to October in projected years. Highest decreasing trend was reported in January for base years which was also decreased in projected years. Greater variation in precipitation trends for projected and base years was reported in February to April. Variations in projected precipitation trend for Punjab and Baluchistan highly accredited in March and April. Seasonal analysis shows large variation in winter, which shows increasing trend for more than 30% of weather stations and this increased trend approaches 40% for projected precipitation. High risk was reported in base year pre-monsoon season where 90% of weather station shows increasing trend but in projected years this trend decreased up to 33%. Finally, the annual precipitation trend has increased for more than 90% of meteorological stations in base (1996-2015) which has decreased for projected year (2041-2060) up to 76%. These result revealed that overall precipitation trend is decreasing in future year which may prolonged the drought in 14% of weather stations under study.

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 in this analysis, preliminary results from the development of a flexible categorization scheme, that scales with grid resolution, are presented.

Developing the Second Generation CMORPH: A Prototype

NASA Astrophysics Data System (ADS)

Xie, Pingping; Joyce, Robert

2014-05-01

A prototype system of the second generation CMORPH is being developed at NOAA Climate Prediction Center (CPC) to produce global analyses of 30-min precipitation on a 0.05deg lat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. First, precipitation estimation / retrievals from various sources are mapped onto a global grid of 0.05deg lat/lon and calibrated against a common reference field to ensure consistency in their precipitation rate PDF structures. The motion vectors for the precipitating cloud systems are then defined using information from both satellite IR observations and precipitation fields generated by the NCEP Climate Forecast System Reanalysis (CFSR). To this end, motion vectors are first computed from CFSR hourly precipitation fields through cross-correlation analysis of consecutive hourly precipitation fields on the global T382 (~35 km) grid. In a similar manner, separate processing is also performed on satellite IR-based precipitation estimates to derive motion vectors from observations. A blended analysis of precipitating cloud motion vectors is then constructed through the combination of CFSR and satellite-derived vectors with an objective analysis technique. Fine resolution mapped PMW precipitation retrievals are then separately propagated along the motion vectors from their respective observation times to the target analysis time from both forward and backward directions. The CMORPH high resolution precipitation analyses are finally constructed through the combination of propagated PMW retrievals with the IR based estimates for the target analysis time. This Kalman Filter based CMORPH processing is performed for rainfall and snowfall fields separately with the same motion vectors. Experiments have been conducted for two periods of two months each, July - August 2009, and January - February 2010, to explore the development of an optimal algorithm that generates global precipitation for summer and winter situations. Preliminary results demonstrated technical feasibility to construct global rainfall and snowfall analyses through the integration of information from multiple sources. More work is underway to refine various technical components of the system for operational applications of the system. Detailed results will be reported at the EGU meeting.

Precipitation recycling as a mechanism for ecoclimatological stability through local and non-local interactions

NASA Astrophysics Data System (ADS)

Dominguez, Francina

This study is the first to analyze the mechanisms that drive precipitation recycling variability at the daily to intraseasonal timescale. A new Dynamic Precipitation Recycling model is developed which, unlike previous models, includes the moisture storage term in the equation of conservation of atmospheric moisture. As shown using scaling analysis, the moisture storage term is non-negligible at small time scales, so the new model enables us to analyze precipitation recycling variability at shorter timescales than traditional models. The daily to intraseasonal analysis enables us to uncover key relationships between recycling and the moisture and energy fluxes. In the second phase of this work, a spatiotemporal analysis of daily precipitation recycling is performed over two regions of North America: the Midwestern United States, and the North American Monsoon System (NAMS) region. These regions were chosen because they present contrasting land-atmosphere interactions. Different physical mechanisms drive precipitation recycling in each region. In the Midwestern United States, evapotranspiration is not significantly affected by soil moisture anomalies, and there is a high recycling ratio during periods of reduced total precipitation. The reason is that, during periods of drier atmospheric conditions, transpiration will continue to provide moisture to the overlying atmosphere and contribute to total rainfall. Consequently, precipitation recycling variability in not driven by changes in evapotranspiration. Precipitable water, sensible heat and moisture fluxes are the main drivers of recycling variability in the Midwest. However, the drier soil moisture conditions over the NAMS region limit evapotranspiration, which will drive recycling variability. In this region, evapotranspiration becomes an important contribution to precipitation after Monsoon onset when total precipitation and evapotranspiration are highest. The precipitation recycling process in the NAMS region relocates moisture from regions of high evapotranspiration like the seasonally dry tropical forests of Mexico to drier regions downwind. During long monsoons, when soil moisture is abundant for a prolonged period of time, precipitation recycling significantly contributes to precipitation during periods of reduced total rainfall. In both the moisture abundant Midwestern region and the drier NAMS region, precipitation recycling plays an important role in maintaining a favorable hydroclimatological environment for vegetation.

Trend analysis of hydro-climatic variables in the north of Iran

NASA Astrophysics Data System (ADS)

Nikzad Tehrani, E.; Sahour, H.; Booij, M. J.

2018-04-01

Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z < -1.96) and an upward trend in annual maximum daily precipitation. Annual and monthly mean flows for most of the months in the Neka basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value < 0.05). Correlation coefficients for Kendall, Spearman's rank and linear regression are 0.43, 0.61, and 0.67, respectively. The spatial presentation of the detected precipitation and streamflow trends showed a downward trend for the mean annual precipitation observed in the upstream part of the study area which is consistent with the streamflow trend. Also, there is a good correlation between monthly and seasonal precipitation and streamflow for all sub-basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.

Precipitate statistics in an Al-Mg-Si-Cu alloy from scanning precession electron diffraction data

NASA Astrophysics Data System (ADS)

Sunde, J. K.; Paulsen, Ø.; Wenner, S.; Holmestad, R.

2017-09-01

The key microstructural feature providing strength to age-hardenable Al alloys is nanoscale precipitates. Alloy development requires a reliable statistical assessment of these precipitates, in order to link the microstructure with material properties. Here, it is demonstrated that scanning precession electron diffraction combined with computational analysis enable the semi-automated extraction of precipitate statistics in an Al-Mg-Si-Cu alloy. Among the main findings is the precipitate number density, which agrees well with a conventional method based on manual counting and measurements. By virtue of its data analysis objectivity, our methodology is therefore seen as an advantageous alternative to existing routines, offering reproducibility and efficiency in alloy statistics. Additional results include improved qualitative information on phase distributions. The developed procedure is generic and applicable to any material containing nanoscale precipitates.

A precipitation regionalization and regime for Iran based on multivariate analysis

NASA Astrophysics Data System (ADS)

Raziei, Tayeb

2018-02-01

Monthly precipitation time series of 155 synoptic stations distributed over Iran, covering 1990-2014 time period, were used to identify areas with different precipitation time variability and regimes utilizing S-mode principal component analysis (PCA) and cluster analysis (CA) preceded by T-mode PCA, respectively. Taking into account the maximum loading values of the rotated components, the first approach revealed five sub-regions characterized by different precipitation time variability, while the second method delineated eight sub-regions featured with different precipitation regimes. The sub-regions identified by the two used methods, although partly overlapping, are different considering their areal extent and complement each other as they are useful for different purposes and applications. Northwestern Iran and the Caspian Sea area were found as the two most distinctive Iranian precipitation sub-regions considering both time variability and precipitation regime since they were well captured with relatively identical areas by the two used approaches. However, the areal extents of the other three sub-regions identified by the first approach were not coincident with the coverage of their counterpart sub-regions defined by the second approach. Results suggest that the precipitation sub-region identified by the two methods would not be necessarily the same, as the first method which accounts for the variance of the data grouped stations with similar temporal variability while the second one which considers a fixed climatology defined by the average over the period 1990-2014 clusters stations having a similar march of monthly precipitation.

Subtropical air masses over eastern Canada: Their links to extreme precipitation

NASA Astrophysics Data System (ADS)

Gyakum, John; Wood, Alice; Milrad, Shawn; Atallah, Eyad

2017-04-01

We investigate extremely warm, moist air masses with an analysis of 850-hPa equivalent potential temperature (θe) extremes at Montreal, Quebec. The utility of using this metric is that it represents the thermodynamic property of air that ascends during a precipitation event. We produce an analysis of the 40 most extreme cases of positive θe, 10 for each season, based upon standardized anomalies from the 33-year climatology. The analysis shows the cases to be characterized by air masses with distinct subtropical traits for all seasons: reduced static stability, anomalously high precipitable water, and anomalously elevated dynamic tropopause heights. Persistent, slow moving upper- and lower-level features were essential in the build up of high- θe air encompassing much of eastern Canada. The trajectory analysis also showed anticyclonic curvature to all paths in all seasons, implying that the subtropical anticyclone is crucial in the transport of high- θe air. These atmospheric rivers during the winter are characterized by trajectories from the subtropical North Atlantic, and over the Gulf Stream current, northward into Montreal. In contrast, the summer anticyclonic trajectories are primarily continental, traveling from Texas north-northeastward into the Great Lakes, and then eastward into Montreal. The role of the air mass in modulating the strength of a precipitation event is addressed with an analysis of the expression, P = RD, where P is the total precipitation, and R is the precipitation rate, averaged through the duration, D, of the event. Though appearing simple, this expression includes R, (assumed to be same as condensation, with an efficiency of 1), which may be expressed as the product of vertical motion and the change of saturation mixing ratio following a moist adiabat, through the troposphere. This expression for R includes the essential ingredients of lift, air mass temperature, and static stability (implicit in vertical motion). We use this expression for precipitation rate to study the extreme precipitation events in Montreal that are associated with these same cases of extreme warm, moist air masses, and their physical impacts on the precipitation rate. Implications of this air mass modulation on precipitation rate are discussed in the context of longer-term global climate change.

Further analysis of a snowfall enhancement project in the Snowy Mountains of Australia

NASA Astrophysics Data System (ADS)

Manton, Michael J.; Peace, Andrew D.; Kemsley, Karen; Kenyon, Suzanne; Speirs, Johanna C.; Warren, Loredana; Denholm, John

2017-09-01

The first phase of the Snowy Precipitation Enhancement Research Project (SPERP-1) was a confirmatory experiment on winter orographic cloud seeding (Manton et al., 2011). Analysis of the data (Manton and Warren, 2011) found that a statistically significant impact of seeding could be obtained by removing any 5-hour experimental units (EUs) for which the amount of released seeding material was below a specified minimum. Analysis of the SPERP-1 data is extended in the present work by first considering the uncertainties in the measurement of precipitation and in the methodology. It is found that the estimation of the natural precipitation in the target area, based solely on the precipitation in the designated control area, is a significant source of uncertainty. A systematic search for optimal predictors shows that both the Froude number of the low-level flow across the mountains and the control precipitation should be used to estimate the natural precipitation. Applying the optimal predictors for the natural precipitation, statistically significant impacts are found using all EUs. This approach also supports a novel analysis of the sensitivity of seeding impacts to environmental variables, such as wind speed and cloud top temperature. The spatial distribution of seeding impact across the target is investigated. Building on the results of SPERP-1, phase 2 of the experiment (SPERP-2) ran from 2010 to 2013 with the target area extended to the north along the mountain ridges. Using the revised methodology, the seeding impacts in SPERP-2 are found to be consistent with those in SPERP-1, provided that the natural precipitation is estimated accurately.

Arctic Climate during Eocene Hyperthermals: Wet Summers on Ellesmere Island?

NASA Astrophysics Data System (ADS)

Greenwood, D. R.; West, C. K.; Basinger, J. F.

2012-12-01

Previous work has shown that during the late Paleocene to middle Eocene, mesothermal conditions (i.e., MAT ~12-15° C) and high precipitation (MAP > 150cm/yr) characterized Arctic climates - an Arctic rain forest. Recent analyses of Arctic Eocene wood stable isotope chemistry are consistent with the annual and seasonal temperature estimates from leaf physiognomy and nearest living relative analogy from fossil plants, including the lack of freezing winters, but is interpreted as showing that there was a summer peak in precipitation - modern analogs are best sought on the summer-wet east coasts (e.g., China, Japan, South Korea) not the winter-wet west coasts of present-day northern temperate continents (e.g., Pacific northwest of North America). Highly seasonal 'monsoon-type' summer-wet precipitation regimes (i.e., summer precip./winter precip. > 3.0) seem to characterize Eocene hyperthermal conditions in several regions of the earth, including the Arctic and Antarctic, based on both climate model sensitivity experiments and the paleoclimate proxy evidence. The leaf physiognomy proxy previously applied to estimate Arctic Paleogene precipitation was leaf area analysis (LAA), a correlation between mean leaf size in woody dicot vegetation and annual precipitation. New data from modern monsoonal sites, however demonstrates that for deciduous-dicot dominated vegetation, summer precipitation determines mean leaf size, not annual totals, and therefore that under markedly seasonal precipitation and/or light regimes that summer precipitation is being estimated using LAA. Presented here is a new analysis of a leaf macrofloras from 3 separate florules of the Margaret Formation (Split Lake, Stenkul Fiord and Strathcona Fiord) from Ellesmere Island that are placed stratigraphically as early Eocene, and likely fall within Eocene thermal maximum 1 (ETM1; = the 'PETM') or ETM2. These floras are each characterized by a mix of large-leafed and small-leafed dicot taxa, with overall mean leaf size across all leaf morphotypes comparable to that previously reported for late Paleocene to middle Eocene floras from Ellesmere and Axel Heiberg islands of Nunavut. Applying the conventional leaf area analysis to the putatively ETM1 floras yielded estimates of mean annual precipitation 100-200cm/yr, consistent with the previous reports for the late Paleocene to middle Eocene. CLAMP analysis applied to these floras yields growing season precipitation comparable to the annual precipitation estimate from leaf area analysis. These data are interpreted as reflecting high summer precipitation in the Arctic during the late Paleocene to middle Eocene, including ETM1, as precipitation in the dark polar winter months will have had no effect on leaf size while the trees were dormant, corroborating the results from Eocene wood chemistry. High summer precipitation (i.e., light-season = wettest season) in the Eocene Arctic during hyperthermals would have contributed to regional warmth.

CO-PRECIPITATION IN QUANTITATIVE ANALYSIS. COMMUNICATION V. THE INFLUENCE EXERCISED BY COMPLEXION UPON THE PRECIPITATION OF ZIRCONIUM PHOSPHATE

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

Babko, A.K.; Shtokalo, M.I.

The influence exercised by ethylenediamino-tetraacetic acid upon some processes of precipitation was investigated. A sharp mopdification of the form of precipitate as well as a decrease of coprecipitation was ium and titanium by means of the phosphate ;method are given. (TCO-W.D.M.)

The Use of Convolutional Neural Network in Relating Precipitation to Circulation

NASA Astrophysics Data System (ADS)

Pan, B.; Hsu, K. L.; AghaKouchak, A.; Sorooshian, S.

2017-12-01

Precipitation prediction in dynamical weather and climate models depends on 1) the predictability of pressure or geopotential height for the forecasting period and 2) the successive work of interpreting the pressure field in terms of precipitation events. The later task is represented as parameterization schemes in numerical models, where detailed computing inevitably blurs the hidden cause-and-effect relationship in precipitation generation. The "big data" provided by numerical simulation, reanalysis and observation networks requires better causation analysis for people to digest and realize their use. While classic synoptical analysis methods are very-often insufficient for spatially distributed high dimensional data, a Convolutional Neural Network(CNN) is developed here to directly relate precipitation with circulation. Case study carried over west coast United States during boreal winter showed that CNN can locate and capture key pressure zones of different structures to project precipitation spatial distribution with high accuracy across hourly to monthly scales. This direct connection between atmospheric circulation and precipitation offers a probe for attributing precipitation to the coverage, location, intensity and spatial structure of characteristic pressure zones, which can be used for model diagnosis and improvement.

Application of an Ensemble Smoother to Precipitation Assimilation

NASA Technical Reports Server (NTRS)

Zhang, Sara; Zupanski, Dusanka; Hou, Arthur; Zupanski, Milija

2008-01-01

Assimilation of precipitation in a global modeling system poses a special challenge in that the observation operators for precipitation processes are highly nonlinear. In the variational approach, substantial development work and model simplifications are required to include precipitation-related physical processes in the tangent linear model and its adjoint. An ensemble based data assimilation algorithm "Maximum Likelihood Ensemble Smoother (MLES)" has been developed to explore the ensemble representation of the precipitation observation operator with nonlinear convection and large-scale moist physics. An ensemble assimilation system based on the NASA GEOS-5 GCM has been constructed to assimilate satellite precipitation data within the MLES framework. The configuration of the smoother takes the time dimension into account for the relationship between state variables and observable rainfall. The full nonlinear forward model ensembles are used to represent components involving the observation operator and its transpose. Several assimilation experiments using satellite precipitation observations have been carried out to investigate the effectiveness of the ensemble representation of the nonlinear observation operator and the data impact of assimilating rain retrievals from the TMI and SSM/I sensors. Preliminary results show that this ensemble assimilation approach is capable of extracting information from nonlinear observations to improve the analysis and forecast if ensemble size is adequate, and a suitable localization scheme is applied. In addition to a dynamically consistent precipitation analysis, the assimilation system produces a statistical estimate of the analysis uncertainty.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

IMPACT OF TRMM PRECIPITATION ON CPTEC’S RPSAS ANALYSIS

NASA Astrophysics Data System (ADS)

Herdies, D. L.; Bastarz, C. F.; Fernandez, J. P.

2009-12-01

In this work a data assimilation study was performed to assess the impact of estimated precipitation from TRMM (Tropical Rainfall Measuring Mission) on the CPTEC (Centro de Previsão de Tempo e Estudos Climáticos at Brasil) RPSAS (Regional Physical-space Statistical Analysis System) analyses and the Eta model forecast over the region of La Plata Basin, during a case o MCC (Mesoscale Convective Complex) occurred between 22th and 23th January 2003. The data assimilation system RPSAS and the mesoscale regional Eta model (both with 20km of spatial resolution) were run together with and without the TRMM precipitation. Is this study the assimilation of precipitation is basically a nudging process and is performed during the first guess stage by the Eta model, like in the NCEP (National Centers for Environmental Predictions) EDAS (Eta Data Assimilation System) precipitation data assimilation. During this process the model adjusts the precipitation by comparing, at which grid point and at which time step, the model precipitation against the TRMM precipitation. Doing this some adjustments are made on the latent heat vertical profile, water vapor mixing ratio and relative humidity, by considering the Betts-Miller-Janjic convective parameterization. On the next step, the RPSAS produces an analysis which covers most of the South America and the adjacent oceans. From this analysis the Eta model produces 6h, 12h, 18h and 24h forecast. Data collected from the SALLJEX (South America Low Level Jet EXperiment) was used to compare the forecasts of the model and the CPTEC 40km Regional Reanalysis was used to compare with the RPSAS analyses. Some preliminary results show that the precipitation assimilation improves the first hours of the forecast (typically 6h). The variables verified were the zonal and meridional wind, geopotential height and the precipitation. The convective precipitation fields were improved, mainly over the 6h forecast. This is an important improvement because the first guess field will serve as an analysis of the next forecast window. Also were noticed that the mean error for those variables was reduced (principally for the zonal wind). This reveals that with an improved first guess field, the model was able to detect the MCC occurred in the north of Argentina, due to the improved representation of the winds fields (direction and intensity), pressure and the surface variables.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region.

PubMed

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region

NASA Astrophysics Data System (ADS)

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Temporal and spatial characteristics of extreme precipitation events in the Midwest of Jilin Province based on multifractal detrended fluctuation analysis method and copula functions

NASA Astrophysics Data System (ADS)

Guo, Enliang; Zhang, Jiquan; Si, Ha; Dong, Zhenhua; Cao, Tiehua; Lan, Wu

2017-10-01

Environmental changes have brought about significant changes and challenges to water resources and management in the world; these include increasing climate variability, land use change, intensive agriculture, and rapid urbanization and industrial development, especially much more frequency extreme precipitation events. All of which greatly affect water resource and the development of social economy. In this study, we take extreme precipitation events in the Midwest of Jilin Province as an example; daily precipitation data during 1960-2014 are used. The threshold of extreme precipitation events is defined by multifractal detrended fluctuation analysis (MF-DFA) method. Extreme precipitation (EP), extreme precipitation ratio (EPR), and intensity of extreme precipitation (EPI) are selected as the extreme precipitation indicators, and then the Kolmogorov-Smirnov (K-S) test is employed to determine the optimal probability distribution function of extreme precipitation indicators. On this basis, copulas connect nonparametric estimation method and the Akaike Information Criterion (AIC) method is adopted to determine the bivariate copula function. Finally, we analyze the characteristics of single variable extremum and bivariate joint probability distribution of the extreme precipitation events. The results show that the threshold of extreme precipitation events in semi-arid areas is far less than that in subhumid areas. The extreme precipitation frequency shows a significant decline while the extreme precipitation intensity shows a trend of growth; there are significant differences in spatiotemporal of extreme precipitation events. The spatial variation trend of the joint return period gets shorter from the west to the east. The spatial distribution of co-occurrence return period takes on contrary changes and it is longer than the joint return period.

Under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear?

PubMed

Ye, Jian-Sheng; Pei, Jiu-Ying; Fang, Chao

2018-03-01

Understanding under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear is useful for accurately predicting the response of ecosystem function to global environmental change. Using long-term (2000-2016) net primary productivity (NPP)-precipitation datasets derived from satellite observations, we identify >5600pixels in the North Hemisphere landmass that fit either linear or nonlinear temporal NPP-precipitation relationships. Differences in climate (precipitation, radiation, ratio of actual to potential evapotranspiration, temperature) and soil factors (nitrogen, phosphorous, organic carbon, field capacity) between the linear and nonlinear types are evaluated. Our analysis shows that both linear and nonlinear types exhibit similar interannual precipitation variabilities and occurrences of extreme precipitation. Permutational multivariate analysis of variance suggests that linear and nonlinear types differ significantly regarding to radiation, ratio of actual to potential evapotranspiration, and soil factors. The nonlinear type possesses lower radiation and/or less soil nutrients than the linear type, thereby suggesting that nonlinear type features higher degree of limitation from resources other than precipitation. This study suggests several factors limiting the responses of plant productivity to changes in precipitation, thus causing nonlinear NPP-precipitation pattern. Precipitation manipulation and modeling experiments should combine with changes in other climate and soil factors to better predict the response of plant productivity under future climate. Copyright © 2017 Elsevier B.V. All rights reserved.

An Ultra-high Resolution Synthetic Precipitation Data for Ungauged Sites

NASA Astrophysics Data System (ADS)

Kim, Hong-Joong; Choi, Kyung-Min; Oh, Jai-Ho

2018-05-01

Despite the enormous damage caused by record heavy rainfall, the amount of precipitation in areas without observation points cannot be known precisely. One way to overcome these difficulties is to estimate meteorological data at ungauged sites. In this study, we have used observation data over Seoul city to calculate high-resolution (250-meter resolution) synthetic precipitation over a 10-year (2005-2014) period. Furthermore, three cases are analyzed by evaluating the rainfall intensity and performing statistical analysis over the 10-year period. In the case where the typhoon "Meari" passed to the west coast during 28-30 June 2011, the Pearson correlation coefficient was 0.93 for seven validation points, which implies that the temporal correlation between the observed precipitation and synthetic precipitation was very good. It can be confirmed that the time series of observation and synthetic precipitation in the period almost completely matches the observed rainfall. On June 28-29, 2011, the estimation of 10 to 30 mm h-1 of continuous strong precipitation was correct. In addition, it is shown that the synthetic precipitation closely follows the observed precipitation for all three cases. Statistical analysis of 10 years of data reveals a very high correlation coefficient between synthetic precipitation and observed rainfall (0.86). Thus, synthetic precipitation data show good agreement with the observations. Therefore, the 250-m resolution synthetic precipitation amount calculated in this study is useful as basic data in weather applications, such as urban flood detection.

Sampling of Atmospheric Precipitation and Deposits for Analysis of Atmospheric Pollution

PubMed Central

Skarżyńska, K.; Polkowska, Ż; Namieśnik, J.

2006-01-01

This paper reviews techniques and equipment for collecting precipitation samples from the atmosphere (fog and cloud water) and from atmospheric deposits (dew, hoarfrost, and rime) that are suitable for the evaluation of atmospheric pollution. It discusses the storage and preparation of samples for analysis and also presents bibliographic information on the concentration ranges of inorganic and organic compounds in the precipitation and atmospheric deposit samples. PMID:17671615

Modelling hydrologic and hydrodynamic processes in basins with large semi-arid wetlands

NASA Astrophysics Data System (ADS)

Fleischmann, Ayan; Siqueira, Vinícius; Paris, Adrien; Collischonn, Walter; Paiva, Rodrigo; Pontes, Paulo; Crétaux, Jean-François; Bergé-Nguyen, Muriel; Biancamaria, Sylvain; Gosset, Marielle; Calmant, Stephane; Tanimoun, Bachir

2018-06-01

Hydrological and hydrodynamic models are core tools for simulation of large basins and complex river systems associated to wetlands. Recent studies have pointed towards the importance of online coupling strategies, representing feedbacks between floodplain inundation and vertical hydrology. Especially across semi-arid regions, soil-floodplain interactions can be strong. In this study, we included a two-way coupling scheme in a large scale hydrological-hydrodynamic model (MGB) and tested different model structures, in order to assess which processes are important to be simulated in large semi-arid wetlands and how these processes interact with water budget components. To demonstrate benefits from this coupling over a validation case, the model was applied to the Upper Niger River basin encompassing the Niger Inner Delta, a vast semi-arid wetland in the Sahel Desert. Simulation was carried out from 1999 to 2014 with daily TMPA 3B42 precipitation as forcing, using both in-situ and remotely sensed data for calibration and validation. Model outputs were in good agreement with discharge and water levels at stations both upstream and downstream of the Inner Delta (Nash-Sutcliffe Efficiency (NSE) >0.6 for most gauges), as well as for flooded areas within the Delta region (NSE = 0.6; r = 0.85). Model estimates of annual water losses across the Delta varied between 20.1 and 30.6 km3/yr, while annual evapotranspiration ranged between 760 mm/yr and 1130 mm/yr. Evaluation of model structure indicated that representation of both floodplain channels hydrodynamics (storage, bifurcations, lateral connections) and vertical hydrological processes (floodplain water infiltration into soil column; evapotranspiration from soil and vegetation and evaporation of open water) are necessary to correctly simulate flood wave attenuation and evapotranspiration along the basin. Two-way coupled models are necessary to better understand processes in large semi-arid wetlands. Finally, such coupled hydrologic and hydrodynamic modelling proves to be an important tool for integrated evaluation of hydrological processes in such poorly gauged, large scale basins. We hope that this model application provides new ways forward for large scale model development in such systems, involving semi-arid regions and complex floodplains.

The role of the subtropical North Atlantic water cycle in recent US extreme precipitation events

NASA Astrophysics Data System (ADS)

Li, Laifang; Schmitt, Raymond W.; Ummenhofer, Caroline C.

2018-02-01

The role of the oceanic water cycle in the record-breaking 2015 warm-season precipitation in the US is analyzed. The extreme precipitation started in the Southern US in the spring and propagated northward to the Midwest and the Great Lakes in the summer of 2015. This seasonal evolution of precipitation anomalies represents a typical mode of variability of US warm-season precipitation. Analysis of the atmospheric moisture flux suggests that such a rainfall mode is associated with moisture export from the subtropical North Atlantic. In the spring, excessive precipitation in the Southern US is attributable to increased moisture flux from the northwestern portion of the subtropical North Atlantic. The North Atlantic moisture flux interacts with local soil moisture which enables the US Midwest to draw more moisture from the Gulf of Mexico in the summer. Further analysis shows that the relationship between the rainfall mode and the North Atlantic water cycle has become more significant in recent decades, indicating an increased likelihood of extremes like the 2015 case. Indeed, two record-high warm-season precipitation events, the 1993 and 2008 cases, both occurred in the more recent decades of the 66 year analysis period. The export of water from the North Atlantic leaves a marked surface salinity signature. The salinity signature appeared in the spring preceding all three extreme precipitation events analyzed in this study, i.e. a saltier-than-normal subtropical North Atlantic in spring followed by extreme Midwest precipitation in summer. Compared to the various sea surface temperature anomaly patterns among the 1993, 2008, and 2015 cases, the spatial distribution of salinity anomalies was much more consistent during these extreme flood years. Thus, our study suggests that preseason salinity patterns can be used for improved seasonal prediction of extreme precipitation in the Midwest.

An in situ USAXS-SAXS-WAXS study of precipitate size distribution evolution in a model Ni-based alloy.

PubMed

Andrews, Ross N; Serio, Joseph; Muralidharan, Govindarajan; Ilavsky, Jan

2017-06-01

Intermetallic γ' precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS-SAXS-WAXS) analysis can be used to evaluate the temporal evolution of an alloy's precipitate size distribution (PSD) and phase structure during in situ heat treatment. Analysis of PSDs from USAXS-SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoiding a priori definition of a functional form of the PSD. However, strong low- q scattering from grain boundaries and/or structure factor effects inhibit MaxEnt analysis of typical alloys. This work describes the extension of Bayesian-MaxEnt analysis methods to data exhibiting structure factor effects and low- q power law slopes and demonstrates their use in an in situ study of precipitate size evolution during heat treatment of a model Ni-Al-Si alloy.

An in situ USAXS–SAXS–WAXS study of precipitate size distribution evolution in a model Ni-based alloy

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

Andrews, Ross N.; Serio, Joseph A.; Muralidharan, Govindarajan

Intermetallic γ' precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS–SAXS–WAXS) analysis can be used to evaluate the temporal evolution of an alloy's precipitate size distribution (PSD) and phase structure duringin situheat treatment. Analysis of PSDs from USAXS–SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoidinga prioridefinition of a functional form of the PSD. However, strong low-qscattering from grain boundaries and/or structuremore » factor effects inhibit MaxEnt analysis of typical alloys. Lastly, this work describes the extension of Bayesian–MaxEnt analysis methods to data exhibiting structure factor effects and low-qpower law slopes and demonstrates their use in anin situstudy of precipitate size evolution during heat treatment of a model Ni–Al–Si alloy.« less

An in situ USAXS–SAXS–WAXS study of precipitate size distribution evolution in a model Ni-based alloy1

PubMed Central

Andrews, Ross N.; Serio, Joseph; Muralidharan, Govindarajan; Ilavsky, Jan

2017-01-01

Intermetallic γ′ precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS–SAXS–WAXS) analysis can be used to evaluate the temporal evolution of an alloy’s precipitate size distribution (PSD) and phase structure during in situ heat treatment. Analysis of PSDs from USAXS–SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoiding a priori definition of a functional form of the PSD. However, strong low-q scattering from grain boundaries and/or structure factor effects inhibit MaxEnt analysis of typical alloys. This work describes the extension of Bayesian–MaxEnt analysis methods to data exhibiting structure factor effects and low-q power law slopes and demonstrates their use in an in situ study of precipitate size evolution during heat treatment of a model Ni–Al–Si alloy. PMID:28656039

An in situ USAXS–SAXS–WAXS study of precipitate size distribution evolution in a model Ni-based alloy

DOE PAGES

Andrews, Ross N.; Serio, Joseph A.; Muralidharan, Govindarajan; ...

2017-05-30

Intermetallic γ' precipitates typically strengthen nickel-based superalloys. The shape, size and spatial distribution of strengthening precipitates critically influence alloy strength, while their temporal evolution characteristics determine the high-temperature alloy stability. Combined ultra-small-, small- and wide-angle X-ray scattering (USAXS–SAXS–WAXS) analysis can be used to evaluate the temporal evolution of an alloy's precipitate size distribution (PSD) and phase structure duringin situheat treatment. Analysis of PSDs from USAXS–SAXS data employs either least-squares fitting of a preordained PSD model or a maximum entropy (MaxEnt) approach, the latter avoidinga prioridefinition of a functional form of the PSD. However, strong low-qscattering from grain boundaries and/or structuremore » factor effects inhibit MaxEnt analysis of typical alloys. Lastly, this work describes the extension of Bayesian–MaxEnt analysis methods to data exhibiting structure factor effects and low-qpower law slopes and demonstrates their use in anin situstudy of precipitate size evolution during heat treatment of a model Ni–Al–Si alloy.« less

New X-Ray Technique to Characterize Nanoscale Precipitates in Aged Aluminum Alloys

NASA Astrophysics Data System (ADS)

Sitdikov, V. D.; Murashkin, M. Yu.; Valiev, R. Z.

2017-10-01

This paper puts forward a new technique for measurement of x-ray patterns, which enables to solve the problem of identification and determination of precipitates (nanoscale phases) in metallic alloys of the matrix type. The minimum detection limit of precipitates in the matrix of the base material provided by this technique constitutes as little as 1%. The identification of precipitates in x-ray patterns and their analysis are implemented through a transmission mode with a larger radiation area, longer holding time and higher diffractometer resolution as compared to the conventional reflection mode. The presented technique has been successfully employed to identify and quantitatively describe precipitates formed in the Al alloy of the Al-Mg-Si system as a result of artificial aging. For the first time, the x-ray phase analysis has been used to identify and measure precipitates formed during the alloy artificial aging.

Prediction of monthly-seasonal precipitation using coupled SVD patterns between soil moisture and subsequent precipitation

Treesearch

Yongqiang Liu

2003-01-01

It was suggested in a recent statistical correlation analysis that predictability of monthly-seasonal precipitation could be improved by using coupled singular value decomposition (SVD) pattems between soil moisture and precipitation instead of their values at individual locations. This study provides predictive evidence for this suggestion by comparing skills of two...

Hydrogen ion speciation in the acid precipitation of the northeastern United States

Treesearch

James N. Galloway; Gene E. Likens; Eric S. Edgerton

1976-01-01

The acidity of precipitation in rural, forested areas of the northeastern United States is dominated by the strong mineral acids, sulfuric and nitric. Weak acids have a negligible effect on the measured acidity (pH) of precipitation. These conclusions are based on total acidity titrations and detailed analysis of organic and inorganic components in precipitation.

Drivers in the Scaling Between Precipitation and Cloud Radiative Impacts in Deep Convection

NASA Astrophysics Data System (ADS)

Rapp, A. D.; Sun, L.; Smalley, K.

2017-12-01

The coupling between changes in radiation and precipitation has been demonstrated by a number of studies and suggests an important link between cloud and precipitation processes for defining climate sensitivity. Precipitation and radiative fluxes from CloudSat/CALIPSO retrieval products are used to examine the relationship between precipitation and cloud radiative impacts through two dimensionless parameters. The surface radiative cooling impact, Rc, represents the ratio of the surface shortwave cloud radiative effect to latent heating (LH) from precipitation. The atmospheric radiative heating impact, Rh, represents the ratio of the atmospheric cloud radiative effect to LH from precipitation. Together, these parameters describe the relationship between precipitation processes and how efficiently clouds cools the surface or heats the atmosphere. Deep convective clouds are identified using the 2B-GEOPROF-LIDAR joint radar-lidar product and the cloud radiative impact parameters are calculated from the 2B-FLXHR-LIDAR fluxes and 2C-RAIN-PROFILE precipitation. Deep convective clouds will be sampled according to their dynamic and thermodynamic regimes to provide insights into the factors that control the scaling between precipitation and radiative impacts. Preliminary results from analysis of precipitating deep convective pixels indicates a strong increase (decrease) in the ratio of atmospheric heating (surface cooling) and precipitation with thermodynamic environment, especially increasing water vapor; however, it remains to be seen whether these results hold when integrated over an entire deep convective cloud system. Analysis of the dependence of Rc and Rh on the cloud horizontal and vertical structure is also planned, which should lead to a better understanding of the role of non-precipitating anvil characteristics in modulating the relationship between precipitation and surface and atmospheric radiative effects.

Impact of Plant Functional Types on Coherence Between Precipitation and Soil Moisture: A Wavelet Analysis

NASA Astrophysics Data System (ADS)

Liu, Qi; Hao, Yonghong; Stebler, Elaine; Tanaka, Nobuaki; Zou, Chris B.

2017-12-01

Mapping the spatiotemporal patterns of soil moisture within heterogeneous landscapes is important for resource management and for the understanding of hydrological processes. A critical challenge in this mapping is comparing remotely sensed or in situ observations from areas with different vegetation cover but subject to the same precipitation regime. We address this challenge by wavelet analysis of multiyear observations of soil moisture profiles from adjacent areas with contrasting plant functional types (grassland, woodland, and encroached) and precipitation. The analysis reveals the differing soil moisture patterns and dynamics between plant functional types. The coherence at high-frequency periodicities between precipitation and soil moisture generally decreases with depth but this is much more pronounced under woodland compared to grassland. Wavelet analysis provides new insights on soil moisture dynamics across plant functional types and is useful for assessing differences and similarities in landscapes with heterogeneous vegetation cover.

Laser-Induced Dynamics of Peroxodicopper(II) Complexes Vary with the Ligand Architecture. One-Photon Two-Electron O2 Ejection and Formation of Mixed-Valent Cu(I)Cu(II)-Superoxide Intermediates.

PubMed

Saracini, Claudio; Ohkubo, Kei; Suenobu, Tomoyoshi; Meyer, Gerald J; Karlin, Kenneth D; Fukuzumi, Shunichi

2015-12-23

Photoexcitation of end-on trans-μ-1,2-peroxodicopper(II) complex [(tmpa)2Cu(II)2(O2)](2+) (1) (λmax = 525 and 600 nm) and side-on μ-η(2):η(2)-peroxodicopper(II) complexes [(N5)Cu(II)2(O2)](2+) (2) and [(N3)Cu(II)2(O2)](2+) (3) at -80 °C in acetone led to one-photon two-electron peroxide-to-dioxygen oxidation chemistry (O2(2-) + hν → O2 + 2e(-)). Interestingly, light excitation of 2 and 3 (having side-on μ-η(2):η(2)-peroxo ligation) led to release of dioxygen, while photoexcitation of 1 (having an end-on trans-1,2-peroxo geometry) did not, even though spectroscopic studies revealed that both reactions proceeded through previously unknown mixed-valent superoxide species: [Cu(II)(O2(•-))Cu(I)](2+) (λmax = 685-740 nm). For 1, this intermediate underwent further fast intramolecular electron transfer to yield an "O2-caged" dicopper(I) adduct, Cu(I)2-O2, and a barrierless stepwise back electron transfer to regenerate 1 occurred. Femtosecond laser excitation of 2 and 3 under the same conditions still led to [Cu(II)(O2(•-))Cu(I)](2+) intermediates that, instead, underwent O2 release with a quantum yield of 0.14 ± 0.1 for 3. Such remarkable differences in reaction pathways likely result from the well-known ligand-derived stability of 2 and 3 vs 1 indicated by ligand-Cu(II/I) redox potentials; (N5)Cu(I) and (N3)Cu(I) complexes are far more stable than (tmpa)Cu(I) species. The fast Cu(I)2/O2 rebinding kinetics was also measured after photoexcitation of 2 and 3, with the results closely tracking those known for the dicopper proteins hemocyanin and tyrosinase, for which the synthetic dicopper(I) precursors [(N5)Cu(I)2](2+) and [(N3)Cu(I)2](2+) and their dioxygen adducts serve as models. The biological relevance of the present findings is discussed, including the potential impact on the solar water splitting process.

Heat treatment of investment cast PH 13-8 Mo stainless steel: Part II. Isothermal aging kinetics

NASA Astrophysics Data System (ADS)

Robino, C. V.; Cieslak, M. J.; Hochanadel, P. W.; Edwards, G. R.

1994-04-01

The hardening response of investment cast PH 13-8 Mo stainless steel has been evaluated by hardness measurements following aging in the temperature range normally specified for this alloy (510 °C to 593 °C). A new relationship between fraction transformed and hardness was developed, and analysis of the data in terms of the kinetics of precipitation, in a manner similar to that frequently applied to other precipitation-hardenable martensitic steels, yielded low time exponents and a low value for the apparent activation energy. The values of the time exponents were 0.49, 0.37, 0.56, and 0.53 at 510 °C, 538 °C, 566 °C, and 593 °C, respectively, and that for the apparent activation energy was 139 kJ/mole. As has been proposed for other maraging type steels, these estimates suggest that Β-NiAl precipitates along or near dislocations and that growth of the precipitates is dominated by dislocation pipe diffusion. However, these predictions were neither supported nor refuted by transmission electron microscopy (TEM) because of difficulties in imaging the Β-NiAl precipitates at the aging times and temperatures used. Further, analysis of the data using the formalism of Wert and Zener for the growth of precipitates with interfering diffusion fields indicated that the estimates of fraction transformed from hardness data are not fully appropriate for maraging type steels. Consideration of the nature of the Avrami analysis and the electron microscopy results suggests that other phenomena, including dislocation recovery and reversion of martensite to austenite, occur at rates sufficient to convolute the Avrami analysis. It is further suggested that these results cast doubt on the fundamental implications of previous analyses of precipitation kinetics in age-hardening martensitic steels. Although the Avrami analysis was found not to provide a tenable description of the precipitation kinetics, it does provide a reasonable methodology for portrayal of the hardening response of PH 13-8 Mo stainless steel.

Impact of parameter fluctuations on the performance of ethanol precipitation in production of Re Du Ning Injections, based on HPLC fingerprints and principal component analysis.

PubMed

Sun, Li-Qiong; Wang, Shu-Yao; Li, Yan-Jing; Wang, Yong-Xiang; Wang, Zhen-Zhong; Huang, Wen-Zhe; Wang, Yue-Sheng; Bi, Yu-An; Ding, Gang; Xiao, Wei

2016-01-01

The present study was designed to determine the relationships between the performance of ethanol precipitation and seven process parameters in the ethanol precipitation process of Re Du Ning Injections, including concentrate density, concentrate temperature, ethanol content, flow rate and stir rate in the addition of ethanol, precipitation time, and precipitation temperature. Under the experimental and simulated production conditions, a series of precipitated resultants were prepared by changing these variables one by one, and then examined by HPLC fingerprint analyses. Different from the traditional evaluation model based on single or a few constituents, the fingerprint data of every parameter fluctuation test was processed with Principal Component Analysis (PCA) to comprehensively assess the performance of ethanol precipitation. Our results showed that concentrate density, ethanol content, and precipitation time were the most important parameters that influence the recovery of active compounds in precipitation resultants. The present study would provide some reference for pharmaceutical scientists engaged in research on pharmaceutical process optimization and help pharmaceutical enterprises adapt a scientific and reasonable cost-effective approach to ensure the batch-to-batch quality consistency of the final products. Copyright © 2016 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution

NASA Astrophysics Data System (ADS)

Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.

2011-12-01

Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite precipitation product, CMORPH, against the U.S. daily precipitation analysis of Climate Prediction Center (CPC) at a daily and .25o scale over the Western U.S.

Global Precipitation Analyses (3-Hourly to Monthly) Using TRMM, SSM/I and other Satellite Information

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric

2002-01-01

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM(Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 20-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 20 year period. Monthly anomalies of precipitation are related to ENS0 variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 deg. latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is discussed. Finally, a TRMM-based 3-hr analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map. This TRMM standard product will be available for the entire TRMM period (January 1998-present). A real-time version of this merged product is being produced and is available at 0.25 deg. latitude-longitude resolution over the latitude range from 5O deg. N-50 deg. S. Examples are shown, including its use in monitoring flood conditions.

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.

Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation

NASA Astrophysics Data System (ADS)

Kim, Beomgeun; Seo, Dong-Jun; Noh, Seong Jin; Prat, Olivier P.; Nelson, Brian R.

2018-01-01

A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.

Constraining precipitation amount and distribution over cold regions using GRACE

NASA Astrophysics Data System (ADS)

Behrangi, A.; Reager, J. T., II; Gardner, A. S.; Fisher, J.

2017-12-01

Current quantitative knowledge on the amount and distribution of precipitation in high-elevation and high latitude regions is limited due to instrumental and retrieval shortcomings. Here we demonstrate how that satellite gravimetry (Gravity Recovery and Climate Experiment, GRACE) can be used to provide an independent estimate of monthly accumulated precipitation using mass balance. Results showed that the GRACE-based precipitation estimate has the highest agreement with most of the commonly used precipitation products in summer, but it deviates from them in cold months, when the other products are expected to have larger error. We also observed that as near surface temperature decreases products tend to underestimate accumulated precipitation retrieved from GRACE. The analysis performed using various products such as GPCP, GPCC, TRMM, and gridded station data over vast regions in high latitudes and two large endorheic basins in High Mountain Asia. Based on the analysis over High Mountain Asia it was found that most of the products capture about or less than 50% of the total precipitation estimated using GRACE in winter. Overall, GPCP showed better agreement with GRACE estimate than other products. Yet on average GRACE showed 30% more annual precipitation than GPCP in the study basin.

Space-time characteristics and statistical predictability of extreme daily precipitation events in the Ohio River Basin

NASA Astrophysics Data System (ADS)

Farnham, D. J.; Doss-Gollin, J.; Lall, U.

2016-12-01

In this study we identify the atmospheric conditions that precede and accompany regional extreme precipitation events with the potential to cause flooding. We begin by identifying a coherent space-time structure in the record of extreme precipitation within the Ohio River Basin through both a Hidden Markov Model and a composite analysis. The transition probabilities associated with the Hidden Markov Model illustrate a tendency for west to east migration of extreme precipitation events (> 99th percentile) at individual stations within the Ohio River Basin. We compute a record of regional extreme precipitation days by requiring that > p% of the basin's stations simultaneously experience extreme precipitation days. A composite analysis of low-level geopotential heights and column integrated precipitable water content for all non-summer seasons confirms a west to east migration and intensification of 1) a low (high) pressure center to the west (east) of the basin, and 2) enhanced precipitable water vapor content that stretches from the Gulf of Mexico to the Northeast US region in the days leading up to regional extreme precipitation days. We define a daily dipole index to summarize the strength of the paired cylonic and aniticyclonic systems to the west and east of the basin and analyze its temporal characteristics and its relationship to the regional extreme precipitation events. Lastly, we investigate and discuss the subseasonal predictability of individual extreme precipitation events and the seasonal predictability of active and inactive seasons, where the activity level is defined by the expected frequency of regional extreme precipitation events.

Evaluation of Extratropical Cyclone Precipitation in the North Atlantic Basin: An analysis of ERA-Interim, WRF, and two CMIP5 models.

PubMed

Booth, James F; Naud, Catherine M; Willison, Jeff

2018-03-01

The representation of extratropical cyclones (ETCs) precipitation in general circulation models (GCMs) and a weather research and forecasting (WRF) model is analyzed. This work considers the link between ETC precipitation and dynamical strength and tests if parameterized convection affects this link for ETCs in the North Atlantic Basin. Lagrangian cyclone tracks of ETCs in ERA-Interim reanalysis (ERAI), the GISS and GFDL CMIP5 models, and WRF with two horizontal resolutions are utilized in a compositing analysis. The 20-km resolution WRF model generates stronger ETCs based on surface wind speed and cyclone precipitation. The GCMs and ERAI generate similar composite means and distributions for cyclone precipitation rates, but GCMs generate weaker cyclone surface winds than ERAI. The amount of cyclone precipitation generated by the convection scheme differs significantly across the datasets, with GISS generating the most, followed by ERAI and then GFDL. The models and reanalysis generate relatively more parameterized convective precipitation when the total cyclone-averaged precipitation is smaller. This is partially due to the contribution of parameterized convective precipitation occurring more often late in the ETC life cycle. For reanalysis and models, precipitation increases with both cyclone moisture and surface wind speed, and this is true if the contribution from the parameterized convection scheme is larger or not. This work shows that these different models generate similar total ETC precipitation despite large differences in the parameterized convection, and these differences do not cause unexpected behavior in ETC precipitation sensitivity to cyclone moisture or surface wind speed.

Bacterially-mediated precipitation of ferric iron during the leaching of basaltic rocks

NASA Astrophysics Data System (ADS)

Schnittker, K.; Navarrete, J. U.; Cappelle, I. J.; Borrok, D. M.

2011-12-01

The bacterially-mediated oxidation of ferrous [Fe(II)] iron in environments where its oxidation is otherwise unfavorable (i.e., acidic and/or anaerobic conditions) results in the formation of ferric iron [Fe(III)] precipitates. The mineralogy and morphologies of these precipitates are dictated by solution biochemistry. In this study, we evaluated Fe(III) precipitates that formed during aerobic bioleaching experiments with Acidithiobacillus ferrooxidans and ilmenite (FeTiO3) and Lunar or Martian basaltic stimulant rocks. Growth media was supplied to support the bacteria; however, all the Fe(II) for chemical energy was supplied by the mineral or rock. During the experiments, the bacteria actively oxidized Fe(II) to Fe(III), resulting in the formation of white and yellow-colored precipitates. In our initial experiments with both ilmentite and basalt, High-Resolution Scanning Electron Microscopic (HRSEM) analysis indicated that the precipitates where small (diameters were less than 5μm and mostly nanometer-scaled), white, and exhibited a platy texture. Networks of mineralized bacterial biofilm were also abundant. In these cases the white precipitates coated the bacteria, forming rod-shaped minerals 5-10μm long by about 1μm in diameter. Many of the rod-shaped minerals formed elongated chains. Energy Dispersive Spectra (EDS) analysis showed that the precipitates were largely composed of Fe and phosphorous (P) with an atomic Fe:P ratio of ˜1. Limited sulfur (S) was also identified as part of the agglomerated precipitates with an atomic Fe:S ratio that ranged from 5 to 10. Phosphorous and S were introduced into the system in considerable amounts as part of the growth media. Additional experiments were performed where we altered the growth media to lower the amount of available P by an order of magnitude. In this case, the experimental behavior remained the same, but the precipitates were more yellow or orange in color relative to those in the experiments using the original growth media. HRSEM/EDS analysis confirmed the presence of minerals with much higher Fe:P ratios (˜2) and much smaller Fe:S ratios (˜0.15). This suggests that the change in growth media chemistry was reflected in precipitates that were rich in S and poorer in P. X-ray diffraction analysis of these precipitates is currently underway. Our results have implications for the interpretation of solution chemistries and precipitation mechanisms associated with biologically-mediated Fe(III)-minerals on Earth, but might also provide insights into possible biosignatures in extraterrestrial systems.

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.

Analysis of air mass trajectories to explain observed variability of tritium in precipitation at the Southern Sierra Critical Zone Observatory, California, USA

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

Visser, Ate; Thaw, Melissa; Esser, Brad

Understanding the behavior of tritium, a radioactive isotope of hydrogen, in the environment is important to evaluate the exposure risk of anthropogenic releases, and for its application as a tracer in hydrology and oceanography. To understand and predict the variability of tritium in precipitation, HYSPLIT air mass trajectories were analyzed for 16 aggregate precipitation samples collected over a 2 year period at irregular intervals at a research site located at 2000 m elevation in the southern Sierra Nevada (California, USA). Attributing the variation in tritium to specific source areas confirms the hypothesis that higher latitude or inland sources bring highermore » tritium levels in precipitation than precipitation originating in the lower latitude Pacific Ocean. In this case, the source of precipitation accounts for 79% of the variation observed in tritium concentrations. In conclusion, air mass trajectory analysis is a promising tool to improve the predictions of tritium in precipitation at unmonitored locations and thoroughly understand the processes controlling transport of tritium in the environment.« less

Analysis of air mass trajectories to explain observed variability of tritium in precipitation at the Southern Sierra Critical Zone Observatory, California, USA

DOE PAGES

Visser, Ate; Thaw, Melissa; Esser, Brad

2017-11-20

Understanding the behavior of tritium, a radioactive isotope of hydrogen, in the environment is important to evaluate the exposure risk of anthropogenic releases, and for its application as a tracer in hydrology and oceanography. To understand and predict the variability of tritium in precipitation, HYSPLIT air mass trajectories were analyzed for 16 aggregate precipitation samples collected over a 2 year period at irregular intervals at a research site located at 2000 m elevation in the southern Sierra Nevada (California, USA). Attributing the variation in tritium to specific source areas confirms the hypothesis that higher latitude or inland sources bring highermore » tritium levels in precipitation than precipitation originating in the lower latitude Pacific Ocean. In this case, the source of precipitation accounts for 79% of the variation observed in tritium concentrations. In conclusion, air mass trajectory analysis is a promising tool to improve the predictions of tritium in precipitation at unmonitored locations and thoroughly understand the processes controlling transport of tritium in the environment.« less

Numerical Simulation of Intense Precipitation Events South of the Alps: Sensitivity to Initial Conditions and Horizontal Resolution

NASA Astrophysics Data System (ADS)

Cacciamani, C.; Cesari, D.; Grazzini, F.; Paccagnella, T.; Pantone, M.

In this paper we describe the results of several numerical experiments performed with the limited area model LAMBO, based on a 1989 version of the NCEP (National Center for Environmental Prediction) ETA model, operational at ARPA-SMR since 1993. The experiments have been designed to assess the impact of different horizontal resolutions and initial conditions on the quality and detail of the forecast, especially as regards the precipitation field in the case of severe flood events. For initial conditions we developed a mesoscale data assimilation scheme, based on the nudging technique. The scheme makes use of upper air and surface meteorological observations to modify ECMWF (European Centre for Medium Range Weather Forecast) operational analyses, used as first-guess fields, in order to better describe smaller scales features, mainly in the lower troposphere. Three flood cases in the Alpine and Mediterranean regions have been simulated with LAMBO, using a horizontal grid spacing of 15 and 5km and starting either from ECMWF initialised analysis or from the result of our mesoscale analysis procedure. The results show that increasing the resolution generally improves the forecast, bringing the precipitation peaks in the flooded areas close to the observed values without producing many spurious precipitation patterns. The use of mesoscale analysis produces a more realistic representation of precipitation patterns giving a further improvement to the forecast of precipitation. Furthermore, when simulations are started from mesoscale analysis, some model-simulated thermodynamic indices show greater vertical instability just in the regions where strongest precipitation occurred.

Phosphatase mediated bioprecipitation of lead as pyromorphite by Achromobacter xylosoxidans.

PubMed

Sharma, Jaya; Shamim, Kashif; Dubey, Santosh Kumar

2018-07-01

Achromobacter xylosoxidans strain SJ11, tolerating up to 4.0 mM lead nitrate, in a defined minimal medium was isolated from the waste of a battery manufacturing industry, Goa, India. Interestingly, it formed white precipitate on exposure to lead nitrate which was also evident from scanning electron micrograph (SEM). Energy dispersive X-ray spectroscopic analysis revealed the presence of lead (48.5% by weight) along with phosphorus and chlorine in the precipitate. Transmission electron microscopy (TEM) of bacterial cells clearly refuted the possibility of intracellular lead uptake confirming extracellular precipitation as a predominant mechanism of lead resistance in this bacterium. The extracellular precipitate was further identified as pyromorphite [Pb 5 (PO 4 ) 3 Cl] by X-ray diffraction analysis. This was also corroborated by fourier transformed infrared spectroscopy (FTIR) indicating a significant involvement of phosphate groups. Atomic absorption spectroscopic analysis clearly demonstrated that 465.8 mg g -1 lead was precipitated by the bacterial cells. There was remarkable increase of 160% in phosphatase activity suggesting it's important role in lead precipitation. This was further substantiated by significant up-regulation of phosphatase, CheZ using LC-MS/MS. Therefore phosphatase mediated extracellular precipitation of lead as pyromorphite by A. xylosoxidans strain SJ11 clearly demonstrated it's potential in bioremediation of lead contaminated environmental sites. Copyright © 2018 Elsevier Ltd. All rights reserved.

Satellite and Model Analysis of the Atmospheric Moisture Budget in High Latitudes: High Resolution Precipitation Over Greenland Studied from Dynamic Method

NASA Technical Reports Server (NTRS)

Bromwich, David H.; Chen, Qiu-shi

2002-01-01

Observations of precipitation over Greenland are limited. Direct precipitation measurements for the whole ice sheet are impractical, and those in the coastal region have substantial uncertainty but may be correctable with some effort. However, the analyzed wind, geopotential height and moisture fields are available for recent years, and the precipitation is retrievable from these fields by a dynamic method. Based on recent Greenland precipitation from dynamic studies, several deficiencies in the precipitation spatial distributions from these dynamic methods were evaluated by Bromwich et al.

Coupling Meteorology, Metal Concentrations, and Pb Isotopes for Source Attribution in Archived Precipitation Samples

EPA Science Inventory

A technique that couples lead (Pb) isotopes and multi-element concentrations with meteorological analysis was used to assess source contributions to precipitation samples at the Bondville, Illinois USA National Trends Network (NTN) site. Precipitation samples collected over a 16 ...

A comparative statistical study of long-term agroclimatic conditions affecting the growth of US winter wheat: Distributions of regional monthly average precipitation on the Great Plains and the state of Maryland and the effect of agroclimatic conditions on yield in the state of Kansas

NASA Technical Reports Server (NTRS)

Welker, J.

1981-01-01

A histogram analysis of average monthly precipitation over 30 and 84 year periods for both Maryland and Kansas was made and the results compared. A second analysis, a statistical assessment of the effect of average monthly precipitation on Kansas winter wheat yield was made. The data sets covered the three periods of 1941-1970, 1887-1970, and 1887-1921. Analyses of the limited data sets used (only the average monthly precipitation and temperature were correlated against yield) indicated that fall precipitation values, especially those of September and October, were more important to winter wheat yield than were spring values, particularly for the period 1941-1970.

Precipitation and Dislocation Strengthening Behaviour of Grade X80 Steel for Pipeline with Strain Based Design

NASA Astrophysics Data System (ADS)

Sun, Weihua; Hu, Shu-e.; Li, Guobao; Yu, Hao

This paper analyzes precipitation and dislocation strengthening behaviors of a 27mm thick Niobium-bearing Grade X80 steel plate for strain based design line pipe manufacture. The steel is produced by thermal-mechanical processing (TMCP) and is characterized with granular bainite and polygonal ferrite microstructure. Mechanical properties of both the steel and the UOE pipe are briefly introduced. Transmission electron microscope (TEM) is used to investigate the fine grain structure, distribution of the precipitates and dislocations in the steel. Precipitate morphologies, volume fractions of M(C,N), M3C, CaS, AlN and Cu are extensively studied respectively by Electrolytic Chemical Phase Analysis (ECPA) and X-ray Small Angle Diffraction (X-ray SAD). Dislocations in the steel are characterized with Positron Annihilation analysis. The results prove that precipitation hardening reveal a 58.1MPa strengthening contribution by the precipitates less than 20nm in size. Dislocation hardening is approximately 176MPa to the present studied steel and 198MPa to the pipe.

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

2004-01-01

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Variability in precipitation in a watershed in the altiplano, Peru and modes of variation

NASA Astrophysics Data System (ADS)

Mazzarino, M.; Brown, C. M.

2012-12-01

This research examines system linkages between climate, water availability, pasture availability, camelids (llamas and alpacas) and indigenous herders in an Andean watershed in southern Peru. In this region, extreme meteorological events such as drought and flood, occur often and have the potential to negatively impact herding livelihoods. Predictability in the system is paramount to reducing risks associated with these events. In the altiplano, a large portion of variability in precipitation has been attributed to the influence of El Nino Southern Oscillation (ENSO). In light of climate change and observations by herders, this research returns to the question of teleconnections in the altiplano. We use December through March precipitation totals obtained from eight meteorological stations for 43 years (1964-2006) and sea surface temperatures (SSTs) in the equatorial Pacific and Atlantic to characterize the hydroclimatology in the watershed and determine modes of variability. Following principal components analysis, prevailing periodicities in regional precipitation were determined using wavelet analysis and spatial correlation and regression analysis were used to determine the relationship between SST anomalies (SSTA's) and precipitation events in the watershed. Results suggest a non-linear and non-stationary mode of variability. We draw three conclusions from the results: 1) Positive precipitation extremes are dominated by an ENSO signal in the Nino 2 region; 2) Post 1987 there is a weak relationship, if any, between anomalously dry years in the precipitation record and SSTA's in the equatorial Pacific; 3) There is a stronger relationship (inverse) between precipitation in the region and SSTA's in the tropical Atlantic than previously believed.

Soil response to long-term projections of extreme temperature and precipitation in the southern La Plata Basin

NASA Astrophysics Data System (ADS)

Pántano, Vanesa C.; Penalba, Olga C.

2017-12-01

Projected changes were estimated considering the main variables which take part in soil-atmosphere interaction. The analysis was focused on the potential impact of these changes on soil hydric condition under extreme precipitation and evapotranspiration, using the combination of Global Climate Models (GCMs) and observational data. The region of study is the southern La Plata Basin that covers part of Argentine territory, where rainfed agriculture production is one of the most important economic activities. Monthly precipitation and maximum and minimum temperatures were used from high quality-controlled observed data from 46 meteorological stations and the ensemble of seven CMIP5 GCMs in two periods: 1970-2005 and 2065-2100. Projected changes in monthly effective temperature and precipitation were analysed. These changes were combined with observed series for each probabilistic interval. The result was used as input variables for the water balance model in order to obtain consequent soil hydric condition (deficit or excess). Effective temperature and precipitation are expected to increase according to the projections of GCMs, with few exceptions. The analysis revealed increase (decrease) in the prevalence of evapotranspiration over precipitation, during spring (winter). Projections for autumn months show precipitation higher than potential evapotranspiration more frequently. Under dry extremes, the analysis revealed higher projected deficit conditions, impacting on crop development. On the other hand, under wet extremes, excess would reach higher values only in particular months. During December, projected increase in temperatures reduces the impact of extreme high precipitation but favours deficit conditions, affecting flower-fructification stage of summer crops.

Matrix precipitation: a general strategy to eliminate matrix interference for pharmaceutical toxic impurities analysis.

PubMed

Yang, Xiaojing; Xiong, Xuewu; Cao, Ji; Luan, Baolei; Liu, Yongjun; Liu, Guozhu; Zhang, Lei

2015-01-30

Matrix interference, which can lead to false positive/negative results, contamination of injector or separation column, incompatibility between sample solution and the selected analytical instrument, and response inhibition or even quenching, is commonly suffered for the analysis of trace level toxic impurities in drug substance. In this study, a simple matrix precipitation strategy is proposed to eliminate or minimize the above stated matrix interference problems. Generally, a sample of active pharmaceutical ingredients (APIs) is dissolved in an appropriate solvent to achieve the desired high concentration and then an anti-solvent is added to precipitate the matrix substance. As a result, the target analyte is extracted into the mixed solution with very less residual of APIs. This strategy has the characteristics of simple manipulation, high recovery and excellent anti-interference capability. It was found that the precipitation ratio (R, representing the ability to remove matrix substance) and the proportion of solvent (the one used to dissolve APIs) in final solution (P, affecting R and also affecting the method sensitivity) are two important factors of the precipitation process. The correlation between R and P was investigated by performing precipitation with various APIs in different solvent/anti-solvent systems. After a detailed mathematical reasoning process, P=20% was proved to be an effective and robust condition to perform the precipitation strategy. The precipitation method with P=20% can be used as a general strategy for toxic impurity analysis in APIs. Finally, several typical examples are described in this article, where the challenging matrix interference issues have been resolved successfully. Copyright © 2014 Elsevier B.V. All rights reserved.

Land surface-precipitation feedback analysis for a landfalling monsoon depression in the Indian region

NASA Astrophysics Data System (ADS)

Baisya, Himadri; Pattnaik, Sandeep; Rajesh, P. V.

2017-03-01

A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6, and Morrison) are examined, and Morrison is chosen for assessing the land surface-precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed soil moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression.

Large‐scale heavy precipitation over central Europe and the role of atmospheric cyclone track types

PubMed Central

Lexer, Annemarie; Homann, Markus; Blöschl, Günter

2017-01-01

ABSTRACT Precipitation patterns over Europe are largely controlled by atmospheric cyclones embedded in the general circulation of the mid‐latitudes. This study evaluates the climatologic features of precipitation for selected regions in central Europe with respect to cyclone track types for 1959–2015, focusing on large‐scale heavy precipitation. The analysis suggests that each of the cyclone track types is connected to a specific pattern of the upper level atmospheric flow, usually characterized by a major trough located over Europe. A dominant upper level cut‐off low (COL) is found over Europe for strong continental (CON) and van Bebber's type (Vb) cyclones which move from the east and southeast into central Europe. Strong Vb cyclones revealed the longest residence times, mainly due to circular propagation paths. The central European cyclone precipitation climate can largely be explained by seasonal track‐type frequency and cyclone intensity; however, additional factors are needed to explain a secondary precipitation maximum in early autumn. The occurrence of large precipitation totals for track events is strongly related to the track type and the region, with the highest value of 45% of all Vb cyclones connected to heavy precipitation in summer over the Czech Republic and eastern Austria. In western Germany, Atlantic winter cyclones are most relevant for heavy precipitation. The analysis of the top 50 precipitation events revealed an outstanding heavy precipitation period from 2006 to 2011 in the Czech Republic, but no gradual long‐term change. The findings help better understand spatio‐temporal variability of heavy precipitation in the context of floods and may be used for evaluating climate models.

Towards the Consideration of Surface and Environment variables for a Microwave Precipitation Algorithm Over Land

NASA Astrophysics Data System (ADS)

Wang, N. Y.; You, Y.; Ferraro, R. R.; Guch, I.

2014-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperatures characteristics similar to precipitation Ongoing work by NASA's GPM microwave radiometer team is constructing databases for the GPROF algorithm through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The at-launch database focuses on stratification by emissivity class, surface temperature and total precipitable water (TPW). We'll perform sensitivity studies to determine the potential role of environmental factors such as land surface temperature, surface elevation, and relative humidity and storm morphology such as storm vertical structure, height, and ice thickness to improve precipitation estimation over land, including rain and snow. In other words, what information outside of the satellite radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

Observed variability of summer precipitation pattern and extreme events in East China associated with variations of the East Asian summer monsoon: VARIABILITY OF SUMMER PRECIPITATION AND EXTREME EVENT IN EAST CHINA

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

Wang, Lei; Qian, Yun; Zhang, Yaocun

This paper presents a comprehensive analysis of interannual and interdecadal variations of summer precipitation and precipitation-related extreme events in China associated with variations of the East Asian summer monsoon (EASM) from 1979-2012. A high-quality daily precipitation dataset covering 2287 weather stations in China is analyzed. Based on the precipitation pattern analysis using empirical orthogonal functions, three sub-periods of 1979-1992 (period I), 1993-1999 (period II) and 2000-2012 (period III) are identified to be representative of the precipitation variability. Similar significant variability of the extreme precipitation indices is found across four sub-regions in eastern China. The spatial patterns of summer mean precipitation,more » the number of days with daily rainfall exceeding 95th percentile precipitation (R95p) and the maximum number of consecutive wet days (CWD) anomalies are consistent, but opposite to that of maximum consecutive dry days (CDD) anomalies during the three sub-periods. However, the spatial patterns of hydroclimatic intensity (HY-INT) are notably different from that of the other three extreme indices, but highly correlated to the dry events. The changes of precipitation anomaly patterns are accompanied by the change of the EASM regime and the abrupt shift of the position of the west Pacific subtropical high around 1992/1993 and 1999/2000, respectively, which influence the moisture transport that contributes most to the precipitation anomalies. Lastly, the EASM intensity is linked to sea surface temperature anomaly over the tropical Indian and Pacific Ocean that influences deep convection over the oceans.« less

Discontinuous precipitation in a nickel-free high nitrogen austenitic stainless steel on solution nitriding

NASA Astrophysics Data System (ADS)

Mohammadzadeh, Roghayeh; Akbari, Alireza; Grumsen, Flemming B.; Somers, Marcel A. J.

2017-10-01

Chromium-rich nitride precipitates in production of nickel-free austenitic stainless steel plates via pressurised solution nitriding of Fe-22.7Cr-2.4Mo ferritic stainless steel at 1473 K (1200 °C) under a nitrogen gas atmosphere was investigated. The microstructure, chemical and phase composition, morphology and crystallographic orientation between the resulted austenite and precipitates were investigated using optical microscopy, X-ray Diffraction (XRD), Scanning and Transmission Electron Microscopy (TEM) and Electron Back Scatter Diffraction (EBSD). On prolonged nitriding, Chromium-rich nitride precipitates were formed firstly close to the surface and later throughout the sample with austenitic structure. Chromium-rich nitride precipitates with a rod or strip-like morphology was developed by a discontinuous cellular precipitation mechanism. STEM-EDS analysis demonstrated partitioning of metallic elements between austenite and nitrides, with chromium contents of about 80 wt.% in the precipitates. XRD analysis indicated that the Chromium-rich nitride precipitates are hexagonal (Cr, Mo)2N. Based on the TEM studies, (Cr, Mo)2N precipitates presented a (1 1 1)γ//(0 0 2)(Cr, Mo)2N, ?γ//?(Cr, Mo)2N orientation relationship with respect to the austenite matrix. EBSD studies revealed that the austenite in the regions that have transformed into austenite and (Cr, Mo)2N have no orientation relation to the untransformed austenite.

Comparison of radar and gauge precipitation data in watershed models across varying spatial and temporal scales

EPA Science Inventory

Precipitation is a key control on watershed hydrologic modelling output, with errors in rainfall propagating through subsequent stages of water quantity and quality analysis. Most watershed models incorporate precipitation data from rain gauges; higher-resolution data sources are...

Multi-scale fluctuation analysis of precipitation in Beijing by Extreme-point Symmetric Mode Decomposition

NASA Astrophysics Data System (ADS)

Li, Jiqing; Duan, Zhipeng; Huang, Jing

2018-06-01

With the aggravation of the global climate change, the shortage of water resources in China is becoming more and more serious. Using reasonable methods to study changes in precipitation is very important for planning and management of water resources. Based on the time series of precipitation in Beijing from 1951 to 2015, the multi-scale features of precipitation are analyzed by the Extreme-point Symmetric Mode Decomposition (ESMD) method to forecast the precipitation shift. The results show that the precipitation series have periodic changes of 2.6, 4.3, 14 and 21.7 years, and the variance contribution rate of each modal component shows that the inter-annual variation dominates the precipitation in Beijing. It is predicted that precipitation in Beijing will continue to decrease in the near future.

The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Arkin, Philip; Chang, Alfred; Ferraro, Ralph; Gruber, Arnold; Janowiak, John; McNab, Alan; Rudolf, Bruno; Schneider, Udo

1997-01-01

The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit -satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5 deg x 2.5 deg latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

Do climate model predictions agree with long-term precipitation trends in the arid southwestern United States?

NASA Astrophysics Data System (ADS)

Elias, E.; Rango, A.; James, D.; Maxwell, C.; Anderson, J.; Abatzoglou, J. T.

2016-12-01

Researchers evaluating climate projections across southwestern North America observed a decreasing precipitation trend. Aridification was most pronounced in the cold (non-monsoonal) season, whereas downward trends in precipitation were smaller in the warm (monsoonal) season. In this region, based upon a multimodel mean of 20 Coupled Model Intercomparison Project 5 models using a business-as-usual (Representative Concentration Pathway 8.5) trajectory, midcentury precipitation is projected to increase slightly during the monsoonal time period (July-September; 6%) and decrease slightly during the remainder of the year (October-June; -4%). We use observed long-term (1915-2015) monthly precipitation records from 16 weather stations to investigate how well measured trends corroborate climate model predictions during the monsoonal and non-monsoonal timeframe. Running trend analysis using the Mann-Kendall test for 15 to 101 year moving windows reveals that half the stations showed significant (p≤0.1), albeit small, increasing trends based on the longest term record. Trends based on shorter-term records reveal a period of significant precipitation decline at all stations representing the 1950s drought. Trends from 1930 to 2015 reveal significant annual, monsoonal and non-monsoonal increases in precipitation (Fig 1). The 1960 to 2015 time window shows no significant precipitation trends. The more recent time window (1980 to 2015) shows a slight, but not significant, increase in monsoonal precipitation and a larger, significant decline in non-monsoonal precipitation. GCM precipitation projections are consistent with more recent trends for the region. Running trends from the most recent time window (mid-1990s to 2015) at all stations show increasing monsoonal precipitation and decreasing Oct-Jun precipitation, with significant trends at 6 of 16 stations. Running trend analysis revealed that the long-term trends were not persistent throughout the series length, but depended on the period examined. Recent trends in Southwest precipitation are directionally consistent with anthropogenic climate change.

Tree-ring indicators of rainfall and streamflow for the Ili-Balkhash Basin, Central Asia since CE 1560

NASA Astrophysics Data System (ADS)

Chen, Feng; Yuan, Yujiang; Yu, Shulong

2017-09-01

We reconstructed previous July - current April total precipitation in the upper Ili-Balkhash Basin of Central Asia, using a transfer equation based on the correlation between regional tree-ring width series and local precipitation data. Dry periods were identified from 1586-1612, 1637-1669, 1695-1721, 1759-1782, 1804-1864, 1907-1930 and 1974-1993, while wet periods occurred from 1560-1585, 1613-1636, 1670-1694, 1722-1758, 1783-1803, 1865-1906, 1931-1973 and 1994-2006. Spatial correlation analysis indicates that our precipitation reconstruction is broadly representative of precipitation in the entire Ili-Balkhash Basin. The precipitation timeseries is also strongly related to streamflow measurements, revealing that variations in precipitation in the upper Ili-Balkhash Basin have a dramatic influence on streamflow into Lake Balkhash. The precipitation reconstruction also compares well with various streamflow reconstructions from the Tien Shan, and exhibits an increasing streamflow trend in the 1980s through 2000s. Spectral analysis showed significant 60-, 33-, 11-, 2.8- and 2.1-year cycles over the past 447 years. Our 447-year precipitation reconstruction provides the basis for comparing past and present hydroclimate changes, which will be important for detection and attribution of hydroclimate variation in the Ili-Balkhash Basin.

An Optimized Trichloroacetic Acid/Acetone Precipitation Method for Two-Dimensional Gel Electrophoresis Analysis of Qinchuan Cattle Longissimus Dorsi Muscle Containing High Proportion of Marbling.

PubMed

Hao, Ruijie; Adoligbe, Camus; Jiang, Bijie; Zhao, Xianlin; Gui, Linsheng; Qu, Kaixing; Wu, Sen; Zan, Linsen

2015-01-01

Longissimus dorsi muscle (LD) proteomics provides a novel opportunity to reveal the molecular mechanism behind intramuscular fat deposition. Unfortunately, the vast amounts of lipids and nucleic acids in this tissue hampered LD proteomics analysis. Trichloroacetic acid (TCA)/acetone precipitation is a widely used method to remove contaminants from protein samples. However, the high speed centrifugation employed in this method produces hard precipitates, which restrict contaminant elimination and protein re-dissolution. To address the problem, the centrifugation precipitates were first grinded with a glass tissue grinder and then washed with 90% acetone (TCA/acetone-G-W) in the present study. According to our result, the treatment for solid precipitate facilitated non-protein contaminant removal and protein re-dissolution, ultimately improving two-dimensional gel electrophoresis (2-DE) analysis. Additionally, we also evaluated the effect of sample drying on 2-DE profile as well as protein yield. It was found that 30 min air-drying did not result in significant protein loss, but reduced horizontal streaking and smearing on 2-DE gel compared to 10 min. In summary, we developed an optimized TCA/acetone precipitation method for protein extraction of LD, in which the modifications improved the effectiveness of TCA/acetone method.

An Optimized Trichloroacetic Acid/Acetone Precipitation Method for Two-Dimensional Gel Electrophoresis Analysis of Qinchuan Cattle Longissimus Dorsi Muscle Containing High Proportion of Marbling

PubMed Central

Hao, Ruijie; Adoligbe, Camus; Jiang, Bijie; Zhao, Xianlin; Gui, Linsheng; Qu, Kaixing; Wu, Sen; Zan, Linsen

2015-01-01

Longissimus dorsi muscle (LD) proteomics provides a novel opportunity to reveal the molecular mechanism behind intramuscular fat deposition. Unfortunately, the vast amounts of lipids and nucleic acids in this tissue hampered LD proteomics analysis. Trichloroacetic acid (TCA)/acetone precipitation is a widely used method to remove contaminants from protein samples. However, the high speed centrifugation employed in this method produces hard precipitates, which restrict contaminant elimination and protein re-dissolution. To address the problem, the centrifugation precipitates were first grinded with a glass tissue grinder and then washed with 90% acetone (TCA/acetone-G-W) in the present study. According to our result, the treatment for solid precipitate facilitated non-protein contaminant removal and protein re-dissolution, ultimately improving two-dimensional gel electrophoresis (2-DE) analysis. Additionally, we also evaluated the effect of sample drying on 2-DE profile as well as protein yield. It was found that 30 min air-drying did not result in significant protein loss, but reduced horizontal streaking and smearing on 2-DE gel compared to 10 min. In summary, we developed an optimized TCA/acetone precipitation method for protein extraction of LD, in which the modifications improved the effectiveness of TCA/acetone method. PMID:25893432

Characteristics of Lake Chad Level Variability and Links to ENSO, Precipitation, and River Discharge

PubMed Central

Demoz, Belay; Gebremariam, Sium

2014-01-01

This study used trend, correlation, and wavelet analysis to characterize Lake Chad (LC) level fluctuations, river discharge, El Niño Southern Oscillation (ENSO), and precipitation regimes and their interrelationships. Linear correlation results indicate a negative association between ENSO and LC level, river discharge and precipitation. Trend analysis shows increasing precipitation in the Lake Chad Basin (LCB) but decreasing LC level. The mode of interannual variability in LC level, rainfall, and ENSO analyzed using wavelet analysis is dominated by 3-4-year periods. Results show that variability in ENSO could explain only 31% and 13% of variations in LC level at Kindjeria and precipitation in the northern LCB, respectively. The wavelet transform coherency (WTC) between LC level of the southern pool at Kalom and ENSO is statistically significant at the 95% confidence level and phase-locked, implying a cause-and-effect association. These strong coherencies coincide with the La Niña years with the exception of 1997-1998 El Niño events. The WTC shows strong covariance between increasing precipitation and LC level in the northern pool at a 2- to 4-year band and 3- to 4-year band localized from 1996 to 2010. Implications for water resource planning and management are discussed. PMID:25538946

Imaging the in-plane distribution of helium precipitates at a Cu/V interface

DOE PAGES

Chen, Di; Li, Nan; Yuryev, Dina; ...

2017-02-15

Here, we describe a transmission electron microscopy investigation of the distribution of helium precipitates within the plane of an interface between Cu and V. Statistical analysis of precipitate locations reveals a weak tendency for interfacial precipitates to align alongmore » $$\\langle$$110$$\\rangle$$-type crystallographic directions within the Cu layer. Comparison of these findings with helium-free Cu/V interfaces suggests that the precipitates may be aggregating preferentially along atomic-size steps in the interface created by threading dislocations in the Cu layer. Our observations also suggest that some precipitates may be aggregating along intersections between interfacial misfit dislocations.« less

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

Tagestad, Jerry; Brooks, Matthew; Cullinan, Valerie

Mojave Desert ecosystem processes are dependent upon the amount and seasonality of precipitation. Multi-decadal periods of drought or above-average rainfall affect landscape vegetation condition, biomass and susceptibility to fire. The seasonality of precipitation events can also affect the likelihood of lightning, a key ignition source for fires. To develop an understanding of precipitation regimes and fire patterns we used monthly average precipitation data and GIS data representing burned areas from 1971-2010. We applied a K-means cluster analysis to the monthly precipitation data identifying three distinct precipitation seasons; winter (October – March), spring (April-June) and summer (July-September) and four discrete precipitationmore » regimes within the Mojave ecoregion.« less

A Winter Precipitation Reconstruction (CE 1810-2012) in the Southeastern Tibetan Plateau and Its Relationship to Salween River Streamflow Variations

NASA Astrophysics Data System (ADS)

Chen, Feng; Yuan, Yujiang; Fan, Zexin; Yu, Shulong

2018-01-01

We established a tree-ring width series from one Yunnan Douglas fir (Pseudotsuga forrestii) stand near the Mingyong glacier terminus of Meili Snow Mountain, southeastern Tibetan Plateau. Correlation analyses indicated that radial growth of Yunnan Douglas firs is largely controlled by variations in winter (November-March) precipitation. The precipitation reconstruction model accounts for 37% of the actual precipitation variance during the common period 1954-2012. Spatial correlations with the gridded precipitation data reveal that the winter precipitation reconstruction represents regional precipitation changes over the southeastern Tibetan Plateau. By comparing our results with other regional tree-ring records, a distinctive amount of common dry and humid periods were found. Our winter precipitation reconstruction shows profound similarities with Salween river streamflow signals as well as regional glacial activity. Cross-wavelet analysis reveals solar and ENSO influences on precipitation and streamflow variations in the southeastern Tibetan Plateau.

The efficiency of average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling in identifying homogeneous precipitation catchments

NASA Astrophysics Data System (ADS)

Chuan, Zun Liang; Ismail, Noriszura; Shinyie, Wendy Ling; Lit Ken, Tan; Fam, Soo-Fen; Senawi, Azlyna; Yusoff, Wan Nur Syahidah Wan

2018-04-01

Due to the limited of historical precipitation records, agglomerative hierarchical clustering algorithms widely used to extrapolate information from gauged to ungauged precipitation catchments in yielding a more reliable projection of extreme hydro-meteorological events such as extreme precipitation events. However, identifying the optimum number of homogeneous precipitation catchments accurately based on the dendrogram resulted using agglomerative hierarchical algorithms are very subjective. The main objective of this study is to propose an efficient regionalized algorithm to identify the homogeneous precipitation catchments for non-stationary precipitation time series. The homogeneous precipitation catchments are identified using average linkage hierarchical clustering algorithm associated multi-scale bootstrap resampling, while uncentered correlation coefficient as the similarity measure. The regionalized homogeneous precipitation is consolidated using K-sample Anderson Darling non-parametric test. The analysis result shows the proposed regionalized algorithm performed more better compared to the proposed agglomerative hierarchical clustering algorithm in previous studies.

Performance of high-resolution satellite precipitation products over China

NASA Astrophysics Data System (ADS)

Shen, Y.; Xiong, A.; Wang, Y.; Xie, P.; Precipitation Merge Team

2010-12-01

A gauge-based analysis of hourly precipitation is constructed on a 0.25°latitude/ longitude grid over China for a 3 year period from 2005 to 2007 by interpolating gauge reports from ~2000 stations (fig.1) collected and quality controlled by the National Meteorological Information Center of the China Meteorological Administration. Gauge-based precipitation analysis is applied to examine the performance of six high-resolution satellite precipitation estimates, including Joyce et al.’s (2004) Climate Prediction Center Morphing Technique (CMORPH) and the arithmetic mean of the microwave estimates used in CMORPH; Huffman et al.’s (2007) Tropical Rainfall Measuring Mission (TRMM) precipitation product 3B42 and its real-time version 3B42RT; Turk et al.’s (2004) Naval Research Laboratory blended product; and Hsu et al.’s (1997) Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Network (PERSIANN). Our results showed the following: (1) all six satellite products are capable of capturing the overall spatial distribution and temporal variations of precipitation reasonably well; (2) performance of the satellite products varies for different regions and different precipitation regimes, with better comparison statistics observed over wet regions and for warm seasons; (3) products based solely on satellite observations present regionally and seasonally varying biases, while the gauge-adjustment procedures applied in TRMM 3B42 remove the large-scale bias almost completely; (4) CMORPH exhibits the best performance in depicting the spatial pattern and temporal variations of precipitation; and (5) both the relative magnitude and the phase of the warm season precipitation over China are estimated quite well, but the early morning peak associated with the Mei-Yu rainfall over central eastern China is substantially under-estimated by all satellite products. The work reported in this paper is an integral part of our efforts to construct an analysis of hourly merged precipitation analysis in the future (Shen et al., 2010). Further work is to extend its temporal coverage and to improve the quality of the CPAP. The dataset for the period of 1900-1952 with only ~100 gauge reports available over mainland China is under consideration for development. Gauge network is an important element to determine the quality of the dataset, while the gauge distribution is very sparse over the northwestern China and the Tibetan Plateau, the effective tool to improve the quality of the dataset over these areas is to merge the gauge observations with the satellite precipitation products which is under way. Figure 1 Number of Chinese stations reporting hourly precipitation over a three-year period from January 2005 to December 2007

Precipitation forecast using artificial neural networks. An application to the Guadalupe Valley, Baja California, Mexico

NASA Astrophysics Data System (ADS)

Herrera-Oliva, C. S.

2013-05-01

In this work we design and implement a method for the determination of precipitation forecast through the application of an elementary neuronal network (perceptron) to the statistical analysis of the precipitation reported in catalogues. The method is limited mainly by the catalogue length (and, in a smaller degree, by its accuracy). The method performance is measured using grading functions that evaluate a tradeoff between positive and negative aspects of performance. The method is applied to the Guadalupe Valley, Baja California, Mexico. Using consecutive intervals of dt=0.1 year, employing the data of several climatological stations situated in and surrounding this important wine industries zone. We evaluated the performance of different models of ANN, whose variables of entrance are the heights of precipitation. The results obtained were satisfactory, except for exceptional values of rain. Key words: precipitation forecast, artificial neural networks, statistical analysis

[Periodic fluctuation features of air temperature, precipitation, and aboveground net primary production of alpine meadow ecosystem on Qinghai-Tibetan Plateau].

PubMed

Zhang, Fa-wei; Li, Hong-qin; Li, Ying-nian; Li, Yi-kang; Lin, Li

2009-03-01

With Mexican Hat function as mother function, a wavelet analysis was conducted on the periodic fluctuation features of air temperature, precipitation, and aboveground net primary production (ANPP) in the Alpine Meadow Ecosystem Research Station, Chinese Academy of Sciences from 1980 to 2007. The results showed that there was a main period of 13 years for the annual fluctuations of air temperature, precipitation, and ANPP. A secondary period of 2 years for the annual fluctuations of air temperature and ANPP had lesser influence, whereas that of 4 years for the annual fluctuation of precipitation had greater effect. Lagged correlation analysis indicated that the annual fluctuation of ANNP was mainly controlled by the air temperature in a 20 years scale and had a weak 5-9 years lag effect, but there was a less correlation between ANPP and precipitation.

Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report

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

Kollias, Pavlos

This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation ratemore » retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.« less

Phosphates behaviours in conversion of FP chlorides

NASA Astrophysics Data System (ADS)

Amamoto, I.; Kofuji, H.; Myochin, M.; Takasaki, Y.; Terai, T.

2009-06-01

The spent electrolyte of the pyroprocessing by metal electrorefining method should be considered for recycling after removal of fission products (FP) such as, alkali metals (AL), alkaline earth metals (ALE), and/or rare earth elements (REE), to reduce the volume of high-level radioactive waste. Among the various methods suggested for this purpose is precipitation by converting FP from chlorides to phosphates. Authors have been carrying out the theoretical analysis and experiment showing the behaviours of phosphate precipitates so as to estimate the feasibility of this method. From acquired results, it was found that AL except lithium and ALE are unlikely to form phosphate precipitates. However their conversion behaviours including REE were compatible with the theoretical analysis; in the case of LaPO 4 as one of the REE precipitates, submicron-size particles could be observed while that of Li 3PO 4 was larger; the precipitates were apt to grow larger at higher temperature; etc.

Design of a Thermal Precipitator for the Characterization of Smoke Particles from Common Spacecraft Materials

NASA Technical Reports Server (NTRS)

Meyer, Marit Elisabeth

2015-01-01

A thermal precipitator (TP) was designed to collect smoke aerosol particles for microscopic analysis in fire characterization research. Information on particle morphology, size and agglomerate structure obtained from these tests supplements additional aerosol data collected. Modeling of the thermal precipitator throughout the design process was performed with the COMSOL Multiphysics finite element software package, including the Eulerian flow field and thermal gradients in the fluid. The COMSOL Particle Tracing Module was subsequently used to determine particle deposition. Modeling provided optimized design parameters such as geometry, flow rate and temperatures. The thermal precipitator was built and testing verified the performance of the first iteration of the device. The thermal precipitator was successfully operated and provided quality particle samples for microscopic analysis, which furthered the body of knowledge on smoke particulates. This information is a key element of smoke characterization and will be useful for future spacecraft fire detection research.

Estimates of the fraction of precipitation seedable under application of the Wyoming weather modification pilot project seeding criteria

NASA Astrophysics Data System (ADS)

Ritzman, Jaclyn M.

The objective of the Wyoming Weather Modification Pilot Project is to evaluate the effect of glaciogenic seeding on wintertime precipitation over two co-located barriers in southeast Wyoming. Orographic clouds are to be targeted if they meet strict criteria. An analysis of the impact of seeding requires knowledge of the amount of precipitation that fell from seedable clouds. This amount of precipitation was determined by applying the strict seeding criteria to an eight-year simulation from the Weather Research and Forecasting model at 4-km horizontal resolution. Results from the analysis from the model suggested that the fraction of seedable precipitation was 35.1% (35.5%) over the Sierra Madre and Medicine Bow mountain ranges from 2000-2008. This fraction decreases to 23.2% (23.0%) under a warmer, future climate scenario over the Sierra Madres (Medicine Bows).

Intraseasonal variability of winter precipitation over central asia and the western tibetan plateau from 1979 to 2013 and its relationship with the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Liu, Heng; Liu, Xiaodong; Dong, Buwen

2017-09-01

Winter precipitation over Central Asia and the western Tibetan Plateau (CAWTP) is mainly a result of the interaction between the westerly circulation and the high mountains around the plateau. Empirical Orthogonal Functions (EOFs), Singular Value Decomposition (SVD), linear regression and composite analysis were used to analyze winter daily precipitation and other meteorological elements in this region from 1979 to 2013, in order to understand how interactions between the regional circulation and topography affect the intraseasonal variability in precipitation. The SVD analysis shows that the winter daily precipitation variability distribution is characterized by a dipole pattern with opposite signs over the northern Pamir Plateau and over the Karakoram Himalaya, similar to the second mode of EOF analysis. This dipole pattern of precipitation anomaly is associated with local anomalies in both the 700 hPa moisture transport and the 500 hPa geopotential height and is probably caused by oscillations in the regional and large-scale circulations, which can influence the westerly disturbance tracks and water vapor transport. The linear regression shows that the anomalous mid-tropospheric circulation over CAWTP corresponds to an anti-phase variation of the 500 hPa geopotential height anomalies over the southern and northern North Atlantic 10 days earlier (at 95% significance level), that bears a similarity to the North Atlantic Oscillation (NAO). The composite analysis reveals that the NAO impacts the downstream regions including CAWTP by controlling south-north two branches of the middle latitude westerly circulation around the Eurasian border. During the positive phases of the NAO, the northern branch of the westerly circulation goes around the northwest Tibetan Plateau, whereas the southern branch encounters the southwest Tibetan Plateau, which leads to reduced precipitation over the northern Pamir Plateau and increased precipitation over the Karakoram Himalaya, and vice versa.

Post-processing Seasonal Precipitation Forecasts via Integrating Climate Indices and the Analog Approach

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhang, Y.; Wood, A.; Lee, H. S.; Wu, L.; Schaake, J. C.

2016-12-01

Seasonal precipitation forecasts are a primary driver for seasonal streamflow prediction that is critical for a range of water resources applications, such as reservoir operations and drought management. However, it is well known that seasonal precipitation forecasts from climate models are often biased and also too coarse in spatial resolution for hydrologic applications. Therefore, post-processing procedures such as downscaling and bias correction are often needed. In this presentation, we discuss results from a recent study that applies a two-step methodology to downscale and correct the ensemble mean precipitation forecasts from the Climate Forecast System (CFS). First, CFS forecasts are downscaled and bias corrected using monthly reforecast analogs: we identify past precipitation forecasts that are similar to the current forecast, and then use the finer-scale observational analysis fields from the corresponding dates to represent the post-processed ensemble forecasts. Second, we construct the posterior distribution of forecast precipitation from the post-processed ensemble by integrating climate indices: a correlation analysis is performed to identify dominant climate indices for the study region, which are then used to weight the analysis analogs selected in the first step using a Bayesian approach. The methodology is applied to the California Nevada River Forecast Center (CNRFC) and the Middle Atlantic River Forecast Center (MARFC) regions for 1982-2015, using the North American Land Data Assimilation System (NLDAS-2) precipitation as the analysis. The results from cross validation show that the post-processed CFS precipitation forecast are considerably more skillful than the raw CFS with the analog approach only. Integrating climate indices can further improve the skill if the number of ensemble members considered is large enough; however, the improvement is generally limited to the first couple of months when compared against climatology. Impacts of various factors such as ensemble size, lead time, and choice of climate indices will also be discussed.

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.

The Effects of Global Warming on Temperature and Precipitation Trends in Northeast America

NASA Astrophysics Data System (ADS)

Francis, F.

2013-12-01

The objective of this paper is to discuss the analysis of results in temperature and precipitation (rainfall) data and how they are affected by the theory of global warming in Northeast America. The topic was chosen because it will show the trends in temperature and precipitation and their relations to global warming. Data was collected from The Global Historical Climatology Network (GHCN). The data range from years of 1973 to 2012. We were able to calculate the yearly and monthly regress to estimate the relationship of variables found in the individual sources. With the use of specially designed software, analysis and manual calculations we are able to give a visualization of these trends in precipitation and temperature and to question if these trends are due to the theory of global warming. With the Calculation of the trends in slope we were able to interpret the changes in minimum and maximum temperature and precipitation. Precipitation had a 9.5 % increase over the past forty years, while maximum temperature increased 1.9 %, a greater increase is seen in minimum temperature of 3.3 % was calculated over the years. The trends in precipitation, maximum and minimum temperature is statistically significant at a 95% level.

Effect of Various Retrogression Regimes on Aging Behavior and Precipitates Characterization of a High Zn-Containing Al-Zn-Mg-Cu Alloy

NASA Astrophysics Data System (ADS)

Wen, Kai; Xiong, Baiqing; Zhang, Yongan; Li, Zhihui; Li, Xiwu; Huang, Shuhui; Yan, Lizhen; Yan, Hongwei; Liu, Hongwei

2018-03-01

In the present work, the influence of various retrogression treatments on hardness, electrical conductivity and mechanical properties of a high Zn-containing Al-Zn-Mg-Cu alloy is investigated and several retrogression regimes subjected to a same strength level are proposed. The precipitates are qualitatively investigated by means of transmission electron microscopy (TEM) and high-resolution transmission electron microscopy techniques. Based on the matrix precipitate observations, the distributions of precipitate size and nearest inter-precipitate distance are extracted from bright-field TEM images projected along <110>Al orientation with the aid of an imaging analysis and an arithmetic method. The results show that GP zones and η' precipitates are the major precipitates and the precipitate size and its distribution range continuously enlarge with the retrogression regime expands to an extent of high temperature. The nearest inter-precipitate distance ranges obtained are quite the same and the average distance of nearest inter-precipitates show a slight increase. The influence of precipitates on mechanical properties is discussed through the interaction relationship between precipitates and dislocations.

Effect of Various Retrogression Regimes on Aging Behavior and Precipitates Characterization of a High Zn-Containing Al-Zn-Mg-Cu Alloy

NASA Astrophysics Data System (ADS)

Wen, Kai; Xiong, Baiqing; Zhang, Yongan; Li, Zhihui; Li, Xiwu; Huang, Shuhui; Yan, Lizhen; Yan, Hongwei; Liu, Hongwei

2018-05-01

In the present work, the influence of various retrogression treatments on hardness, electrical conductivity and mechanical properties of a high Zn-containing Al-Zn-Mg-Cu alloy is investigated and several retrogression regimes subjected to a same strength level are proposed. The precipitates are qualitatively investigated by means of transmission electron microscopy (TEM) and high-resolution transmission electron microscopy techniques. Based on the matrix precipitate observations, the distributions of precipitate size and nearest inter-precipitate distance are extracted from bright-field TEM images projected along <110>Al orientation with the aid of an imaging analysis and an arithmetic method. The results show that GP zones and η' precipitates are the major precipitates and the precipitate size and its distribution range continuously enlarge with the retrogression regime expands to an extent of high temperature. The nearest inter-precipitate distance ranges obtained are quite the same and the average distance of nearest inter-precipitates show a slight increase. The influence of precipitates on mechanical properties is discussed through the interaction relationship between precipitates and dislocations.

Assimilation of radar quantitative precipitation estimations in the Canadian Precipitation Analysis (CaPA)

NASA Astrophysics Data System (ADS)

Fortin, Vincent; Roy, Guy; Donaldson, Norman; Mahidjiba, Ahmed

2015-12-01

The Canadian Precipitation Analysis (CaPA) is a data analysis system used operationally at the Canadian Meteorological Center (CMC) since April 2011 to produce gridded 6-h and 24-h precipitation accumulations in near real-time on a regular grid covering all of North America. The current resolution of the product is 10-km. Due to the low density of the observational network in most of Canada, the system relies on a background field provided by the Regional Deterministic Prediction System (RDPS) of Environment Canada, which is a short-term weather forecasting system for North America. For this reason, the North American configuration of CaPA is known as the Regional Deterministic Precipitation Analysis (RDPA). Early in the development of the CaPA system, weather radar reflectivity was identified as a very promising additional data source for the precipitation analysis, but necessary quality control procedures and bias-correction algorithms were lacking for the radar data. After three years of development and testing, a new version of CaPA-RDPA system was implemented in November 2014 at CMC. This version is able to assimilate radar quantitative precipitation estimates (QPEs) from all 31 operational Canadian weather radars. The radar QPE is used as an observation source and not as a background field, and is subject to a strict quality control procedure, like any other observation source. The November 2014 upgrade to CaPA-RDPA was implemented at the same time as an upgrade to the RDPS system, which brought minor changes to the skill and bias of CaPA-RDPA. This paper uses the frequency bias indicator (FBI), the equitable threat score (ETS) and the departure from the partial mean (DPM) in order to assess the improvements to CaPA-RDPA brought by the assimilation of radar QPE. Verification focuses on the 6-h accumulations, and is done against a network of 65 synoptic stations (approximately two stations per radar) that were withheld from the station data assimilated by CaPA-RDPA. It is shown that the ETS and the DPM scores are both improved for precipitation events between 0.2 mm and 25 mm per 6-h, and that the FBI is unchanged.

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

Composite Analysis of Cold Season Atmospheric River Events: Extreme Precipitation and Flooding over the Western United States

NASA Astrophysics Data System (ADS)

Eldardiry, H.; Hossain, F.

2017-12-01

Atmospheric Rivers (ARs) are narrow elongated corridors with horizontal water vapor transport located within the warm sector of extratropical cyclones. While it is widely known that most of heavy rainfall events across the western United States (US) are driven by ARs, the connection between atmospheric conditions and precipitation during an AR event has not been fully documented. In this study, we present a statistical analysis of the connection between precipitation, temperature, wind, and snowpack during the cold season AR events hitting the coastal regions of the western US. For each AR event, the precipitation and other atmospheric variables are retrieved through the dynamic downscaling of NCEP/NCAR Reanalysis product using the Advanced Research Weather Research and Forecasting Model (ARW-WRF). The results show a low frequency of precipitation (below 0.3) during AR events that reflects the connection of AR with extreme precipitation. Examining the horizontal wind speed during AR events indicates a high correlation (above 0.7) with precipitation. In addition, high levels of snow water equivalence (SWE) are also noticed along the mountainous regions, e.g., Cascade Range and Sierra-Nevada mountain range, during most of AR events. Addressing the impact of duration on the frequency of precipitation, we develop Intensity-Duration-Frequency (IDF) curves during AR events that can potentially describe the future predictability of precipitation along the north and south coast. To complement our analysis, we further investigate the flooding events recorded in the National Centers for Environmental Information (NCEI) storm events database. While some flooding events are attributed to heavy rainfall associated with an AR event, other flooding events are significantly connected to the increase in the snowmelt before the flooding date. Thus, we introduce an index that describes the contribution of rainfall vs snowmelt and categorizes the flooding events during an AR event into rain-driven and snow-driven events. Such categorization can provide insight into whether or not an AR will produce extreme precipitation or flooding. The results from such investigations are important to understand historical AR events and assess how precipitation and flooding might evolve in future climate.

Depletion of abundant plant RuBisCO protein using the protamine sulfate precipitation method.

PubMed

Kim, Yu Ji; Lee, Hye Min; Wang, Yiming; Wu, Jingni; Kim, Sang Gon; Kang, Kyu Young; Park, Ki Hun; Kim, Yong Chul; Choi, In Soo; Agrawal, Ganesh Kumar; Rakwal, Randeep; Kim, Sun Tae

2013-07-01

Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is the most abundant plant leaf protein, hampering deep analysis of the leaf proteome. Here, we describe a novel protamine sulfate precipitation (PSP) method for the depletion of RuBisCO. For this purpose, soybean leaf total proteins were extracted using Tris-Mg/NP-40 extraction buffer. Obtained clear supernatant was subjected to the PSP method, followed by 13% SDS-PAGE analysis of total, PS-supernatant and -precipitation derived protein samples. In a dose-dependent experiment, 0.1% w/v PS was found to be sufficient for precipitating RuBisCO large and small subunits (LSU and SSU). Western blot analysis confirmed no detection of RuBisCO LSU in the PS-supernatant proteins. Application of this method to Arabidopsis, rice, and maize leaf proteins revealed results similar to soybean. Furthermore, 2DE analyses of PS-treated soybean leaf displayed enriched protein profile for the protein sample derived from the PS-supernatant than total proteins. Some enriched 2D spots were subjected to MALDI-TOF-TOF analysis and were successfully assigned for their protein identity. Hence, the PSP method is: (i) simple, fast, economical, and reproducible for RuBisCO precipitation from the plant leaf sample; (ii) applicable to both dicot and monocot plants; and (iii) suitable for downstream proteomics analysis. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interlaboratory comparability, bias, and precision for four laboratories measuring constituents in precipitation, November 1982-August 1983

USGS Publications Warehouse

Brooks, M.H.; Schroder, L.J.; Malo, B.A.

1985-01-01

Four laboratories were evaluated in their analysis of identical natural and simulated precipitation water samples. Interlaboratory comparability was evaluated using analysis of variance coupled with Duncan 's multiple range test, and linear-regression models describing the relations between individual laboratory analytical results for natural precipitation samples. Results of the statistical analyses indicate that certain pairs of laboratories produce different results when analyzing identical samples. Analyte bias for each laboratory was examined using analysis of variance coupled with Duncan 's multiple range test on data produced by the laboratories from the analysis of identical simulated precipitation samples. Bias for a given analyte produced by a single laboratory has been indicated when the laboratory mean for that analyte is shown to be significantly different from the mean for the most-probable analyte concentrations in the simulated precipitation samples. Ion-chromatographic methods for the determination of chloride, nitrate, and sulfate have been compared with the colorimetric methods that were also in use during the study period. Comparisons were made using analysis of variance coupled with Duncan 's multiple range test for means produced by the two methods. Analyte precision for each laboratory has been estimated by calculating a pooled variance for each analyte. Analyte estimated precisions have been compared using F-tests and differences in analyte precisions for laboratory pairs have been reported. (USGS)

Climate signature of Northwest U.S. precipitation Extremes

NASA Astrophysics Data System (ADS)

Kushnir, Y.; Nakamura, J.

2017-12-01

The climate signature of precipitation extremes in the Northwest U.S. - the region that includes Oregon, Washington, Idaho, Montana and Wyoming - is studied using composite analysis of atmospheric fields leading to and associated with extreme rainfall events. A K-Medoids cluster analysis is applied to winter (November-February) months, maximum 5-day precipitation amounts calculated from 1-degree gridded daily rainfall between 1950/51 and 2013/14. The clustering divides the region into three sub-regions: one over the far eastern part of the analysis domain, includeing most of Montana and Wyoming. Two other sub-regions are in the west, lying north and south of the latitude of 45N. Using the time series corresponding to the Medoid centers, we extract the largest (top 5%) monthly extreme events to form the basis for the composite analysis. The main circulation feature distinguishing a 5-day extreme precipitation event in the two western sub-regions of the Northwest is the presence of a large, blocking, high pressure anomaly over the Gulf of Alaska about a week before the beginning of the 5-day intense precipitation event. The high pressure center intensifies considerably with time, drifting slowly westward, up to a day before the extreme event. During that time, a weak low pressure centers appears at 30N, to the southwest of the high, deepening as it moves east. As the extreme rainfall event is about to begin, the now deep low is encroaching on the Northwest coast while its southern flank taps well south into the subtropical Pacific, drawing moisture from as south as 15N. During the 5-day extreme precipitation event the high pressure center moves west and weakens while the now intense low converges large amounts of subtropical moisture to precipitate over the western Northwest. The implication of this analysis for extended range prediction is assessed.

Regional variability of the frequency distribution of daily precipitation and the synoptic characteristics of heavy precipitation events in present and future climate simulations

NASA Astrophysics Data System (ADS)

DeAngelis, Anthony M.

Changes in the characteristics of daily precipitation in response to global warming may have serious impacts on human life and property. An analysis of precipitation in climate models is performed to evaluate how well the models simulate the present climate and how precipitation may change in the future. Models participating in phase 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) have substantial biases in their simulation of heavy precipitation intensity over parts of North America during the 20th century. Despite these biases, the large-scale atmospheric circulation accompanying heavy precipitation is either simulated realistically or the strength of the circulation is overestimated. The biases are not related to the large-scale flow in a simple way, pointing toward the importance of other model deficiencies, such as coarse horizontal resolution and convective parameterizations, for the accurate simulation of intense precipitation. Although the models may not sufficiently simulate the intensity of precipitation, their realistic portrayal of the large-scale circulation suggests that projections of future precipitation may be reliable. In the CMIP5 ensemble, the distribution of daily precipitation is projected to undergo substantial changes in response to future atmospheric warming. The regional distribution of these changes was investigated, revealing that dry days and days with heavy-extreme precipitation are projected to increase at the expense of light-moderate precipitation over much of the middle and low latitudes. Such projections have serious implications for future impacts from flood and drought events. In other places, changes in the daily precipitation distribution are characterized by a shift toward either wetter or drier conditions in the future, with heavy-extreme precipitation projected to increase in all but the driest subtropical subsidence regions. Further analysis shows that increases in heavy precipitation in midlatitudes are largely explained by thermodynamics, including increases in atmospheric water vapor. However, in low latitudes and northern high latitudes, changes in vertical velocity accompanying heavy precipitation are also important. The strength of the large-scale atmospheric circulation is projected to change in accordance with vertical velocity in many places, though the circulation patterns, and therefore physical mechanisms that generate heavy precipitation, may remain the same.

Precipitation From a Multiyear Database of Convection-Allowing WRF Simulations

NASA Astrophysics Data System (ADS)

Goines, D. C.; Kennedy, A. D.

2018-03-01

Convection-allowing models (CAMs) have become frequently used for operational forecasting and, more recently, have been utilized for general circulation model downscaling. CAM forecasts have typically been analyzed for a few case studies or over short time periods, but this limits the ability to judge the overall skill of deterministic simulations. Analysis over long time periods can yield a better understanding of systematic model error. Four years of warm season (April-August, 2010-2013)-simulated precipitation has been accumulated from two Weather Research and Forecasting (WRF) models with 4 km grid spacing. The simulations were provided by the National Center for Environmental Prediction (NCEP) and the National Severe Storms Laboratory (NSSL), each with different dynamic cores and parameterization schemes. These simulations are evaluated against the NCEP Stage-IV precipitation data set with similar 4 km grid spacing. The spatial distribution and diurnal cycle of precipitation in the central United States are analyzed using Hovmöller diagrams, grid point correlations, and traditional verification skill scoring (i.e., ETS; Equitable Threat Score). Although NCEP-WRF had a high positive error in total precipitation, spatial characteristics were similar to observations. For example, the spatial distribution of NCEP-WRF precipitation correlated better than NSSL-WRF for the Northern Plains. Hovmöller results exposed a delay in initiation and decay of diurnal precipitation by NCEP-WRF while both models had difficulty in reproducing the timing and location of propagating precipitation. ETS was highest for NSSL-WRF in all domains at all times. ETS was also higher in areas of propagating precipitation compared to areas of unorganized diurnal scattered precipitation. Monthly analysis identified unique differences between the two models in their abilities to correctly simulate the spatial distribution and zonal motion of precipitation through the warm season.

Assessment of Precipitation Anomalies in California Using TRMM and MERRA Data

NASA Technical Reports Server (NTRS)

Savtchenko, Andrey K.; Huffman, George; Vollmer, Bruce

2015-01-01

Using modern satellite (Tropical Rainfall Measuring Mission, TRMM, 1998-2014) and reanalysis (Modern-Era Retrospective Analysis for Research and Applications, MERRA, 1979-2015) data, we reassess certain aspects of the precipitation climate in California from the past decades. California has a well-pronounced rain season that peaks in December-February. However, the 95% confidence interval around the climatological precipitation during these months imply that deviations on the order of 60% of the expected amounts are very likely during the most important period of the rain season. While these positive and negative anomalies alternate almost every year and tend to cancel each other, severe multiyear declines of precipitation in California appear on decadal scales. The 1986-1994 decline of precipitation was similar to the current one that started in 2011 and is apparent in the reanalysis data. In terms of accumulated deficits of precipitation, that episode was no less severe than the current one. While El Niño (the warm phase of the El Nino-Southern Oscillation, ENSO) is frequently cited as the natural forcing expected to bring a relief from drought, our assessment is that ENSO has been driving at best only 6% of precipitation variability in California in the past three decades. Using fractional risk analysis of precipitation during typical versus drying periods, we show that the likelihood of losing the most intensive precipitation events drastically increases during the multiyear drying events. Storms delivering up to 50% of the precipitation in California are driven by atmospheric rivers making landfall. However, these phenomena can be suppressed and even blocked by persistent ridges of atmospheric pressure in the northeast Pacific. The reanalysis and satellite data are proven to be reliable to the extent where they yield information on developing conditions and observed precipitation anomalies.

Investigating Satellite Microwave observations of Precipitation in Different Climate Regimes

NASA Astrophysics Data System (ADS)

Wang, N.; Ferraro, R. R.

2013-12-01

Microwave satellite remote sensing of precipitation over land is a challenging problem due to the highly variable land surface emissivity, which, if not properly accounted for, can be much greater than the precipitation signal itself, especially in light rain/snow conditions. Additionally, surfaces such as arid land, deserts and snow cover have brightness temperature characteristics similar to precipitation Ongoing work by GPM microwave radiometer team is constructing databases through a variety of means, however, there is much uncertainty as to what is the optimal information needed for the wide array of sensors in the GPM constellation, including examination of regional conditions. The original data sets will focus on stratification by emissivity class, surface temperature and total perceptible water. We'll perform sensitivity studies to determine the potential role of ancillary data (e.g., land surface temperature, snow cover/water equivalent, etc.) to improve precipitation estimation over land in different climate regimes, including rain and snow. In other words, what information outside of the radiances can help describe the background and subsequent departures from it that are active precipitating regions? It is likely that this information will be a function of the various precipitation regimes. Statistical methods such as Principal Component Analysis (PCA) will be utilized in this task. Databases from a variety of sources are being constructed. They include existing satellite microwave measurements of precipitating and non-precipitating conditions, ground radar precipitation rate estimates, surface emissivity climatology from satellites, surface temperature and TPW from NWP reanalysis. Results from the analysis of these databases with respect to the microwave precipitation sensitivity to the variety of environmental conditions in different climate regimes will be discussed.

Responses of Mean and Extreme Precipitation to Deforestation in the Maritime Continent

NASA Astrophysics Data System (ADS)

Chen, C. C.; Lo, M. H.; Yu, J. Y.

2017-12-01

Anthropogenic land use and land cover change, including tropical deforestation, could have substantial effects on local surface energy and water budgets, and thus on the atmospheric stability which may result in changes in precipitation. Maritime Continent has undergone severe deforestation in recent decades but has received less attention than Amazon or Congo rainforests. Therefore, this study is to decipher the precipitation response to deforestation in the Maritime Continent. We conduct deforestation experiments using Community Earth System Model (CESM) and through converting the tropical rainforest into grassland. The results show that deforestation in Maritime Continent leads to an increase in both mean temperature and mean precipitation. Moisture budget analysis indicates that the increase in precipitation is associated with the vertically integrated vertical moisture advection, especially the dynamic component (changes in convection). In addition, through moist static energy (MSE) budget analysis, we find the atmosphere among deforested areas become unstable owing to the combined effects of positive specific humidity anomalies at around 850 hPa and anomalous warming extended from the surface to 750 hPa. This instability will induce anomalous ascending motion, which could enhance the low-level moisture convergence, providing water vapor from the surrounding warm ocean. To further evaluate the precipitation response to deforestation, we examine the precipitation changes under La Niña events and global warming scenario using CESM Atmospheric Model Intercomparison Project (AMIP) simulations and Representative Concentration Pathway (RCP) 8.5 simulations. We find that the precipitation increase caused by deforestation in Maritime Continent is comparable in magnitude to that generated by either natural variability or global warming forcing. Besides the changes in mean precipitation, preliminary results show the extreme precipitation also increases. We will further explore how the extreme precipitation changes with the deforestation forcing.

Status of High Latitude Precipitation Estimates from Observations and Reanalyses

NASA Technical Reports Server (NTRS)

Behrangi, Ali; Christensen, Matthew; Richardson, Mark; Lebsock, Matthew; Stephens, Graeme; Huffman, George J.; Bolvin, David T.; Adler, Robert F.; Gardner, Alex; Lambrigtsen, Bjorn H.;

A simple reactive-transport model of calcite precipitation in soils and other porous media

NASA Astrophysics Data System (ADS)

Kirk, G. J. D.; Versteegen, A.; Ritz, K.; Milodowski, A. E.

2015-09-01

Calcite formation in soils and other porous media generally occurs around a localised source of reactants, such as a plant root or soil macro-pore, and the rate depends on the transport of reactants to and from the precipitation zone as well as the kinetics of the precipitation reaction itself. However most studies are made in well mixed systems, in which such transport limitations are largely removed. We developed a mathematical model of calcite precipitation near a source of base in soil, allowing for transport limitations and precipitation kinetics. We tested the model against experimentally-determined rates of calcite precipitation and reactant concentration-distance profiles in columns of soil in contact with a layer of HCO3--saturated exchange resin. The model parameter values were determined independently. The agreement between observed and predicted results was satisfactory given experimental limitations, indicating that the model correctly describes the important processes. A sensitivity analysis showed that all model parameters are important, indicating a simpler treatment would be inadequate. The sensitivity analysis showed that the amount of calcite precipitated and the spread of the precipitation zone were sensitive to parameters controlling rates of reactant transport (soil moisture content, salt content, pH, pH buffer power and CO2 pressure), as well as to the precipitation rate constant. We illustrate practical applications of the model with two examples: pH changes and CaCO3 precipitation in the soil around a plant root, and around a soil macro-pore containing a source of base such as urea.

Variability of extreme weather events over the equatorial East Africa, a case study of rainfall in Kenya and Uganda

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Omony, George William

2018-01-01

This study investigates the variability of extreme rainfall events over East Africa (EA), using indices from the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis was based on observed daily rainfall from 23 weather stations, with length varying within 1961 and 2010. The indices considered are: wet days ( R ≥1 mm), annual total precipitation in wet days (PRCPTOT), simple daily intensity index (SDII), heavy precipitation days ( R ≥ 10 mm), very heavy precipitation days ( R ≥ 20 mm), and severe precipitation ( R ≥ 50 mm). The non-parametric Mann-Kendall statistical analysis was carried out to identify trends in the data. Temporal precipitation distribution was different from station to station. Almost all indices considered are decreasing with time. The analysis shows that the PRCPTOT, very heavy precipitation, and severe precipitation are generally declining insignificantly at 5 % significant level. The PRCPTOT is evidently decreasing over Arid and Semi-Arid Land (ASAL) as compared to other parts of EA. The number of days that recorded heavy rainfall is generally decreasing but starts to rise in the last decade although the changes are insignificant. Both PRCPTOT and heavy precipitation show a recovery in trend starting in the 1990s. The SDII shows a reduction in most areas, especially the in ASAL. The changes give a possible indication of the ongoing climate variability and change which modify the rainfall regime of EA. The results form a basis for further research, utilizing longer datasets over the entire region to reduce the generalizations made herein. Continuous monitoring of extreme events in EA is critical, given that rainfall is projected to increase in the twenty-first century.

Development of a Video-Microscopic Tool To Evaluate the Precipitation Kinetics of Poorly Water Soluble Drugs: A Case Study with Tadalafil and HPMC.

PubMed

Christfort, Juliane Fjelrad; Plum, Jakob; Madsen, Cecilie Maria; Nielsen, Line Hagner; Sandau, Martin; Andersen, Klaus; Müllertz, Anette; Rades, Thomas

2017-12-04

Many drug candidates today have a low aqueous solubility and, hence, may show a low oral bioavailability, presenting a major formulation and drug delivery challenge. One way to increase the bioavailability of these drugs is to use a supersaturating drug delivery strategy. The aim of this study was to develop a video-microscopic method, to evaluate the effect of a precipitation inhibitor on supersaturated solutions of the poorly soluble drug tadalafil, using a novel video-microscopic small scale setup. Based on preliminary studies, a degree of supersaturation of 29 was chosen for the supersaturation studies with tadalafil in FaSSIF. Different amounts of hydroxypropyl methyl cellulose (HPMC) were predissolved in FaSSIF to give four different concentrations, and the supersaturated system was then created using a solvent shift method. Precipitation of tadalafil from the supersaturated solutions was monitored by video-microscopy as a function of time. Single-particle analysis was possible using commercially available software; however, to investigate the entire population of precipitating particles (i.e., their number and area covered in the field of view), an image analysis algorithm was developed (multiparticle analysis). The induction time for precipitation of tadalafil in FaSSIF was significantly prolonged by adding 0.01% (w/v) HPMC to FaSSIF, and the maximum inhibition was reached at 0.1% (w/v) HPMC, after which additional HPMC did not further increase the induction time. The single-particle and multiparticle analyses yielded the same ranking of the HPMC concentrations, regarding the inhibitory effect on precipitation. The developed small scale method to assess the effect of precipitation inhibitors can speed up the process of choosing the right precipitation inhibitor and the concentration to be used.

Analysis of aerosol-cloud-precipitation interactions based on MODIS data

NASA Astrophysics Data System (ADS)

Cheng, Feng; Zhang, Jiahua; He, Junliang; Zha, Yong; Li, Qiannan; Li, Yunmei

2017-01-01

Aerosols exert an indirect impact on climate change via its impact on clouds by altering its radiative and optical properties which, in turn, changes the process of precipitation. Over recent years how to study the indirect climate effect of aerosols has become an important research topic. In this study we attempted to understand the complex mutual interactions among aerosols, clouds and precipitation through analysis of the spatial correlation between aerosol optical depth (AOD), cloud effective radius (CER) and precipitation during 2000-2012 in central-eastern China that has one of the highest concentrations of aerosols globally. With the assistance of moderate resolution imaging spectroradiometer (MODIS)-derived aerosol and cloud product data, this analysis focuses on regional differentiation and seasonal variation of the correlation in which in situ observed precipitation was incorporated. On the basis of the achieved results, we proposed four patterns depicting the mutual interactions between aerosols, clouds and precipitation. They characterize the indirect effects of aerosols on the regional scale. These effects can be summarized as complex seasonal variations and north-south regional differentiation over the study area. The relationship between AOD and CER is predominated mostly by the first indirect effect (the negative correlation between AOD and CER) in the north of the study area in the winter and spring seasons, and over the entire study area in the summer season. The relationship between CER and precipitation is dominated chiefly by the second indirect effect (the positive correlation between CER and precipitation) in the northern area in summer and over the entire study area in autumn. It must be noted that aerosols are not the factor affecting clouds and rainfall singularly. It is the joint effect of aerosols with other factors such as atmospheric dynamics that governs the variation in clouds and rainfall.

Global analyses of water vapor, cloud and precipitation derived from a diagnostic assimilation of SSM/I geophysical retrievals

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Cohen, Charles

1990-01-01

An analytical approach is described for diagnostically assimilating moisture data from Special Sensor Microwave Imager (SSM/I) into a global analysis of water vapor, cloud content, and precipitation. In this method, 3D fields of wind and temperature values taken from ECMWF gridded analysis are used to drive moisture conservation equations with parameterized microphysical treatment of vapor, liquid, and ice; the evolving field of water vapor is periodically updated or constrained by SSM/I retrievals of precipitable water. Initial results indicate that this diagnostic model can produce realistic large-scale fields of cloud and precipitation. The resulting water vapor analyses agree well with SSM/I and have an additional advantage of being synoptic.

Investigation of mesoscale precipitation processes in the Carolinas using a radar-based climatology

NASA Astrophysics Data System (ADS)

Boyles, Ryan Patrick

The complex topography, shoreline, soils, and land use patterns makes the Carolinas a unique location to study mesoscale processes. Using gage-calibrated radar estimates and a series of numerical model simulations, warm season mesoscale precipitation patterns are analyzed over the Carolinas. Gage-calibrated radar precipitation estimates are compared with surface gage observations. Stage IV estimates generally compared better than Stage II estimates, but some Stage II and Stage IV estimates have gross errors during autumn, winter, and spring seasons. Analysis of days when sea breeze is observed suggests that sea breeze induced precipitation occurs on nearly 40% of days in June, July, and August, but only 18% in May and 6% of days in April. Precipitation on days with sea breeze convection can contribute to over 50% of seasonal precipitation. Rainfall associated with sea breeze is generally maximized along east-facing shores 10-20 km inland, and minimized along south-facing shores in North Carolina. The shape of the shoreline along Cape Fear is associated with a local precipitation maximum that may be caused by the convergence of two sea breeze fronts from the south and east shores. Differential heating associated with contrasting soils along the Carolina Sandhills is suggested as a mechanism for enhancement in local precipitation. A high-resolution summer precipitation climatology suggests that precipitation is enhanced along the Sandhills region in both wet and dry years. Analysis of four numerical simulations suggests that contrasts in soils over the Carolinas Sandhills dominates over vegetation contrasts to produce heat flux gradients and a convergence zone along the sand-to-clay transition. Orographically induced precipitation is consistently observed in the summer, and appears to be isolated along windward slopes at 20km--40km from the ridge line. Amounts over external ridges are generally 50-100% higher than amounts observed over the foothills. Precipitation amounts over interior ridges and valleys are lower than observed on exterior ridges and are similar to values observed over the foothills. When compared with Stage IV estimates, the PRISM (Precipitation-elevation Regressions on Independent Slopes Model) method for estimating precipitation in complex terrain appears to largely over-estimate precipitation amounts over the interior ridges.

The Vaiont Slide. A Geotechnical Analysis Based on New Geologic Observations of the Failure Surface. Volume 2. Appendices A through G

DTIC Science & Technology

1985-06-01

Al B , STATIC SLOPE ANALYSIS METHOD USED FOR THE WAONT SLIDE -ANALYSES~ty D. L. Anderson ................................... B1 C SECTIONS,,USED...years 1960, 1961, 1962 and 1963 are given in this appendix in Tables Al , A2, A3 and A4, respectively. These were supplied through the courtesy of E.N.E.L...Tables Table Al . Daily precipitation record, Erto - 1960 Table A2. Daily precipitation record, Erto - 1961 Table A3. Daily precipitation record, Erto

Calibration of collection procedures for the determination of precipitation chemistry

Treesearch

James N. Galloway; Gene E. Likens

1976-01-01

Precipitation is currently collected by several methods, including several different designs of collection apparatus. We are investigating these differing methods and designs to determine which gives the most representative sample of precipitation for the analysis of some 25 chemical parameters. The experimental site, located in Ithaca, New York, has 22 collectors of...

Multicentury Reconstruction of Precipitations (1300-2014) in Eastern Canada from Tree-Ring Width and Carbon and Oxygen Isotopes

NASA Astrophysics Data System (ADS)

Giguère, Claudie; Boucher, Étienne; Bergeron, Yves

2016-04-01

Tree ring series enabling long hydroclimatic reconstructions are scarce in Northeastern America, mostly because most boreal species are rather thermo-dependant. Here we propose a new multi-proxy analysis (tree-ring, δ13C and δ18O) from one of the oldest Thuja occidentalis population in NE America (lake Duparquet, Quebec). These rare precipitation-sensitive, long-living trees (> 800 years) grow on xeric rocky shores and their potential for paleo-hydroclimatic reconstructions (based on ring widths solely) was previously assessed. The objectives of this study are twofold i) to strengthen the hydroclimatic signal of this long tree-ring chronology by adding analysis of stable isotope ratios (δ13C and δ18O) and ii) to reconstruct summer precipitation back to 1300 AD, which will represent, by far, the longest high-resolution hydroclimatic reconstruction in this region. A tree-ring chronology was constructed from 61 trees sampled in standing position. Eleven trees were also sampled to produce pooled carbon and oxygen isotope chronologies (annually resolved) with a replication of five to six trees per year. Signal analysis (correlation between climatic data and proxy values) confirms that growth is positively influenced by spring precipitations (May-June), while δ13C is negatively correlated to summer precipitation (June to August) and positively to June temperature. Adding δ18O analysis will strengthen the signal even more, since wood cellulose should be enriched in δ18O when high evapotranspiration conditions prevail. Based on a multi-proxy approach, a summer precipitation reconstruction was developed and compared to other temperature reconstructions from this region as well as to southernmost hydroclimatic reconstructions (e.g. Cook et al). A preliminary analysis of external and internal forcing is proposed in conclusion.

Development of a Multiple Input Integrated Pole-to-Pole Global CMORPH

NASA Astrophysics Data System (ADS)

Joyce, R.; Xie, P.

2013-12-01

A test system is being developed at NOAA Climate Prediction Center (CPC) to produce a passive microwave (PMW), IR-based, and model integrated high-resolution precipitation estimation on a 0.05olat/lon grid covering the entire globe from pole to pole. Experiments have been conducted for a summer Test Bed period using data for July and August of 2009. The pole-to-pole global CMORPH system is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). First, retrievals of instantaneous precipitation rates from PMW observations aboard nine low earth orbit (LEO) satellites are decoded and pole-to-pole mapped onto a 0.05olat/lon grid over the globe. Also precipitation estimates from LEO AVHRR retrievals are derived using a PDF matching of LEO IR with calibrated microwave combined (MWCOMB) precipitation retrievals. The motion vectors for the precipitating cloud systems are defined using information from both satellite IR observations and precipitation fields generated by the NCEP Climate Forecast System Reanalysis (CFSR). To this end, motion vectors are first computed for the CFSR hourly precipitation fields through cross-correlation analysis of consecutive hourly precipitation fields on the global T382 (~35 km) grid. In a similar manner, separate processing is also performed on satellite IR-based precipitation estimates to derive motion vectors from observations. A blended analysis of precipitating cloud motion vectors is then constructed through the combination of CFSR and satellite-derived vectors utilizing a two-dimensional optimal interpolation (2D-OI) method, in which CFSR-derived motion vectors are used as the first guess and subsequently satellite derived vectors modify the first guess. Weights used to generate the combinations are defined under the OI framework as a function of error statistics for the CFSR and satellite IR based motion vectors. The screened and calibrated PMW and AVHRR derived precipitation estimates are then separately spatially propagated forward and backward in time, using precipitating cloud motion vectors, from their observation time to the next PMW observation. The PMW estimates propagated in both the forward and backward directions are then combined with propagated IR-based precipitation estimates under the Kalman Filter framework, with weights defined based on previously determined error statistics dependent on latitude, season, surface type, and temporal distance from observation time. Performance of the pole-to-pole global CMORPH and its key components, including combined PMW (MWCOMB), IR-based, and model precipitation, as well as model-derived, IR-based, and blended precipitation motion vectors, will be examined against NSSL Q2 radar observed precipitation estimates over CONUS, Finland FMI radar precipitation, and a daily gauge-based analysis including daily Canadian surface reports over global land. Also an initial investigation will be performed over a January - February 2010 winter Test Bed period. Detailed results will be reported at the Fall 2013 AGU Meeting.

Monotonic trends in spatio-temporal distribution and concentration of monsoon precipitation (1901-2002), West Bengal, India

NASA Astrophysics Data System (ADS)

Chatterjee, Soumendu; Khan, Ansar; Akbari, Hashem; Wang, Yupeng

2016-12-01

This paper intended to investigate spatio-temporal monotonic trend and shift in concentration of monsoon precipitation across West Bengal, India, by analysing the time series of monthly precipitation from 18 weather stations during the period from 1901 to 2002. In dealing with, the inhomogeneity in the precipitation series, RHtestsV4 software package is used to detect, and adjust for, multiple change points (shifts) that could exist in data series. Finally, the cumulative deviation test was applied at 5% significant level to check the homogeneity (presence of historic changes by cumulative deviations test). Afterward, non-parametric Mann-Kendall (MK) test and Theil-Sen estimator (TSE) was applied to detect of nature and slope of trends; and, Sequential Mann Kendall (SQMK) test was applied for detection of turning point and magnitude of change in trends. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation in precipitation data series. Four indices- precipitation concentration index (PCI), precipitation concentration degree (PCD), precipitation concentration period (PCP) and fulcrum (centre of gravity) were used to detect precipitation concentration and the spatial pattern in it. The application of the above-mentioned procedures has shown very notable statewide monotonic trend for monsoon precipitation time series. Regional cluster analysis by SQMK found increasing precipitation in mountain and coastal regions in general, except during the non- monsoon seasons. The results show that higher PCI values were mainly observed in South Bengal, whereas lower PCI values were mostly detected in North Bengal. The PCI values are noticeably larger in places where both monsoon total precipitation and span of rainy season are lower. The results of PCP reveal that precipitation in Gangetic Bengal mostly occurs in summer (monsoon season), and the rainy season arrives earlier in North Bengal than South Bengal, whereas the results of PCD also indicate that the precipitation in North Bengal was more dispersed within a year than that in South Bengal. The concentration characteristic of precipitation could be detected by fulcrum analysis, and significant concentration over most of West Bengal was obvious within July month band. Precipitation trend observed in West Bengal is compared with that in Central India (CI) region and comparison of precipitation departure with Indian monsoon and Gangetic Bengal can be explained by forecasting ensemble.

Estimation of groundwater recharge parameters by time series analysis

USGS Publications Warehouse

Naff, Richard L.; Gutjahr, Allan L.

1983-01-01

A model is proposed that relates water level fluctuations in a Dupuit aquifer to effective precipitaton at the top of the unsaturated zone. Effective precipitation, defined herein as that portion of precipitation which becomes recharge, is related to precipitation measured in a nearby gage by a two-parameter function. A second-order stationary assumption is used to connect the spectra of effective precipitation and water level fluctuations. Measured precipitation is assumed to be Gaussian, in order to develop a transfer function that relates the spectra of measured and effective precipitation. A nonlinear least squares technique is proposed for estimating parameters of the effective-precipitation function. Although sensitivity analyses indicate difficulties that may be encountered in the estimation procedure, the methods developed did yield convergent estimates for two case studies.

Precipitation data in a mountainous catchment in Honduras: quality assessment and spatiotemporal characteristics

NASA Astrophysics Data System (ADS)

Westerberg, I.; Walther, A.; Guerrero, J.-L.; Coello, Z.; Halldin, S.; Xu, C.-Y.; Chen, D.; Lundin, L.-C.

2010-08-01

An accurate description of temporal and spatial precipitation variability in Central America is important for local farming, water supply and flood management. Data quality problems and lack of consistent precipitation data impede hydrometeorological analysis in the 7,500 km2 Choluteca River basin in central Honduras, encompassing the capital Tegucigalpa. We used precipitation data from 60 daily and 13 monthly stations in 1913-2006 from five local authorities and NOAA's Global Historical Climatology Network. Quality control routines were developed to tackle the specific data quality problems. The quality-controlled data were characterised spatially and temporally, and compared with regional and larger-scale studies. Two gap-filling methods for daily data and three interpolation methods for monthly and mean annual precipitation were compared. The coefficient-of-correlation-weighting method provided the best results for gap-filling and the universal kriging method for spatial interpolation. In-homogeneity in the time series was the main quality problem, and 22% of the daily precipitation data were too poor to be used. Spatial autocorrelation for monthly precipitation was low during the dry season, and correlation increased markedly when data were temporally aggregated from a daily time scale to 4-5 days. The analysis manifested the high spatial and temporal variability caused by the diverse precipitation-generating mechanisms and the need for an improved monitoring network.

Determination of strontium-90 in milk samples using a controlled precipitation clean-up step prior to ion-chromatography.

PubMed

Cobb, J; Warwick, P; Carpenter, R C; Morrison, R T

1995-12-01

Strontium-90 may be determined by beta-counting its yttrium-90 daughter following separation by ion-chromatography, using a three column system comprising a chelating concentrator column, a cation-exchange column and an anion-exchange separator column. The column system has previously been applied to the determination of strontium-90 in water and urine samples. The applicability of the system to the analysis of milk is hampered by the large concentrations of calcium present, which significantly reduces the extraction of yttrium-90 by the concentrator column. A maximum of approximately 200 mg of calcium can be present for the successful extraction of yttrium-90, which greatly limits the quantity of milk that can be analysed. The quantity of milk analysed can be increased by the inclusion of a controlled precipitation step prior to the ion-chromatographic separation. The precipitation is carried out on acid digested milk samples by the addition of ammonia solution until the addition of one drop causes a reduction in pH resulting in the precipitation of calcium hydrogenphosphate. Under these conditions, approximately 20% of the calcium present in the original milk sample is precipitated, yttrium-90 is precipitated whereas strontium-90 is not precipitated. Dissolution of the precipitate, followed by separation of yttrium-90 using the ion-chromatography system facilitates the analysis of a litre of milk with recoveries of greater than 80%.

Comparison of Four Precipitation Forcing Datasets in Land Information System Simulations over the Continental U.S.

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Kumar, Sujay V.; Kuligowski, Robert J.; Langston, Carrie

2013-01-01

The NASA Short ]term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real ]time configuration of the NASA Land Information System (LIS) with the Noah land surface model (LSM). Output from the SPoRT ]LIS run is used to initialize land surface variables for local modeling applications at select National Weather Service (NWS) partner offices, and can be displayed in decision support systems for situational awareness and drought monitoring. The SPoRT ]LIS is run over a domain covering the southern and eastern United States, fully nested within the National Centers for Environmental Prediction Stage IV precipitation analysis grid, which provides precipitation forcing to the offline LIS ]Noah runs. The SPoRT Center seeks to expand the real ]time LIS domain to the entire Continental U.S. (CONUS); however, geographical limitations with the Stage IV analysis product have inhibited this expansion. Therefore, a goal of this study is to test alternative precipitation forcing datasets that can enable the LIS expansion by improving upon the current geographical limitations of the Stage IV product. The four precipitation forcing datasets that are inter ]compared on a 4 ]km resolution CONUS domain include the Stage IV, an experimental GOES quantitative precipitation estimate (QPE) from NESDIS/STAR, the National Mosaic and QPE (NMQ) product from the National Severe Storms Laboratory, and the North American Land Data Assimilation System phase 2 (NLDAS ]2) analyses. The NLDAS ]2 dataset is used as the control run, with each of the other three datasets considered experimental runs compared against the control. The regional strengths, weaknesses, and biases of each precipitation analysis are identified relative to the NLDAS ]2 control in terms of accumulated precipitation pattern and amount, and the impacts on the subsequent LSM spin ]up simulations. The ultimate goal is to identify an alternative precipitation forcing dataset that can best support an expansion of the real ]time SPoRT ]LIS to a domain covering the entire CONUS.

Why Is Rainfall Error Analysis Requisite for Data Assimilation and Climate Modeling?

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.

2004-01-01

Given the large temporal and spatial variability of precipitation processes, errors in rainfall observations are difficult to quantify yet crucial to making effective use of rainfall data for improving atmospheric analysis, weather forecasting, and climate modeling. We highlight the need for developing a quantitative understanding of systematic and random errors in precipitation observations by examining explicit examples of how each type of errors can affect forecasts and analyses in global data assimilation. We characterize the error information needed from the precipitation measurement community and how it may be used to improve data usage within the general framework of analysis techniques, as well as accuracy requirements from the perspective of climate modeling and global data assimilation.

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

Trend analysis and forecast of precipitation, reference evapotranspiration and rainfall deficit in the Blackland Prairie of eastern Mississippi

USDA-ARS?s Scientific Manuscript database

Trend analysis and estimation of monthly and annual precipitation, reference evapotranspiration (ETo) and rainfall deficit are essential for water resources management and cropping system design. Rainfall, ETo, and water deficit patterns and trends in eastern Mississippi USA for a 120-year period (1...

Determination of Sulfate by Conductometric Titration: An Undergraduate Laboratory Experiment

ERIC Educational Resources Information Center

Garcia, Jennifer; Schultz, Linda D.

2016-01-01

The classic technique for sulfate analysis in an undergraduate quantitative analysis lab involves precipitation as the barium salt with barium chloride, collection of the precipitate by gravity filtration using ashless filter paper, and removal of the filter paper by charring over a Bunsen burner. The entire process is time-consuming, hazardous,…

A Preliminary Examination of the Second Generation CMORPH Real-time Production

NASA Astrophysics Data System (ADS)

Joyce, R.; Xie, P.; Wu, S.

2017-12-01

The second generation CMORPH (CMORPH2) has started test real-time production of 30-minute precipitation estimates on a 0.05olat/lon grid over the entire globe, from pole-to-pole. The CMORPH2 is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) and LEO platforms, and precipitation simulations from the NCEP operational global forecast system (GFS). Inputs from the various sources are first inter-calibrated to ensure quantitative consistencies in representing precipitation events of different intensities through PDF calibration against a common reference standard. The inter-calibrated PMW retrievals and IR-based precipitation estimates are then propagated from their respective observation times to the target analysis time along the motion vectors of the precipitating clouds. Motion vectors are first derived separately from the satellite IR based precipitation estimates and the GFS precipitation fields. These individually derived motion vectors are then combined through a 2D-VAR technique to form an analyzed field of cloud motion vectors over the entire globe. The propagated PMW and IR based precipitation estimates are finally integrated into a single field of global precipitation through the Kalman Filter framework. A set of procedures have been established to examine the performance of the CMORPH2 real-time production. CMORPH2 satellite precipitation estimates are compared against the CPC daily gauge analysis, Stage IV radar precipitation over the CONUS, and numerical model forecasts to discover potential shortcomings and quantify improvements against the first generation CMORPH. Special attention has been focused on the CMORPH behavior over high-latitude areas beyond the coverage of the first generation CMORPH. Detailed results will be reported at the AGU.

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

NASA Astrophysics Data System (ADS)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

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

NASA Technical Reports Server (NTRS)

Ashouri, Hamed; Sorooshian, Soroosh; Hsu, Kuo-Lin; Bosilovich, Michael G.; Lee, Jaechoul; Wehner, Michael F.; Collow, Allison

2016-01-01

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-scale 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. MERRA tends 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) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most 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 the Gulf 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 that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

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 that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. The increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.« less

Regional trends in early-monsoon rainfall over Vietnam and CCSM4 attribution

NASA Astrophysics Data System (ADS)

Li, R.; Wang, S. S.-Y.; Gillies, R. R.; Buckley, B. M.; Yoon, J.-H.; Cho, C.

2018-04-01

The analysis of precipitation trends for Vietnam revealed that early-monsoon precipitation has increased over the past three decades but to varying degrees over the northern, central and southern portions of the country. Upon investigation, it was found that the change in early-monsoon precipitation is associated with changes in the low-level cyclonic airflow over the South China Sea and Indochina that is embedded in the large-scale atmospheric circulation associated with a "La Niña-like" anomalous sea surface temperature pattern with warming in the western Pacific and Indian Oceans and cooling in the eastern Pacific. The Community Climate System Model version 4 (CCSM4) was subsequently used for an attribution analysis. Over northern Vietnam an early-monsoon increase in precipitation is attributed to changes in both greenhouse gases and natural forcing. For central Vietnam, the observed increase in early-monsoon precipitation is reproduced by the simulation forced with greenhouse gases. However, over southern Vietnam the early-monsoon precipitation increase is less definitive where aerosols were seen to be preponderant but natural forcing through the role of the Interdecadal Pacific Oscillation may well be a factor that is not resolved by CCSM4. Increased early-monsoonal precipitation over the coastal lowland and deltas has the potential to amplify economic and human losses.

A Century Trend of Precipitation in Forest Watersheds from the Lower Mississippi River Basin

NASA Astrophysics Data System (ADS)

Feng, G.; Ouyang, Y.; Leininger, T.; Han, Y.

2017-12-01

Estimates of hydrological processes in forest watersheds are essential to water supply planning, water quality protection, water resources management, and ecological restoration; whereas the century precipitation variation due to climate change could exacerbate forest watershed hydrological processes and add uncertainties to the processes. In this study, the multivariate statisitcal analysis technique was employed to identify a century temporal trend of precipitation in forest watersheds from the Lower Mississippi River Basin (LMRB). Seveal surface water monitoring stations in the LMRB, located in forest watersheds with very little land use disturbance and a century record, were selected to obtain precipitation data. Using frequency distribution analysis with HYDSTRA model, we found that the mean annual precipitation in a decadal scale increased as time elapsed over a 100-year period. Our study further revealed that the precipitation intensity for one-hour duration increased sigificantly in every 10 years for a 100-year period. During this period, the annual mean dry day frequency decreased in a decadal scale, whereas the annual mean wet day frequency increased for the same scale. Results indicated the precipitation pattern has been altered in the LMRB and the selected forest watersheds in this basin seems to become wetter during the past 100 years as a result of climate change.

Ecohydrology of dry regions of the United States: Precipitation pulses and intraseasonal drought

Treesearch

William K. Lauenroth; John B. Bradford

2009-01-01

Distribution of precipitation event sizes and interval lengths between events are important characteristics of arid and semi-arid climates. Understanding their importance will contribute to our ability to understand ecosystem dynamics in these regions. Our objective for this paper was to present a comprehensive analysis of the daily precipitation regimes of arid and...

JPSS Preparations at the Satellite Proving Ground for Marine, Precipitation, and Satellite Analysis

NASA Technical Reports Server (NTRS)

Folmer, Michael J.; Berndt, E.; Clark, J.; Orrison, A.; Kibler, J.; Sienkiewicz, J.; Nelson, J.; Goldberg, M.; Sjoberg, W.

2016-01-01

The ocean prediction center at the national hurricane center's tropical analysis and forecast Branch, the Weather Prediction center and the Satellite analysis branch of NESDIS make up the Satellite Proving Ground for Marine, Precipitation and Satellite Analysis. These centers had early exposure to JPSS products using the S-NPP Satellite that was launched in 2011. Forecasters continue to evaluate new products in anticipation for the launch of JPSS-1 sometime in 2017.

Impact of the surface wind flow on precipitation characteristics over the southern Himalayas: GPM observations

NASA Astrophysics Data System (ADS)

Zhang, Aoqi; Fu, Yunfei; Chen, Yilun; Liu, Guosheng; Zhang, Xiangdong

2018-04-01

The distribution and influence of precipitation over the southern Himalayas have been investigated on regional and global scales. However, previous studies have been limited by the insufficient emphasis on the precipitation triggers or the lack of droplet size distribution (DSD) data. Here, precipitating systems were identified using Global Precipitation Mission dual-frequency radar data, and then categorized into five classes according to surface flow from the European Centre for Medium-Range Weather Forecast Interim data. The surface flow is introduced to indicate the precipitation triggers, which is validated in this study. Using case and statistical analysis, we show that the precipitating systems with different surface flow had different precipitation characteristics, including spatio-temporal features, reflectivity profile, DSD, and rainfall intensity. Furthermore, the results show that the source of the surface flow influences the intensity and DSD of precipitation. The terrain exerts different impacts on the precipitating systems of five categories, leading to various distributions of precipitation characteristics over the southern Himalayas. Our results suggest that the introduction of surface flow and DSD for precipitating systems provides insight into the complex precipitation of the southern Himalayas. The different characteristics of precipitating systems may be caused by the surface flow. Therefore, future study on the orographic precipitations should take account the impact of the surface flow and its relevant dynamic mechanism.

Regionalization of precipitation characteristics in Iran's Lake Urmia basin

NASA Astrophysics Data System (ADS)

Fazel, Nasim; Berndtsson, Ronny; Uvo, Cintia Bertacchi; Madani, Kaveh; Kløve, Bjørn

2018-04-01

Lake Urmia in northwest Iran, once one of the largest hypersaline lakes in the world, has shrunk by almost 90% in area and 80% in volume during the last four decades. To improve the understanding of regional differences in water availability throughout the region and to refine the existing information on precipitation variability, this study investigated the spatial pattern of precipitation for the Lake Urmia basin. Daily rainfall time series from 122 precipitation stations with different record lengths were used to extract 15 statistical descriptors comprising 25th percentile, 75th percentile, and coefficient of variation for annual and seasonal total precipitation. Principal component analysis in association with cluster analysis identified three main homogeneous precipitation groups in the lake basin. The first sub-region (group 1) includes stations located in the center and southeast; the second sub-region (group 2) covers mostly northern and northeastern part of the basin, and the third sub-region (group 3) covers the western and southern edges of the basin. Results of principal component (PC) and clustering analyses showed that seasonal precipitation variation is the most important feature controlling the spatial pattern of precipitation in the lake basin. The 25th and 75th percentiles of winter and autumn are the most important variables controlling the spatial pattern of the first rotated principal component explaining about 32% of the total variance. Summer and spring precipitation variations are the most important variables in the second and third rotated principal components, respectively. Seasonal variation in precipitation amount and seasonality are explained by topography and influenced by the lake and westerly winds that are related to the strength of the North Atlantic Oscillation. Despite using incomplete time series with different lengths, the identified sub-regions are physically meaningful.

Global modeling of land water and energy balances. Part III: Interannual variability

USGS Publications Warehouse

Shmakin, A.B.; Milly, P.C.D.; Dunne, K.A.

2002-01-01

The Land Dynamics (LaD) model is tested by comparison with observations of interannual variations in discharge from 44 large river basins for which relatively accurate time series of monthly precipitation (a primary model input) have recently been computed. When results are pooled across all basins, the model explains 67% of the interannual variance of annual runoff ratio anomalies (i.e., anomalies of annual discharge volume, normalized by long-term mean precipitation volume). The new estimates of basin precipitation appear to offer an improvement over those from a state-of-the-art analysis of global precipitation (the Climate Prediction Center Merged Analysis of Precipitation, CMAP), judging from comparisons of parallel model runs and of analyses of precipitation-discharge correlations. When the new precipitation estimates are used, the performance of the LaD model is comparable to, but not significantly better than, that of a simple, semiempirical water-balance relation that uses only annual totals of surface net radiation and precipitation. This implies that the LaD simulations of interannual runoff variability do not benefit substantially from information on geographical variability of land parameters or seasonal structure of interannual variability of precipitation. The aforementioned analyses necessitated the development of a method for downscaling of long-term monthly precipitation data to the relatively short timescales necessary for running the model. The method merges the long-term data with a reference dataset of 1-yr duration, having high temporal resolution. The success of the method, for the model and data considered here, was demonstrated in a series of model-model comparisons and in the comparisons of modeled and observed interannual variations of basin discharge.

Precipitates studies in ultrafine-grained Al alloys with enhanced strength and conductivity

NASA Astrophysics Data System (ADS)

Sitdikov, V. D.; Murashkin, M. Yu.; Valiev, R. Z.

2017-05-01

The paper analyzes precipitation of nanosized particles in dynamically aged Al-Mg-Si alloy subjected to high pressure torsion in the temperature range from 25°C to 230°C. Precipitate types are identified and quantified within the frames of the modified X-ray phase analysis (XPA) technique. The generality and difference in the mechanisms and kinetics of precipitation during artificial and dynamic strain aging are analyzed, which opens new ways to further increase properties in promising aluminum conductors.

Diagnostic Analysis of Second Strengthen Heavy Rain in Western Guangdong for NO.1011 Typhoon Fanapi

NASA Astrophysics Data System (ADS)

Liu, L.

2013-12-01

In order to learn more about the development mechanism of the rainstorm which is caused by No.1101 super typhoon "Fanapi", this paper use weather diagnostic methods to study two processes of heavy rain after "Fanapi" landed in the western part of Guangdong by applying Ncep1 ° × 1 ° reanalysis data and observed precipitation data. Through the preliminary analysis of this typhoon rainstorm, the result shows that cold air and water vapor transmission mainly cause the second strengthen precipitation ,the isoline slope of pseudoequivalent potential temperature reflect the second strengthen precipitation ,the upper troposphere high potential vorticity pass down and the cold dry air in the upper atomosphere confronts with the warm moist air in the lower atmosphere so that the precipitation increase.

Cadmium, copper, lead, and zinc determination in precipitation: A comparison of inductively coupled plasma atomic emission spectrometry and graphite furnace atomization atomic absorption spectrometry

USGS Publications Warehouse

Reddy, M.M.; Benefiel, M.A.; Claassen, H.C.

1987-01-01

Selected trace element analysis for cadmium, copper, lead, and zinc in precipitation samples by inductively coupled plasma atomic emission Spectrometry (ICP) and by atomic absorption spectrometry with graphite furnace atomization (AAGF) have been evaluated. This task was conducted in conjunction with a longterm study of precipitation chemistry at high altitude sites located in remote areas of the southwestern United States. Coefficients of variation and recovery values were determined for a standard reference water sample for all metals examined for both techniques. At concentration levels less than 10 micrograms per liter AAGF analyses exhibited better precision and accuracy than ICP. Both methods appear to offer the potential for cost-effective analysis of trace metal ions in precipitation. ?? 1987 Springer-Verlag.

Spatial Intensity Duration Frequency Relationships Using Hierarchical Bayesian Analysis for Urban Areas

NASA Astrophysics Data System (ADS)

Rupa, Chandra; Mujumdar, Pradeep

2016-04-01

In urban areas, quantification of extreme precipitation is important in the design of storm water drains and other infrastructure. Intensity Duration Frequency (IDF) relationships are generally used to obtain design return level for a given duration and return period. Due to lack of availability of extreme precipitation data for sufficiently large number of years, estimating the probability of extreme events is difficult. Typically, a single station data is used to obtain the design return levels for various durations and return periods, which are used in the design of urban infrastructure for the entire city. In an urban setting, the spatial variation of precipitation can be high; the precipitation amounts and patterns often vary within short distances of less than 5 km. Therefore it is crucial to study the uncertainties in the spatial variation of return levels for various durations. In this work, the extreme precipitation is modeled spatially using the Bayesian hierarchical analysis and the spatial variation of return levels is studied. The analysis is carried out with Block Maxima approach for defining the extreme precipitation, using Generalized Extreme Value (GEV) distribution for Bangalore city, Karnataka state, India. Daily data for nineteen stations in and around Bangalore city is considered in the study. The analysis is carried out for summer maxima (March - May), monsoon maxima (June - September) and the annual maxima rainfall. In the hierarchical analysis, the statistical model is specified in three layers. The data layer models the block maxima, pooling the extreme precipitation from all the stations. In the process layer, the latent spatial process characterized by geographical and climatological covariates (lat-lon, elevation, mean temperature etc.) which drives the extreme precipitation is modeled and in the prior level, the prior distributions that govern the latent process are modeled. Markov Chain Monte Carlo (MCMC) algorithm (Metropolis Hastings algorithm within a Gibbs sampler) is used to obtain the samples of parameters from the posterior distribution of parameters. The spatial maps of return levels for specified return periods, along with the associated uncertainties, are obtained for the summer, monsoon and annual maxima rainfall. Considering various covariates, the best fit model is selected using Deviance Information Criteria. It is observed that the geographical covariates outweigh the climatological covariates for the monsoon maxima rainfall (latitude and longitude). The best covariates for summer maxima and annual maxima rainfall are mean summer precipitation and mean monsoon precipitation respectively, including elevation for both the cases. The scale invariance theory, which states that statistical properties of a process observed at various scales are governed by the same relationship, is used to disaggregate the daily rainfall to hourly scales. The spatial maps of the scale are obtained for the study area. The spatial maps of IDF relationships thus generated are useful in storm water designs, adequacy analysis and identifying the vulnerable flooding areas.

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

NASA Astrophysics Data System (ADS)

Liu, Meixian; Xu, Xianli; Sun, Alex

2015-07-01

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Spatial distribution of the daily precipitation concentration index in Southern Russia

NASA Astrophysics Data System (ADS)

Vyshkvarkova, Elena; Voskresenskaya, Elena; Martin-Vide, Javier

2018-05-01

The territory of Southern Russia presents a great diversity of climates and complex orography that lead to a very different precipitation distribution. Annual precipitation amounts differ between 222 mm in the coast of the Caspian Sea and > 2000 mm in the highest parts of the Caucasus Mountains. In order to investigate the statistical structure of daily precipitation across the study region the daily precipitation Concentration Index (CI) was used. In present paper, the CI was calculated for 42 meteorological stations during the 1970-2010 period. The analysis of precipitation concentration identified that the distribution of daily precipitation is more regular over the west, north and south regions compared to the east (the Caspian Sea coast and the Caspian Depression). The Crimean peninsula is characterized by low CI values in the north and high values in the eastern part.

A teleconnection between subtropical convection and higher latitude wave activity in the Atlantic

NASA Astrophysics Data System (ADS)

Cruz, Antonio DeJesus

Rossby waves are waves in potential vorticity that propagate along the extratropical tropopause and can be impacted by the advection of low-PV air originating from the subtropics. In this study, the subtropical precipitation influence on the extratropical Rossby wave activity during the Atlantic winter season is investigated for a ten year period. Using both TRMM and TIGGE 12-Hr forecasted precipitation data, heavy precipitation events were identified near the footprints regions of warm conveyor belts in the northern Atlantic, specifically in the Gulf of Mexico and Bermuda region. The extratropical Rossby waves were then analyzed using PV on a 320K surface. By use of wavelet transforms, the amplitude of the Rossby waves were analyzed as a function of wavelength and longitude. The interaction between a single heavy precipitation event and the extratropical Rossby waves was examined for the days preceding and the week following the event. A climatological analysis of heavy precipitation events was conducted on the winter seasons from 2006 - 2015. Case study and climatological analysis identified the following: A ridge in the Northern Atlantic undergoes amplification downstream of the heavy precipitation event in the days following the event. A southerly flow, likely associated with a warm conveyor belt, connects the region of the heavy precipitation event and the extratropical tropopause. The interaction was most prominent during the late winter season and during the heaviest of precipitation events. The teleconnection identified in this study highlights a mechanism by which cloud-scale subtropical precipitation is connected to synoptic scale extratropical dynamics in the Atlantic.

Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin, Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Peng; Xia, Jun; Zhang, Yongyong; Han, Jian; Wu, Xia

2017-11-01

Because drought is a very common and widespread natural disaster, it has attracted a great deal of academic interest. Based on 12-month time scale standardized precipitation indices (SPI12) calculated from precipitation data recorded between 1960 and 2015 at 22 weather stations in the Tarim River Basin (TRB), this study aims to identify the trends of SPI and drought duration, severity, and frequency at various quantiles and to perform cluster analysis of drought events in the TRB. The results indicated that (1) both precipitation and temperature at most stations in the TRB exhibited significant positive trends during 1960-2015; (2) multiple scales of SPIs changed significantly around 1986; (3) based on quantile regression analysis of temporal drought changes, the positive SPI slopes indicated less severe and less frequent droughts at lower quantiles, but clear variation was detected in the drought frequency; and (4) significantly different trends were found in drought frequency probably between severe droughts and drought frequency.

Ca removal and Mg recovery from flue gas desulfurization (FGD) wastewater by selective precipitation.

PubMed

Xia, Min; Ye, Chunsong; Pi, Kewu; Liu, Defu; Gerson, Andrea R

2017-11-01

Selective removal of Ca and recovery of Mg by precipitation from flue gas desulfurization (FGD) wastewater has been investigated. Thermodynamic analysis of four possible additives, Na 2 CO 3 , Na 2 C 2 O 4 , NaF and Na 2 SO 4 , indicated that both carbonate and oxalate could potentially provide effective separation of Ca via precipitation from Mg in FGD wastewater. However, it was found experimentally that the carbonate system was not as effective as oxalate in this regard. The oxalate system performed considerably better, with Ca removal efficiency of 96% being obtained, with little Mg inclusion at pH 6.0 when the dosage was ×1.4 the stoichiometric requirement. On this basis, the subsequent recovery process for Mg was carried out using NaOH with two-step precipitation. The product was confirmed to be Mg(OH) 2 (using X-ray diffraction and thermo gravimetric analysis) with elemental analysis suggesting a purity of 99.3 wt.%.

Bias-correction of PERSIANN-CDR Extreme Precipitation Estimates Over the United States

NASA Astrophysics Data System (ADS)

Faridzad, M.; Yang, T.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Ground-based precipitation measurements can be sparse or even nonexistent over remote regions which make it difficult for extreme event analysis. PERSIANN-CDR (CDR), with 30+ years of daily rainfall information, provides an opportunity to study precipitation for regions where ground measurements are limited. In this study, the use of CDR annual extreme precipitation for frequency analysis of extreme events over limited/ungauged basins is explored. The adjustment of CDR is implemented in two steps: (1) Calculated CDR bias correction factor at limited gauge locations based on the linear regression analysis of gauge and CDR annual maxima precipitation; and (2) Extend the bias correction factor to the locations where gauges are not available. The correction factors are estimated at gauge sites over various catchments, elevation zones, and climate regions and the results were generalized to ungauged sites based on regional and climatic similarity. Case studies were conducted on 20 basins with diverse climate and altitudes in the Eastern and Western US. Cross-validation reveals that the bias correction factors estimated on limited calibration data can be extended to regions with similar characteristics. The adjusted CDR estimates also outperform gauge interpolation on validation sites consistently. It is suggested that the CDR with bias adjustment has a potential for study frequency analysis of extreme events, especially for regions with limited gauge observations.

Exploring Historical Coffee and Climate Relations in Southern Guatemala: An Integration of Tree Ring Analysis and Remote Sensing Data =

NASA Astrophysics Data System (ADS)

Pons, Diego

This dissertation makes use of a physical geography perspective to examine the relationship between agriculture and climate in Guatemala using dendrochronology. I examined the potential of high-resolution climate proxy data from dendrochronology to help fill in the gaps of past climate information to better understand the natural and anthropogenic variability of precipitation which, in turn, can inform Guatemala's agriculture sector. This research has demonstrated successful cross-dating and climate sensitivity of Abies guatemalensis in the Pacific slope of Guatemala. Based on this, I have produced a 124-year record of mean precipitation from June-July-August. The mean precipitation from June-July-August at this site seems to receive an important influence from the sea surface temperature (SST) in the Pacific Ocean in the form of El Nino-Southern Oscillation (ENSO) in the region 3.4. The analysis on the frequency of the precipitation records suggests that single year droughts dominate the record yet, periods of 9 years below-average rainfall can persist. Likewise, single year pluvial events also dominate the evaluated period. The long-term reconstruction of precipitation allowed to describe past relationships between coffee plantations and pests. For instance, the frequency analysis suggests that 4 or more consecutive periods of above-average precipitation are associated with several coffee pests and subsequently great economical losses due to crop failures, including the last coffee leaf rust crisis. This study also presents a streamflow reconstruction of the Upper Samala River watershed using a tree ring-width chronology derived from the Guatemalan fir (Abies guatemalensis) to reconstruct mean August-September-October streamflow volumes for the period 1889-2013. Our analysis shows that strong statistical correlations are present between tree-ring width measurements and monthly natural streamflow series. The mean August-September-October streamflow variability is dominated by single year events for both above and below the long-term mean. This reconstruction reveals important teleconnections with the ENSO 3.4 region and it is to our knowledge, the only streamflow reconstruction in Guatemala using tree-ring measurements. This new long-term record will be useful to recalculate historical discharge peaks and floods that affect agricultural areas in the mid and lower basin but also the hydroelectric production. Our analysis suggests that records from the GIMMS 3g v.0 Normalized Difference Vegetation Index (NDVI), are inversely correlated to precipitation in the Upper Samala River watershed at the location of the A. guatemalensis forest stand Kanchej. This suggest that the net solar radiation income during the cloud-free timing throughout the mid-summer drought could be partially responsible for promoting cloudiness by heating the SST and hence, promoting precipitation during the second peak of precipitation during September and October. The independent analyses of precipitation and NDVI sensitivity of A. guatemalensis and the correlation between precipitation and NDVI suggest that precipitation is a modulator of radial growth of A. guatemalensis in this location of Guatemala. These findings can be used to refine the knowledge on the climatic controls on A. guatemalensis radial growth.

Spatio-temporal characteristics of the extreme precipitation by L-moment-based index-flood method in the Yangtze River Delta region, China

NASA Astrophysics Data System (ADS)

Yin, Yixing; Chen, Haishan; Xu, Chong-Yu; Xu, Wucheng; Chen, Changchun; Sun, Shanlei

2016-05-01

The regionalization methods, which "trade space for time" by pooling information from different locations in the frequency analysis, are efficient tools to enhance the reliability of extreme quantile estimates. This paper aims at improving the understanding of the regional frequency of extreme precipitation by using regionalization methods, and providing scientific background and practical assistance in formulating the regional development strategies for water resources management in one of the most developed and flood-prone regions in China, the Yangtze River Delta (YRD) region. To achieve the main goals, L-moment-based index-flood (LMIF) method, one of the most popular regionalization methods, is used in the regional frequency analysis of extreme precipitation with special attention paid to inter-site dependence and its influence on the accuracy of quantile estimates, which has not been considered by most of the studies using LMIF method. Extensive data screening of stationarity, serial dependence, and inter-site dependence was carried out first. The entire YRD region was then categorized into four homogeneous regions through cluster analysis and homogenous analysis. Based on goodness-of-fit statistic and L-moment ratio diagrams, generalized extreme-value (GEV) and generalized normal (GNO) distributions were identified as the best fitted distributions for most of the sub-regions, and estimated quantiles for each region were obtained. Monte Carlo simulation was used to evaluate the accuracy of the quantile estimates taking inter-site dependence into consideration. The results showed that the root-mean-square errors (RMSEs) were bigger and the 90 % error bounds were wider with inter-site dependence than those without inter-site dependence for both the regional growth curve and quantile curve. The spatial patterns of extreme precipitation with a return period of 100 years were finally obtained which indicated that there are two regions with highest precipitation extremes and a large region with low precipitation extremes. However, the regions with low precipitation extremes are the most developed and densely populated regions of the country, and floods will cause great loss of human life and property damage due to the high vulnerability. The study methods and procedure demonstrated in this paper will provide useful reference for frequency analysis of precipitation extremes in large regions, and the findings of the paper will be beneficial in flood control and management in the study area.

Multiresolution comparison of precipitation datasets for large-scale models

NASA Astrophysics Data System (ADS)

Chun, K. P.; Sapriza Azuri, G.; Davison, B.; DeBeer, C. M.; Wheater, H. S.

2014-12-01

Gridded precipitation datasets are crucial for driving large-scale models which are related to weather forecast and climate research. However, the quality of precipitation products is usually validated individually. Comparisons between gridded precipitation products along with ground observations provide another avenue for investigating how the precipitation uncertainty would affect the performance of large-scale models. In this study, using data from a set of precipitation gauges over British Columbia and Alberta, we evaluate several widely used North America gridded products including the Canadian Gridded Precipitation Anomalies (CANGRD), the National Center for Environmental Prediction (NCEP) reanalysis, the Water and Global Change (WATCH) project, the thin plate spline smoothing algorithms (ANUSPLIN) and Canadian Precipitation Analysis (CaPA). Based on verification criteria for various temporal and spatial scales, results provide an assessment of possible applications for various precipitation datasets. For long-term climate variation studies (~100 years), CANGRD, NCEP, WATCH and ANUSPLIN have different comparative advantages in terms of their resolution and accuracy. For synoptic and mesoscale precipitation patterns, CaPA provides appealing performance of spatial coherence. In addition to the products comparison, various downscaling methods are also surveyed to explore new verification and bias-reduction methods for improving gridded precipitation outputs for large-scale models.

The Precipitation Characteristics of ISCCP Tropical Weather States

NASA Technical Reports Server (NTRS)

Lee, Dongmin; Oreopoulos, Lazaros; Huffman, George J.; Rossow, William B.; Kang, In-Sik

2011-01-01

We examine the daytime precipitation characteristics of the International Satellite Cloud Climatology Project (ISCCP) weather states in the extended tropics (35 deg S to 35 deg N) for a 10-year period. Our main precipitation data set is the TRMM Multisatellite Precipitation Analysis 3B42 data set, but Global Precipitation Climatology Project daily data are also used for comparison. We find that the most convective weather state (WS1), despite an occurrence frequency below 10%, is the most dominant state with regard to surface precipitation, producing both the largest mean precipitation rates when present and the largest percent contribution to the total precipitation of the tropical zone of our study; yet, even this weather state appears to not precipitate about half the time. WS1 exhibits a modest annual cycle of domain-average precipitation rate, but notable seasonal shifts in its geographic distribution. The precipitation rates of the other weather states tend to be stronger when occurring before or after WS1. The relative contribution of the various weather states to total precipitation is different between ocean and land, with WS1 producing more intense precipitation on average over ocean than land. The results of this study, in addition to advancing our understanding of the current state of tropical precipitation, can serve as a higher order diagnostic test on whether it is distributed realistically among different weather states in atmospheric models.

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.

Land surface-precipitation feedback and ramifications on storm dynamics.

NASA Astrophysics Data System (ADS)

Baisya, H.; PV, R.; Pattnaik, S.

2017-12-01

A series of numerical experiments are carried out to investigate the sensitivity of a landfalling monsoon depression to land surface conditions using the Weather Research and Forecasting (WRF) model. Results suggest that precipitation is largely modulated by moisture influx and precipitation efficiency. Three cloud microphysical schemes (WSM6, WDM6, and Morrison) are examined, and Morrison is chosen for assessing the land surface-precipitation feedback analysis, owing to better precipitation forecast skills. It is found that increased soil moisture facilitates Moisture Flux Convergence (MFC) with reduced moisture influx, whereas a reduced soil moisture condition facilitates moisture influx but not MFC. A higher Moist Static Energy (MSE) is noted due to increased evapotranspiration in an elevated moisture scenario which enhances moist convection. As opposed to moist surface, sensible heat dominates in a reduced moisture scenario, ensued by an overall reduction in MSE throughout the Planetary Boundary Layer (PBL). Stability analysis shows that Convective Available Potential Energy (CAPE) is comparable in magnitude for both increased and decreased moisture scenarios, whereas Convective Inhibition (CIN) shows increased values for the reduced moisture scenario as a consequence of drier atmosphere leading to suppression of convection. Simulations carried out with various fixed soil moisture levels indicate that the overall precipitation features of the storm are characterized by initial soil moisture condition, but precipitation intensity at any instant is modulated by soil moisture availability. Overall results based on this case study suggest that antecedent soil moisture plays a crucial role in modulating precipitation distribution and intensity of a monsoon depression.

Quantitative measurement for the microstructural parameters of nano-precipitates in Al-Mg-Si-Cu alloys

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

Li, Kai

Size, number density and volume fraction of nano-precipitates are important microstructural parameters controlling the strengthening of materials. In this work a widely accessible, convenient, moderately time efficient method with acceptable accuracy and precision has been provided for measurement of volume fraction of nano-precipitates in crystalline materials. The method is based on the traditional but highly accurate technique of measuring foil thickness via convergent beam electron diffraction. A new equation is proposed and verified with the aid of 3-dimensional atom probe (3DAP) analysis, to compensate for the additional error resulted from the hardly distinguishable contrast of too short incomplete precipitates cutmore » by the foil surface. The method can be performed on a regular foil specimen with a modern LaB{sub 6} or field-emission-gun transmission electron microscope. Precisions around ± 16% have been obtained for precipitate volume fractions of needle-like β″/C and Q precipitates in an aged Al-Mg-Si-Cu alloy. The measured number density is close to that directly obtained using 3DAP analysis by a misfit of 4.5%, and the estimated precision for number density measurement is about ± 11%. The limitations of the method are also discussed. - Highlights: •A facile method for measuring volume fraction of nano-precipitates based on CBED •An equation to compensate for small invisible precipitates, with 3DAP verification •Precisions around ± 16% for volume fraction and ± 11% for number density.« less

Analysis of precipitation data in Bangladesh through hierarchical clustering and multidimensional scaling

NASA Astrophysics Data System (ADS)

Rahman, Md. Habibur; Matin, M. A.; Salma, Umma

2017-12-01

The precipitation patterns of seventeen locations in Bangladesh from 1961 to 2014 were studied using a cluster analysis and metric multidimensional scaling. In doing so, the current research applies four major hierarchical clustering methods to precipitation in conjunction with different dissimilarity measures and metric multidimensional scaling. A variety of clustering algorithms were used to provide multiple clustering dendrograms for a mixture of distance measures. The dendrogram of pre-monsoon rainfall for the seventeen locations formed five clusters. The pre-monsoon precipitation data for the areas of Srimangal and Sylhet were located in two clusters across the combination of five dissimilarity measures and four hierarchical clustering algorithms. The single linkage algorithm with Euclidian and Manhattan distances, the average linkage algorithm with the Minkowski distance, and Ward's linkage algorithm provided similar results with regard to monsoon precipitation. The results of the post-monsoon and winter precipitation data are shown in different types of dendrograms with disparate combinations of sub-clusters. The schematic geometrical representations of the precipitation data using metric multidimensional scaling showed that the post-monsoon rainfall of Cox's Bazar was located far from those of the other locations. The results of a box-and-whisker plot, different clustering techniques, and metric multidimensional scaling indicated that the precipitation behaviour of Srimangal and Sylhet during the pre-monsoon season, Cox's Bazar and Sylhet during the monsoon season, Maijdi Court and Cox's Bazar during the post-monsoon season, and Cox's Bazar and Khulna during the winter differed from those at other locations in Bangladesh.

Productivity responses of desert vegetation to precipitation patterns across a rainfall gradient.

PubMed

Li, Fang; Zhao, Wenzhi; Liu, Hu

2015-03-01

The influences of previous-year precipitation and episodic rainfall events on dryland plants and communities are poorly quantified in the temperate desert region of Northwest China. To evaluate the thresholds and lags in the response of aboveground net primary productivity (ANPP) to variability in rainfall pulses and seasonal precipitation along the precipitation-productivity gradient in three desert ecosystems with different precipitation regimes, we collected precipitation data from 2000 to 2012 in Shandan (SD), Linze (LZ) and Jiuquan (JQ) in northwestern China. Further, we extracted the corresponding MODIS Normalized Difference Vegetation Index (NDVI, a proxy for ANPP) datasets at 250 m spatial resolution. We then evaluated different desert ecosystems responses using statistical analysis, and a threshold-delay model (TDM). TDM is an integrative framework for analysis of plant growth, precipitation thresholds, and plant functional type strategies that capture the nonlinear nature of plant responses to rainfall pulses. Our results showed that: (1) the growing season NDVIINT (INT stands for time-integrated) was largely correlated with the warm season (spring/summer) at our mildly-arid desert ecosystem (SD). The arid ecosystem (LZ) exhibited a different response, and the growing season NDVIINT depended highly on the previous year's fall/winter precipitation and ANPP. At the extremely arid site (JQ), the variability of growing season NDVIINT was equally correlated with the cool- and warm-season precipitation; (2) some parameters of threshold-delay differed among the three sites: while the response of NDVI to rainfall pulses began at about 5 mm for all the sites, the maximum thresholds in SD, LZ, and JQ were about 55, 35 and 30 mm respectively, increasing with an increase in mean annual precipitation. By and large, more previous year's fall/winter precipitation, and large rainfall events, significantly enhanced the growth of desert vegetation, and desert ecosystems should be much more adaptive under likely future scenarios of increasing fall/winter precipitation and large rainfall events. These results highlight the inherent complexity in predicting how desert ecosystems will respond to future fluctuations in precipitation.

The effect of acid precipitation on tree growth in eastern North America

Treesearch

Charles V. Cogbill

1976-01-01

Detailed study of the history of forest tree growth by tree-ring analysis is used to assess the effect of acid precipitation. The pattern and historical trends of acid precipitation deposition are compared with growth trends from mature forest stands in New Hampshire and Tennessee. No clear indication of a regional, synchronized decrease in tree growth was found. The...

Precipitation trends in the Canary Islands

NASA Astrophysics Data System (ADS)

García-Herrera, Ricardo; Gallego, David; Hernández, Emiliano; Gimeno, Luis; Ribera, Pedro; Calvo, Natalia

2003-02-01

A strong decreasing trend in the Canary Islands' precipitation is detected by studying daily rainfall time series for the second half of the 20th century. An analysis of the extreme events shows that this trend is due mainly to a decrease in the upper percentiles of the precipitation distribution. The results suggest that local factors play a fundamental role on extreme event behaviour.

Developing a regional retrospective ensemble precipitation dataset for watershed hydrology modeling, Idaho, USA

NASA Astrophysics Data System (ADS)

Flores, A. N.; Smith, K.; LaPorte, P.

2011-12-01

Applications like flood forecasting, military trafficability assessment, and slope stability analysis necessitate the use of models capable of resolving hydrologic states and fluxes at spatial scales of hillslopes (e.g., 10s to 100s m). These models typically require precipitation forcings at spatial scales of kilometers or better and time intervals of hours. Yet in especially rugged terrain that typifies much of the Western US and throughout much of the developing world, precipitation data at these spatiotemporal resolutions is difficult to come by. Ground-based weather radars have significant problems in high-relief settings and are sparsely located, leaving significant gaps in coverage and high uncertainties. Precipitation gages provide accurate data at points but are very sparsely located and their placement is often not representative, yielding significant coverage gaps in a spatial and physiographic sense. Numerical weather prediction efforts have made precipitation data, including critically important information on precipitation phase, available globally and in near real-time. However, these datasets present watershed modelers with two problems: (1) spatial scales of many of these datasets are tens of kilometers or coarser, (2) numerical weather models used to generate these datasets include a land surface parameterization that in some circumstances can significantly affect precipitation predictions. We report on the development of a regional precipitation dataset for Idaho that leverages: (1) a dataset derived from a numerical weather prediction model, (2) gages within Idaho that report hourly precipitation data, and (3) a long-term precipitation climatology dataset. Hourly precipitation estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA) are stochastically downscaled using a hybrid orographic and statistical model from their native resolution (1/2 x 2/3 degrees) to a resolution of approximately 1 km. Downscaled precipitation realizations are conditioned on hourly observations from reporting gages and then conditioned again on the Parameter-elevation Regressions on Independent Slopes Model (PRISM) at the monthly timescale to reflect orographic precipitation trends common to watersheds of the Western US. While this methodology potentially introduces cross-pollination of errors due to the re-use of precipitation gage data, it nevertheless achieves an ensemble-based precipitation estimate and appropriate measures of uncertainty at a spatiotemporal resolution appropriate for watershed modeling.

Tropical Atlantic-Korea teleconnection pattern during boreal summer season

NASA Astrophysics Data System (ADS)

Ham, Yoo-Geun; Chikamoto, Yoshimitsu; Kug, Jong-Seong; Kimoto, Masahide; Mochizuki, Takashi

2017-10-01

The remote impact of tropical Atlantic sea surface temperature (SST) variability on Korean summer precipitation is examined based on observational data analysis along with the idealized and hindcast model experiments. Observations show a significant correlation (i.e. 0.64) between Korean precipitation anomalies (averaged over 120-130°E, 35-40°N) and the tropical Atlantic SST index (averaged over 60°W-20°E, 30°S-30°N) during the June-July-August (JJA) season for the 1979-2010 period. Our observational analysis and partial-data assimilation experiments using the coupled general circulation model demonstrate that tropical Atlantic SST warming induces the equatorial low-level easterly over the western Pacific through a reorganization of the global Walker Circulation, causing a decreased precipitation over the off-equatorial western Pacific. As a Gill-type response to this diabatic forcing, an anomalous low-level anticyclonic circulation appears over the Philippine Sea, which transports wet air from the tropics to East Asia through low-level southerly, resulting an enhanced precipitation in the Korean peninsula. Multi-model hindcast experiments also show that predictive skills of Korean summer precipitation are improved by utilizing predictions of tropical Atlantic SST anomalies as a predictor for Korean precipitation anomalies.

Protein precipitation of diluted samples in SDS-containing buffer with acetone leads to higher protein recovery and reproducibility in comparison with TCA/acetone approach.

PubMed

Santa, Cátia; Anjo, Sandra I; Manadas, Bruno

2016-07-01

Proteomic approaches are extremely valuable in many fields of research, where mass spectrometry methods have gained an increasing interest, especially because of the ability to perform quantitative analysis. Nonetheless, sample preparation prior to mass spectrometry analysis is of the utmost importance. In this work, two protein precipitation approaches, widely used for cleaning and concentrating protein samples, were tested and compared in very diluted samples solubilized in a strong buffer (containing SDS). The amount of protein recovered after acetone and TCA/acetone precipitation was assessed, as well as the protein identification and relative quantification by SWATH-MS yields were compared with the results from the same sample without precipitation. From this study, it was possible to conclude that in the case of diluted samples in denaturing buffers, the use of cold acetone as precipitation protocol is more favourable than the use of TCA/acetone in terms of reproducibility in protein recovery and number of identified and quantified proteins. Furthermore, the reproducibility in relative quantification of the proteins is even higher in samples precipitated with acetone compared with the original sample. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improvements to the gridding of precipitation data across Europe under the E-OBS scheme

NASA Astrophysics Data System (ADS)

Cornes, Richard; van den Besselaar, Else; Jones, Phil; van der Schrier, Gerard; Verver, Ge

2016-04-01

Gridded precipitation data are a valuable resource for analyzing past variations and trends in the hydroclimate. Such data also provide a reference against which model simulations may be driven, compared and/or adjusted. The E-OBS precipitation dataset is widely used for such analyses across Europe, and is particularly valuable since it provides a spatially complete, daily field across the European domain. In this analysis, improvements to the E-OBS precipitation dataset will be presented that aim to provide a more reliable estimate of grid-box precipitation values, particularly in mountainous areas and in regions with a relative sparsity of input station data. The established three-stage E-OBS gridding scheme is retained, whereby monthly precipitation totals are gridded using a thin-plate spline; daily anomalies are gridded using indicator kriging; and the final dataset is produced by multiplying the two grids. The current analysis focuses on improving the monthly thin-plate spline, which has overall control on the final daily dataset. The results from different techniques are compared and the influence on the final daily data is assessed by comparing the data against gridded country-wide datasets produced by various National Meteorological Services

Preparation of polyethylene sacks for collection of precipitation samples for chemical analysis

USGS Publications Warehouse

Schroder, L.J.; Bricker, A.W.

1985-01-01

Polyethylene sacks are used to collect precipitation samples. Washing polyethylene with acetone, hexane, methanol, or nitric acid can change the adsorptive characteristics of the polyethylene. In this study, simulated precipitation at pH 4.5 was in contact with the polyethylene sacks for 21 days; subsamples were removed for chemical analysis at 7, 14, and 21 days after intitial contact. Sacks washed with acetone adsorbed iron and lithium; sacks washed with hexane adsorbed barium, iron , and lithium; sacks washed with methanol adsorbed calcium and iron; and sacks washed with 0.30 N nitric acid adsorbed iron. Leaching the plastic sacks with 0.15 N nitric acid did not result in 100-percent recovery of any of the adsorbed metals. Washing polyethylene sacks with dilute nitric acid caused the pH of the simulated precipitation to be decreased by 0.2 pH unit after 1 week of contact with the polyethylene. The specific conductance increased by 10 microsiemens per centimeter. Contamination of precipitation samples by lead was determined to be about 0.1 microgram per liter from contact with precleaned polyethylene sacks. No measurable contamination of precipitation samples by zinc occurred. (USGS)

Precipitation and floodiness: forecasts of flood hazard at the regional scale

NASA Astrophysics Data System (ADS)

Stephens, Liz; Day, Jonny; Pappenberger, Florian; Cloke, Hannah

2016-04-01

In 2008, a seasonal forecast of an increased likelihood of above-normal rainfall in West Africa led the Red Cross to take early humanitarian action (such as prepositioning of relief items) on the basis that this forecast implied heightened flood risk. However, there are a number of factors that lead to non-linearity between precipitation anomalies and flood hazard, so in this presentation we use a recently developed global-scale hydrological model driven by the ERA-Interim/Land precipitation reanalysis (1980-2010) to quantify this non-linearity. Using these data, we introduce the concept of floodiness to measure the incidence of floods over a large area, and quantify the link between monthly precipitation, river discharge and floodiness anomalies. Our analysis shows that floodiness is not well correlated with precipitation, demonstrating the problem of using seasonal precipitation forecasts as a proxy for forecasting flood hazard. This analysis demonstrates the value of developing hydrometeorological forecasts of floodiness for decision-makers. As a result, we are now working with the European Centre for Medium-Range Weather Forecasts and the Joint Research Centre, as partners of the operational Global Flood Awareness System (GloFAS), to implement floodiness forecasts in real-time.

Trends in precipitation and streamflow and changes in stream morphology in the Fountain Creek watershed, Colorado, 1939-99

USGS Publications Warehouse

Stogner, Sr., Robert W.

2000-01-01

The Fountain Creek watershed, located in and along the eastern slope of the Front Range section of the southern Rocky Mountains, drains approximately 930 square miles of parts of Teller, El Paso, and Pueblo Counties in eastern Colorado. Streamflow in the watershed is dominated by spring snowmelt runoff and storm runoff during the summer monsoon season. Flooding during the 1990?s has resulted in increased streambank erosion. Property loss and damage associated with flooding and bank erosion has cost area residents, businesses, utilities, municipalities, and State and Federal agencies millions of dollars. Precipitation (4 stations) and streamflow (6 stations) data, aerial photographs, and channel reconnaissance were used to evaluate trends in precipitation and streamflow and changes in channel morphology. Trends were evaluated for pre-1977, post-1976, and period-of-record time periods. Analysis revealed the lack of trend in total annual and seasonal precipitation during the pre-1977 time period. In general, the analysis also revealed the lack of trend in seasonal precipitation for all except the spring season during the post-1976 time period. Trend analysis revealed a significant upward trend in long-term (period of record) total annual and spring precipitation data, apparently due to a change in total annual precipitation throughout the Fountain Creek watershed. During the pre-1977 time period, precipitation was generally below average; during the post- 1976 time period, total annual precipitation was generally above average. During the post- 1976 time period, an upward trend in total annual and spring precipitation was indicated at two stations. Because two of four stations evaluated had upward trends for the post-1976 period and storms that produce the most precipitation are isolated convection storms, it is plausible that other parts of the watershed had upward precipitation trends that could affect trends in streamflow. Also, because of the isolated nature of convection storms that hit some areas of the watershed and not others, it is difficult to draw strong conclusions on relations between streamflow and precipitation. Trends in annual instantaneous peak streamflow, 70th percentile, 90th percentile, maximum daily-mean streamflow (100th percentile), 7-, 14-, and 30-day high daily-mean stream- flow duration, minimum daily-mean streamflow (0th percentile), 10th percentile, 30th percentile, and 7-, 14-, 30-day low daily-mean streamflow duration were evaluated. In general, instantaneous peak streamflow has not changed significantly at most of the stations evaluated. Trend analysis revealed the lack of a significant upward trend in streamflow at all stations for the pre-1977 time period. Trend tests indicated a significant upward trend in high and low daily-mean streamflow statistics for the post-1976 period. Upward trends in high daily-mean streamflow statistics may be an indication that changes in land use within the watershed have increased the rate and magnitude of runoff. Upward trends in low daily-mean 2 Trends in Precipitation and Streamflow and Changes in Stream Morphology in the Fountain Creek Watershed, Colorado, 1939-99 streamflow statistics may be related to changes in water use and management. An analysis of the relation between streamflow and precipitation indicated that changes in water management have had a marked effect on streamflow. Observable change in channel morphology and changes in distribution and density of vegetation varied with magnitude, duration, and frequency of large streamflow events, and increases in the magnitude and duration of low streamflows. Although more subtle, low stream- flows were an important component of day-to-day channel erosion. Substantial changes in channel morphology were most often associated with infrequent large or catastrophic streamflow events that erode streambed and banks, alter stream course, and deposit large amounts of sediment in the flood plain.

Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

NASA Technical Reports Server (NTRS)

Gottschalck, Jon; Meng, Jesse; Rodel, Matt; Houser, paul

2005-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly sensitive to precipitation, with differences in spring and summer as large as 45% depending on the choice of precipitation input.

Precipitation chemistry of Lhasa and other remote towns, Tibet

NASA Astrophysics Data System (ADS)

Zhang, David D.; Peart, Mervyn; Jim, C. Y.; He, Y. Q.; Li, B. S.; Chen, J. A.

Precipitation event samples during 1987-1988 field expedition periods and 1997, 1998, 1999 and 2000 have been collected at Lhasa, Dingri, Dangxiong and Amdo, Tibet. The sampling and analysis were based on WMO recommendations for a background network with some modifications according to local conditions and environmental characteristics. The following precipitation constituents and related parameters were measured: pH, conductivity, CO 2 partial pressure, total suspended particles, and the content of K +, Na +, Ca 2+, Mg 2+, Fe, Mn, NH 4+, Cl -, NO 2-, NO 3-, SO42- Br-, HCO 3- and HPO 42-. Some atmospheric dust samples have also been collected. Over 300 precipitation events have been measured for pH and conductivity. Among these, 60 have been analysed for their chemical components. The results show that Lhasa's precipitation events were constantly alkaline with weighted averages of pH 8.36 in the 1987-1988 period, and 7.5 for 1997 to 1999. Only one event was weakly acidic during 1997-1999. Although CO 2 partial pressure, a major producer of acidity in natural water on the Plateau, falls with increasing elevation, the lowest measured CO 2 partial pressure can only raise pH value by 0.1 units in the sampling areas. Chemical analysis indicates that the major contributor to alkaline precipitation is the continental dust, which is rich in calcium. The analysis also shows that Tibet is still one of the cleanest areas in the world with little air pollution. However, the decline of pH from the 1980s to 1990s, which was reflected by an increase of NO 3- and SO 42- in precipitation, alerts us to the urgency of environmental protection in this fragile paradise.

Long-term trend analysis on total and extreme precipitation over Shasta Dam watershed.

PubMed

Toride, Kinya; Cawthorne, Dylan L; Ishida, Kei; Kavvas, M Levent; Anderson, Michael L

2018-06-01

California's interconnected water system is one of the most advanced water management systems in the world, and understanding of long-term trends in atmospheric and hydrologic behavior has increasingly being seen as vital to its future well-being. Knowledge of such trends is hampered by the lack of long-period observation data and the uncertainty surrounding future projections of atmospheric models. This study examines historical precipitation trends over the Shasta Dam watershed (SDW), which lies upstream of one of the most important components of California's water system, Shasta Dam, using a dynamical downscaling methodology that can produce atmospheric data at fine time-space scales. The Weather Research and Forecasting (WRF) model is employed to reconstruct 159years of long-term hourly precipitation data at 3km spatial resolution over SDW using the 20th Century Reanalysis Version 2c dataset. Trend analysis on this data indicates a significant increase in total precipitation as well as a growing intensity of extreme events such as 1, 6, 12, 24, 48, and 72-hour storms over the period of 1851 to 2010. The turning point of the increasing trend and no significant trend periods is found to be 1940 for annual precipitation and the period of 1950 to 1960 for extreme precipitation using the sequential Mann-Kendall test. Based on these analysis, we find the trends at the regional scale do not necessarily apply to the watershed-scale. The sharp increase in the variability of annual precipitation since 1970s is also detected, which implies an increase in the occurrence of extreme wet and dry conditions. These results inform long-term planning decisions regarding the future of Shasta Dam and California's water system. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparison of Extreme Precipitation Return Levels using Spatial Bayesian Hierarchical Modeling versus Regional Frequency Analysis

NASA Astrophysics Data System (ADS)

Love, C. A.; Skahill, B. E.; AghaKouchak, A.; Karlovits, G. S.; England, J. F.; Duren, A. M.

2017-12-01

We compare gridded extreme precipitation return levels obtained using spatial Bayesian hierarchical modeling (BHM) with their respective counterparts from a traditional regional frequency analysis (RFA) using the same set of extreme precipitation data. Our study area is the 11,478 square mile Willamette River basin (WRB) located in northwestern Oregon, a major tributary of the Columbia River whose 187 miles long main stem, the Willamette River, flows northward between the Coastal and Cascade Ranges. The WRB contains approximately two ­thirds of Oregon's population and 20 of the 25 most populous cities in the state. The U.S. Army Corps of Engineers (USACE) Portland District operates thirteen dams and extreme precipitation estimates are required to support risk­ informed hydrologic analyses as part of the USACE Dam Safety Program. Our intent is to profile for the USACE an alternate methodology to an RFA that was developed in 2008 due to the lack of an official NOAA Atlas 14 update for the state of Oregon. We analyze 24-hour annual precipitation maxima data for the WRB utilizing the spatial BHM R package "spatial.gev.bma", which has been shown to be efficient in developing coherent maps of extreme precipitation by return level. Our BHM modeling analysis involved application of leave-one-out cross validation (LOO-CV), which not only supported model selection but also a comprehensive assessment of location specific model performance. The LOO-CV results will provide a basis for the BHM RFA comparison.

Changes to the temporal distribution of daily precipitation

NASA Astrophysics Data System (ADS)

Rajah, Kailash; O'Leary, Tess; Turner, Alice; Petrakis, Gabriella; Leonard, Michael; Westra, Seth

2014-12-01

Changes to the temporal distribution of daily precipitation were investigated using a data set of 12,513 land-based stations from the Global Historical Climatology Network. The distribution of precipitation was measured using the Gini index (which describes how uniformly precipitation is distributed throughout a year) and the annual number of wet days. The Mann-Kendall test and a regression analysis were used to assess the direction and rate of change to both indices. Over the period of 1976-2000, East Asia, Central America, and Brazil exhibited a decrease in the number of both wet and light precipitation days, and eastern Europe exhibited a decrease in the number of both wet and moderate precipitation days. In contrast, the U.S., southern South America, western Europe, and Australia exhibited an increase in the number of both wet and light precipitation days. Trends in both directions were field significant at the global scale.

The Signature of Southern Hemisphere Atmospheric Circulation Patterns in Antarctic Precipitation

PubMed Central

Thompson, David W. J.; van den Broeke, Michiel R.

2017-01-01

Abstract We provide the first comprehensive analysis of the relationships between large‐scale patterns of Southern Hemisphere climate variability and the detailed structure of Antarctic precipitation. We examine linkages between the high spatial resolution precipitation from a regional atmospheric model and four patterns of large‐scale Southern Hemisphere climate variability: the southern baroclinic annular mode, the southern annular mode, and the two Pacific‐South American teleconnection patterns. Variations in all four patterns influence the spatial configuration of precipitation over Antarctica, consistent with their signatures in high‐latitude meridional moisture fluxes. They impact not only the mean but also the incidence of extreme precipitation events. Current coupled‐climate models are able to reproduce all four patterns of atmospheric variability but struggle to correctly replicate their regional impacts on Antarctic climate. Thus, linking these patterns directly to Antarctic precipitation variability may allow a better estimate of future changes in precipitation than using model output alone. PMID:29398735

Estimating Global Precipitation for Science and Application

NASA Technical Reports Server (NTRS)

Huffman, George J.

2013-01-01

Over the past two decades there has been vigorous development in the satellite assets and the algorithms necessary to estimate precipitation around the globe. In particular the highly successful joint NASAJAXA Tropical Rainfall Measuring Mission (TRMM) and the upcoming Global Precipitation Measurement (GPM) mission, also joint between NASA and JAXA, have driven these issues. At the same time, the long-running Global Precipitation Climatology Project (GPCP) continues to extend a stable, climate-oriented view of global precipitation. This talk will provide an overview of these projects and the wider international community of precipitation datasets, sketch plans for next-generation products, and provide some examples of the best use for the different products. One key lesson learned is that different data sets are needed to address the variety of issues that need precipitation data, including detailed 3-D views of hurricanes, flash flood forecasting, drought analysis, and global change.

Precipitation Indices as a Tool for Climate-Resilient Development in the Peruvian Andes

NASA Astrophysics Data System (ADS)

Chisolm, R. E.; McKinney, D. C.

2016-12-01

The local people living in the mountains of the Ancash Department in Peru have noticed changes in their water supply as climate change has altered precipitation patterns. They are seeking adaptation solutions to help guarantee the reliability of their water supply, but there has been very little analysis of historical data to evaluate and justify these adaptation solutions. In addition, Peru's Ministry of Economy and Finance now requires that climate change be part of the vulnerability assessment for all public investment project proposals, but there are currently no tools or methods of data analysis for including climate change in vulnerability assessments. Compounding the difficulties of considering climate change in the sustainability of development projects is the scarcity of climate data in the region and the difficulty of accessing existing data. To counteract this problem, the Peruvian government recommends using local people's perceptions of change as a proxy for gauged climate data. This work focuses on precipitation data analysis in the mountains of Ancash, Peru. The objectives of this analysis were to determine the accuracy of the local population's perceptions of climate change and to investigate how changes in precipitation patterns might impact public investment projects. The precipitation data analysis was compared to a local study of perceptions of change to determine whether or not these perceptions might be used in lieu of gauged climate data. It appears that people's perceptions of precipitation trends do not accurately reflect the trends observed in the gauged data. The methods of analysis were designed so that the results may be useful for public investment projects with a particular emphasis on agricultural projects. The data were analyzed for trends, seasonal patterns and variability. Dry spells were examined, and the results indicate that droughts during the rainy season have become more frequent and of longer duration. This could have significant impact on agricultural projects. It is likely that the current practice of relying exclusively on wet season rainfall to meet crop water requirements may not be sustainable in the future. Further analysis of climate data is needed to generate a regional climatic characterization that can be used for climate-resilient development projects.

THRESH—Software for tracking rainfall thresholds for landslide and debris-flow occurrence, user manual

USGS Publications Warehouse

Baum, Rex L.; Fischer, Sarah J.; Vigil, Jacob C.

2018-02-28

Precipitation thresholds are used in many areas to provide early warning of precipitation-induced landslides and debris flows, and the software distribution THRESH is designed for automated tracking of precipitation, including precipitation forecasts, relative to thresholds for landslide occurrence. This software is also useful for analyzing multiyear precipitation records to compare timing of threshold exceedance with dates and times of historical landslides. This distribution includes the main program THRESH for comparing precipitation to several kinds of thresholds, two utility programs, and a small collection of Python and shell scripts to aid the automated collection and formatting of input data and the graphing and further analysis of output results. The software programs can be deployed on computing platforms that support Fortran 95, Python 2, and certain Unix commands. The software handles rainfall intensity-duration thresholds, cumulative recent-antecedent precipitation thresholds, and peak intensity thresholds as well as various measures of antecedent precipitation. Users should have predefined rainfall thresholds before running THRESH.

Precipitation behavior in austenitic and ferritic steels during fast neutron irradiation and thermal aging*1

NASA Astrophysics Data System (ADS)

Kawanishi, H.; Hajima, R.; Sekimura, N.; Arai, Y.; Ishino, S.

1988-07-01

Precipitation behavior has been studied using a carbon extraction replica technique in Ti-modified Type 316 stainless steels (JPCA-2) and 9Cr-2Mo ferritic/martensitic steels (JFMS) irradiated to 8.1 × 10 24 n/m 2 at 873 and 673 K, respectively, in the experimental fast breeder reactor JOYO. Precipitate identification and compositional analysis were carried out on extracted replicas. The results were compared to those from the as-received steel and a control which had been given the same thermal as-treatment as the specimens received during irradiations. Carbides, Ti-sulphides and phosphides were precipitated in JPCA-2. Precipitate observed in JFMS included carbides, Laves-phases and phosphides. The precipitates in both steels were concluded to be stable under irradiation except for MC and M 6C in JPCA-2. Small MC particles were found precipitated in JPCA-2 during both irradiation and aging. Irradiation proved to promote the precipitation of M 6C in JPCA-2.

Cost-Risk Trade-off of Solar Radiation Management and Mitigation under Long-Tailed Climate Sensitivity Probability Density Distributions

NASA Astrophysics Data System (ADS)

Roshan, E.; Mohammadi Khabbazan, M.; Held, H.

2016-12-01

Solar radiation management (SRM) might be able to reduce the anthropogenic global mean temperature rise but unable to do so for other climate variables such as precipitation, particularly with respect to regional disparities due to changes in planetary energy budget. We apply cost-risk analysis (CRA), which is a decision analytic framework that trades off the expected welfare-loss from climate policies costs against the climate risks from exceeding an environmental target. Here, in both global- and `Giorgi'-regional-scale analyses, we study the optimal mix of SRM and mitigation under probabilistic knowledge about climate sensitivity, in our numerics ranging from 1.01°C to 7.17°C. To do so, we generalize CRA for the sake of including temperature risk, global and regional precipitation risks. Social welfare is maximized in three scenarios, considering a convex combination of climate risks: temperature-risk-only, precipitation-risk-only, and equally weighted both-risks. Our global results represent 100%, 65%, and 90% compliance with 2°C-temperature target and simultaneously 0%, 100%, and 100% compliance with 2°C-compatible-precipitation corridor respectively in temperature-risk-only, precipitation-risk-only, and both-risks scenarios. On the other hand, our regional results emphasize that SRM would alleviate the global mean temperature to be complied with 2°C-temperature target for about 100%, 95%, and 95% of climate sensitivities in temperature-risk-only, precipitation-risk-only, and both-risks scenarios, respectively. However, half of the regions suffer a very high precipitation risks when the society only cares about global temperature reduction in temperature-risk-only scenario. Our results indicate that although SRM might almost substitute for mitigation in the global analysis, it only saves about a half of the welfare-loss in a purely mitigation-based analysis (from economic costs and climate risks, in terms of BGE) when considering regional precipitation risks.

Precipitation of molybdenum(V) as the hydroxide and its separation from rhenium.

PubMed

Yatirajam, V; Ahuja, U; Kakkar, L R

1975-03-01

A study of the conditions for precipitation of molybdenum(V) hydroxide shows that for Mo concentration 1 mg ml about 97.5% of the Mo can be precipitated between pH 5 and 5.8. Lower concentrations of molybdenum(V) or molybdenum(VI) can be precipitated quantitatively by using 20 times the amount of zirconium as collector, at the same pH. On this basis, a simple method is given for quantitative separation of rhenium from large amounts of molybdenum and is attested by analysis of synthetic and molybdenite samples.

Spring 1991 Meeting outstanding papers

NASA Astrophysics Data System (ADS)

The Atmospheric Sciences Committee has presented Kaye Brubaker and Jichun Shi with Outstanding Student Paper awards for presentations given at the AGU 1991 Spring Meeting, held in Baltimore May 28-31.Brubaker's paper, “Precipitation Recycling Estimated from Atmospheric Data,” presented quantitative estimates of the contribution of locallyevaporated moisture to precipitation over several large continental regions. Recycled precipitation is defined as water that evaporates from the land surface of a specified region and falls again as precipitation within the region. Brubaker applied a control volume analysis based on a model proposed by Budyko.

Precipitating Factors for Acute Heart Failure Hospitalization and Long-Term Survival

PubMed Central

Berkovitch, Anat; Maor, Elad; Sabbag, Avi; Chernomordik, Fernando; Elis, Avishay; Arbel, Yaron; Goldenberg, Ilan; Grossman, Ehud; Klempfner, Robert

2015-01-01

Abstract Heart failure (HF) patients have frequent exacerbations leading to high consumption of medical services and recurrent hospitalizations. Different precipitating factors have various effects on long-term survival. We investigated 2212 patients hospitalized with a diagnosis of either acute HF or acute exacerbation of chronic HF. Patients were divided into 2 primary precipitant groups: ischemic (N = 979 [46%]) and nonischemic (N = 1233 [54%]). The primary endpoint was all-cause mortality. Multivariate analysis demonstrated that the presence of a nonischemic precipitant was associated with a favorable in-hospital outcome (OR 0.64; CI 0.43–0.94), but with a significant increase in the risk of 10-year mortality (HR 1.12; CI 1.01–1.21). Consistently, the cumulative probability of 10-year mortality was significantly higher among patients with a nonischemic versus ischemic precipitant (83% vs 90%, respectively; Log-rank P value <0.001). Subgroup analysis showed that among the nonischemic precipitant, the presence of renal dysfunction and infection were both associated with poor short-term outcomes (OR 1.56, [P < 0.001] and OR 1.35 [P < 0.001], respectively), as well as long-term (HR 1.59 [P < 0.001] and HR 1.24 [P < 0.001], respectively). Identification of precipitating factors for acute HF hospitalization has important short- and long-term implications that can be used for improved risk stratification and management. PMID:26717369

The Sensitivity of Regional Precipitation to Global Temperature Change and Forcings

NASA Astrophysics Data System (ADS)

Tebaldi, C.; O'Neill, B. C.; Lamarque, J. F.

2016-12-01

Global policies are most commonly formulated in terms of climate targets, like the much talked about 1.5° and 2°C warming thresholds identified as critical by the recent Paris agreements. But what does a target defined in terms of a globally averaged quantity mean in terms of expected regional changes? And, in particular, what should we expect in terms of significant changes in precipitation over specific regional domains for these and other incrementally different global goals? In this talk I will summarize the result of an analysis that aimed at characterizing the sensitivity of regional temperatures and precipitation amounts to changes in global average temperature. The analysis uses results from a multi-model ensemble (CMIP5), which allows us to address structural uncertainty in future projections, a type of uncertainty particularly relevant when considering precipitation changes. I will show what type of changes in global temperature and forcing levels bring about significant and pervasive changes in regional precipitation, contrasting its sensitivity to that of regional temperature changes. Because of the large internal variability of regional precipitation, I will show that significant changes in average regional precipitation can be detected only for fairly large separations (on the order of 2.5° or 3°C) in global average temperature levels, differently from the much higher sensitivity shown by regional temperatures.

Impacts of half a degree additional warming on the Asian summer monsoon rainfall characteristics

NASA Astrophysics Data System (ADS)

Lee, Donghyun; Min, Seung-Ki; Fischer, Erich; Shiogama, Hideo; Bethke, Ingo; Lierhammer, Ludwig; Scinocca, John F.

2018-04-01

This study investigates the impacts of global warming of 1.5 °C and 2.0 °C above pre-industrial conditions (Paris Agreement target temperatures) on the South Asian and East Asian monsoon rainfall using five atmospheric global climate models participating in the ‘Half a degree Additional warming, Prognosis and Projected Impacts’ (HAPPI) project. Mean and extreme precipitation is projected to increase under warming over the two monsoon regions, more strongly in the 2.0 °C warmer world. Moisture budget analysis shows that increases in evaporation and atmospheric moisture lead to the additional increases in mean precipitation with good inter-model agreement. Analysis of daily precipitation characteristics reveals that more-extreme precipitation will have larger increase in intensity and frequency responding to the half a degree additional warming, which is more clearly seen over the South Asian monsoon region, indicating non-linear scaling of precipitation extremes with temperature. Strong inter-model relationship between temperature and precipitation intensity further demonstrates that the increased moisture with warming (Clausius-Clapeyron relation) plays a critical role in the stronger intensification of more-extreme rainfall with warming. Results from CMIP5 coupled global climate models under a transient warming scenario confirm that half a degree additional warming would bring more frequent and stronger heavy precipitation events, exerting devastating impacts on the human and natural system over the Asian monsoon region.

Determination of fluorine concentrations using wavelength dispersive X-ray fluorescence (WDXRF) spectrometry to analyze fluoride precipitates.

NASA Astrophysics Data System (ADS)

Lee, H. A.; Lee, J.; Kwon, E.; Kim, D.; Yoon, H. O.

2015-12-01

In recent times, fluorine has been receiving increasing attention due to the possibility for chemical (HF) leakage accidents and its high toxicity to human and environment. In this respect, a novel approach for the determination of fluorine concentrations in water samples using wavelength dispersive X-ray fluorescence (WDXRF) spectrometry was investigated in this study. The main disadvantage of WDXRF technique for fluorine analysis is low analytical sensitivity for light elements with atomic number (Z) less than 15. To overcome this problem, we employed the precipitation reaction which fluoride is reacted with cation such as Al3+ and/or Ca2+ prior to WDXRF analysis because of their high analytical sensitivity. The cation was added in fluoride solutions to form precipitate (AlF3 and/or CaF2) and then the solution was filtered through Whatman filter. After drying at 60 °C for 5 min, the filter was coated with X-ray film and directly analyzed using WDXRF spectrometry. Consequently, we analyzed the cation on filter and subsequently fluorine concentration was calculated inversely based on chemical form of precipitate. This method can improve the analytical sensitivity of WDXRF technique for fluorine analysis and be applicable to various elements that can make precipitate.

Correlation between total precipitable water and precipitation over East Asia

NASA Astrophysics Data System (ADS)

Keum, Wangho; Lim, Gyu-Ho

2017-04-01

The precipitation rate(PR) and the total precipitable water(TPW) interact with various physical mechanisms. The correlation of two variables changes with difference of domain resolution and characteristics of the region. This poster analyzes the correlation between PR and TPW over East Asia using Cyclostationary Empirical Orthogonal Function(CSEOF) which is one of the PCA analysis. The CSEOF is useful to search a periodic pattern of the data. The anomalies which is subtracted climatological mean from the original data are used to represent annual cycles. Two variances of ERA-Interim Monthly Total Column Water vapor and GPCP monthly precipitation amounts with 372 time since January, 1984 to December, 2014 are decomposed into several modes separately. The first mode which explain largest variance are used in analysis. PC of both PR and TPW increase recently on mean value and amplitude, and they show considerable correlation on phase. The correlation coefficient of PR and TPW is 0.61 and maintains the same values by month. The result of harmonic analysis shows 2 to 6 year oscillations. As result of decomposed modes of two variables, there is the relationship between TPW PC series and horizontal moisture gradient. The Horizontal moist gradient can change affect moisture flux convergence which is one of important variable of rainfall events.

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.

Thermodynamic and dynamic contributions to future changes in summer precipitation over Northeast Asia and Korea: a multi-RCM study

NASA Astrophysics Data System (ADS)

Lee, Donghyun; Min, Seung-Ki; Jin, Jonghun; Lee, Ji-Woo; Cha, Dong-Hyun; Suh, Myoung-Seok; Ahn, Joong-Bae; Hong, Song-You; Kang, Hyun-Suk; Joh, Minsu

2017-12-01

This study examines future changes in precipitation over Northeast Asia and Korea using five regional climate model (RCM) simulations driven by single global climate model (GCM) under two representative concentration pathway (RCP) emission scenarios. Focusing on summer season (June-July-August) when heavy rains dominate in this region, future changes in precipitation and associated variables including temperature, moisture, and winds are analyzed by comparing future conditions (2071-2100) with a present climate (1981-2005). Physical mechanisms are examined by analyzing moisture flux convergence at 850 hPa level, which is found to have a close relationship to precipitation and by assessing contribution of thermodynamic effect (TH, moisture increase due to warming) and dynamic effect (DY, atmospheric circulation change) to changes in the moisture flux convergence. Overall background warming and moistening are projected over the Northeast Asia with a good inter-RCM agreement, indicating dominant influence of the driving GCM. Also, RCMs consistently project increases in the frequency of heavy rains and the intensification of extreme precipitation over South Korea. Analysis of moisture flux convergence reveals competing impacts between TH and DY. The TH effect contributes to the overall increases in mean precipitation over Northeast Asia and in extreme precipitation over South Korea, irrespective of models and scenarios. However, DY effect is found to induce local-scale precipitation decreases over the central part of the Korean Peninsula with large inter-RCM and inter-scenario differences. Composite analysis of daily anomaly synoptic patterns indicates that extreme precipitation events are mainly associated with the southwest to northeast evolution of large-scale low-pressure system in both present and future climates.

Impact of climate change on precipitation distribution and water availability in the Nile using CMIP5 GCM ensemble.

NASA Astrophysics Data System (ADS)

Mekonnen, Z. T.; Gebremichael, M.

2017-12-01

ABSTRACT In a basin like the Nile where millions of people depend on rainfed agriculture and surface water resources for their livelihoods, changes in precipitation will have tremendous social and economic consequences. General circulation models (GCMs) have been associated with high uncertainty in their projection of future precipitation for the Nile basin. Some studies tried to compare performance of different GCMs by doing a Multi-Model comparison for the region. Many indicated that there is no single model that gives the "best estimate" of precipitation for a very complex and large basin like the Nile. In this study, we used a combination of satellite and long term rain gauge precipitation measurements (TRMM and CenTrends) to evaluate the performance of 10 GCMs from the 5th Coupled Model Intercomparison Project (CMIP5) at different spatial and seasonal scales and produce a weighted ensemble projection. Our results confirm that there is no single model that gives best estimate over the region, hence the approach of creating an ensemble depending on how the model performed in specific areas and seasons resulted in an improved estimate of precipitation compared with observed values. Following the same approach, we created an ensemble of future precipitation projections for four different time periods (2000-2024, 2025-2049 and 2050-2100). The analysis showed that all the major sub-basins of the Nile will get will get more precipitation with time, even though the distribution with in the sub basin might be different. Overall the analysis showed a 15 % increase (125 mm/year) by the end of the century averaged over the area up to the Aswan dam. KEY WORDS: Climate Change, CMIP5, Nile, East Africa, CenTrends, Precipitation, Weighted Ensembles

Spatiotemporal variations of the twentieth century Tibetan Plateau precipitation based on the monthly 2.5° reconstructed data

NASA Astrophysics Data System (ADS)

Shen, Samuel S. P.; Clarke, Gregori; Shen, Bo-Wen; Yao, Tandong

2017-12-01

This paper studies the spatiotemporal variations of precipitation over the Tibetan Plateau (TP) region with latitude and longitude ranges of (25° N, 45° N) and (65° E, 105° E) of the twentieth century from January 1901-December 2000. A long-term (January 1901-December 2009) TP monthly precipitation dataset with 2.5° latitude-longitude resolution is generated in this paper using spectral optimal gridding (SOG) method. The method uses the Global Precipitation Climatology Center (GPCC) ground station data to anchor the basis of empirical orthogonal functions (EOFs) computed from the Global Precipitation Climatology Project (GPCP) data. Our gridding takes teleconnection into account and uses data from stations both within and outside of the TP region. While the annual total precipitation increased at an approximate rate of 2.6 mm per decade in the period of 1971-2000 exists, no significant increase of TP precipitation from 1901 to 2000 was found. Our rate is less than those of previous publications based only on the TP stations because our data consider the entire TP region, including desert and high-altitude areas. An analysis of extremes and spatiotemporal patterns of our data shows that our reconstructed data can properly quantify the reported disasters of flooding and droughts in India, Bangladesh, and China for the following events: flooding in 1988 and 1998 and drought in 1972. Our time-frequency analysis using the empirical mode decomposition method shows that our nonlinear trend agrees well with the linear trend in the period from 1971 to 2000. The spatiotemporal variation characteristics documented in this paper can help understand atmospheric circulations on TP precipitation and validate the TP precipitation in climate models.

A Preliminary Analysis of Precipitation Properties and Processes during NASA GPM IFloodS

NASA Technical Reports Server (NTRS)

Carey, Lawrence; Gatlin, Patrick; Petersen, Walt; Wingo, Matt; Lang, Timothy; Wolff, Dave

2014-01-01

The Iowa Flood Studies (IFloodS) is a NASA Global Precipitation Measurement (GPM) ground measurement campaign, which took place in eastern Iowa from May 1 to June 15, 2013. The goals of the field campaign were to collect detailed measurements of surface precipitation using ground instruments and advanced weather radars while simultaneously collecting data from satellites passing overhead. Data collected by the radars and other ground instruments, such as disdrometers and rain gauges, will be used to characterize precipitation properties throughout the vertical column, including the precipitation type (e.g., rain, graupel, hail, aggregates, ice crystals), precipitation amounts (e.g., rain rate), and the size and shape of raindrops. The impact of physical processes, such as aggregation, melting, breakup and coalescence on the measured liquid and ice precipitation properties will be investigated. These ground observations will ultimately be used to improve rainfall estimates from satellites and in particular the algorithms that interpret raw data for the upcoming GPM mission's Core Observatory satellite, which launches in 2014. The various precipitation data collected will eventually be used as input to flood forecasting models in an effort to improve capabilities and test the utility and limitations of satellite precipitation data for flood forecasting. In this preliminary study, the focus will be on analysis of NASA NPOL (S-band, polarimetric) radar (e.g., radar reflectivity, differential reflectivity, differential phase, correlation coefficient) and NASA 2D Video Disdrometers (2DVDs) measurements. Quality control and processing of the radar and disdrometer data sets will be outlined. In analyzing preliminary cases, particular emphasis will be placed on 1) documenting the evolution of the rain drop size distribution (DSD) as a function of column melting processes and 2) assessing the impact of range on ground-based polarimetric radar estimates of DSD properties.

Simulation of Water Sources and Precipitation Recycling for the MacKenzie, Mississippi and Amazon River Basins

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Chern, Jiun-Dar

2005-01-01

An atmospheric general circulation model simulation for 1948-1997 of the water budgets for the MacKenzie, Mississippi and Amazon River basins is presented. In addition to the water budget, we include passive tracers to identify the geographic sources of water for the basins, and the analysis focuses on the mechanisms contributing to precipitation recycling in each basin. While each basin s precipitation recycling has a strong dependency on evaporation during the mean annual cycle, the interannual variability of the recycling shows important relationships with the atmospheric circulation. The MacKenzie River basin has only a weak interannual dependency on evaporation, where the variations in zonal moisture transport from the Pacific Ocean can affect the basin water cycle. On the other hand, the Mississippi River basin has strong interannual dependencies on evaporation. While the precipitation recycling weakens with increased low level jet intensity, the evaporation variations exert stronger influence in providing water vapor for convective precipitation at the convective cloud base. High precipitation recycling is also found to be partly connected to warm SSTs in the tropical Pacific Ocean. The Amazon River basin evaporation exhibits small interannual variations, so that the interannual variations of precipitation recycling are related to atmospheric moisture transport from the tropical south Atlantic Ocean. Increasing SSTs over the 50-year period are causing increased easterly transport across the basin. As moisture transport increases, the Amazon precipitation recycling decreases (without real time varying vegetation changes). In addition, precipitation recycling from a bulk diagnostic method is compared to the passive tracer method used in the analysis. While the mean values are different, the interannual variations are comparable between each method. The methods also exhibit similar relationships to the terms of the basin scale water budgets.

Trend analysis and forecast of precipitation, reference evapotranspiration, and rainfall deficit in the Blackland Prairie of eastern Mississippi

Treesearch

Gary Feng; Stacy Cobb; Zaid Abdo; Daniel K. Fisher; Ying Ouyang; Ardeshir Adeli; Johnie N. Jenkins

2016-01-01

Trend analysis and estimation of monthly and annual precipitation, reference evapotranspiration ET, and rainfall deficit are essential for water-resources management and cropping-system design. Rainfall, ET, and water-deficit patterns and trends at Macon in eastern Mississippi for a 120-yr period (1894-2014) were analyzed for annual, seasonal, and monthly...

Analysis of satellite precipitation over East Africa during last decades

NASA Astrophysics Data System (ADS)

Cattani, Elsa; Wenhaji Ndomeni, Claudine; Merino, Andrés; Levizzani, Vincenzo

2016-04-01

Daily accumulated precipitation time series from satellite retrieval algorithms (e.g., ARC2 and TAMSAT) are exploited to extract the spatial and temporal variability of East Africa (EA - 5°S-20°N, 28°E-52°E) precipitation during last decades (1983-2013). The Empirical Orthogonal Function (EOF) analysis is applied to precipitation time series to investigate the spatial and temporal variability in particular for October-November-December referred to as the short rain season. Moreover, the connection among EA's precipitation, sea surface temperature, and soil moisture is analyzed through the correlation with the dominant EOF modes of variability. Preliminary results concern the first two EOF's modes for the ARC2 data set. EOF1 is characterized by an inter-annual variability and a positive correlation between precipitation and El Niño, positive Indian Ocean Dipole mode, and soil moisture, while EOF2 shows a dipole structure of spatial variability associated with a longer scale temporal variability. This second dominant mode is mostly linked to sea surface temperature variations in the North Atlantic Ocean. Further analyses are carried out by computing the time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml), i.e. RX1day, RX5day, CDD, CDD, CWD, SDII, PRCPTOT, R10, R20. The purpose is to identify the occurrenes of extreme events (droughts and floods) and extract precipitation temporal variation by trend analysis (Mann-Kendall technique). Results for the ARC2 data set demonstrate the existence of a dipole spatial pattern in the linear trend of the time series of PRCPTOT (annual precipitation considering days with a rain rate > 1 mm) and SDII (average precipitation on wet days over a year). A negative trend is mainly present over West Ethiopia and Sudan, whereas a positive trend is exhibited over East Ethiopia and Somalia. CDD (maximum number of consecutive dry days) and CWD (maximum number of consecutive wet days) time series do not exhibit a similar behavior and trends are generally weaker with a lower significance level with respect to PRCPTOT and SDII.

Scaling and clustering effects of extreme precipitation distributions

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Li, Jianfeng

2012-08-01

SummaryOne of the impacts of climate change and human activities on the hydrological cycle is the change in the precipitation structure. Closely related to the precipitation structure are two characteristics: the volume (m) of wet periods (WPs) and the time interval between WPs or waiting time (t). Using daily precipitation data for a period of 1960-2005 from 590 rain gauge stations in China, these two characteristics are analyzed, involving scaling and clustering of precipitation episodes. Our findings indicate that m and t follow similar probability distribution curves, implying that precipitation processes are controlled by similar underlying thermo-dynamics. Analysis of conditional probability distributions shows a significant dependence of m and t on their previous values of similar volumes, and the dependence tends to be stronger when m is larger or t is longer. It indicates that a higher probability can be expected when high-intensity precipitation is followed by precipitation episodes with similar precipitation intensity and longer waiting time between WPs is followed by the waiting time of similar duration. This result indicates the clustering of extreme precipitation episodes and severe droughts or floods are apt to occur in groups.

Monitoring Precipitation from Space: targeting Hydrology Community?

NASA Astrophysics Data System (ADS)

Hong, Y.; Turk, J.

2005-12-01

During the past decades, advances in space, sensor and computer technology have made it possible to estimate precipitation nearly globally from a variety of observations in a relatively direct manner. The success of Tropical Precipitation Measuring Mission (TRMM) has been a significant advance for modern precipitation estimation algorithms to move toward daily quarter degree measurements, while the need for precipitation data at temporal-spatial resolutions compatible with hydrologic modeling has been emphasized by the end user: hydrology community. Can the future deployment of Global Precipitation Measurement constellation of low-altitude orbiting satellites (covering 90% of the global with a sampling interval of less than 3-hours), in conjunction with the existing suite of geostationary satellites, results in significant improvements in scale and accuracy of precipitation estimates suitable for hydrology applications? This presentation will review the current state of satellite-derived precipitation estimation and demonstrate the early results and primary barriers to full global high-resolution precipitation coverage. An attempt to facilitate the communication between data producers and users will be discussed by developing an 'end-to-end' uncertainty propagation analysis framework to quantify both the precipitation estimation error structure and the error influence on hydrological modeling.

Climate Drivers of Spatiotemporal Variability of Precipitation in the Source Region of Yangtze River

NASA Astrophysics Data System (ADS)

Du, Y.; Berndtsson, R.; An, D.; Yuan, F.

2017-12-01

Variability of precipitation regime has significant influence on the environment sustainability in the source region of Yangtze River, especially when the vegetation degradation and biodiversity reduction have already occurred. Understanding the linkage between variability of local precipitation and global teleconnection patterns is essential for water resources management. Based on physical reasoning, indices of the climate drivers can provide a practical way of predicting precipitation. Due to high seasonal variability of precipitation, climate drivers of the seasonal precipitation also varies. However, few reports have gone through the teleconnections between large scale patterns with seasonal precipitation in the source region of Yangtze River. The objectives of this study are therefore (1) assessment of temporal trend and spatial variability of precipitation in the source region of Yangtze River; (2) identification of climate indices with strong influence on seasonal precipitation anomalies; (3) prediction of seasonal precipitation based on revealed climate indices. Principal component analysis and Spearman rank correlation were used to detect significant relationships. A feed-forward artificial neural network(ANN) was developed to predict seasonal precipitation using significant correlated climate indices. Different influencing climate indices were revealed for precipitation in each season, with significant level and lag times. Significant influencing factors were selected to be the predictors for ANN model. With correlation coefficients between observed and simulated precipitation over 0.5, the results were eligible to predict the precipitation of spring, summer and winter using teleconnections, which can improve integrated water resources management in the source region of Yangtze River.

Risk assessment of precipitation extremes in northern Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Jun; Pei, Ying; Zhang, Yanwei; Ge, Quansheng

2018-05-01

This study was conducted using daily precipitation records gathered at 37 meteorological stations in northern Xinjiang, China, from 1961 to 2010. We used the extreme value theory model, generalized extreme value (GEV) and generalized Pareto distribution (GPD), statistical distribution function to fit outputs of precipitation extremes with different return periods to estimate risks of precipitation extremes and diagnose aridity-humidity environmental variation and corresponding spatial patterns in northern Xinjiang. Spatiotemporal patterns of daily maximum precipitation showed that aridity-humidity conditions of northern Xinjiang could be well represented by the return periods of the precipitation data. Indices of daily maximum precipitation were effective in the prediction of floods in the study area. By analyzing future projections of daily maximum precipitation (2, 5, 10, 30, 50, and 100 years), we conclude that the flood risk will gradually increase in northern Xinjiang. GEV extreme value modeling yielded the best results, proving to be extremely valuable. Through example analysis for extreme precipitation models, the GEV statistical model was superior in terms of favorable analog extreme precipitation. The GPD model calculation results reflect annual precipitation. For most of the estimated sites' 2 and 5-year T for precipitation levels, GPD results were slightly greater than GEV results. The study found that extreme precipitation reaching a certain limit value level will cause a flood disaster. Therefore, predicting future extreme precipitation may aid warnings of flood disaster. A suitable policy concerning effective water resource management is thus urgently required.

Gypsum crystals observed in experimental and natural sea ice

NASA Astrophysics Data System (ADS)

Geilfus, N.-X.; Galley, R. J.; Cooper, M.; Halden, N.; Hare, A.; Wang, F.; Søgaard, D. H.; Rysgaard, S.

2013-12-01

gypsum has been predicted to precipitate in sea ice, it has never been observed. Here we provide the first report on gypsum precipitation in both experimental and natural sea ice. Crystals were identified by X-ray diffraction analysis. Based on their apparent distinguishing characteristics, the gypsum crystals were identified as being authigenic. The FREeZing CHEMistry (FREZCHEM) model results support our observations of both gypsum and ikaite precipitation at typical in situ sea ice temperatures and confirms the "Gitterman pathway" where gypsum is predicted to precipitate. The occurrence of authigenic gypsum in sea ice during its formation represents a new observation of precipitate formation and potential marine deposition in polar seas.

Relative importance of precipitation frequency and intensity in inter-annual variation of precipitation in Singapore during 1980-2013

NASA Astrophysics Data System (ADS)

Li, Xin; Babovic, Vladan

2017-04-01

Observed studies on inter-annual variation of precipitation provide insight into the response of precipitation to anthropogenic climate change and natural climate variability. Inter-annual variation of precipitation results from the concurrent variations of precipitation frequency and intensity, understanding of the relative importance of frequency and intensity in the variability of precipitation can help fathom its changing properties. Investigation of the long-term changes of precipitation schemes has been extensively carried out in many regions across the world, however, detailed studies of the relative importance of precipitation frequency and intensity in inter-annual variation of precipitation are still limited, especially in the tropics. Therefore, this study presents a comprehensive framework to investigate the inter-annual variation of precipitation and the dominance of precipitation frequency and intensity in a tropical urban city-state, Singapore, based on long-term (1980-2013) daily precipitation series from 22 rain gauges. First, an iterative Mann-Kendall trend test method is applied to detect long-term trends in precipitation total, frequency and intensity at both annual and seasonal time scales. Then, the relative importance of precipitation frequency and intensity in inducing the inter-annual variation of wet-day precipitation total is analyzed using a dominance analysis method based on linear regression. The results show statistically significant upward trends in wet-day precipitation total, frequency and intensity at annual time scale, however, these trends are not evident during the monsoon seasons. The inter-annual variation of wet-day precipitation is mainly dominated by precipitation intensity for most of the stations at annual time scale and during the Northeast monsoon season. However, during the Southwest monsoon season, the inter-annual variation of wet-day precipitation is mainly dominated by precipitation frequency. These results have implications for water resources management practices in Singapore.

Observations and simulations of the western United States' hydroclimate

NASA Astrophysics Data System (ADS)

Guirguis, Kristen

While very important from an economical and societal point of view, estimating precipitation in the western United States remains an unsolved and challenging problem. This is due to difficulties in observing and modeling precipitation in complex terrain. This research examines this issue by (i) providing a systematic evaluation of precipitation observations to quantify data uncertainty; and (ii) investigating the ability of the Ocean-Land-Atmosphere Model (OLAM) to simulate the winter hydroclimate in this region. This state-of-the-art, non-hydrostatic model has the capability of simulating simultaneously all scales of motions at various resolutions. This research intercompares nine precipitation datasets commonly used in hydrometeorological research in two ways. First, using principal component analysis, a precipitation climatology is conducted for the western U.S. from which five unique precipitation climates are identified. From this analysis, data uncertainty is shown to be primarily due to differences in (i) precipitation over the Rocky Mountains, (ii) the eastward wet-to-dry precipitation gradient during the cold season, (iii) the North American Monsoon signal, and (iv) precipitation in the desert southwest during spring and summer. The second intercomparison uses these five precipitation regions to provide location-specific assessments of uncertainty, which is shown to be dependent on season, location. Long-range weather forecasts on the order of a season are important for water-scarce regions such as the western U.S. The modeling component of this research looks at the ability of the OLAM to simulate the hydroclimate in the western U.S. during the winter of 1999. Six global simulations are run, each with a different spatial resolution over the western U.S. (360 km down to 11 km). For this study, OLAM is configured as for a long-range seasonal hindcast but with observed sea surface temperatures. OLAM precipitation compares well against observations, and is generally within the range of data uncertainty. Observed and simulated synoptic meteorological conditions are examined during the wettest and driest events. OLAM is shown to reproduce the appropriate anomaly fields, which is encouraging since it demonstrates the capability of a global climate model, driven only by SSTs and initial conditions, to represent meteorological features associated with daily precipitation variability.

The Role of Precipitation Recycling in the Propagation and Intensification of Droughts in North America

NASA Astrophysics Data System (ADS)

Herrera-Estrada, J. E.; Sheffield, J.; Martinez-Agudelo, J. A.; Dominguez, F.; Wood, E. F.

2017-12-01

Predicting droughts allows stakeholders to mitigate some of the negative impacts of these natural disasters. However, there are still large gaps of knowledge regarding the physical drivers of drought onset, development, and recovery. These gaps have limited our ability to predict some important droughts and to understand how they may be affected by climate change. One physical mechanism that has been linked to the evolution of droughts is precipitation recycling, but its role has not been quantified in detail. Here we use a precipitation recycling model that backtracks the spatial origins of precipitation using vertically integrated moisture fluxes and evapotranspiration data. This allows us to estimate the climatology of moisture sources and sinks, and identify from where moisture fails to arrive when a given region experiences a drought. ERA-Interim data is used to drive this precipitation recycling model from 1980 to 2016 throughout North America and its surrounding oceans. The climatological analysis shows that oceans contribute around 80% of the precipitation over North America during winter, while precipitation that originates from evapotranspiration over land reaches a relative contribution of 60% in the summer. Precipitation contributions from the Pacific Ocean were found to be significantly and positively correlated with ENSO and PDO indices. Furthermore, a regression analysis showed that dry soil moisture in the US Southwest reduces moisture exports to the US Midwest, which in turn can dry soil moisture in the US Midwest. Given that up to 13% of precipitation over the US Midwest was found to be locally recycled, there is a multiplier effect whereby a 10 mm/month reduction in precipitation imports into the region leads to an additional decrease of 0.8 mm/month (on average) from reduced local precipitation recycling, causing a drought to intensify. It was also found that during extensive droughts (e.g. 2011 in Texas and 2012 in the US Midwest), precipitation deficits from land were as large and sometimes larger than those from the oceans. These results demonstrate a mechanism by which droughts can propagate spatially downwind, and point out to processes that need to be captured accurately by models used in operational seasonal forecasting and in climate change studies.

Understanding Oceanic Heavy Precipitation Using Scatterometer, Satellite Precipitation, and Reanalysis Products

NASA Technical Reports Server (NTRS)

Garg, Piyush; Nesbitt, Stephen W.; Lang, Timothy J.; Chronis, Themis

2016-01-01

The primary aim of this study is to understand the heavy precipitation events over Oceanic regions using vector wind retrievals from space based scatterometers in combination with precipitation products from satellite and model reanalysis products. Heavy precipitation over oceans is a less understood phenomenon and this study tries to fill in the gaps which may lead us to a better understanding of heavy precipitation over oceans. Various phenomenon may lead to intense precipitation viz. MJO (Madden-Julian Oscillation), Extratropical cyclones, MCSs (Mesoscale Convective Systems), that occur inside or outside the tropics and if we can decipher the physical mechanisms behind occurrence of heavy precipitation, then it may lead us to a better understanding of such events which further may help us in building more robust weather and climate models. During a heavy precipitation event, scatterometer wind observations may lead us to understand the governing dynamics behind that event near the surface. We hypothesize that scatterometer winds can observe significant changes in the near-surface circulation and that there are global relationships among these quantities. To the degree to which this hypothesis fails, we will learn about the regional behavior of heavy precipitation-producing systems over the ocean. We use a "precipitation feature" (PF) approach to enable statistical analysis of a large database of raining features.

Verifying Diurnal Variations of Global Precipitation in Three New Global Reanalyses

NASA Astrophysics Data System (ADS)

Wu, S.; Xie, P.; Sun, F.; Joyce, R.

2013-12-01

Diurnal variations of global precipitation and their representation in three sets of new generation global reanalyses are examined using the reprocessed and bias corrected CMORPH satellite precipitation estimates. The CMORPH satellite precipitation estimates are produced on an 8km by 8km grid over the globe (60oS-60oN) and in a 30-min interval covering a 15-year period from 1998 to the present through combining information from IR and PMW observations from all available satellites. Bias correction is performed for the raw CMORPH precipitation estimates through calibration against an gauge-based analysis over land and against the pentad GPCP analysis over ocean. The reanalyses examined here include the NCEP CFS reanalysis (CFSR), NASA/GSFC MERRA, and ECMWF Interim. The bias-corrected CMORPH is integrated from its original resolution to the reanalyses grid systems to facilitate the verification. First, quantitative agreements between the reanalysis precipitation fields and the CMORPH satellite observation are examined over the global domain. Precipitation structures associated with the large-scale topography are well reproduced when compared against the observation. Evolution of precipitation patterns with the development of transient weather systems are captured by the CFSR and two other reanalyses. The reanalyses tend to generate precipitation fields with wider raining areas and reduced intensity for heavy rainfall cases compared the observations over both land and ocean. Seasonal migration of global precipitation depicted in the 15-year CMORPH satellite observations is very well captured by the three sets of new reanalyses, although magnitude of precipitation is larger, especially in the CFSR, compared to that in the observations. In general, the three sets of new reanalyses exhibit substantial improvements in their performance to represent global precipitation distributions and variations. In particular, the new reanalyses produced precipitation variations of fine time/space scales collated in the observations. The diurnal cycle of the precipitation is reasonably well reproduced by the reanalyses over many global oceanic and land areas. Diurnal amplitude of the reanalyses precipitation, defined as the standard deviation of the 24 hourly mean values, is smaller than that in the observations over most of the oceanic regions, attributable largely to the continuous weak precipitation throughout the diurnal cycle in all of the three reanalyses. Over ocean, the pattern of diurnal variations of precipitation in the reanalyses is quite similar to that in the observations, with the timing of maximum precipitation shifted by1-3 hours. Over land especially over Africa, the reanalyses tend to produce maximum precipitation around noon, much earlier than that in the observations. Particularly noticeable is the diurnal cycle of warm season precipitation over CONUS in association with the eastward propagation of meso-scale systems distinct in the observations. None of the three new reanalyses are capable of detecting this pattern of diurnal variations. A comprehensive description and diagnostic discussions will be given at the AGU meeting.

Assessment of the performance of CORDEX-South Asia experiments for monsoonal precipitation over the Himalayan region during present climate: part I

NASA Astrophysics Data System (ADS)

Ghimire, S.; Choudhary, A.; Dimri, A. P.

2018-04-01

Analysis of regional climate simulations to evaluate the ability of 11 Coordinated Regional Climate Downscaling Experiment in South Asia experiments (CORDEX-South Asia) along with their ensemble to produce precipitation from June to September (JJAS) over the Himalayan region have been carried out. These suite of 11 combinations come from 6 regional climate models (RCMs) driven with 10 initial and boundary conditions from different global climate models and are collectively referred here as 11 CORDEX South Asia experiments. All the RCMs use a similar domain and are having similar spatial resolution of 0.44° ( 50 km). The set of experiments are considered to study precipitation sensitivity associated with the Indian summer monsoon (ISM) over the study region. This effort is made as ISM plays a vital role in summertime precipitation over the Himalayan region which acts as driver for the sustenance of habitat, population, crop, glacier, hydrology etc. In addition, so far the summer monsoon precipitation climatology over the Himalayan region has not been studied with the help of CORDEX data. Thus this study is initiated to evaluate the ability of the experiments and their ensemble in reproducing the characteristics of summer monsoon precipitation over Himalayan region, for the present climate (1970-2005). The precipitation climatology, annual precipitation cycles and interannual variabilities from each simulation have been assessed against the gridded observational dataset: Asian Precipitation-Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources for the given time period. Further, after the selection of the better performing experiment the frequency distribution of precipitation was also studied. In this study, an approach has also been made to study the degree of agreement among individual experiments as a way to quantify the uncertainty among them. The experiments though show a wide variation among themselves and individually over time and space in simulating precipitation distribution over the study region, but noticeably along the foothills of the Himalayas all the simulations show dry precipitation bias against the corresponding observation. In addition, as we move towards higher elevation regions these experiments in general show wet bias. The experiment driven by EC-EARTH global climate model and downscaled using Rossby Center regional Atmospheric model version 4 developed by Swedish Meteorological and Hydrological Institute (SMHI-RCA4) simulate precipitation closely in correspondence with the observation. The ensemble outperforms the result of individual experiments. Correspondingly, different kinds of statistical analysis like spatial and temporal correlation, Taylor diagram, frequency distribution and scatter plot have been performed to compare the model output with observation and to explain the associated resemblance, robustness and dynamics statistically. Through the bias and ensemble spread analysis, an estimation of the uncertainty of the model fields and the degree of agreement among them has also been carried out in this study. Overview of the study suggests that these experiments facilitate precipitation evolution and structure over the Himalayan region with certain degree of uncertainty.

Quantifying spatial variability of AgI cloud seeding benefits and Ag enrichments in snow

NASA Astrophysics Data System (ADS)

Fisher, J.; Benner, S. G.; Lytle, M. L.; Kunkel, M. L.; Blestrud, D.; Holbrook, V. P.; Parkinson, S.; Edwards, R.

2016-12-01

Glaciogenic cloud seeding is an important scientific technology for enhancing water resources across in the Western United States. Cloud seeding enriches super cooled liquid water layers with plumes of silver iodide (AgI), an artificial ice nuclei. Recent studies using target-control regression analysis and modeling estimate glaciogenic cloud seeding increases snow precipitation between 3-15% annually. However, the efficacy of cloud seeding programs is difficult to assess using weather models and statistics alone. This study will supplement precipitation enhancement statistics and Weather Research and Forecasting (WRF) model outputs with ultra-trace chemistry. Combining precipitation enhancement estimates with trace chemistry data (to estimate AgI plume targeting accuracy) may provide a more robust analysis. Precipitation enhancement from the 2016 water year will be modeled two ways. First, by using double-mass curve. Annual SNOTEL data of the cumulative SWE in unseeded areas and cumulative SWE in seeded areas will be compared before, and after, the cloud seeding program's initiation in 2003. Any change in the double-mass curve's slope after 2003 may be attributed to cloud seeding. Second, WRF model estimates of precipitation will be compared to the observed precipitation at SNOTEL sites. The difference between observed and modeled precipitation in AgI seeded regions may also be attributed to cloud seeding (assuming modeled and observed data are comparable at unseeded SNOTEL stations). Ultra-trace snow chemistry data from the 2016 winter season will be used to validate whether estimated precipitation increases are positively correlated with the mass of silver in the snowpack.

Formation of crystalline Zn-Al layered double hydroxide precipitates on γ-alumina: the role of mineral dissolution.

PubMed

Li, Wei; Livi, Kenneth J T; Xu, Wenqian; Siebecker, Matthew G; Wang, Yujun; Phillips, Brian L; Sparks, Donald L

2012-11-06

To better understand the sequestration of toxic metals such as nickel (Ni), zinc (Zn), and cobalt (Co) as layered double hydroxide (LDH) phases in soils, we systematically examined the presence of Al and the role of mineral dissolution during Zn sorption/precipitation on γ-Al(2)O(3) (γ-alumina) at pH 7.5 using extended X-ray absorption fine structure spectroscopy (EXAFS), high-resolution transmission electron microscopy (HR-TEM), synchrotron-radiation powder X-ray diffraction (SR-XRD), and (27)Al solid-state NMR. The EXAFS analysis indicates the formation of Zn-Al LDH precipitates at Zn concentration ≥0.4 mM, and both HR-TEM and SR-XRD reveal that these precipitates are crystalline. These precipitates yield a small shoulder at δ(Al-27) = +12.5 ppm in the (27)Al solid-state NMR spectra, consistent with the mixed octahedral Al/Zn chemical environment in typical Zn-Al LDHs. The NMR analysis provides direct evidence for the existence of Al in the precipitates and the migration from the dissolution of γ-alumina substrate. To further address this issue, we compared the Zn sorption mechanism on a series of Al (hydr)oxides with similar chemical composition but differing dissolubility using EXAFS and TEM. These results suggest that, under the same experimental conditions, Zn-Al LDH precipitates formed on γ-alumina and corundum but not on less soluble minerals such as bayerite, boehmite, and gibbsite, which point outs that substrate mineral surface dissolution plays an important role in the formation of Zn-Al LDH precipitates.

Multi-pentad prediction of precipitation variability over Southeast Asia during boreal summer using BCC_CSM1.2

NASA Astrophysics Data System (ADS)

Li, Chengcheng; Ren, Hong-Li; Zhou, Fang; Li, Shuanglin; Fu, Joshua-Xiouhua; Li, Guoping

2018-06-01

Precipitation is highly variable in space and discontinuous in time, which makes it challenging for models to predict on subseasonal scales (10-30 days). We analyze multi-pentad predictions from the Beijing Climate Center Climate System Model version 1.2 (BCC_CSM1.2), which are based on hindcasts from 1997 to 2014. The analysis focus on the skill of the model to predict precipitation variability over Southeast Asia from May to September, as well as its connections with intraseasonal oscillation (ISO). The effective precipitation prediction length is about two pentads (10 days), during which the skill measured by anomaly correlation is greater than 0.1. In order to further evaluate the performance of the precipitation prediction, the diagnosis results of the skills of two related circulation fields show that the prediction skills for the circulation fields exceed that of precipitation. Moreover, the prediction skills tend to be higher when the amplitude of ISO is large, especially for a boreal summer intraseasonal oscillation. The skills associated with phases 2 and 5 are higher, but that of phase 3 is relatively lower. Even so, different initial phases reflect the same spatial characteristics, which shows higher skill of precipitation prediction in the northwest Pacific Ocean. Finally, filter analysis is used on the prediction skills of total and subseasonal anomalies. The results of the two anomaly sets are comparable during the first two lead pentads, but thereafter the skill of the total anomalies is significantly higher than that of the subseasonal anomalies. This paper should help advance research in subseasonal precipitation prediction.

Solid precipitation measurement intercomparison in Bismarck, North Dakota, from 1988 through 1997

USGS Publications Warehouse

Ryberg, Karen R.; Emerson, Douglas G.; Macek-Rowland, Kathleen M.

2009-01-01

A solid precipitation measurement intercomparison was recommended by the World Meteorological Organization (WMO) and was initiated after approval by the ninth session of the Commission for Instruments and Methods of Observation. The goal of the intercomparison was to assess national methods of measuring solid precipitation against methods whose accuracy and reliability were known. A field study was started in Bismarck, N. Dak., during the 1988-89 winter as part of the intercomparison. The last official field season of the WMO intercomparison was 1992-93; however, the Bismarck site continued to operate through the winter of 1996-97. Precipitation events at Bismarck were categorized as snow, mixed, or rain on the basis of descriptive notes recorded as part of the solid precipitation intercomparison. The rain events were not further analyzed in this study. Catch ratios (CRs) - the ratio of the precipitation catch at each gage to the true precipitation measurement (the corrected double fence intercomparison reference) - were calculated. Then, regression analysis was used to develop equations that model the snow and mixed precipitation CRs at each gage as functions of wind speed and temperature. Wind speed at the gages, functions of temperature, and upper air conditions (wind speed and air temperature at 700 millibars pressure) were used as possible explanatory variables in the multiple regression analysis done for this study. The CRs were modeled by using multiple regression analysis for the Tretyakov gage, national shielded gage, national unshielded gage, AeroChem gage, national gage with double fence, and national gage with Wyoming windshield. As in earlier studies by the WMO, wind speed and air temperature were found to influence the CR of the Tretyakov gage. However, in this study, the temperature variable represented the average upper air temperature over the duration of the event. The WMO did not use upper air conditions in its analysis. The national shielded and unshielded gages where found to be influenced by functions of wind speed only, as in other studies, but the upper air wind speed was used as an explanatory variable in this study. The AeroChem gage was not used in the WMO intercomparison study for 1987-93. The AeroChem gage had a highly varied CR at Bismarck, and a number of variables related to wind speed and temperature were used in the model for the CR. Despite extensive efforts to find a model for the national gage with double fence, no statistically significant regression model was found at the 0.05 level of statistical significance. The national gage with Wyoming windshield had a CR modeled by temperature and wind speed variables, and the regression relation had the highest coefficient of determination (R2 = 0.572) and adjusted coefficient of multiple determination (R2a = 0.476) of all of the models identified for any gage. Three of the gage CRs evaluated could be compared with those in the WMO intercomparison study for 1987-93. The WMO intercomparison had the advantage of a much larger dataset than this study. However, the data in this study represented a longer time period. Snow precipitation catch is highly varied depending on the equipment used and the weather conditions. Much of the variation is not accounted for in the WMO equations or in the equations developed in this study, particularly for unshielded gages. Extensive attempts at regression analysis were made with the mixed precipitation data, but it was concluded that the sample sizes were not large enough to model the CRs. However, the data could be used to test the WMO intercomparison equations. The mixed precipitation equations for the Tretyakov and national shielded gages are similar to those for snow in that they are more likely to underestimate precipitation when observed amounts were small and overestimate precipitation when observed amounts were relatively large. Mixed precipitation is underestimated by the WMO adjustment and t

Irradiation-induced precipitation and mechanical properties of vanadium alloys at <430 C

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

Chung, H.M.; Gazda, J.; Smith, D.L.

Recent attention to V-base alloys has focused on the effect of low-temperature (<430 C) irradiation on tensile and impact properties of V-4Cr-4Ti. In previous studies, dislocation channeling, which causes flow localization and severe loss of work-hardening capability, has been attributed to dense, irradiation-induced precipitation of very fine particles. However, efforts to identify the precipitates were unsuccessful until now. In this study, analysis by transmission electron microscopy (TEM) was conducted on unalloyed V, V-5Ti, V-3Ti-1Si, and V-4Cr-4Ti specimens that were irradiated at <430 C in conventional and dynamic helium charging experiments. By means of dark-field imaging and selected-area-diffraction analysis, the characteristicmore » precipitates were identified to be (V,Ti{sub 1{minus}x})(C,O,N). In V-3Ti-1Si, precipitation of (V,Ti{sub 1{minus}x})(C,O,N) was negligible at <430 C, and as a result, dislocation channeling did not occur and work-hardening capability was high.« less

Pathway of FeEDTA transformation and its impact on performance of NOx removal in a chemical absorption-biological reduction integrated process

PubMed Central

Li, Wei; Zhao, Jingkai; Zhang, Lei; Xia, Yinfeng; Liu, Nan; Li, Sujing; Zhang, Shihan

2016-01-01

A novel chemical absorption-biological reduction (CABR) integrated process, employing ferrous ethylenediaminetetraacetate (Fe(II)EDTA) as a solvent, is deemed as a potential option for NOx removal from the flue gas. Previous work showed that the Fe(II)EDTA concentration was critical for the NOx removal in the CABR process. In this work, the pathway of FeEDTA (Fe(III)/Fe(II)-EDTA) transformation was investigated to assess its impact on the NOx removal in a biofilter. Experimental results revealed that the FeEDTA transformation involved iron precipitation and EDTA degradation. X-ray photoelectron spectroscopy analysis confirmed the iron was precipitated in the form of Fe(OH)3. The iron mass balance analysis showed 44.2% of the added iron was precipitated. The EDTA degradation facilitated the iron precipitation. Besides chemical oxidation, EDTA biodegradation occurred in the biofilter. The addition of extra EDTA helped recover the iron from the precipitation. The transformation of FeEDTA did not retard the NO removal. In addition, EDTA rather than the iron concentration determined the NO removal efficiency. PMID:26743930

Ceftriaxone-associated gallbladder sludge. Identification of calcium-ceftriaxone salt as a major component of gallbladder precipitate

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

Park, H.Z.; Lee, S.P.; Schy, A.L.

1991-06-01

Ceftriaxone, a third-generation cephalosporin, is partially excreted into bile. With its clinical use, the formation of gallbladder sludge detected by ultrasonography has been reported. Four surgical specimens were examined and no gallstones were found. Instead, fine precipitates of 20-250 microns were present. Microscopically, there was a small number of cholesterol monohydrate crystals and bilirubin granules among an abundant amount of granular-crystalline material that was not morphologically cholesterol monohydrate crystals. The chemical composition of the precipitates (n = 4) was determined. There was a small amount of cholesterol (1.7% +/- 0.8%) and bilirubin (13.9% +/- 0.74%). The major component of themore » precipitate was a residue. On further analysis using thin-layer chromatography, high-performance liquid chromatography, and electron microprobe analysis, the residue was identified as a calcium salt of ceftriaxone. The residue also had identical crystal morphology and chromatographic elution profile as authentic calcium-ceftriaxone standards. It is concluded that ceftriaxone, after excretion and being concentrated in the gallbladder bile, can form a precipitate. The major constituent has been identified as a ceftriaxone-calcium salt.« less

Analysis of long-term trends (1950–2009) in precipitation, runoff and runoff coefficient in major urban watersheds in the United States

USGS Publications Warehouse

Velpuri, N.M.; Senay, G.B.

2013-01-01

This study investigates the long-term trends in precipitation, runoff and runoff coefficient in major urban watersheds in the United States. The seasonal Mann–Kendall trend test was performed on monthly precipitation, runoff and runoff coefficient data from 1950 to 2009 obtained from 62 urban watersheds covering 21 major urban centers in the United States. The results indicate that only five out of 21 urban centers in the United States showed an uptrend in precipitation. Twelve urban centers showed an uptrend in runoff coefficient. However, six urban centers did not show any trend in runoff coefficient, and three urban centers showed a significant downtrend. The highest rate of change in precipitation, runoff and runoff coefficient was observed in the Houston urban watershed. Based on the results obtained, we also attributed plausible causes for the trends. Our analysis indicated that while a human only influence is observed in most of the urban watersheds, a combined climate and human influence is observed in the central United States.

Vector Analysis of Ionic Collision on CaCO3 Precipitation Based on Vibration Time History

NASA Astrophysics Data System (ADS)

Mangestiyono, W.; Muryanto, S.; Jamari, J.; Bayuseno, A. P.

2017-05-01

Vibration effects on the piping system can result from the internal factor of fluid or the external factor of the mechanical equipment operation. As the pipe vibrated, the precipitation process of CaCO3 on the inner pipe could be affected. In the previous research, the effect of vibration on CaCO3 precipitation in piping system was clearly verified. This increased the deposition rate and decreased the induction time. However, the mechanism of vibration control in CaCO3 precipitation process as the presence of vibration has not been recognized yet. In the present research, the mechanism of vibration affecting the CaCO3 precipitation was investigated through vector analysis of ionic collision. The ionic vector force was calculated based on the amount of the activation energy and the vibration force was calculated based on the vibration sensor data. The vector resultant of ionic collision based on the vibration time history was analyzed to prove that vibration brings ionic collision randomly to the planar horizontal direction and its collision model was suspected as the cause of the increasing deposition rate.

The optimization of microalgal culturing in liquid digestate after struvite precipitation using gray relational analysis.

PubMed

Jiang, Yiqi; Wang, Hong; Wang, Wannan; Deng, Liangwei; Wang, Wenguo

2018-05-01

Liquid digestate (LD) is highly turbid and contains ammonium (NH 4 + -N), which negatively influences microalgal growth. Therefore, a method of reducing LD turbidity and NH 4 + -N content is proposed, using struvite precipitation. To obtain struvite precipitation supernatant with an ideal UV transmittance, NH 4 + -N concentration, and N/P ratio for microalgal growth, the effects of pH and the molar ratio of NH 4 + /Mg 2+ /PO 4 3- were studied. Results show that the optimal NH 4 + /Mg 2+ /PO 4 3- molar ratio was 1:1.5:1.5, with a pH value of 8.5, following NaOH addition. Gray relational analysis (GRA) was applied to obtain a relative gray scale for the evaluation of multiple outputs. Results show that Chlorella regularis FACHB-1068 was the optimal microalgae species to support growth in the struvite precipitation supernatant. Using struvite precipitation and treatment with cultured C. regularis FACHB-1068 for 7 days, the removal efficiencies of NH 4 + -N, PO 4 3- -P, and COD in LD were 96.52, 99.33, and 35.30%, respectively.

Ten-Year Analysis of the Forest Fire Smoke in the Russian Far East

DTIC Science & Technology

2005-07-25

factor when we monitor the environmental pollution by wide distribution of fire smoke. We examined the relation among the forest fire, smoke, and precipitation, and showed the importance role of precipitation.

An analysis of input errors in precipitation-runoff models using regression with errors in the independent variables

USGS Publications Warehouse

Troutman, Brent M.

1982-01-01

Errors in runoff prediction caused by input data errors are analyzed by treating precipitation-runoff models as regression (conditional expectation) models. Independent variables of the regression consist of precipitation and other input measurements; the dependent variable is runoff. In models using erroneous input data, prediction errors are inflated and estimates of expected storm runoff for given observed input variables are biased. This bias in expected runoff estimation results in biased parameter estimates if these parameter estimates are obtained by a least squares fit of predicted to observed runoff values. The problems of error inflation and bias are examined in detail for a simple linear regression of runoff on rainfall and for a nonlinear U.S. Geological Survey precipitation-runoff model. Some implications for flood frequency analysis are considered. A case study using a set of data from Turtle Creek near Dallas, Texas illustrates the problems of model input errors.

The Microstructure and Gamma Prime Distributions in Inertia Friction Welded Joint of P/M Superalloy FGH96

NASA Astrophysics Data System (ADS)

Zhang, Chi; Shen, Wenfei; Zhang, Liwen; Xia, Yingnan; Li, Ruiqin

2017-04-01

A gamma prime ( γ') precipitation ( 35% in volume)-hardened powder metallurgy (P/M) superalloy FGH96 was welded using inertia friction welding (IFW). The microstructure and γ' distributions in the joints in two conditions, hot isostatic pressed state and solution-treated and aged state, were characterized. The recrystallization of grains, the dissolution and re-precipitation of γ' in the joints were discussed in terms of the temperature evolutions which were calculated by finite element model analysis. Regardless of the initial states, fully recrystallized fine grain structure formed at welded zone. Meanwhile, very fine γ' precipitations were re-precipitated at the welded zone. These recrystallized grain structure and fine re-precipitated γ' resulted in increasing hardness of IFW joint while making the hardness dependent on the microstructure and γ' precipitation.

Precipitation in Madeira island and atmospheric rivers in the winter seasons

NASA Astrophysics Data System (ADS)

Couto, Flavio T.; Salgado, Rui; João Costa, Maria; Prior, Victor

2016-04-01

This study aims to analyse the distribution of the daily accumulated precipitation in the Madeira's highlands over a 10-year period, as well as the main characteristics associated with atmospheric rivers (ARs) affecting the island during 10 winter seasons, and their impact in the rainfall amounts recorded near the mountain crest in the south-eastern part of the island. The period between September 2002 and November 2012 is considered for the analysis. The ARs have been identified from the total precipitable water vapour field extracted from the Atmospheric Infrared Sounder (AIRS). The AIRS observations were downloaded for a domain covering large part of the North Atlantic Ocean. The precipitable water vapour field from the European Centre for Medium-range Weather Forecasts (ECMWF) analysis was also used aiming to support the AIRS data when there was no satellite information over the island. The daily accumulated precipitation at surface showed generally drier summers, while the highest accumulated precipitation are recorded mainly during the winter, although some significant events may occur also in autumn and spring seasons. The patterns of the precipitable water vapour field when ARs reach the island were investigated, and even if great part of the atmospheric rivers reaches the island in a dissipation stage, some rivers are heavy enough to reach the Madeira Island. In this situation, the water vapour transport could be observed in two main configurations and transporting significant water vapour amounts toward the Madeira from the tropical region. This study lead to conclude that the atmospheric rivers, when associated to high values of precipitable water vapour over the island can provide favourable conditions to the development of precipitation, sometimes associated with high amounts. However, it was also found that many cases of high to extreme accumulated precipitation at the surface were not associated to this kind of moisture transport.

Key drivers of precipitation isotopes in Windhoek, Namibia (2012-2016)

NASA Astrophysics Data System (ADS)

Kaseke, K. F.; Wang, L.; Wanke, H.

2017-12-01

Southern African climate is characterized by large variability with precipitation model estimates varying by as much as 70% during summer. This difference between model estimates is partly because most models associate precipitation over Southern Africa with moisture inputs from the Indian Ocean while excluding inputs from the Atlantic Ocean. However, growing evidence suggests that the Atlantic Ocean may also contribute significant amounts of moisture to the region. This four-year (2012-2016) study investigates the isotopic composition (δ18O, δ2H and δ17O) of event-scale precipitation events, the key drivers of isotope variations and the origins of precipitation experienced in Windhoek, Namibia. Results indicate large storm-to-storm isotopic variability δ18O (25‰), δ2H (180‰) and δ17O (13‰) over the study period. Univariate analysis showed significant correlations between event precipitation isotopes and local meteorological parameters; lifted condensation level, relative humidity (RH), precipitation amount, average wind speed, surface and air temperature (p < 0.05). The number of significant correlations between local meteorological parameters and monthly isotopes was much lower suggesting loss of information through data aggregation. Nonetheless, the most significant isotope driver at both event and monthly scales was RH, consistent with the semi-arid classification of the site. Multiple linear regression analysis suggested RH, precipitation amount and air temperature were the most significant local drivers of precipitation isotopes accounting for about 50% of the variation implying that about 50% could be attributed to source origins. HYSLPIT trajectories indicated that 78% of precipitation originated from the Indian Ocean while 21% originated from the Atlantic Ocean. Given that three of the four study years were droughts while two of the three drought years were El Niño related, our data also suggests that δ'17O-δ'18O could be a useful tool to differentiate local vs synoptic (El Niño) droughts.

Pluviometric characterization of the Coca river basin by using a stochastic rainfall model

NASA Astrophysics Data System (ADS)

González-Zeas, Dunia; Chávez-Jiménez, Adriadna; Coello-Rubio, Xavier; Correa, Ángel; Martínez-Codina, Ángela

2014-05-01

An adequate design of the hydraulic infrastructures, as well as, the prediction and simulation of a river basin require historical records with a greater temporal and spatial resolution. However, the lack of an extensive network of precipitation data, the short time scale data and the incomplete information provided by the available rainfall stations limit the analysis and design of complex hydraulic engineering systems. As a consequence, it is necessary to develop new quantitative tools in order to face this obstacle imposed by ungauged or poorly gauged basins. In this context, the use of a spatial-temporal rainfall model allows to simulate the historical behavior of the precipitation and at the same time, to obtain long-term synthetic series that preserve the extremal behavior. This paper provides a characterization of the precipitation in the Coca river basin located in Ecuador by using RainSim V3, a robust and well tested stochastic rainfall model based on a spatial-temporal Neyman-Scott rectangular pulses process. A preliminary consistency analysis of the historical rainfall data available has been done in order to identify climatic regions with similar precipitation behavior patterns. Mean and maximum yearly and monthly fields of precipitation of high resolution spaced grids have been obtained through the use of interpolation techniques. According to the climatological similarity, long time series of daily temporal resolution of precipitation have been generated in order to evaluate the model skill in capturing the structure of daily observed precipitation. The results show a good performance of the model in reproducing very well the gross statistics, including the extreme values of rainfall at daily scale. The spatial pattern represented by the observed and simulated precipitation fields highlights the existence of two important regions characterized by different pluviometric comportment, with lower precipitation in the upper part of the basin and higher precipitation in the lower part of the basin.

Yielding Unexpected Results: Precipitation of Ba[subscript3](PO[subscript4])[subscript2] and Implications for Teaching Solubility Principles in the General Chemistry Curriculum

ERIC Educational Resources Information Center

Hazen, Jeffery L.; Cleary, David A.

2014-01-01

Precipitation of barium phosphate from aqueous solutions of a barium salt and a phosphate salt forms the basis for a number of conclusions drawn in general chemistry. For example, the formation of a solid white precipitate is offered as evidence that barium phosphate is insoluble. Furthermore, analysis of the supernatant is used to illustrate the…

Precipitation composition and wet deposition temporal pattern in Central Serbia for the period from 1998 to 2004.

PubMed

Golobocanin, D; Zujić, A; Milenković, A; Miljević, N

2008-07-01

Bulk samples collected on a daily basis at three principal meteorological stations in central Serbia were analyzed on chloride (Cl(-)), nitrate (NO(3)(-)), sulfate (SO(4)(2-)), sodium (Na(+)), ammonium (NH(4)(+)), potassium (K(+)), calcium (Ca(2+)), and magnesium (Mg(2+)) in addition to precipitation amount, pH and conductivity measurements over the period 1998-2004. The data were subjected to variety of analyses (linear regression, principal component analysis, time series analysis) to characterize precipitation chemistry in the study area. The most abundant ion was SO(2-)(4) with annual volume weighted mean concentration of 242 microeq L(-1). Neutralization of precipitation acidity occurs both as a result of the dissolution of alkaline compounds containing Ca(2+), Mg(2+), and K(+) as well as the absorption of ammonia. The ratio of SO(4)(2-)/NO(3)(-) was above 5, which indicated that the combustion process of low-grade domestic lignite for electricity generation from coal-fired thermal power plants was the main source of pollution in the investigated area. A considerable mean annual bulk wet deposition of SO(4)-S determined by precipitation amount and concentrations of sulfate in the precipitation was calculated to be 12-35 kg ha(-1).

[Comparison of acetonitrile, ethanol and chromatographic column to eliminate high-abundance proteins in human serum].

PubMed

Li, Yin; Liao, Ming; He, Xiao; Zhou, Yi; Luo, Rong; Li, Hongtao; Wang, Yun; He, Min

2012-11-01

To compare the effects of acetonitrile precipitation, ethanol precipitation and multiple affinity chromatography column Human 14 removal to eliminate high-abundance proteins in human serum. Elimination of serum high-abundance proteins performed with acetonitrile precipitation, ethanol precipitation and multiple affinity chromatography column Human 14 removal. Bis-Tris Mini Gels electrophoresis and two-dimensional gel electrophoresis to detect the effect. Grey value analysis from 1-DE figure showed that after serum processed by acetonitrile method, multiple affinity chromatography column Human 14 removal method and ethanol method, the grey value of albumin changed into 157.2, 40.8 and 8.2 respectively from the original value of 19. 2-DE analysis results indicated that using multiple affinity chromatography column Human 14 method, the protein points noticeable increased by 137 compared to the original serum. After processed by acetonitrile method and ethanol method, the protein point reduced, but the low abundance protein point emerged. The acetonitrile precipitation could eliminate the vast majority of high abundance proteins in serum and gain more proteins of low molecular weight, ethanol precipitation could eliminate part of high abundance proteins in serum, but low abundance proteins less harvested, and multiple affinity chromatography column Human 14 method could effectively removed the high abundance proteins, and keep a large number of low abundance proteins.

Enhanced precipitation variability decreases grass- and increases shrub-productivity

PubMed Central

Gherardi, Laureano A.; Sala, Osvaldo E.

2015-01-01

Although projections of precipitation change indicate increases in variability, most studies of impacts of climate change on ecosystems focused on effects of changes in amount of precipitation, overlooking precipitation variability effects, especially at the interannual scale. Here, we present results from a 6-y field experiment, where we applied sequences of wet and dry years, increasing interannual precipitation coefficient of variation while maintaining a precipitation amount constant. Increased precipitation variability significantly reduced ecosystem primary production. Dominant plant-functional types showed opposite responses: perennial-grass productivity decreased by 81%, whereas shrub productivity increased by 67%. This pattern was explained by different nonlinear responses to precipitation. Grass productivity presented a saturating response to precipitation where dry years had a larger negative effect than the positive effects of wet years. In contrast, shrubs showed an increasing response to precipitation that resulted in an increase in average productivity with increasing precipitation variability. In addition, the effects of precipitation variation increased through time. We argue that the differential responses of grasses and shrubs to precipitation variability and the amplification of this phenomenon through time result from contrasting root distributions of grasses and shrubs and competitive interactions among plant types, confirmed by structural equation analysis. Under drought conditions, grasses reduce their abundance and their ability to absorb water that then is transferred to deep soil layers that are exclusively explored by shrubs. Our work addresses an understudied dimension of climate change that might lead to widespread shrub encroachment reducing the provisioning of ecosystem services to society. PMID:26417095

Precipitation Depth-Duration-Frequency Analysis for the Nevada National Security Site and Surrounding Areas

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

Chen, Li; Miller, Julianne J.

Accurate precipitation frequency data are important for Environmental Management Soils Activities on the Nevada National Security Site (NNSS). These data are important for environmental assessments performed for regulatory closure of Soils Corrective Action Unit (CAU) Sites, as well as engineering mitigation designs and post-closure monitoring strategies to assess and minimize potential contaminant migration from Soils CAU Sites. Although the National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (Bonnin et al., 2011) provides precipitation frequency data for the NNSS area, the NNSS-specific observed precipitation data were not consistent with the NOAA Atlas 14 predicted data. This is primarily due to themore » NOAA Atlas 14 products being produced from analyses without including the approximately 30 NNSS precipitation gage records, several of which approach or exceed 50 year of record. Therefore, a study of precipitation frequency that incorporated the NNSS precipitation gage records into the NOAA Atlas 14 dataset, was performed specifically for the NNSS to derive more accurate site-specific precipitation data products. Precipitation frequency information, such as the depth-duration-frequency (DDF) relationships, are required to generate synthetic standard design storm hydrographs and assess actual precipitation events. In this study, the actual long-term NNSS precipitation gage records, some of which are the longest gage records in southern and central Nevada, were analyzed to allow for more accurate precipitation DDF estimates to be developed for the NNSS. Gridded maps of precipitation frequency for the NNSS and surrounding areas were then produced.« less

Modelling probabilities of heavy precipitation by regional approaches

NASA Astrophysics Data System (ADS)

Gaal, L.; Kysely, J.

2009-09-01

Extreme precipitation events are associated with large negative consequences for human society, mainly as they may trigger floods and landslides. The recent series of flash floods in central Europe (affecting several isolated areas) on June 24-28, 2009, the worst one over several decades in the Czech Republic as to the number of persons killed and the extent of damage to buildings and infrastructure, is an example. Estimates of growth curves and design values (corresponding e.g. to 50-yr and 100-yr return periods) of precipitation amounts, together with their uncertainty, are important in hydrological modelling and other applications. The interest in high quantiles of precipitation distributions is also related to possible climate change effects, as climate model simulations tend to project increased severity of precipitation extremes in a warmer climate. The present study compares - in terms of Monte Carlo simulation experiments - several methods to modelling probabilities of precipitation extremes that make use of ‘regional approaches’: the estimation of distributions of extremes takes into account data in a ‘region’ (‘pooling group’), in which one may assume that the distributions at individual sites are identical apart from a site-specific scaling factor (the condition is referred to as ‘regional homogeneity’). In other words, all data in a region - often weighted in some way - are taken into account when estimating the probability distribution of extremes at a given site. The advantage is that sampling variations in the estimates of model parameters and high quantiles are to a large extent reduced compared to the single-site analysis. We focus on the ‘region-of-influence’ (ROI) method which is based on the identification of unique pooling groups (forming the database for the estimation) for each site under study. The similarity of sites is evaluated in terms of a set of site attributes related to the distributions of extremes. The issue of the size of the region is linked with a built-in test on regional homogeneity of data. Once a pooling group is delineated, weights based on a dissimilarity measure are assigned to individual sites involved in a pooling group, and all (weighted) data are employed in the estimation of model parameters and high quantiles at a given location. The ROI method is compared with the Hosking-Wallis (HW) regional frequency analysis, which is based on delineating fixed regions (instead of flexible pooling groups) and assigning unit weights to all sites in a region. The comparison of the performance of the individual regional models makes use of data on annual maxima of 1-day precipitation amounts at 209 stations covering the Czech Republic, with altitudes ranging from 150 to 1490 m a.s.l. We conclude that the ROI methodology is superior to the HW analysis, particularly for very high quantiles (100-yr return values). Another advantage of the ROI approach is that subjective decisions - unavoidable when fixed regions in the HW analysis are formed - may efficiently be suppressed, and almost all settings of the ROI method may be justified by results of the simulation experiments. The differences between (any) regional method and single-site analysis are very pronounced and suggest that the at-site estimation is highly unreliable. The ROI method is then applied to estimate high quantiles of precipitation amounts at individual sites. The estimates and their uncertainty are compared with those from a single-site analysis. We focus on the eastern part of the Czech Republic, i.e. an area with complex orography and a particularly pronounced role of Mediterranean cyclones in producing precipitation extremes. The design values are compared with precipitation amounts recorded during the recent heavy precipitation events, including the one associated with the flash flood on June 24, 2009. We also show that the ROI methodology may easily be transferred to the analysis of precipitation extremes in climate model outputs. It efficiently reduces (random) variations in the estimates of parameters of the extreme value distributions in individual gridboxes that result from large spatial variability of heavy precipitation, and represents a straightforward tool for ‘weighting’ data from neighbouring gridboxes within the estimation procedure. The study is supported by the Grant Agency of AS CR under project B300420801.

What records have we been breaking?

USGS Publications Warehouse

Bartholow, J.M.; Milhous, R.

2002-01-01

"Today was another record-breaking day," the evening radio or television declares. High temperatures, low temperatures, floods, drought - take your choice. But how can we put these pronouncements in perspective? What do they really mean?We present two types of information in this article: 1) an analysis of daily air temperature and precipitation for Fort Collins and 2) an analysis of annual precipitation for Fort Collins. Each analysis provides a different meaning to the statement about a record-breaking day or year.

Comparison of NEXRAD multisensor precipitation estimates to rain gage observations in and near DuPage County, Illinois, 2002–12

USGS Publications Warehouse

Spies, Ryan R.; Over, Thomas M.; Ortel, Terry W.

2018-05-21

In this report, precipitation data from 2002 to 2012 from the hourly gridded Next-Generation Radar (NEXRAD)-based Multisensor Precipitation Estimate (MPE) precipitation product are compared to precipitation data from two rain gage networks—an automated tipping bucket network of 25 rain gages operated by the U.S. Geological Survey (USGS) and 51 rain gages from the volunteer-operated Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network—in and near DuPage County, Illinois, at a daily time step to test for long-term differences in space, time, and distribution. The NEXRAD–MPE data that are used are from the fifty 2.5-mile grid cells overlying the rain gages from the other networks. Because of the challenges of measuring of frozen precipitation, the analysis period is separated between days with or without the chance of freezing conditions. The NEXRAD–MPE and tipping-bucket rain gage precipitation data are adjusted to account for undercatch by multiplying by a previously determined factor of 1.14. Under nonfreezing conditions, the three precipitation datasets are broadly similar in cumulative depth and distribution of daily values when the data are combined spatially across the networks. However, the NEXRAD–MPE data indicate a significant trend relative to both rain gage networks as a function of distance from the NEXRAD radar just south of the study area. During freezing conditions, of the USGS network rain gages only the heated gages were considered, and these gages indicate substantial mean undercatch of 50 and 61 percent compared to the NEXRAD–MPE and the CoCoRaHS gages, respectively. The heated USGS rain gages also indicate substantially lower quantile values during freezing conditions, except during the most extreme (highest) events. Because NEXRAD precipitation products are continually evolving, the report concludes with a discussion of recent changes in those products and their potential for improved precipitation estimation. An appendix provides an analysis of spatially combined NEXRAD–MPE precipitation data as a function of temperature at an hourly time scale and indicates, among other results, that most precipitation in the study area occurs at moderate temperatures of 30 to 74 degrees Fahrenheit. However, when precipitation does occur, its intensity increases with temperature to about 86 degrees Fahrenheit.

What is the variability in US west coast winter precipitation during strong El Niño events?

NASA Astrophysics Data System (ADS)

Kumar, Arun; Chen, Mingyue

2017-10-01

Motivated by the fact that the spatial pattern of the observed precipitation anomalies during 2015/16 winter (a year of strong El Niño) over the west coast of the US and that of the El Niño composite precipitation pattern had considerable differences, the variability in the winter precipitation during strong El Niño events is assessed. The analysis is based on a set of hindcasts (1982-2011) and real-time forecasts (2012-2015) from NCEP Climate Forecast System version 2 (CFSv2), and the following aspects for seasonal mean precipitation variability were examined: (1) the mean signal during strong El Niño based on the composite analysis, and further, the variability from the composite on an event-to-event basis; (2) probability of occurrence for precipitation anomalies to be opposite to the signal (inferred as the composite mean); (3) the probability to have precipitation anomaly in different categories varying from wet to dry; and (4) variations in the characteristics of precipitation from OND, NDJ, to DJF (early to late boreal winter). The results show that the model forecasted seasonal mean precipitation composite for strong El Niño was similar to the linear regression signal with the Niño 3.4 index in observations, with negative anomalies over the Pacific Northwest and positive anomalies over California. However, although in response to an El Niño event, the California precipitation PDF was shifted towards positive values relative to the climatological PDF, the overlap between climatological PDF and the PDF for El Niño events was considerable. This is because of the large variability in seasonal mean outcomes of precipitation from one forecast to another, and therefore, chances to have precipitation anomalies with their sign opposite to the composite El Niño signal remain appreciable. In this paradigm, although the seasonal mean precipitation during 2015/16 winter over the west coast of the US differed from the mean signal for a strong El Niño event, the observed anomalies were well within the envelope of possible outcomes. This has significant implications for seasonal predictability and prediction skill, and further, poses challenges for decision makers in the uptake of seasonal forecast information.

On Mars' atmospheric sputtering after MAVEN first two years

NASA Astrophysics Data System (ADS)

Leblanc, F.; Modolo, R.; Curry, S.; Luhmann, J. G.; Lillis, R.; Chaufray, J. Y.; Hara, T.; McFadden, J.; Halekas, J.; Eparvier, F.; Larson, D.; Connerney, J.; Jakosky, B.

2017-09-01

Mars may have lost a significant part of its atmosphere into space along its history, in particular since the end of its internal dynamo, 4.1 Gyr ago. The sputtering of the atmosphere by precipitating planetary picked up ions accelerated by the solar wind is one of the processes that could have significantly contributed to this atmospheric escape. We here present a two years base analysis of MAVEN observation of the precipitating flux, in particular the dependency of the precipitating intensity with solar zenith angle and used this measurement to model the expected escape rate and exosphere induced by this precipitation.

Quantifying Main Trends in Lysozyme Nucleation: The Effects of Precipitant Concentration, Supersaturation and Impurities

NASA Technical Reports Server (NTRS)

Burke, Michael W.; Leardi, Riccardo; Judge, Russell A.; Pusey, Marc L.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

Full factorial experimental design incorporating multi-linear regression analysis of the experimental data allows quick identification of main trends and effects using a limited number of experiments. In this study these techniques were employed to identify the effect of precipitant concentration, supersaturation, and the presence of an impurity, the physiological lysozyme dimer, on the nucleation rate and crystal dimensions of the tetragonal forin of chicken egg white lysozyme. Decreasing precipitant concentration, increasing supers aturation, and increasing impurity, were found to increase crystal numbers. The crystal axial ratio decreased with increasing precipitant concentration, independent of impurity.

Surface complexation and precipitate geometry for aqueous Zn(II) sorption on ferrihydrite: II. XANES analysis and simulation

USGS Publications Warehouse

Waychunas, G.A.; Fuller, C.C.; Davis, J.A.; Rehr, J.J.

2003-01-01

X-ray absorption near-edge spectroscopy (XANES) analysis of sorption complexes has the advantages of high sensitivity (10- to 20-fold greater than extended X-ray absorption fine structure [EXAFS] analysis) and relative ease and speed of data collection (because of the short k-space range). It is thus a potentially powerful tool for characterization of environmentally significant surface complexes and precipitates at very low surface coverages. However, quantitative analysis has been limited largely to "fingerprint" comparison with model spectra because of the difficulty of obtaining accurate multiple-scattering amplitudes for small clusters with high confidence. In the present work, calculations of the XANES for 50- to 200-atom clusters of structure from Zn model compounds using the full multiple-scattering code Feff 8.0 accurately replicate experimental spectra and display features characteristic of specific first-neighbor anion coordination geometry and second-neighbor cation geometry and number. Analogous calculations of the XANES for small molecular clusters indicative of precipitation and sorption geometries for aqueous Zn on ferrihydrite, and suggested by EXAFS analysis, are in good agreement with observed spectral trends with sample composition, with Zn-oxygen coordination and with changes in second-neighbor cation coordination as a function of sorption coverage. Empirical analysis of experimental XANES features further verifies the validity of the calculations. The findings agree well with a complete EXAFS analysis previously reported for the same sample set, namely, that octahedrally coordinated aqueous Zn2+ species sorb as a tetrahedral complex on ferrihydrite with varying local geometry depending on sorption density. At significantly higher densities but below those at which Zn hydroxide is expected to precipitate, a mainly octahedral coordinated Zn2+ precipitate is observed. An analysis of the multiple scattering paths contributing to the XANES demonstrates the importance of scattering paths involving the anion sublattice. We also describe the specific advantages of complementary quantitative XANES and EXAFS analysis and estimate limits on the extent of structural information obtainable from XANES analysis. ?? 2003 Elsevier Science Ltd.

Heavy precipitation events in northern Switzerland

NASA Astrophysics Data System (ADS)

Giannakaki, Paraskevi; Martius, Olivia

2013-04-01

Heavy precipitation events in the Alpine region often cause floods, rock-falls and mud slides with severe consequences for population and economy. Breaking synoptic Rossby waves located over western Europe, play a central role in triggering such heavy rain events in southern Switzerland (e.g. Massacand et al. 1998). In contrast, synoptic scale structures triggering heavy precipitation on the north side of the Swiss Alps and orographic effects have so far not been studied comprehensively. An observation based high resolution precipitation data set for Switzerland and the Alps (MeteoSwiss) is used to identify heavy precipitation events affecting the north side of the Swiss Alps for the time period 1961-2010. For these events a detailed statistical and dynamical analysis of the upper level flow is conducted using ECMWFs ERA-40 and ERA-Interim reanalysis data sets. For the analysis north side of the Swiss Alps is divided in two investigation areas north-eastern and western Switzerland following the Swiss climate change scenarios (Bey et al. 2011). A subjective classification of upper level structures triggering heavy precipitation events in the areas of interest is presented. Four classes are defined based on the orientation and formation of the dynamical tropopause during extreme events in the northern part of Switzerland and its sub-regions. The analysis is extended by a climatology of breaking waves and cut-offs following the method of Wernli and Sprenger (2007) to examine their presence and location during extreme events. References Bey I., Croci-Maspoli M., Fuhrer J., Kull C, Appenzeller C., Knutti R. and Schär C. Swiss Climate Change Scenarios CH2011, C2SM, MeteoSwiss, ETH, NCCR Climate, OcCC (2011), http://dx.doi.org/10.3929/ethz-a-006720559 Massacand A., H. Wernli, and H.C. Davies, 1998. Heavy precipitation on the Alpine South side: An upper-level precursor. Geophys. Res. Lett., 25, 1435-1438. MeteoSwiss 2011. Documentation of Meteoswiss grid-data products, daily precipitation (final analysis): Rhiresd. Available at: http://www.meteosuisse.admin.ch/web/en/services/data_portal/gridded_datasets/precip.html Wernli. H., and M. Sprenger, 2007. Identification and ERA-15 climatology of potential vorticity streamers and cutoffs near the extratropical tropopause. J. Atmos. Sci., 64, 1569-1586.

Controls over spatial and seasonal variations on isotopic composition of the precipitation along the central and eastern portion of Brazil.

PubMed

Gastmans, Didier; Santos, Vinícius; Galhardi, Juliana Aparecida; Gromboni, João Felipe; Batista, Ludmila Vianna; Miotlinski, Konrad; Chang, Hung Kiang; Govone, José Silvio

2017-10-01

Based on Global Network Isotopes in Precipitation (GNIP) isotopic data set, a review of the spatial and temporal variability of δ 18 O and δ 2 H in precipitation was conducted throughout central and eastern Brazil, indicating that dynamic interactions between Intertropical and South Atlantic Convergence Zones, Amazon rainforest, and Atlantic Ocean determine the variations on the isotopic composition of precipitation over this area. Despite the seasonality and latitude effects observed, a fair correlation with precipitation amount was found. In addition, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) air mass back trajectories were used to quantify the factors controlling daily variability in stable isotopes in precipitation. Through a linear multiple regression analysis, it was observed that temporal variations were consistent with the meteorological parameters derived from HYSPLIT, particularly precipitation amount along the trajectory and mix depth, but are not dependent on vapour residence time in the atmosphere. These findings also indicate the importance of convective systems to control the isotopic composition of precipitation in tropical and subtropical regions.

Assessment of Drought Severity Using Normal Precipitation Index (Case Study: Sistan and Baluchistan Province)

NASA Astrophysics Data System (ADS)

Rahimi, D.; Movahedi, S.

2009-04-01

In the last decades, water crisis is one of the most important critical phenomenons in the environment planning and human society's management which affecting on development aspects in the international, national and regional levels. In this research, have been considered the Drought as the main parameter in water rare serious. For drought assessment, can treat the different methods, such as statistical model, meteorological and hydrological methods. In this research, have been used the Normal Precipitation index to meteorological analysis of drought severity in Sistan and Baluchistan province with high drought severity during recent years. According to the obtained result, the annual precipitation of studied area was between 36 to 52 percent more than mean precipitation of province. 10%-23 percent of precipitation amount involved the drought threshold border, 3%-13 percent of precipitations contain the weakness drought, 6.7% -23 percent were considered for moderate drought, 6%-20 percent involved the severe drought and ultimately, 6.7% to 23 percent of precipitations were considered as very severe drought. Keywords: Drought, Normal index, precipitation, Sistan and Baluchistan

Regional and local increases in storm intensity in the San Francisco Bay Area, USA, between 1890 and 2010

NASA Astrophysics Data System (ADS)

Russo, Tess A.; Fisher, Andrew T.; Winslow, Dustin M.

2013-04-01

Studies of extreme precipitation have documented changes at the continental scale during the twentieth century, but few studies have quantified changes at small to regional spatial scales during the same time. We analyze historic data from over 600 precipitation stations in the San Francisco Bay Area (SFBA), California, to assess whether there have been statistically significant changes in extreme precipitation between 1890 and 2010. An annual exceedance probability analysis of extreme precipitation events in the SFBA, coupled with a Markov chain Monte Carlo algorithm, reveals an increase in the occurrence of large events. The depth-duration-frequency characteristics of maximum annual precipitation events having durations of 1 h to 60 days indicate on average an increase in storm intensity in the last 120 years, with the intensity of the largest (least frequent) events increasing the most. Mean annual precipitation (MAP) also increased during the study period, but the relative increase in extreme event intensity exceeds that of MAP, indicating that a greater fraction of precipitation fell during large events. Analysis of data from subareas within the SFBA region indicates considerable heterogeneity in the observed nonstationarity; for example, the 5 day, 25 year event exceedance depth changed by +26%, +16%, and -1% in San Francisco, Santa Rosa, and San Jose, respectively. These results emphasize the importance of analyzing local data for accurate risk assessment, emergency planning, resource management, and climate model calibration.

Sensitive indicators of Stipa bungeana response to precipitation under ambient and elevated CO2 concentration

NASA Astrophysics Data System (ADS)

Shi, Yaohui; Zhou, Guangsheng; Jiang, Yanling; Wang, Hui; Xu, Zhenzhu

2018-02-01

Precipitation is a primary environmental factor in the semiarid grasslands of northern China. With increased concentrations of atmospheric greenhouse gases, precipitation regimes will change, and high-impact weather events may be more common. Currently, many ecophysiological indicators are known to reflect drought conditions, but these indicators vary greatly among species, and few studies focus on the applicability of these drought indicators under high CO2 conditions. In this study, five precipitation levels (- 30%, - 15%, control, + 15%, and + 30%) were used to simulate the effects of precipitation change on 18 ecophysiological characteristics in Stipa bungeana, including leaf area, plant height, leaf nitrogen (N), and chlorophyll content, among others. Two levels of CO2 concentration (ambient, 390 ppm; 550 ppm) were used to simulate the effects of elevated CO2 on these drought indicators. Using gray relational analysis and phenotypic plasticity analysis, we found that total leaf area or leaf number (morphology), leaf water potential or leaf water content (physiology), and aboveground biomass better reflected the water status of S. bungeana under ambient and elevated CO2 than the 13 other analyzed variables. The sensitivity of drought indicators changed under the elevated CO2 condition. By quantifying the relationship between precipitation and the five most sensitive indicators, we found that the thresholds of precipitation decreased under elevated CO2 concentration. These results will be useful for objective monitoring and assessment of the occurrence and development of drought events in S. bungeana grasslands.

Exploring New Pathways in Precipitation Assimilation

NASA Technical Reports Server (NTRS)

Hou, Arthur; Zhang, Sara Q.

2004-01-01

Precipitation assimilation poses a special challenge in that the forward model for rain in a global forecast system is based on parameterized physics, which can have large systematic errors that must be rectified to use precipitation data effectively within a standard statistical analysis framework. We examine some key issues in precipitation assimilation and describe several exploratory studies in assimilating rainfall and latent heating information in NASA's global data assimilation systems using the forecast model as a weak constraint. We present results from two research activities. The first is the assimilation of surface rainfall data using a time-continuous variational assimilation based on a column model of the full moist physics. The second is the assimilation of convective and stratiform latent heating retrievals from microwave sensors using a variational technique with physical parameters in the moist physics schemes as a control variable. We will show the impact of assimilating these data on analyses and forecasts. Among the lessons learned are (1) that the time-continuous application of moisture/temperature tendency corrections to mitigate model deficiencies offers an effective strategy for assimilating precipitation information, and (2) that the model prognostic variables must be allowed to directly respond to an improved rain and latent heating field within an analysis cycle to reap the full benefit of assimilating precipitation information. of microwave radiances versus retrieval information in raining areas, and initial efforts in developing ensemble techniques such as Kalman filter/smoother for precipitation assimilation. Looking to the future, we discuss new research directions including the assimilation

Projected change in East Asian summer monsoon by dynamic downscaling: Moisture budget analysis

NASA Astrophysics Data System (ADS)

Jung, Chun-Yong; Shin, Ho-Jeong; Jang, Chan Joo; Kim, Hyung-Jin

2015-02-01

The summer monsoon considerably affects water resource and natural hazards including flood and drought in East Asia, one of the world's most densely populated area. In this study, we investigate future changes in summer precipitation over East Asia induced by global warming through dynamical downscaling with the Weather Research and Forecast model. We have selected a global model from the Coupled Model Intercomparison Project Phase 5 based on an objective evaluation for East Asian summer monsoon and applied its climate change under Representative Concentration Pathway 4.5 scenario to a pseudo global warming method. Unlike the previous studies that focused on a qualitative description of projected precipitation changes over East Asia, this study tried to identify the physical causes of the precipitation changes by analyzing a local moisture budget. Projected changes in precipitation over the eastern foothills area of Tibetan Plateau including Sichuan Basin and Yangtze River displayed a contrasting pattern: a decrease in its northern area and an increase in its southern area. A local moisture budget analysis indicated the precipitation increase over the southern area can be mainly attributed to an increase in horizontal wind convergence and surface evaporation. On the other hand, the precipitation decrease over the northern area can be largely explained by horizontal advection of dry air from the northern continent and by divergent wind flow. Regional changes in future precipitation in East Asia are likely to be attributed to different mechanisms which can be better resolved by regional dynamical downscaling.

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

Li, X.J., E-mail: lixj@alum.imr.ac.cn

During the deposition of diamond films on Ti alloy substrates, titanium carbide is a common precipitated phase, preferentially formed at the interfacial region. However, in this case, the precipitation of an ordered structure of titanium carbide has not been reported. In our work, a long periodic ordered structure of TiC has been observed at the deposited diamond film/Ti alloy interface by high resolution transmission electron microscopy (HRTEM). The long periodic ordered structure is identified as 6H-type. The formation mechanism is revealed by comparative studies on the different structures of TiC precipitated under different diamond deposition conditions in terms of depositionmore » time, atmosphere and temperature. A large number of carbon vacancies in the interfacial precipitated TiC phase are verified through electron energy loss spectroscopy (EELS) quantification analysis. However, an ordered arrangement of these carbon vacancies occurs only when the interfacial stress is large enough to induce the precipitation of 6H-type TiC. The supplementary analysis by X-ray diffraction (XRD) further confirms that additional diffraction peaks presented in the XRD patterns are corresponding to the precipitation of 6H-type TiC. - Highlights: •Different structures of TiC are observed during deposited diamond on Ti alloy. •One is common NaCl structure, the other is periodic structure. •The periodic structure is identified as 6H-type by HRTEM. •Carbon vacancies are verified to always exist in the TiC phase. •The precipitation of 6H-type TiC is mainly affected by interfacial stress.« less

Changes in Large-Scale Atmospheric Circulation Associated with Increased Extreme Precipitation Events in the Northeast United States

NASA Astrophysics Data System (ADS)

Collow, A.; Bosilovich, M. G.; Koster, R. D.

2016-12-01

Over the past two decades a statistically significant increase in the frequency of summertime extreme precipitation events has been observed over the northeastern United States - the largest such increase in the US in terms of area and magnitude. In an effort to characterize synoptic scale patterns and changes to the atmospheric circulation associated with extreme precipitation events in this region, atmospheric fields from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) are composited on days that exceed the 90th percentile of precipitation from the CPC-Unified daily gauge-based precipitation observations. Changes over time in composites of sea level pressure, 500 hPa height, and the vertical profile of equivalent potential temperature indicate that the observed increase in extreme precipitation events is associated with extratropical cyclones, including cut off low pressure and frontal systems. Analysis of the Eady maximum growth rate, an indicator for storm tracks, shows that storms tracks in recent years have shifted southward. In addition, mean summertime transient meridional winds have decreased over time, slowing baroclinic systems and causing stationary systems to become more frequent, in agreement with previous studies examining blocking due to high pressure systems. The Atlantic Ocean provides a significant supply of moisture that converges over the region when a cyclonic circulation is situated to the south, and the statistically significant increase in Eady maximum growth rate over time there provides an increasingly improved thermodynamic environment for extreme precipitation events.

Winter Precipitation in North America and the Pacific-North America Pattern in GEOS-S2Sv2 Seasonal Hindcast

NASA Technical Reports Server (NTRS)

Li, Zhao; Molod, Andrea; Schubert, Siegfried

2018-01-01

Reliable prediction of precipitation remains one of the most pivotal and complex challenges in seasonal forecasting. Previous studies show that various large-scale climate modes, such as ENSO, PNA and NAO play significant role in winter precipitation variability over the Northern America. The influences are most pronounced in years of strong indices of such climate modes. This study evaluates model bias, predictability and forecast skills of monthly winter precipitation in GEOS5-S2S 2.0 retrospective forecast from 1981 to 2016, with emphasis on the forecast skill of precipitation over North America during the extreme events of ENSO, PNA and NAO by applying EOF and composite analysis.

The Sensitivity of Orographic Precipitation to Flow Direction

NASA Astrophysics Data System (ADS)

Mass, C.; Picard, L.

2015-12-01

An area of substantial interest is the sensitivity of orographic precipitation to the characteristics of the incoming flow and to the surrounding environment. Some studies have suggested substantial sensitivity of precipitation within individual river drainages for relatively small directional or stability variations of incoming flow. A characterization of such flow sensitivity would be of great value for hydrometeorological prediction, the determination of Probable Maximum Precipitation statistics, and for quantifying the uncertainty in precipitation and hydrological forecasts. To gain insight into this problem, an idealized version of the Weather Research and Forecasting (WRF) modeling system was created in which simulations are driven by a single vertical sounding, with the assumption of thermal wind balance. The actual terrain is used and the full physics complement of the modeling system. The presentation will show how precipitation over the Olympic Mountains of Washington State varies as flow direction changes. This analysis will include both the aggregate precipitation over the barrier and the precipitation within individual drainages or areas. The role of surrounding terrain and the nearby coastline are also examined by removing these features from simulations. Finally, the impact of varying flow stability and speed on the precipitation over this orographic feature will be described.

Using cloud and climate data to understand warm season hydrometeorology from diurnal to monthly timescales

NASA Astrophysics Data System (ADS)

Betts, A. K.; Tawfik, A. B.; Desjardins, R. L.

2016-12-01

We use 600 station years of hourly data from 14 stations on the Canadian Prairies to map the warm season hydrometeorology. The months from April (after snowmelt) to September, have a very similar coupling between surface thermodynamics and opaque cloud cover, which has been calibrated to give cloud radiative forcing. We can derive both the mean diurnal ranges and the diurnal imbalances as a function of opaque cloud cover. For the monthly diurnal climate, we compute the coupling coefficients with opaque cloud cover and lagged precipitation. In April the diurnal cycle climate has memory of precipitation back to freeze-up in November. During the growing season months of June, July and August, there is memory of precipitation back to March. Monthly mean temperature depends strongly on cloud but little on precipitation, while monthly mean mixing ratio depends on precipitation, but rather little on cloud. The coupling coefficients to cloud and precipitation change with increasing monthly precipitation anomaly. This observational climate analysis provides a firm basis for model evaluation.

Quantitative analysis of Bordeaux red wine precipitates by solid-state NMR: Role of tartrates and polyphenols.

PubMed

Prakash, Shipra; Iturmendi, Nerea; Grelard, Axelle; Moine, Virginie; Dufourc, Erick

2016-05-15

Stability of wines is of great importance in oenology matters. Quantitative estimation of dark red precipitates formed in Merlot and Cabernet Sauvignon wine from Bordeaux region for vintages 2012 and 2013 was performed during the oak barrel ageing process. Precipitates were obtained by placing wine at -4°C or 4°C for 2-6 days and monitored by periodic sampling during a one-year period. Spectroscopic identification of the main families of components present in the precipitate powder was performed with (13)C solid-state CPMAS NMR and 1D and 2D solution NMR of partially water re-solubilized precipitates. The study revealed that the amount of precipitate obtained is dependent on vintage, temperature and grape variety. Major components identified include potassium bitartrate, polyphenols, polysaccharides, organic acids and free amino acids. No evidence was found for the presence of proteins. The influence of main compounds found in the precipitates is discussed in relation to wine stability. Copyright © 2016. Published by Elsevier Ltd.

Emerging European winter precipitation pattern linked to atmospheric circulation changes over the North Atlantic region in recent decades

NASA Astrophysics Data System (ADS)

Ummenhofer, Caroline C.; Seo, Hyodae; Kwon, Young-Oh; Parfitt, Rhys; Brands, Swen; Joyce, Terrence M.

2017-08-01

Dominant European winter precipitation patterns over the past century, along with their associated extratropical North Atlantic circulation changes, are evaluated using cluster analysis. Contrary to the four regimes traditionally identified based on daily wintertime atmospheric circulation patterns, five distinct seasonal precipitation regimes are detected here. Recurrent precipitation patterns in each regime are linked to changes in atmospheric blocking, storm track, and sea surface temperatures across the North Atlantic region. Multidecadal variability in the frequency of the precipitation patterns reveals more (fewer) winters with wet conditions in northern (southern) Europe in recent decades and an emerging distinct pattern of enhanced wintertime precipitation over the northern British Isles. This pattern has become unusually common since the 1980s and is associated with changes in moisture transport and more frequent atmospheric river events. The observed precipitation changes post-1950 coincide with changes in storm track activity over the central/eastern North Atlantic toward the northern British Isles.

Model Errors in Simulating Precipitation and Radiation fields in the NARCCAP Hindcast Experiment

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, D. E.; Mearns, L. O.; Mattmann, C. A.; McGinnis, S. A.; Goodale, C. E.; Hart, A. F.; Crichton, D. J.

2012-12-01

The relationship between the model errors in simulating precipitation and radiation fields including the surface insolation and OLR, is examined from the multi-RCM NARCCAP hindcast experiment for the conterminous U.S. region. Findings in this study suggest that the RCM biases in simulating precipitation are related with those in simulating radiation fields. For a majority of RCMs participated in the NARCCAP hindcast experiment as well as their ensemble, the spatial pattern of the insolation bias is negatively correlated with that of the precipitation bias, suggesting that the biases in precipitation and surface insolation are systematically related, most likely via the cloud fields. The relationship varies according to seasons as well with stronger relationship between the simulated precipitation and surface insolation during winter. This suggests that the RCM biases in precipitation and radiation are related via cloud fields. Additional analysis on the RCM errors in OLR is underway to examine more details of this relationship.

Impact of condensed tannin size as individual and mixed polymers on bovine serum albumin precipitation.

PubMed

Harbertson, James F; Kilmister, Rachel L; Kelm, Mark A; Downey, Mark O

2014-10-01

Condensed tannins composed of epicatechin from monomer to octamer were isolated from cacao (Theobroma cacao, L.) seeds and added to bovine serum albumin (BSA) individually and combined as mixtures. When added to excess BSA the amount of tannin precipitated increased with tannin size. The amount of tannin required to precipitate BSA varied among the polymers with the trimer requiring the most to precipitate BSA (1000 μg) and octamer the least (50 μg). The efficacy of condensed tannins for protein precipitation increased with increased degree of polymerisation (or size) from trimers to octamers (monomers and dimers did not precipitate BSA), while mixtures of two sizes primarily had an additive effect. This study demonstrates that astringent perception is likely to increase with increasing polymer size. Further research to expand our understanding of astringent perception and its correlation with protein precipitation would benefit from sensory analysis of condensed tannins across a range of polymer sizes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Synoptic Conditions and Moisture Sources Actuating Extreme Precipitation in Nepal

NASA Astrophysics Data System (ADS)

Bohlinger, Patrik; Sorteberg, Asgeir; Sodemann, Harald

2017-12-01

Despite the vast literature on heavy-precipitation events in South Asia, synoptic conditions and moisture sources related to extreme precipitation in Nepal have not been addressed systematically. We investigate two types of synoptic conditions—low-pressure systems and midlevel troughs—and moisture sources related to extreme precipitation events. To account for the high spatial variability in rainfall, we cluster station-based daily precipitation measurements resulting in three well-separated geographic regions: west, central, and east Nepal. For each region, composite analysis of extreme events shows that atmospheric circulation is directed against the Himalayas during an extreme event. The direction of the flow is regulated by midtropospheric troughs and low-pressure systems traveling toward the respective region. Extreme precipitation events feature anomalous high abundance of total column moisture. Quantitative Lagrangian moisture source diagnostic reveals that the largest direct contribution stems from land (approximately 75%), where, in particular, over the Indo-Gangetic Plain moisture uptake was increased. Precipitation events occurring in this region before the extreme event likely provided additional moisture.

Application of physical scaling towards downscaling climate model precipitation data

NASA Astrophysics Data System (ADS)

Gaur, Abhishek; Simonovic, Slobodan P.

2018-04-01

Physical scaling (SP) method downscales climate model data to local or regional scales taking into consideration physical characteristics of the area under analysis. In this study, multiple SP method based models are tested for their effectiveness towards downscaling North American regional reanalysis (NARR) daily precipitation data. Model performance is compared with two state-of-the-art downscaling methods: statistical downscaling model (SDSM) and generalized linear modeling (GLM). The downscaled precipitation is evaluated with reference to recorded precipitation at 57 gauging stations located within the study region. The spatial and temporal robustness of the downscaling methods is evaluated using seven precipitation based indices. Results indicate that SP method-based models perform best in downscaling precipitation followed by GLM, followed by the SDSM model. Best performing models are thereafter used to downscale future precipitations made by three global circulation models (GCMs) following two emission scenarios: representative concentration pathway (RCP) 2.6 and RCP 8.5 over the twenty-first century. The downscaled future precipitation projections indicate an increase in mean and maximum precipitation intensity as well as a decrease in the total number of dry days. Further an increase in the frequency of short (1-day), moderately long (2-4 day), and long (more than 5-day) precipitation events is projected.

Geostatistical Study of Precipitation on the Island of Crete

NASA Astrophysics Data System (ADS)

Agou, Vasiliki D.; Varouchakis, Emmanouil A.; Hristopulos, Dionissios T.

2015-04-01

Understanding and predicting the spatiotemporal patterns of precipitation in the Mediterranean islands is an important topic of research, which is emphasized by alarming long-term predictions for increased drought conditions [4]. The analysis of records from drought-prone areas around the world has demonstrated that precipitation data are non-Gaussian. Typically, such data are fitted to the gamma distribution function and then transformed into a normalized index, the so-called Standardized Precipitation Index (SPI) [5]. The SPI can be defined for different time scales and has been applied to data from various regions [2]. Precipitation maps can be constructed using the stochastic method of Ordinary Kriging [1]. Such mathematical tools help to better understand the space-time variability and to plan water resources management. We present preliminary results of an ongoing investigation of the space-time precipitation distribution on the island of Crete (Greece). The study spans the time period from 1948 to 2012 and extends over an area of 8 336 km2. The data comprise monthly precipitation measured at 56 stations. Analysis of the data showed that the most severe drought occurred in 1950 followed by 1989, whereas the wettest year was 2002 followed by 1977. A spatial trend was observed with the spatially averaged annual precipitation in the West measured at about 450mm higher than in the East. Analysis of the data also revealed strong correlations between the precipitation in the western and eastern parts of the island. In addition to longitude, elevation (masl) was determined to be an important factor that exhibits strong linear correlation with precipitation. The precipitation data exhibit wet and dry periods with strong variability even during the wet period. Thus, fitting the data to specific probability distribution models has proved challenging. Different time scales, e.g. monthly, biannual, and annual have been investigated. Herein we focus on annual precipitation which are fitted locally to a three-parameter probability distribution, based on which a normalized index is derived. We use the Spartan variogram function to model space-time correlations, because it is more flexible than classical models [3]. The performance of the variogram model is tested by means of leave-one-out cross validation. The variogram model is then used in connection with ordinary kriging to generate precipitation maps for the entire island. In the future, we will explore the joint spatiotemporal evolution of precipitation patterns on Crete. References [1] P. Goovaerts. Geostatistical approaches for incorporating elevation into the spatial interpolation of precipitation. Journal of Hydrology, 228(1):113-129, 2000. [2] N. B. Guttman. Accepting the standardized precipitation index: a calculation algorithm. American Water Resource Association, 35(2):311-322, 1999. [3] D. T Hristopulos. Spartan Gibbs random field models for geostatistical applications. SIAM Journal on Scientific Computing, 24(6):2125-2162, 2003. [4] A.G. Koutroulis, A.-E.K. Vrohidou, and I.K. Tsanis. Spatiotemporal characteristics of meteorological drought for the island of Crete. Journal of Hydrometeorology, 12(2):206-226, 2011. [5] T. B. McKee, N. J. Doesken, and J. Kleist. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, page 179-184, Anaheim, California, 1993.

Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change

NASA Astrophysics Data System (ADS)

van der Wiel, Karin; Kapnick, Sarah B.; van Oldenborgh, Geert Jan; Whan, Kirien; Philip, Sjoukje; Vecchi, Gabriel A.; Singh, Roop K.; Arrighi, Julie; Cullen, Heidi

2017-02-01

A stationary low pressure system and elevated levels of precipitable water provided a nearly continuous source of precipitation over Louisiana, United States (US), starting around 10 August 2016. Precipitation was heaviest in the region broadly encompassing the city of Baton Rouge, with a 3-day maximum found at a station in Livingston, LA (east of Baton Rouge), from 12 to 14 August 2016 (648.3 mm, 25.5 inches). The intense precipitation was followed by inland flash flooding and river flooding and in subsequent days produced additional backwater flooding. On 16 August, Louisiana officials reported that 30 000 people had been rescued, nearly 10 600 people had slept in shelters on the night of 14 August and at least 60 600 homes had been impacted to varying degrees. As of 17 August, the floods were reported to have killed at least 13 people. As the disaster was unfolding, the Red Cross called the flooding the worst natural disaster in the US since Super Storm Sandy made landfall in New Jersey on 24 October 2012. Before the floodwaters had receded, the media began questioning whether this extreme event was caused by anthropogenic climate change. To provide the necessary analysis to understand the potential role of anthropogenic climate change, a rapid attribution analysis was launched in real time using the best readily available observational data and high-resolution global climate model simulations. The objective of this study is to show the possibility of performing rapid attribution studies when both observational and model data and analysis methods are readily available upon the start. It is the authors' aspiration that the results be used to guide further studies of the devastating precipitation and flooding event. Here, we present a first estimate of how anthropogenic climate change has affected the likelihood of a comparable extreme precipitation event in the central US Gulf Coast. While the flooding event of interest triggering this study occurred in south Louisiana, for the purposes of our analysis, we have defined an extreme precipitation event by taking the spatial maximum of annual 3-day inland maximum precipitation over the region of 29-31° N, 85-95° W, which we refer to as the central US Gulf Coast. Using observational data, we find that the observed local return time of the 12-14 August precipitation event in 2016 is about 550 years (95 % confidence interval (CI): 450-1450). The probability for an event like this to happen anywhere in the region is presently 1 in 30 years (CI 11-110). We estimate that these probabilities and the intensity of extreme precipitation events of this return time have increased since 1900. A central US Gulf Coast extreme precipitation event has effectively become more likely in 2016 than it was in 1900. The global climate models tell a similar story; in the most accurate analyses, the regional probability of 3-day extreme precipitation increases by more than a factor of 1.4 due to anthropogenic climate change. The magnitude of the shift in probabilities is greater in the 25 km (higher-resolution) climate model than in the 50 km model. The evidence for a relation to El Niño half a year earlier is equivocal, with some analyses showing a positive connection and others none.

Constraining Aerosol-Cloud-Precipitation Interactions of Orographic Mixed-Phase Clouds with Trajectory Budgets

NASA Astrophysics Data System (ADS)

Glassmeier, F.; Lohmann, U.

2016-12-01

Orographic precipitation is prone to strong aerosol-cloud-precipitation interactions because the time for precipitation development is limited to the ascending section of mountain flow. At the same time, cloud microphysical development is constraint by the strong dynamical forcing of the orography. In this contribution, we discuss how changes in the amount and composition of droplet- and ice-forming aerosols influence precipitation in idealized simulations of stratiform orographic mixed-phase clouds. We find that aerosol perturbations trigger compensating responses of different precipitation formation pathways. The effect of aerosols is thus buffered. We explain this buffering by the requirement to fulfill aerosol-independent dynamical constraints. For our simulations, we use the regional atmospheric model COSMO-ART-M7 in a 2D setup with a bell-shaped mountain. The model is coupled to a 2-moment warm and cold cloud microphysics scheme. Activation and freezing rates are parameterized based on prescribed aerosol fields that are varied in number, size and composition. Our analysis is based on the budget of droplet water along trajectories of cloud parcels. The budget equates condensation as source term with precipitation formation from autoconversion, accretion, riming and the Wegener-Bergeron-Findeisen process as sink terms. Condensation, and consequently precipitation formation, is determined by dynamics and largely independent of the aerosol conditions. An aerosol-induced change in the number of droplets or crystals perturbs the droplet budget by affecting precipitation formation processes. We observe that this perturbation triggers adjustments in liquid and ice water content that re-equilibrate the budget. As an example, an increase in crystal number triggers a stronger glaciation of the cloud and redistributes precipitation formation from collision-coalescence to riming and from riming to vapor deposition. We theoretically confirm the dominant effect of water content adjustments over number changes by estimating susceptibilities d ln P / d ln N of precipitation formation P to droplet or crystal number N from the budget equation. The susceptibility analysis also reveals that aerosol perturbations to droplet and crystal number compensate each other.

Influences of Local Sea-Surface Temperatures and Large-scale Dynamics on Monthly Precipitation Inferred from Two 10-year GCM-Simulations

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.; Zhou, Y.; Lau, W. K.-M.

2007-01-01

Two parallel sets of 10-year long: January 1, 1982 to December 31, 1991, simulations were made with the finite volume General Circulation Model (fvGCM) in which the model integrations were forced with prescribed sea-surface temperature fields (SSTs) available as two separate SST-datasets. One dataset contained naturally varying monthly SSTs for the chosen period, and the oth& had the 12-monthly mean SSTs for the same period. Plots of evaporation, precipitation, and atmosphere-column moisture convergence, binned by l C SST intervals show that except for the tropics, the precipitation is more strongly constrained by large-scale dynamics as opposed to local SST. Binning data by SST naturally provided an ensemble average of data contributed from disparate locations with same SST; such averages could be expected to mitigate all location related influences. However, the plots revealed: i) evaporation, vertical velocity, and precipitation are very robust and remarkably similar for each of the two simulations and even for the data from 1987-ENSO-year simulation; ii) while the evaporation increased monotonically with SST up to about 27 C, the precipitation did not; iii) precipitation correlated much better with the column vertical velocity as opposed to SST suggesting that the influence of dynamical circulation including non-local SSTs is stronger than local-SSTs. The precipitation fields were doubly binned with respect to SST and boundary-layer mass and/or moisture convergence. The analysis discerned the rate of change of precipitation with local SST as a sum of partial derivative of precipitation with local SST plus partial derivative of precipitation with boundary layer moisture convergence multiplied by the rate of change of boundary-layer moisture convergence with SST (see Eqn. 3 of Section 4.5). This analysis is mathematically rigorous as well as provides a quantitative measure of the influence of local SST on the local precipitation. The results were recast to examine the dependence of local rainfall on local SSTs; it was discernible only in the tropics. Our methodology can be used for computing relationship between any forcing function and its effect(s) on a chosen field.

GNSS Polarimetric Radio Occultations: Thermodynamical Structure of pecipitating clouds

NASA Astrophysics Data System (ADS)

De La Torre Juarez, M.; Padulles, R.; Cardellach, E.; Turk, F. J.; Tomás, S.; Ao, C. O.

2016-12-01

Recent analysis of changes in the hydrological sensitivity during a recent weakening of transient warming show that the representation of the processes linking the condensation of water vapor and the growth and invigoration of convective precipitation produce the greatest disparities between cloud resolving models and current observations of convective cloud systems. The temperature and moisture structure of a cloud environment is the main control on the thermodynamical processes leading to the development of precipitation. The surrounding environmental state acts as the broader sink and source for moisture exchange between clouds and their surroundings. As precipitation develops, water vapor condensation leads to an evolving 3D temperature and moisture structure in and near clouds different from the larger scale structure or the clear-sky environment. Yet there is a gap in existing space-based observations since conventional IR and microwave sounding data are degraded in the presence of clouds and precipitation. GNSS radio occultations (RO) are a low-cost approach to sounding the global atmosphere with high precision, accuracy and vertical resolution inside clouds and across land-ocean boundaries. GNSS provides reliable, sustained signal sources. While current RO provide no direct information on the associated precipitation state, a recently studied concept of Polarimetric RO (PRO) can characterize the moist thermodynamics within precipitating systems. Since precipitation-sized hydrometeors are non-spherically shaped, precipitation induces a cross-polarized component during propagation through clouds, recorded by a dual-channel RO receiver as a differential phase shift. Theoretical analysis performed using coincident TRMM Precipitation Radar and COSMIC observations shows that the polarimetric phase shift is sensitive to the path-integrated rain rate. Based on the expected signal-to-noise ratio (SNR) of simulated PRO measurements, the precision of the differential phase signal averaged over 1-sec has been estimated greater than 1.5 mm, with rain rates exceeding 5 mm hr-1 detectable above the instrument noise level 90% of the time. We present the technique and show analyses that prove its potential to characterize the lapse rate inside precipitating vs. non-precipitating clouds.

Parametric Sensitivity Analysis for the Asian Summer Monsoon Precipitation Simulation in the Beijing Climate Center AGCM Version 2.1

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

Yang, Ben; Zhang, Yaocun; Qian, Yun

In this study, we apply an efficient sampling approach and conduct a large number of simulations to explore the sensitivity of the simulated Asian summer monsoon (ASM) precipitation, including the climatological state and interannual variability, to eight parameters related to the cloud and precipitation processes in the Beijing Climate Center AGCM version 2.1 (BCC_AGCM2.1). Our results show that BCC_AGCM2.1 has large biases in simulating the ASM precipitation. The precipitation efficiency and evaporation coefficient for deep convection are the most sensitive parameters in simulating the ASM precipitation. With optimal parameter values, the simulated precipitation climatology could be remarkably improved, e.g. increasedmore » precipitation over the equator Indian Ocean, suppressed precipitation over the Philippine Sea, and more realistic Meiyu distribution over Eastern China. The ASM precipitation interannual variability is further analyzed, with a focus on the ENSO impacts. It shows the simulations with better ASM precipitation climatology can also produce more realistic precipitation anomalies during El Niño decaying summer. In the low-skill experiments for precipitation climatology, the ENSO-induced precipitation anomalies are most significant over continents (vs. over ocean in observation) in the South Asian monsoon region. More realistic results are derived from the higher-skill experiments with stronger anomalies over the Indian Ocean and weaker anomalies over India and the western Pacific, favoring more evident easterly anomalies forced by the tropical Indian Ocean warming and stronger Indian Ocean-western Pacific tele-connection as observed. Our model results reveal a strong connection between the simulated ASM precipitation climatological state and interannual variability in BCC_AGCM2.1 when key parameters are perturbed.« less

High Resolution Hydro-climatological Projections for Western Canada

NASA Astrophysics Data System (ADS)

Erler, Andre Richard

Accurate identification of the impact of global warming on water resources and hydro-climatic extremes represents a significant challenge to the understanding of climate change on the regional scale. Here an analysis of hydro-climatic changes in western Canada is presented, with specific focus on the Fraser and Athabasca River basins and on changes in hydro-climatic extremes. The analysis is based on a suite of simulations designed to characterize internal variability, as well as model uncertainty. A small ensemble of Community Earth System Model version 1 (CESM1) simulations was employed to generate global climate projections, which were downscaled to 10 km resolution using the Weather Research and Forecasting model (WRF V3.4.1) with several sets of physical parameterizations. Downscaling was performed for a historical validation period and a mid- and end-21st-century projection period, using the RCP8.5 greenhouse gas trajectory. Daily station observations and monthly gridded datasets were used for validation. Changes in hydro-climatic extremes are characterized using Extreme Value Analysis. A novel method of aggregating data from climatologically similar stations was employed to increase the statistical power of the analysis. Changes in mean and extreme precipitation are found to differ strongly between seasons and regions, but (relative) changes in extremes generally follow changes in the (seasonal) mean. At the end of the 21st century, precipitation and precipitation extremes are projected to increase by 30% at the coast in fall and land-inwards in winter, while the projected increase in summer precipitation is smaller and changes in extremes are often not statistically significant. Reasons for the differences between seasons, the role of precipitation recycling in atmospheric water transport, and the sensitivity to physics parameterizations are discussed. Major changes are projected for the Fraser River basin, including earlier snowmelt and a 50% reduction in peak runoff. Combined with higher evapotranspiration, a significant increase in late summer drought risk is likely, but increasing fall precipitation might also increase the risk of moderate flooding. In the Athabasca River basin, increasing winter precipitation and snowmelt is balanced by increasing evapotranspiration in summer and no significant change in flood or drought risk is projected.

South Asian monsoon precipitation in CMIP 5: a link between inter-model spread and the representations of tropical convection

DOE PAGES

Hagos, Samson; Leung, L. Ruby; Ashfaq, Moetasim; ...

2018-03-20

CMIP 5 models exhibit a mean dry bias and a large inter-model spread in simulating South Asian monsoon precipitation but the origins of the bias and spread are not well understood. Using moisture and energy budget analysis that exploits the weak temperature gradients in the tropics, we derived a non-linear relationship between the normalized precipitation and normalized precipitable water that is similar to the non-linear relationship between precipitation and precipitable water found in previous observational studies. About half of the 21 models analyzed fall in the steep gradient of the non-linear relationship where small differences in the normalized precipitable watermore » in the equatorial Indian Ocean (EIO) manifest in large differences in normalized precipitation in the region. Models with larger normalized precipitable water in the EIO during spring contribute disproportionately to the large inter-model spread and multi-model mean dry bias in monsoon precipitation through perturbations of the large-scale winds. Thus the intermodel spread in precipitable water over EIO leads to the dry bias in the multi-model mean South Asian monsoon precipitation. The models with high normalized precipitable water over EIO also project larger response to warming and dominate the inter-model spread in the multi-model projections of monsoon rainfall. Conversely, models on the flat side of the relationship between normalized precipitation and precipitable water are in better agreement with each other and with observations. On average these models project a smaller increase in the projected monsoon precipitation than that from multi-model mean. As a result, this study identified the normalized precipitable water over EIO, which is determined by the relationship between the profiles of convergence and moisture and therefore is an essential outcome of the treatment of convection, as a key metric for understanding model biases and differentiating model skill in simulating South Asian monsoon precipitation.« less

South Asian monsoon precipitation in CMIP 5: a link between inter-model spread and the representations of tropical convection

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

Hagos, Samson; Leung, L. Ruby; Ashfaq, Moetasim

CMIP 5 models exhibit a mean dry bias and a large inter-model spread in simulating South Asian monsoon precipitation but the origins of the bias and spread are not well understood. Using moisture and energy budget analysis that exploits the weak temperature gradients in the tropics, we derived a non-linear relationship between the normalized precipitation and normalized precipitable water that is similar to the non-linear relationship between precipitation and precipitable water found in previous observational studies. About half of the 21 models analyzed fall in the steep gradient of the non-linear relationship where small differences in the normalized precipitable watermore » in the equatorial Indian Ocean (EIO) manifest in large differences in normalized precipitation in the region. Models with larger normalized precipitable water in the EIO during spring contribute disproportionately to the large inter-model spread and multi-model mean dry bias in monsoon precipitation through perturbations of the large-scale winds. Thus the intermodel spread in precipitable water over EIO leads to the dry bias in the multi-model mean South Asian monsoon precipitation. The models with high normalized precipitable water over EIO also project larger response to warming and dominate the inter-model spread in the multi-model projections of monsoon rainfall. Conversely, models on the flat side of the relationship between normalized precipitation and precipitable water are in better agreement with each other and with observations. On average these models project a smaller increase in the projected monsoon precipitation than that from multi-model mean. As a result, this study identified the normalized precipitable water over EIO, which is determined by the relationship between the profiles of convergence and moisture and therefore is an essential outcome of the treatment of convection, as a key metric for understanding model biases and differentiating model skill in simulating South Asian monsoon precipitation.« less

Copper Oxide Precipitates in NBS Standard Reference Material 482

PubMed Central

Windsor, Eric S.; Carlton, Robert A.; Gillen, Greg; Wight, Scott A.; Bright, David S.

2002-01-01

Copper oxide has been detected in the copper containing alloys of NBS Standard Reference Material (SRM) 482. This occurrence is significant because it represents heterogeneity within a standard reference material that was certified to be homogeneous on a micrometer scale. Oxide occurs as elliptically to spherically shaped precipitates whose size differs with alloy composition. The largest precipitates occur in the Au20-Cu80 alloy and range in size from submicrometer up to 2 μm in diameter. Precipitates are observed using light microscopy, electron microscopy, and secondary ion mass spectrometry (SIMS). SIMS has demonstrated that the precipitates are present within all the SRM 482 wires that contain copper. Only the pure gold wire is precipitate free. Initial results from the analysis of the Au20-Cu80 alloy indicate that the percentage of precipitates is less than 1 % by area. Electron probe microanalysis (EPMA) of large (2 μm) precipitates in this same alloy indicates that precipitates are detectable by EPMA and that their composition differs significantly from the certified alloy composition. The small size and low percentage of these oxide precipitates minimizes the impact that they have upon the intended use of this standard for electron probe microanalysis. Heterogeneity caused by these oxide precipitates may however preclude the use of this standard for automated EPMA analyses and other microanalysis techniques. PMID:27446759

Effects of combined silicon and molybdenum alloying on the size and evolution of microalloy precipitates in HSLA steels containing niobium and titanium

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

Pavlina, Erik J., E-mail: e.pavlina@deakin.edu.au; Van Tyne, C.J.; Speer, J.G.

2015-04-15

The effects of combined silicon and molybdenum alloying additions on microalloy precipitate formation in austenite after single- and double-step deformations below the austenite no-recrystallization temperature were examined in high-strength low-alloy (HSLA) steels microalloyed with titanium and niobium. The precipitation sequence in austenite was evaluated following an interrupted thermomechanical processing simulation using transmission electron microscopy. Large (~ 105 nm), cuboidal titanium-rich nitride precipitates showed no evolution in size during reheating and simulated thermomechanical processing. The average size and size distribution of these precipitates were also not affected by the combined silicon and molybdenum additions or by deformation. Relatively fine (< 20more » nm), irregular-shaped niobium-rich carbonitride precipitates formed in austenite during isothermal holding at 1173 K. Based upon analysis that incorporated precipitate growth and coarsening models, the combined silicon and molybdenum additions were considered to increase the diffusivity of niobium in austenite by over 30% and result in coarser precipitates at 1173 K compared to the lower alloyed steel. Deformation decreased the size of the niobium-rich carbonitride precipitates that formed in austenite. - Highlights: • We examine combined Si and Mo additions on microalloy precipitation in austenite. • Precipitate size tends to decrease with increasing deformation steps. • Combined Si and Mo alloying additions increase the diffusivity of Nb in austenite.« less

Precipitable water vapor budget associated with MJO represented in newly-released JRA-55 reanalysis data

NASA Astrophysics Data System (ADS)

Yokoi, S.

2013-12-01

The Japan Meteorological Agency (JMA) recently released a new reanalysis dataset JRA-55 with the use of a JMA operational prediction model and 4D-VAR data assimilation. To evaluate merit in utilizing the JRA-55 dataset to investigate dynamics of the tropical intraseasonal variability (ISV) including the Madden-Julian Oscillation (MJO), this study examines ISV-scale precipitable water vapor (PWV) budget over the period 1989-2012. The ISV-scale PWV anomaly related to the boreal-winter MJO propagates eastward along with precipitation, consistent with the SSM/I PWV product. Decomposition of the PWV tendency into that simulated by the model and the analysis increment estimated by the data assimilation reveals that the model makes the PWV anomaly move eastward. On the other hand, the analysis increment exhibits positive values over the area where the PWV anomaly is positive, indicating that the model tends to damp the MJO signal. Note that the analysis increment over the Maritime Continent has comparable magnitude to the model tendency. The positive analysis increment may mainly be caused by an excess of precipitation anomaly with respect to the magnitude of PWV anomaly. In addition to the boreal-winter MJO, this study also examines the PWV budget associated with northward-propagating ISV during the boreal summer and find similar relationship between the PWV anomaly and analysis increment.

The New 20-Year Global Precipitation Climatology Project (GPCP) Merged Satellite and Rainguage Monthly Analysis

NASA Technical Reports Server (NTRS)

Adler, Robert; Huffman, George; Xie, Ping Ping; Rudolf, Bruno; Gruber, Arnold; Janowiak, John

1999-01-01

A new 20-year, monthly, globally complete precipitation analysis has been completed as part of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP). This Version 2 of the community generated data set is a result of combining the procedures and data sets as described. The global, monthly, 2.5x 2.5 degree latitude-longitude product utilizes precipitation estimates from low-orbit microwave sensors (SSM/1) and geosynchronous IR sensors and raingauge information over land. The low-orbit microwave estimates are used to adjust or correct the geosynchronous IR estimates, thereby maximizing the utility of the more physically-based microwave estimates and the finer time sampling of the geosynchronous observations. Information from raingauges is blended into the analyses over land. In the 1986-present period TOVS-based precipitation estimates are adjusted to GPCP fields and used in polar regions to produce globally-complete results. The extension back to 1979 utilizes the procedures of Xie and Arkin and their OLR Precipitation Index (OPI). The 20-year climatology of the Version 2 GPCP analysis indicates the expected features of a very strong Pacific Ocean ITCZ and SPCZ with maximum 20-year means approaching 10 mm/day. A similar strength maximum over land is evident over Borneo. Weaker maxima in the tropics occur in the Atlantic ITCZ and over South America and Africa. In mid-latitudes of the Northern Hemisphere the Western Pacific and Western Atlantic maxima have values of approximately 7 mm/day, while in the Southern Hemisphere the mid-latitude maxima are located southeast of Africa, in mid-Pacific as an extension of the SPCZ and southeast of South America. In terms of global totals the GPCP analysis shows 2.7 mm/day (3.0 mm/day over ocean; 2.1 mm/day over land), similar to the Jaeger climatology, but not other climatologies. Zonal averages peak at 6 mm/day at 7*N with mid-latitude peaks of about 3 mm/day at 40-45* latitude. Poleward of 45* the GPCP analysis shows larger zonally-averaged values than most previous satellite-based estimates, although the values are similar to tl,ie Jaeger climatology. Over both ocean areas and at high latitudes the analysis requires additional validation and comparison with special, independent data sets from field experiments and from the Tropical Rain Measuring Mission (TRMM) to confirm the absolute magnitude and variations of precipitation seen in the analysis. Interannual and other variations of the global fields will be shown focusing on the recent ('97-'99) ENSO event compared with previous events, including teleconnections at mid and high latitudes. An ENSO Precipitation Index (ESPI) calculated using the new data set will be described and related to the evolution of the ENSO events during the 20-year period.

Study of lithium extraction from brine water, Bledug Kuwu, Indonesia by the precipitation series of oxalic acid and carbonate sodium

NASA Astrophysics Data System (ADS)

Sulistiyono, Eko; Lalasari, Latifa Hanum; Mayangsari, W.; Prasetyo, A. B.

2018-05-01

Lithium is one of the key elements in the development of batteries for electric car applications. Currently, the resources of the world's lithium are derived from brine water and lithium mineral based on spodumene rock. Indonesia which is located in the area of the ring of fire, has potential brine water resources in some area, such as brine water from Bledug Kuwu, Central Java that used in this research. The purposes of this research are to characterize brine water, Bledug Kuwu and to investigate the influence of chemical solvents on Li, Na, K, Ca, Mg, Al, B ion precipitation from brine water. This research was done with 2 times the process of chemical precipitation that runs series as follows: 5 liters of brine water were chemically precipitated using 400 ml of 12.43 N oxalic acid and followed by chemical precipitation using 400 mL of 7.07 N sodium carbonate solutions. Evaporation and filtration processes were also done twice in an effort to separate white precipitate and filtrate. The filtrate was analyzed by ICP-OES and white precipitates (salts) were analyzed by SEM, XRD, and XRF. The result shows that oxalate precipitation process extracted 32.24% Al, 23.42% B, 22.43% Ca, 14.26% Fe, 3.21 % K, 9.86% Na and 14.26% Li, the following process by carbonate precipitation process extracted 98.86% Mg, 73% Ca, 22.53% Li, 82.04% Al, 14.38% B, 12.50% K, 2.27% Na. There is 63.21% lithium is not extracted from the series process. The SEM analysis shows that the structure of granules on the precipitated salts by oxalic acid form gentle cubic-shaped solid. In the other hand, oxalate precipitation followed by sodium carbonate has various particle sizes and the shape of crystals is fragments, prism and cube look like magnesium carbonate, calcium chloride, and calcite's crystal respectively. This is in accordance with XRD analysis that phases of whewellite (CaC2O4.H2O), disodium oxalate (Na2C2O4), magnesite (MgCO3), calcium lithium aluminum (Al1.19 Ca1Li0.81), dolomite (CaCO3.MgCO3) appear in salt precipitated by oxalic acid. For salt precipitated by oxalic acid and sodium carbonate look peaks of dolomite and calcite (CaCO3) as main components. Lithium carbonate (Li2CO3) and calcium chloride (CaCl2) also are described with high peak intensity in this precipitation. A series of precipitation process shows that lithium is precipitated together with calcium, aluminum, and carbonate.

Precipitation Retrievals in typhoon domain combining of FY3C MWHTS Observations and WRF Predicted Models

NASA Astrophysics Data System (ADS)

Jieying, HE; Shengwei, ZHANG; Na, LI

2017-02-01

A passive sub-millimeter precipitation retrievals algorithm is provided based on Microwave Humidity and Temperature Sounder (MWHTS) onboard the Chinese Feng Yun 3C (FY-3C) satellite. Using the validated global reference physical model NCEP/WRF/VDISORT), NCEP data per 6 hours are downloaded to run the Weather Research and Forecast model WRF, and derive the typical precipitation data from the whole world. The precipitation retrieval algorithm can operate either on land or on seawater for global. To simply the calculation procedure and save the training time, principle component analysis (PCA) was adapted to filter out the redundancy caused by scanning angle and surface effects, as well as system noise. According to the comparison and validation combing with other precipitation sources, it is demonstrated that the retrievals are reliable for surface precipitation rate higher than 0.1 mm/h at 15km resolution.

Effective removal of coordinated copper from wastewater using a new dithiocarbamate-type supramolecular heavy metal precipitant.

PubMed

Fu, Fenglian; Zeng, Haiyan; Cai, Qinhong; Qiu, Rongliang; Yu, Jimmy; Xiong, Ya

2007-11-01

A new dithiocarbamate-type heavy metal precipitant, sodium 1,3,5-hexahydrotriazinedithiocarbamate (HTDC), was prepared and used to remove coordinated copper from wastewater. In the reported dithiocarbamate-type precipitants, HTDC possesses the highest percentage of the effective functional groups. It could effectively precipitate copper to less than 0.5mgl(-1) from both synthetic and actual industrial wastewater containing CuEDTA in the range of pH 3-9. UV-vis spectral investigation and elemental analysis suggested that the precipitate was a kind of coordination supramolecular compound, [Cu(3)(HTDC)(2)](n). The toxicity characteristic leaching procedure (TCLP) and semi-dynamic leaching test (SDLT) indicated that the supramolecular precipitate was non-hazardous and stable in weak acid and alkaline conditions. Tests of an anion exchange resin D231 provided a clue to simultaneously remove excess HTDC and residual CuEDTA in practical process of wastewater treatment.

Linking a completely three-dimensional nanostrain to a structural transformation eigenstrain.

PubMed

Tirry, Wim; Schryvers, Dominique

2009-09-01

Ni-Ti is one of the most popular shape-memory alloys, a phenomenon resulting from a martensitic transformation. Commercial Ni-Ti-based alloys are often thermally treated to contain Ni(4)Ti(3) precipitates. The presence of these precipitates can introduce an extra transformation step related to the so-called R-phase. It is believed that the strain field surrounding the precipitates, caused by the matrix-precipitate lattice mismatch, lies at the origin of this intermediate transformation step. Atomic-resolution transmission electron microscopy in combination with geometrical phase analysis is used to measure the elastic strain field surrounding these precipitates. By combining measurements from two different crystallographic directions, the three-dimensional strain matrix is determined from two-dimensional measurements. Comparison of the measured strain matrix to the eigenstrain of the R-phase shows that both are very similar and that the introduction of the R-phase might indeed compensate the elastic strain introduced by the precipitate.

Linking a completely three-dimensional nanostrain to a structural transformation eigenstrain

NASA Astrophysics Data System (ADS)

Tirry, Wim; Schryvers, Dominique

2009-09-01

Ni-Ti is one of the most popular shape-memory alloys, a phenomenon resulting from a martensitic transformation. Commercial Ni-Ti-based alloys are often thermally treated to contain Ni4Ti3 precipitates. The presence of these precipitates can introduce an extra transformation step related to the so-called R-phase. It is believed that the strain field surrounding the precipitates, caused by the matrix-precipitate lattice mismatch, lies at the origin of this intermediate transformation step. Atomic-resolution transmission electron microscopy in combination with geometrical phase analysis is used to measure the elastic strain field surrounding these precipitates. By combining measurements from two different crystallographic directions, the three-dimensional strain matrix is determined from two-dimensional measurements. Comparison of the measured strain matrix to the eigenstrain of the R-phase shows that both are very similar and that the introduction of the R-phase might indeed compensate the elastic strain introduced by the precipitate.

Inventory of File sref_nmm.t03z.pgrb221.p1.f00.grib2

Science.gov Websites

ground VGRD analysis V-Component of Wind [m/s] 015 surface WEASD analysis Water Equivalent of Accumulated day acc f Convective Precipitation [kg/m^2] 018 surface WEASD 0-0 day acc f Water Equivalent of Potential Temperature [K] 403 surface NCPCP 0-0 day acc f Large-Scale Precipitation (non-convective) [kg/m^2

Inventory of File sref_nmb.t03z.pgrb221.p1.f00.grib2

Science.gov Websites

ground VGRD analysis V-Component of Wind [m/s] 015 surface WEASD analysis Water Equivalent of Accumulated day acc f Convective Precipitation [kg/m^2] 018 surface WEASD 0-0 day acc f Water Equivalent of Potential Temperature [K] 403 surface NCPCP 0-0 day acc f Large-Scale Precipitation (non-convective) [kg/m^2

Use of artificial neural network for spatial rainfall analysis

NASA Astrophysics Data System (ADS)

Paraskevas, Tsangaratos; Dimitrios, Rozos; Andreas, Benardos

2014-04-01

In the present study, the precipitation data measured at 23 rain gauge stations over the Achaia County, Greece, were used to estimate the spatial distribution of the mean annual precipitation values over a specific catchment area. The objective of this work was achieved by programming an Artificial Neural Network (ANN) that uses the feed-forward back-propagation algorithm as an alternative interpolating technique. A Geographic Information System (GIS) was utilized to process the data derived by the ANN and to create a continuous surface that represented the spatial mean annual precipitation distribution. The ANN introduced an optimization procedure that was implemented during training, adjusting the hidden number of neurons and the convergence of the ANN in order to select the best network architecture. The performance of the ANN was evaluated using three standard statistical evaluation criteria applied to the study area and showed good performance. The outcomes were also compared with the results obtained from a previous study in the area of research which used a linear regression analysis for the estimation of the mean annual precipitation values giving more accurate results. The information and knowledge gained from the present study could improve the accuracy of analysis concerning hydrology and hydrogeological models, ground water studies, flood related applications and climate analysis studies.

A hybrid orographic plus statistical model for downscaling daily precipitation in Northern California

USGS Publications Warehouse

Pandey, G.R.; Cayan, D.R.; Dettinger, M.D.; Georgakakos, K.P.

2000-01-01

A hybrid (physical-statistical) scheme is developed to resolve the finescale distribution of daily precipitation over complex terrain. The scheme generates precipitation by combining information from the upper-air conditions and from sparsely distributed station measurements; thus, it proceeds in two steps. First, an initial estimate of the precipitation is made using a simplified orographic precipitation model. It is a steady-state, multilayer, and two-dimensional model following the concepts of Rhea. The model is driven by the 2.5?? ?? 2.5?? gridded National Oceanic and Atmospheric Administration-National Centers for Environmental Prediction upper-air profiles, and its parameters are tuned using the observed precipitation structure of the region. Precipitation is generated assuming a forced lifting of the air parcels as they cross the mountain barrier following a straight trajectory. Second, the precipitation is adjusted using errors between derived precipitation and observations from nearby sites. The study area covers the northern half of California, including coastal mountains, central valley, and the Sierra Nevada. The model is run for a 5-km rendition of terrain for days of January-March over the period of 1988-95. A jackknife analysis demonstrates the validity of the approach. The spatial and temporal distributions of the simulated precipitation field agree well with the observed precipitation. Further, a mapping of model performance indices (correlation coefficients, model bias, root-mean-square error, and threat scores) from an array of stations from the region indicates that the model performs satisfactorily in resolving daily precipitation at 5-km resolution.

Precipitation Recycling and the Vertical Distribution of Local and Remote Sources of Water for Precipitation

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Atlas, Robert (Technical Monitor)

2002-01-01

Precipitation recycling is defined as the amount of water that evaporates from a region that precipitates within the same region. This is also interpreted as the local source of water for precipitation. In this study, the local and remote sources of water for precipitation have been diagnosed through the use of passive constituent tracers that represent regional evaporative sources along with their transport and precipitation. We will discuss the differences between this method and the simpler bulk diagnostic approach to precipitation recycling. A summer seasonal simulation has been analyzed for the regional sources of the United States Great Plains precipitation. While the tropical Atlantic Ocean (including the Gulf of Mexico) and the local continental sources of precipitation are most dominant, the vertically integrated column of water contains substantial water content originating from the Northern Pacific Ocean, which is not precipitated. The vertical profiles of regional water sources indicate that local Great Plains source of water dominates the lower troposphere, predominantly in the PBL. However, the Pacific Ocean source is dominant over a large portion of the middle to upper troposphere. The influence of the tropical Atlantic Ocean is reasonably uniform throughout the column. While the results are not unexpected given the formulation of the model's convective parameterization, the analysis provides a quantitative assessment of the impact of local evaporation on the occurrence of convective precipitation in the GCM. Further, these results suggest that local source of water is not well mixed throughout the vertical column.

Precipitation Recycling in the NASA GEOS Data Assimilation System

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Schubert, Siegfried; Molod, Andrea; Takacs, Lawrence L.

1999-01-01

Analysis of precipitation recycling can improve the understanding of regional hydrologic anomalies, especially their evolution and maintenance. Diagnostic models of the recycling of precipitation and are applied to 15 years of the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). Recycled precipitation is defined as the fraction of precipitation within a given region that originated as surface evaporation from the same region. The focus of the present work is on the interannual variability of the central United States hydrologic cycle and precipitation recycling. The extreme years of 1988 (drought) and 1993 (flood) are compared with the 15 year base period mean annual cycle. The results indicate that recycling ratio (the amount of precipitation with a local source relative to the total precipitation) is greater in 1988 than both the base period mean and the 1993 season (with 1993 recycling ratio less than the mean). On the other hand, both the summers of 1988 and 1993 show less total recycled precipitation than the mean. The results also show that precipitation recycling may have been more important in the spring of 1993, when the region was primed for flooding, than the summer, when the sever flooding occurred. The diagnostic approaches to precipitation recycling suffer from some weaknesses. Numerical simulations and assimilation using passive tracers have the potential to provide more accurate calculations of precipitation recycling and the remote sources of water. This ability is being incorporated into the latest GEOS data assimilation system, and some preliminary results will be presented.

Modeling investigation of controlling factors in the increasing ratio of nitrate to non-seasalt sulfate in precipitation over Japan

NASA Astrophysics Data System (ADS)

Itahashi, Syuichi; Uno, Itsushi; Hayami, Hiroshi; Fujita, Shin-ichi

2014-08-01

Anthropogenic emissions in East Asia have been increasing during the three decades since 1980, as the population of East Asia has grown and the economies in East Asian countries have expanded. This has been particularly true in China, where NOx emissions have been rising continuously. However, because of fuel-gas desulfurization systems introduced as part of China’s 11th Five-Year Plan (2006-2010), SO2 emissions in China reached a peak in 2005-2006 and have declined since then. These drastic changes in emission levels of acidifying species are likely to have caused substantial changes in the precipitation chemistry. The absolute concentration of compounds in precipitation is inherently linked to precipitation amount; therefore, we use the ratio of nitrate (NO) to non-seasalt sulfate (nss-SO2-) concentration in precipitation as an index for evaluating acidification, which we call Ratio. In this study, we analyzed the long-term behavior of Ratio in precipitation over the Japanese archipelago during 2000-2011 and estimated the factors responsible for changes in Ratio in precipitation by using a model simulation. This analysis showed that Ratio was relatively constant at 0.5-0.6 between 2000 and 2005, and subsequently increased to 0.6-0.7 between 2006 and 2011. These changes in Ratio corresponded remarkably well to the changes of NOx/SO2 emissions ratio in China; this correspondence suggests that anthropogenic emissions from China were responsible for most of the change in precipitation chemistry over Japan. Sensitivity analysis elucidated that the increase in NOx emissions and the decrease in SO2 emissions contributed equally to the increases in Ratio. Considering both emission changes in China enables to capture the observed increasing trend of Ratio in Japan.

Classification of Meteorological Influences Surrounding Extreme Precipitation Events in the United States using the MERRA-2 Reanalysis

NASA Technical Reports Server (NTRS)

Collow, Allie Marquardt; Bosilovich, Mike; Ullrich, Paul; Hoeck, Ian

2017-01-01

Extreme precipitation events can have a large impact on society through flooding that can result in property destruction, crop losses, economic losses, the spread of water-borne diseases, and fatalities. Observations indicate there has been a statistically significant increase in extreme precipitation events over the past 15 years in the Northeastern United States and other localized regions of the country have become crippled with record flooding events, for example, the flooding that occurred in the Southeast United States associated with Hurricane Matthew in October 2016. Extreme precipitation events in the United States can be caused by various meteorological influences such as extratropical cyclones, tropical cyclones, mesoscale convective complexes, general air mass thunderstorms, upslope flow, fronts, and the North American Monsoon. Reanalyses, such as the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), have become a pivotal tool to study the meteorology surrounding extreme precipitation events. Using days classified as an extreme precipitation events based on a combination of observational gauge and radar data, two techniques for the classification of these events are used to gather additional information that can be used to determine how events have changed over time using atmospheric data from MERRA-2. The first is self organizing maps, which is an artificial neural network that uses unsupervised learning to cluster like patterns and the second is an automated detection technique that searches for characteristics in the atmosphere that define a meteorological phenomena. For example, the automated detection for tropical cycles searches for a defined area of suppressed sea level pressure, alongside thickness anomalies aloft, indicating the presence of a warm core. These techniques are employed for extreme precipitation events in preselected regions that were chosen based an analysis of the climatology of precipitation.

Version 4 IMERG: Investigating Runs and High Latitudes

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K. L.; Joyce, R.; Kidd, C.; Nelkin, E. J.; Sorooshian, S.; Tan, J.; Xie, P.

2016-12-01

The Integrated Multi-satellitE Retrievals for GPM (IMERG) merged precipitation product is being computed by the U.S. Global Precipitation Measurement mission (GPM) science team, based on intercalibrated estimates from the international constellation of precipitation-relevant satellites and other data. Recently, GPM upgraded the precipitation retrieval algorithms applied to individual sensors, and following that, IMERG was upgraded to Version 4. These data sets are computed at the half hour, 0.1° x 0.1° resolution over the latitude belt 60°N-S. Various latency requirements for different users are accommodated by computing IMERG in three "Runs" - Early, Late, and Final (5 hours, 15 hours, and 2.5 months after observation time, respectively). The near-real-time Early and Late Runs and the research-quality Final Run incorporate increasing amounts of data; examples will highlight the contribution that additional data make for each Run. From Early to Late, the addition of backward propagated data in the Late allows temporally weighted interpolation of forward and backward propagated precipitation, rather than the forward-only extrapolation in the Early. From Late to Final, the major addition is the direct use of monthly precipitation gauge analysis (the Global Precipitation Climatology Centre's Monitoring Analysis), which mitigates the satellite biases over land for the Early and Late. In addition, the new capabilities of the input algorithms at higher latitudes will be discussed, both during the snow season and the summer rain season. These inputs have a dominant role in determining the utility of IMERG in all seasons. Rainfall over non-frozen surface is reasonably well represented, while precipitation over frozen surfaces is still a topic of active research.

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

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

Wood, Robert; Wyant, Matthew; Bretherton, Christopher S.

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21 month (April 2009-December 2010) comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulusmore » and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1- 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from at Graciosa are being compared with short-range forecasts made a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.« less

Clouds, aerosol, and precipitation in the Marine Boundary Layer: An ARM mobile facility deployment

DOE PAGES

Wood, Robert; Luke, Ed; Wyant, Matthew; ...

2014-04-27

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009-December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the Northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulusmore » and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1-11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging.The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.« less

Clouds, Aerosols, and Precipitation in the Marine Boundary Layer: An Arm Mobile Facility Deployment

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

Wood, Robert; Wyant, Matthew; Bretherton, Christopher S.

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) 38 deployment at Graciosa Island in the Azores generated a 21 month (April 2009-December 2010) 39 comprehensive dataset documenting clouds, aerosols and precipitation using the Atmospheric 40 Radiation Measurement (ARM) Mobile Facility (AMF). The scientific aim of the deployment is 41 to gain improved understanding of the interactions of clouds, aerosols and precipitation in the 42 marine boundary layer. 43 Graciosa Island straddles the boundary between the subtropics and midlatitudes in the 44 Northeast Atlantic Ocean, and consequently experiences a great diversity of meteorological and 45 cloudiness conditions. Lowmore » clouds are the dominant cloud type, with stratocumulus and cumulus 46 occurring regularly. Approximately half of all clouds contained precipitation detectable as radar 47 echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1-48 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide 49 range of aerosol conditions was sampled during the deployment consistent with the diversity of 50 sources as indicated by back trajectory analysis. Preliminary findings suggest important two-way 51 interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation 52 and cloud radiative properties while being controlled in part by precipitation scavenging. 53 The data from at Graciosa are being compared with short-range forecasts made a variety 54 of models. A pilot analysis with two climate and two weather forecast models shows that they 55 reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well, 56 but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to 57 be a long-term ARM site that became operational in October 2013.« less

Extreme precipitation events and related weather patterns over Iraq

NASA Astrophysics Data System (ADS)

raheem Al-nassar, Ali; Sangrà, Pablo; Alarcón, Marta

2016-04-01

This study aims to investigate the extreme precipitation events and the associated weather phenomena in the Middle East and particularly in Iraq. For this purpose we used Baghdad daily precipitation records from the Iraqi Meteorological and Seismology Organization combined with ECMWF (ERA-Interim) reanalysis data for the period from January 2002 to December 2013. Extreme events were found statistically at the 90% percentile of the recorded precipitation, and were highly correlated with hydrological flooding in some cities of Iraq. We identified fifteen extreme precipitation events. The analysis of the corresponding weather patterns (500 hPa and 250 hPa geopotential and velocity field distribution) indicated that 5 events were related with cut off low causing the highest precipitation (180 mm), 3 events related with rex block (158 mm), 3 events related with jet streak occurrence (130 mm) and 4 events related with troughs (107 mm). . Five of these events caused flash floods and in particular one of them related with a rex block was the most dramatic heavy rain event in Iraq in 30 years. We investigated for each case the convective instability and dynamical forcing together with humidity sources. For convective instability we explored the distribution of the K index and SWEAT index. For dynamical forcing we analyzed at several levels Q vector, divergence, potential and relative vorticity advection and omega vertical velocity. Source of humidity was investigated through humidity and convergence of specific humidity distribution. One triggering factor of all the events is the advection and convergence of humidity from the Red Sea and the Persian Gulf. Therefore a necessary condition for extreme precipitation in Iraq is the advection and convergence of humidity from the Red Sea and Persian Gulf. Our preliminary analysis also indicates that extreme precipitation events are primary dynamical forced playing convective instability a secondary role.

Separation and characterization of acetyl and non-acetyl hemicelluloses of Arundo donax by ammonium sulfate precipitation.

PubMed

Peng, Feng; Bian, Jing; Peng, Pai; Xiao, Huan; Ren, Jun-Li; Xu, Feng; Sun, Run-Cang

2012-04-25

Delignified Arundo donax was sequentially extracted with DMSO, saturated barium hydroxide, and 1.0 M aqueous NaOH solution. The yields of the soluble fractions were 10.2, 6.7, and 10.0% (w/w), respectively, of the dry Arundo donax materials. The DMSO-, Ba(OH)(2)- and NaOH-soluble hemicellulosic fractions were further fractionated into two subfractions by gradient 50% and 80% saturation ammonium sulfate precipitation, respectively. Monosaccharide, molecular weight, FT-IR, and 1D ((1)H and (13)C) and 2D (HSQC) NMR analysis revealed the differences in structural characteristics and physicochemical properties among the subfractions. The subfractions precipitated with 50% saturation ammonium sulfate had lower arabinose/xylose and glucuronic acid/xylose ratios but had higher molecular weight than those of the subfractions precipitated by 80% saturation ammonium sulfate. FT-IR and NMR analysis revealed that the highly acetylated DMSO-soluble hemicellulosic subfraction (H(D50)) could be precipitated with a relatively lower concentration of 50% saturated ammonium sulfate, and thus the gradient ammonium sulfate precipitation technique could discriminate acetyl and non-acetyl hemicelluloses. It was found that the DMSO-soluble subfraction H(D50) precipitated by 50% saturated ammonium sulfate mainly consisted of poorly substituted O-acetyl arabino-4-O-methylglucurono xylan with terminal units of arabinose linked on position 3 of xylose, 4-O-methylglucuronic acid residues linked on position 2 of the xylan bone, and the acetyl groups (degree of acetylation, 37%) linked on position 2 or 3. The DMSO-soluble subfraction H(D80) precipitated by 80% saturated ammonium sulfate was mainly composed of highly substituted arabino-4-O-methylglucurono xylan and β-d-glucan.

Precipitation Estimate Using NEXRAD Ground-Based Radar Images: Validation, Calibration and Spatial Analysis

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

Zhang, Xuesong

2012-12-17

Precipitation is an important input variable for hydrologic and ecological modeling and analysis. Next Generation Radar (NEXRAD) can provide precipitation products that cover most of the continental United States with a high resolution display of approximately 4 × 4 km2. Two major issues concerning the applications of NEXRAD data are (1) lack of a NEXRAD geo-processing and geo-referencing program and (2) bias correction of NEXRAD estimates. In this chapter, a geographic information system (GIS) based software that can automatically support processing of NEXRAD data for hydrologic and ecological models is presented. Some geostatistical approaches to calibrating NEXRAD data using rainmore » gauge data are introduced, and two case studies on evaluating accuracy of NEXRAD Multisensor Precipitation Estimator (MPE) and calibrating MPE with rain-gauge data are presented. The first case study examines the performance of MPE in mountainous region versus south plains and cold season versus warm season, as well as the effect of sub-grid variability and temporal scale on NEXRAD performance. From the results of the first case study, performance of MPE was found to be influenced by complex terrain, frozen precipitation, sub-grid variability, and temporal scale. Overall, the assessment of MPE indicates the importance of removing bias of the MPE precipitation product before its application, especially in the complex mountainous region. The second case study examines the performance of three MPE calibration methods using rain gauge observations in the Little River Experimental Watershed in Georgia. The comparison results show that no one method can perform better than the others in terms of all evaluation coefficients and for all time steps. For practical estimation of precipitation distribution, implementation of multiple methods to predict spatial precipitation is suggested.« less

Development of the NHM-LETKF regional reanalysis system assimilating conventional observations only

NASA Astrophysics Data System (ADS)

Fukui, S.; Iwasaki, T.; Saito, K. K.; Seko, H.; Kunii, M.

2016-12-01

The information about long-term high-resolution atmospheric fields is very useful for studying meso-scale responses to climate change or analyzing extreme events. We are developing a NHM-LETKF (the local ensemble transform Kalman filter with the nonhydrostatic model of the Japan Meteorological Agency (JMA)) regional reanalysis system assimilating only conventional observations that are available over about 60 years such as surface observations at observatories and upper air observations with radiosondes. The domain covers Japan and its surroundings. Before the long-term reanalysis is performed, an experiment using the system was conducted over August in 2014 in order to identify effectiveness and problems of the regional reanalysis system. In this study, we investigated the six-hour accumulated precipitations obtained by integration from the analysis fields. The reproduced precipitation was compared with the JMA's Radar/Rain-gauge Analyzed Precipitation data over Japan islands and the precipitation of JRA-55, which is used as lateral boundary conditions. The comparisons reveal the underestimation of the precipitation in the regional reanalysis. The underestimation is improved by extending the forecast time. In the regional reanalysis system, the analysis fields are derived using the ensemble mean fields, where the conflicting components among ensemble members are filtered out. Therefore, it is important to tune the inflation factor and lateral boundary perturbations not to smooth the analysis fields excessively and to consider more time to spin-up the fields. In the extended run, the underestimation still remains. This implies that the underestimation is attributed to the forecast model itself as well as the analysis scheme.

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

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

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 that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. The increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.« less

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.

Analysis of extreme summers and prior late winter/spring conditions in central Europe

NASA Astrophysics Data System (ADS)

Träger-Chatterjee, C.; Müller, R. W.; Bendix, J.

2013-05-01

Drought and heat waves during summer in mid-latitudes are a serious threat to human health and agriculture and have negative impacts on the infrastructure, such as problems in energy supply. The appearance of such extreme events is expected to increase with the progress of global warming. A better understanding of the development of extremely hot and dry summers and the identification of possible precursors could help improve existing seasonal forecasts in this regard, and could possibly lead to the development of early warning methods. The development of extremely hot and dry summer seasons in central Europe is attributed to a combined effect of the dominance of anticyclonic weather regimes and soil moisture-atmosphere interactions. The atmospheric circulation largely determines the amount of solar irradiation and the amount of precipitation in an area. These two variables are themselves major factors controlling the soil moisture. Thus, solar irradiation and precipitation are used as proxies to analyse extreme sunny and dry late winter/spring and summer seasons for the period 1958-2011 in Germany and adjacent areas. For this purpose, solar irradiation data from the European Center for Medium Range Weather Forecast 40-yr and interim re-analysis dataset, as well as remote sensing data are used. Precipitation data are taken from the Global Precipitation Climatology Project. To analyse the atmospheric circulation geopotential data at 850 hPa are also taken from the European Center for Medium Range Weather Forecast 40-yr and interim re-analysis datasets. For the years in which extreme summers in terms of high solar irradiation and low precipitation are identified, the previous late winter/spring conditions of solar irradiation and precipitation in Germany and adjacent areas are analysed. Results show that if the El Niño-Southern Oscillation (ENSO) is not very intensely developed, extremely high solar irradiation amounts, together with extremely low precipitation amounts during late winter/spring, might serve as precursor of extremely sunny and dry summer months to be expected.

Characteristics of cloud occurrence using ceilometer measurements and its relationship to precipitation over Seoul

NASA Astrophysics Data System (ADS)

Lee, Sanghee; Hwang, Seung-On; Kim, Jhoon; Ahn, Myoung-Hwan

2018-03-01

Clouds are an important component of the atmosphere that affects both climate and weather, however, their contributions can be very difficult to determine. Ceilometer measurements can provide high resolution information on atmospheric conditions such as cloud base height (CBH) and vertical frequency of cloud occurrence (CVF). This study presents the first comprehensive analysis of CBH and CVF derived using Vaisala CL51 ceilometers at two urban stations in Seoul, Korea, during a three-year period from January 2014 to December 2016. The average frequency of cloud occurrence detected by the ceilometers is 54.3%. It is found that the CL51 is better able to capture CBH as compared to another ceilometer CL31 at a nearby meteorological station because it could detect high clouds more accurately. Frequency distributions for CBH up to 13,000 m providing detailed vertical features with 500-m interval show 55% of CBHs below 2 km for aggregated CBHs. A bimodal frequency distribution was observed for three-layers CBHs. A monthly variation of CVF reveals that frequency concentration of lower clouds is found in summer and winter, and higher clouds more often detected in spring and autumn. Monthly distribution features of cloud occurrence and precipitation are depending on seasons and it might be easy to define their relationship due to higher degree of variability of precipitation than cloud occurrence. However, a fluctuation of cloud occurrence frequency in summer is similar to precipitation in trend, whereas clouds in winter are relatively frequent but precipitation is not accompanied. In addition, recent decrease of summer precipitation could be mostly explained by a decrease of cloud occurrence. Anomalous precipitation recorded sometimes is considerably related to corresponding cloud occurrence. The diurnal and daily variations of CBH and CVF from ceilometer observations and the analysis of microwave radiometer measurements for two typical cloudiness cases are also reviewed in parallel. This analysis in finer temporal scale exhibits that utilization of ground-based observations together could help to analyze the cloud behaviors.

Quality-assurance results for field pH and specific-conductance measurements, and for laboratory analysis, National Atmospheric Deposition Program and National Trends Network; January 1980-September 1984

USGS Publications Warehouse

Schroder, L.J.; Brooks, M.H.; Malo, B.A.; Willoughby, T.C.

1986-01-01

Five intersite comparison studies for the field determination of pH and specific conductance, using simulated-precipitation samples, were conducted by the U.S.G.S. for the National Atmospheric Deposition Program and National Trends Network. These comparisons were performed to estimate the precision of pH and specific conductance determinations made by sampling-site operators. Simulated-precipitation samples were prepared from nitric acid and deionized water. The estimated standard deviation for site-operator determination of pH was 0.25 for pH values ranging from 3.79 to 4.64; the estimated standard deviation for specific conductance was 4.6 microsiemens/cm at 25 C for specific-conductance values ranging from 10.4 to 59.0 microsiemens/cm at 25 C. Performance-audit samples with known analyte concentrations were prepared by the U.S.G.S.and distributed to the National Atmospheric Deposition Program 's Central Analytical Laboratory. The differences between the National Atmospheric Deposition Program and national Trends Network-reported analyte concentrations and known analyte concentrations were calculated, and the bias and precision were determined. For 1983, concentrations of calcium, magnesium, sodium, and chloride were biased at the 99% confidence limit; concentrations of potassium and sulfate were unbiased at the 99% confidence limit. Four analytical laboratories routinely analyzing precipitation were evaluated in their analysis of identical natural- and simulated precipitation samples. Analyte bias for each laboratory was examined using analysis of variance coupled with Duncan 's multiple-range test on data produced by these laboratories, from the analysis of identical simulated-precipitation samples. Analyte precision for each laboratory has been estimated by calculating a pooled variance for each analyte. Interlaboratory comparability results may be used to normalize natural-precipitation chemistry data obtained from two or more of these laboratories. (Author 's abstract)

Investigating precipitation changes of anthropic origin: data and methodological issues

NASA Astrophysics Data System (ADS)

de Lima, Isabel; Lovejoy, Shaun

2017-04-01

There is much concern about the social, environmental and economic impacts of climate change that could result directly from changes in temperature and precipitation. For temperature, the situation is better understood; but despite the many studies that have been already dedicated to precipitation, change in this process - that could be associated to the transition to the Anthropocene - has not yet been convincingly proven. A large fraction of those studies have been exploring temporal (linear) trends in local precipitation, sometimes using records over only a few decades; other fewer studies have been dedicated to investigating global precipitation change. Overall, precipitation change of anthropic origin has showed to be difficult to establish with high statistical significance and, moreover, different data and products have displayed important discrepancies; this is valid even for global precipitation. We argue that the inadequate resolution and length of the data commonly used, as well as methodological issues, are among the main factors limiting the ability to identify the signature of change in precipitation. We propose several ways in which one can hope to improve the situation - or at least - clarify the difficulties. From the point of view of statistical analysis, the problem is one of detecting a low frequency anthropogenic signal in the presence of "noise" - the natural variability (the latter includes both internal dynamics and responses to volcanic, solar or other natural forcings). A consequence is that as one moves to longer and longer time scales, fluctuations are increasingly averaged and at some point, the anthropogenic signal will stand out above the natural variability noise. This approach can be systematized using scaling fluctuation analysis to characterizing different precipitation scaling regimes: weather, macroweather, climate - from higher to lower frequencies; in the anthropocene, the macroweather regime covers the range of time scales from about a month to ≈30 years. We illustrate this using local gauge data and three qualitatively different global scale precipitation products (from gauges, reanalyses and a satellite and gauge hybrid) that allow to investigate precipitation from monthly to centennial scales and in space from planetary down to 5°x5° scales. By systematically characterizing precipitation variability across wide ranges of time and space scales, we show that the anthropogenic signal only exceeded the natural variability at time scales larger than ≈20 years, so that the disagreement in the trends can be traced to these low frequencies.

Development of a global historic monthly mean precipitation dataset

NASA Astrophysics Data System (ADS)

Yang, Su; Xu, Wenhui; Xu, Yan; Li, Qingxiang

2016-04-01

Global historic precipitation dataset is the base for climate and water cycle research. There have been several global historic land surface precipitation datasets developed by international data centers such as the US National Climatic Data Center (NCDC), European Climate Assessment & Dataset project team, Met Office, etc., but so far there are no such datasets developed by any research institute in China. In addition, each dataset has its own focus of study region, and the existing global precipitation datasets only contain sparse observational stations over China, which may result in uncertainties in East Asian precipitation studies. In order to take into account comprehensive historic information, users might need to employ two or more datasets. However, the non-uniform data formats, data units, station IDs, and so on add extra difficulties for users to exploit these datasets. For this reason, a complete historic precipitation dataset that takes advantages of various datasets has been developed and produced in the National Meteorological Information Center of China. Precipitation observations from 12 sources are aggregated, and the data formats, data units, and station IDs are unified. Duplicated stations with the same ID are identified, with duplicated observations removed. Consistency test, correlation coefficient test, significance t-test at the 95% confidence level, and significance F-test at the 95% confidence level are conducted first to ensure the data reliability. Only those datasets that satisfy all the above four criteria are integrated to produce the China Meteorological Administration global precipitation (CGP) historic precipitation dataset version 1.0. It contains observations at 31 thousand stations with 1.87 × 107 data records, among which 4152 time series of precipitation are longer than 100 yr. This dataset plays a critical role in climate research due to its advantages in large data volume and high density of station network, compared to other datasets. Using the Penalized Maximal t-test method, significant inhomogeneity has been detected in historic precipitation datasets at 340 stations. The ratio method is then employed to effectively remove these remarkable change points. Global precipitation analysis based on CGP v1.0 shows that rainfall has been increasing during 1901-2013 with an increasing rate of 3.52 ± 0.5 mm (10 yr)-1, slightly higher than that in the NCDC data. Analysis also reveals distinguished long-term changing trends at different latitude zones.

Analysis of large soil samples for actinides

DOEpatents

Maxwell, III; Sherrod, L [Aiken, SC

2009-03-24

A method of analyzing relatively large soil samples for actinides by employing a separation process that includes cerium fluoride precipitation for removing the soil matrix and precipitates plutonium, americium, and curium with cerium and hydrofluoric acid followed by separating these actinides using chromatography cartridges.

Land-Climate Feedbacks in Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Asharaf, Shakeel; Ahrens, Bodo

2016-04-01

In an attempt to identify how land surface states such as soil moisture influence the monsoonal precipitation climate over India, a series of numerical simulations including soil moisture sensitivity experiments was performed. The simulations were conducted with a nonhydrostatic regional climate model (RCM), the Consortium for Small-Scale Modeling (COSMO) in climate mode (CCLM) model, which was driven by the European Center for Medium-Range Weather Forecasts (ECMWF) Interim reanalysis (ERA-Interim) data. Results showed that pre-monsoonal soil moisture has a significant impact on monsoonal precipitation formation and large-scale atmospheric circulations. The analysis revealed that even a small change in the processes that influence precipitation via changes in local evapotranspiration was able to trigger significant variations in regional soil moisture-precipitation feedback. It was observed that these processes varied spatially from humid to arid regions in India, which further motivated an examination of soil-moisture memory variation over these regions and determination of the ISM seasonal forecasting potential. A quantitative analysis indicated that the simulated soil-moisture memory lengths increased with soil depth and were longer in the western region than those in the eastern region of India. Additionally, the subsequent precipitation variance explained by soil moisture increased from east to west. The ISM rainfall was further analyzed in two different greenhouse gas emission scenarios: the Special Report on Emissions Scenario (SRES: B1) and the new Representative Concentration Pathways (RCPs: RCP4.5). To that end, the CCLM and its driving global-coupled atmospheric-oceanic model (GCM), ECHAM/MPIOM were used in order to understand the driving processes of the projected inter-annual precipitation variability and associated trends. Results inferred that the projected rainfall changes were the result of two largely compensating processes: increase of remotely induced precipitation and decrease of precipitation efficiency. However, the complementing precipitation components and their simulation uncertainties rendered climate projections of the Indian summer monsoon rainfall as an ongoing, highly ambiguous challenge for both the GCM and the RCM.

Projected changes to precipitation extremes over the Canadian Prairies using multi-RCM ensemble

NASA Astrophysics Data System (ADS)

Masud, M. B.; Khaliq, M. N.; Wheater, H. S.

2016-12-01

Information on projected changes to precipitation extremes is needed for future planning of urban drainage infrastructure and storm water management systems and to sustain socio-economic activities and ecosystems at local, regional and other scales of interest. This study explores the projected changes to seasonal (April-October) precipitation extremes at daily, hourly and sub-hourly scales over the Canadian Prairie Provinces of Alberta, Saskatchewan, and Manitoba, based on the North American Regional Climate Change Assessment Program multi-Regional Climate Model (RCM) ensemble and regional frequency analysis. The performance of each RCM is evaluated regarding boundary and performance errors to study various sources of uncertainties and the impact of large-scale driving fields. In the absence of RCM-simulated short-duration extremes, a framework is developed to derive changes to extremes of these durations. Results from this research reveal that the relative changes in sub-hourly extremes are higher than those in the hourly and daily extremes. Overall, projected changes in precipitation extremes are larger for southeastern parts of this region than southern and northern areas, and smaller for southwestern and western parts of the study area. Keywords: climate change, precipitation extremes, regional frequency analysis, NARCCAP, Canadian Prairie provinces

Precipitation-Induced Changes in Microstrain and Its Relation with Hardness and Tempering Parameter in 17-4 PH Stainless Steel

NASA Astrophysics Data System (ADS)

Mahadevan, S.; Manojkumar, R.; Jayakumar, T.; Das, C. R.; Rao, B. P. C.

2016-06-01

17-4 PH (precipitation hardening) stainless steel is a soft martensitic stainless steel strengthened by aging at appropriate temperature for sufficient duration. Precipitation of copper particles in the martensitic matrix during aging causes coherency strains which improves the mechanical properties, namely hardness and strength of the matrix. The contributions to X-ray diffraction (XRD) profile broadening due to coherency strains caused by precipitation and crystallite size changes due to aging are separated and quantified using the modified Williamson-Hall approach. The estimated normalized mean square strain and crystallite size are used to explain the observed changes in hardness. Microstructural changes observed in secondary electron images are in qualitative agreement with crystallite size changes estimated from XRD profile analysis. The precipitation kinetics in the age-hardening regime and overaged regime are studied from hardness changes and they follow the Avrami kinetics and Wilson's model, respectively. In overaged condition, the hardness changes are linearly correlated to the tempering parameter (also known as Larson-Miller parameter). Similar linear variation is observed between the normalized mean square strain (determined from XRD line profile analysis) and the tempering parameter, in the incoherent regime which is beyond peak microstrain conditions.

An application of sample entropy to precipitation in Paraíba State, Brazil

NASA Astrophysics Data System (ADS)

Xavier, Sílvio Fernando Alves; da Silva Jale, Jader; Stosic, Tatijana; dos Santos, Carlos Antonio Costa; Singh, Vijay P.

2018-05-01

A climate system is characterized to be a complex non-linear system. In order to describe the complex characteristics of precipitation series in Paraíba State, Brazil, we aim the use of sample entropy, a kind of entropy-based algorithm, to evaluate the complexity of precipitation series. Sixty-nine meteorological stations are distributed over four macroregions: Zona da Mata, Agreste, Borborema, and Sertão. The results of the analysis show that intricacies of monthly average precipitation have differences in the macroregions. Sample entropy is able to reflect the dynamic change of precipitation series providing a new way to investigate complexity of hydrological series. The complexity exhibits areal variation of local water resource systems which can influence the basis for utilizing and developing resources in dry areas.

Frequency analysis and its spatiotemporal characteristics of precipitation extreme events in China during 1951-2010

NASA Astrophysics Data System (ADS)

Shao, Yuehong; Wu, Junmei; Ye, Jinyin; Liu, Yonghe

2015-08-01

This study investigates frequency analysis and its spatiotemporal characteristics of precipitation extremes based on annual maximum of daily precipitation (AMP) data of 753 observation stations in China during the period 1951-2010. Several statistical methods including L-moments, Mann-Kendall test (MK test), Student's t test ( t test) and analysis of variance ( F-test) are used to study different statistical properties related to frequency and spatiotemporal characteristics of precipitation extremes. The results indicate that the AMP series of most sites have no linear trends at 90 % confidence level, but there is a distinctive decrease trend in Beijing-Tianjin-Tangshan region. The analysis of abrupt changes shows that there are no significant changes in most sites, and no distinctive regional patterns within the mutation sites either. An important innovation different from the previous studies is the shift in the mean and the variance which are also studied in this paper in order to further analyze the changes of strong and weak precipitation extreme events. The shift analysis shows that we should pay more attention to the drought in North China and to the flood control and drought in South China, especially to those regions that have no clear trend and have a significant shift in the variance. More important, this study conducts the comprehensive analysis of a complete set of quantile estimates and its spatiotemporal characteristic in China. Spatial distribution of quantile estimation based on the AMP series demonstrated that the values gradually increased from the Northwest to the Southeast with the increment of duration and return period, while the increasing rate of estimation is smooth in the arid and semiarid region and is rapid in humid region. Frequency estimates of 50-year return period are in agreement with the maximum observations of AMP series in the most stations, which can provide more quantitative and scientific basis for decision making.

Contributions of natural climate changes and human activities to the trend of extreme precipitation

NASA Astrophysics Data System (ADS)

Gao, Lu; Huang, Jie; Chen, Xingwei; Chen, Ying; Liu, Meibing

2018-06-01

This study focuses on the analysis of the nonstationarity characteristics of extreme precipitation and their attributions in the southeastern coastal region of China. The maximum daily precipitation (MDP) series is extracted from observations at 79 meteorological stations in the study area during the first flood season (April-June) from 1960 to 2012. The trends of the mean (Mn) and variance (Var) of MDP are detected using the Generalized Additive Models for Location, Scale, and Shape parameters (GAMLSS) and Mann-Kendall test. The contributions of natural climate change and human activities to the Mn and Var changes of MDP are investigated using six large-scale circulation variables and emissions of four greenhouse gases based on GAMLSS and a contribution analysis method. The results demonstrate that the nonstationarity of extreme precipitation on local scales is significant. The Mn and Var of extreme precipitation increase in the north of Zhejiang, the middle of Fujian, and the south of Guangdong. In general, natural climate change contributes more to Mn from 1960 to 2012 than to Var. However, human activities cause a greater Var in the rapid socioeconomic development period (1986-2012) than in the slow socioeconomic development period (1960-1985), especially in Zhejiang and Guangdong. The community should pay more attention to the possibility of extreme precipitation events and associated disasters triggered by human activities.

On Mars' Atmospheric Sputtering after Maven First two Years

NASA Astrophysics Data System (ADS)

Leblanc, F.; Modolo, R.; Curry, S.; Luhmann, J. G.; Lillis, R. J.; Chaufray, J. Y.; Hara, T.; McFadden, J. P.; Halekas, J. S.; Epavier, F.; Connerney, J. E. P.; Jakosky, B. M.

2017-12-01

Mars likely lost a significant part of its atmosphere to space during its history. The sputtering of the atmosphere by precipitating planetary picked up ions accelerated by the solar wind is one of the processes that could have significantly contributed to this atmospheric escape, in particular since the cessation of its global magnetic field, 4.0-4.1 Gyr ago. We here present a two year baseline analysis of MAVEN observations of the precipitating flux, in particular the dependence of the precipitating flux on solar zenith angle. We use this measurement to model the expected escape rate and exospheric structure induced by this precipitation.

A simple and effective method for detecting precipitated proteins in MALDI-TOF MS.

PubMed

Oshikane, Hiroyuki; Watabe, Masahiko; Nakaki, Toshio

2018-04-01

MALDI-TOF MS has developed rapidly into an essential analytical tool for the life sciences. Cinnamic acid derivatives are generally employed in routine molecular weight determinations of intact proteins using MALDI-TOF MS. However, a protein of interest may precipitate when mixed with matrix solution, perhaps preventing MS detection. We herein provide a simple approach to enable the MS detection of such precipitated protein species by means of a "direct deposition method" -- loading the precipitant directly onto the sample plate. It is thus expected to improve routine MS analysis of intact proteins. Copyright © 2018. Published by Elsevier Inc.

The relationship between extreme precipitation events and landslides distributions in 2009 in Lower Austria

NASA Astrophysics Data System (ADS)

Katzensteiner, H.; Bell, R.; Petschko, H.; Glade, T.

2012-04-01

The prediction and forecast of widespread landsliding for a given triggering event is an open research question. Numerous studies tried to link spatial rainfall and landslide distributions. This study focuses on analysing the relationship between intensive precipitation and rainfall-triggered shallow landslides in the year 2009 in Lower Austria. Landslide distributions were gained from the building ground register, which is maintained by the Geological Survey of Lower Austria. It contains detailed information of landslides, which were registered due to damage reports. Spatially distributed rainfall estimates were extracted from INCA (Integrated Nowcasting through Comprehensive Analysis) precipitation analysis, which is a combination of station data interpolation and radar data in a spatial resolution of 1km developed by the Central Institute for Meteorology and Geodynamics (ZAMG), Vienna, Austria. The importance of the data source is shown by comparing rainfall data based on reference gauges, spatial interpolation and INCA-analysis for a certain storm period. INCA precipitation data can detect precipitating cells that do not hit a station but might trigger a landslide, which is an advantage over the application of reference stations for the definition of rainfall thresholds. Empirical thresholds at regional scale were determined based on rainfall-intensity and duration in the year 2009 and landslide information. These thresholds are dependent on the criteria which separate the landslide triggering and non-triggering precipitation events from each other. Different approaches for defining thresholds alter the shape of the threshold as well. A temporarily threshold I=8,8263*D^(-0.672) for extreme rainfall events in summer in Lower Austria was defined. A verification of the threshold with similar events of other years as well as following analyses based on a larger landslide database are in progress.

Examination of Satellite and Model Reanalysis Precipitation with Climate Oscillations

NASA Astrophysics Data System (ADS)

Donato, T. F.; Houser, P. R.

2016-12-01

The purpose of this study is to examine the efficacy of satellite and model reanalysis precipitation with climate oscillations. Specifically, we examine and compare the relationship between the Global Precipitation Climate Project (GPCP) with Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2) in regards to four climate indices: The North Atlantic Oscillation, Southern Oscillation Index, the Southern Annular Mode and Solar Activity. This analysis covers a 35-year observation period from 1980 through 2015. We ask two questions: How is global and regional precipitation changing over the observation period, and how are global and regional variations in precipitation related to global climate variation? We explore and compare global and regional precipitation trends between the two data sets. To do this, we constructed a total of 56 Regions of Interest (ROI). Nineteen of the ROIs were focused on geographic regions including continents, ocean basins, and marginal seas. Twelve ROIs examine hemispheric processes. The remaining 26 regions are derived from spatial-temporal classification analysis of GPCP data over a ten-year period (2001-2010). These regions include the primary wet and dry monsoon regions, regions influenced by western boundary currents, and orography. We investigate and interpret the monthly, seasonal and yearly global and regional response to the selected climate indices. Initial results indicate that no correlation exist between the GPCP data and Merra-2 data. Preliminary qualitative assessment between GCPC and solar activity suggest a possible relationship in intra-annual variability. This work is performed under the State of the Global Water and Energy Cycle (SWEC) project, a NASA-sponsored program in support of NASA's Energy and Water cycle Study (NEWS).

High-range resolution spectral analysis of precipitation through range imaging of the Chung-Li VHF radar

NASA Astrophysics Data System (ADS)

Tsai, Shih-Chiao; Chen, Jenn-Shyong; Chu, Yen-Hsyang; Su, Ching-Lun; Chen, Jui-Hsiang

2018-01-01

Multi-frequency range imaging (RIM) has been operated in the Chung-Li very high-frequency (VHF) radar, located on the campus of National Central University, Taiwan, since 2008. RIM processes the echo signals with a group of closely spaced transmitting frequencies through appropriate inversion methods to obtain high-resolution distribution of echo power in the range direction. This is beneficial to the investigation of the small-scale structure embedded in dynamic atmosphere. Five transmitting frequencies were employed in the radar experiment for observation of the precipitating atmosphere during the period between 21 and 23 August 2013. Using the Capon and Fourier methods, the radar echoes were synthesized to retrieve the temporal signals at a smaller range step than the original range resolution defined by the pulse width, and such retrieved temporal signals were then processed in the Doppler frequency domain to identify the atmosphere and precipitation echoes. An analysis called conditional averaging was further executed for echo power, Doppler velocity, and spectral width to verify the potential capabilities of the retrieval processing in resolving small-scale precipitation and atmosphere structures. Point-by-point correction of range delay combined with compensation of range-weighting function effect has been performed during the retrieval of temporal signals to improve the continuity of power spectra at gate boundaries, making the small-scale structures in the power spectra more natural and reasonable. We examined stratiform and convective precipitation and demonstrated their different structured characteristics by means of the Capon-processed results. The new element in this study is the implementation of RIM on spectral analysis, especially for precipitation echoes.

Linear and nonlinear characteristics of the runoff response to regional climate factors in the Qira River basin, Xinjiang, Northwest China.

PubMed

Xue, Jie; Gui, Dongwei

2015-01-01

The inland river watersheds of arid Northwest China represent an example of how, in recent times, climatic warming has increased the complexity of Earth's hydrological processes. In the present study, the linear and nonlinear characteristics of the runoff response to temperature and precipitation were investigated in the Qira River basin, located on the northern slope of the Kunlun Mountains. The results showed that average temperature on annual and seasonal scales has displayed a significantly increasing trend, but this has not been reflected in accumulated precipitation and runoff. Using path analysis, a positive link between precipitation and runoff was found both annually and in the summer season. Conversely, it was found that the impact of temperature on runoff has been negative since the 1960s, attributable to higher evaporation and infiltration in the Qira River basin. Over the past 50 years, abrupt changes in annual temperature, precipitation and runoff occurred in 1997, 1987 and 1995, respectively. Combined with analysis using the correlation dimension method, it was found that the temperature, precipitation and runoff, both annually and seasonally, possessed chaotic dynamic characteristics, implying that complex hydro-climatic processes must be introduced into other variables within models to describe the dynamics. In addition, as determined via rescaled range analysis, a consistent annual and seasonal decreasing trend in runoff under increasing temperature and precipitation conditions in the future should be taken into account. This work may provide a theoretical perspective that can be applied to the proper use and management of oasis water resources in the lower reaches of river basins like that of the Qira River.

Linear and nonlinear characteristics of the runoff response to regional climate factors in the Qira River basin, Xinjiang, Northwest China

PubMed Central

Xue, Jie

2015-01-01

The inland river watersheds of arid Northwest China represent an example of how, in recent times, climatic warming has increased the complexity of Earth’s hydrological processes. In the present study, the linear and nonlinear characteristics of the runoff response to temperature and precipitation were investigated in the Qira River basin, located on the northern slope of the Kunlun Mountains. The results showed that average temperature on annual and seasonal scales has displayed a significantly increasing trend, but this has not been reflected in accumulated precipitation and runoff. Using path analysis, a positive link between precipitation and runoff was found both annually and in the summer season. Conversely, it was found that the impact of temperature on runoff has been negative since the 1960s, attributable to higher evaporation and infiltration in the Qira River basin. Over the past 50 years, abrupt changes in annual temperature, precipitation and runoff occurred in 1997, 1987 and 1995, respectively. Combined with analysis using the correlation dimension method, it was found that the temperature, precipitation and runoff, both annually and seasonally, possessed chaotic dynamic characteristics, implying that complex hydro-climatic processes must be introduced into other variables within models to describe the dynamics. In addition, as determined via rescaled range analysis, a consistent annual and seasonal decreasing trend in runoff under increasing temperature and precipitation conditions in the future should be taken into account. This work may provide a theoretical perspective that can be applied to the proper use and management of oasis water resources in the lower reaches of river basins like that of the Qira River. PMID:26244113

Applications of Bayesian Procrustes shape analysis to ensemble radar reflectivity nowcast verification

NASA Astrophysics Data System (ADS)

Fox, Neil I.; Micheas, Athanasios C.; Peng, Yuqiang

2016-07-01

This paper introduces the use of Bayesian full Procrustes shape analysis in object-oriented meteorological applications. In particular, the Procrustes methodology is used to generate mean forecast precipitation fields from a set of ensemble forecasts. This approach has advantages over other ensemble averaging techniques in that it can produce a forecast that retains the morphological features of the precipitation structures and present the range of forecast outcomes represented by the ensemble. The production of the ensemble mean avoids the problems of smoothing that result from simple pixel or cell averaging, while producing credible sets that retain information on ensemble spread. Also in this paper, the full Bayesian Procrustes scheme is used as an object verification tool for precipitation forecasts. This is an extension of a previously presented Procrustes shape analysis based verification approach into a full Bayesian format designed to handle the verification of precipitation forecasts that match objects from an ensemble of forecast fields to a single truth image. The methodology is tested on radar reflectivity nowcasts produced in the Warning Decision Support System - Integrated Information (WDSS-II) by varying parameters in the K-means cluster tracking scheme.

Impact of AIRS Thermodynamic Profiles on Precipitation Forecasts for Atmospheric River Cases Affecting the Western United States

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley T.; Jedlovec, Gary J.; Blakenship, Clay B.; Wick, Gary A.; Neiman, Paul J.

2013-01-01

This project is a collaborative activity between the NASA Short-term Prediction Research and Transition (SPoRT) Center and the NOAA Hydrometeorology Testbed (HMT) to evaluate a SPoRT Advanced Infrared Sounding Radiometer (AIRS: Aumann et al. 2003) enhanced moisture analysis product. We test the impact of assimilating AIRS temperature and humidity profiles above clouds and in partly cloudy regions, using the three-dimensional variational Gridpoint Statistical Interpolation (GSI) data assimilation (DA) system (Developmental Testbed Center 2012) to produce a new analysis. Forecasts of the Weather Research and Forecasting (WRF) model initialized from the new analysis are compared to control forecasts without the additional AIRS data. We focus on some cases where atmospheric rivers caused heavy precipitation on the US West Coast. We verify the forecasts by comparison with dropsondes and the Cooperative Institute for Research in the Atmosphere (CIRA) Blended Total Precipitable Water product.

Thematic Analysis of Medical Notes Offers Preliminary Insight into Precipitants for Asian Suicide Attempters: An Exploratory Study.

PubMed

Choo, Carol C; Ho, Roger C; Burton, André A D

2018-04-20

One important dynamic risk factor for suicide assessment includes suicide precipitant. This exploratory study used a qualitative paradigm to look into the themes surrounding precipitants for suicide attempts in Singapore. Medical records related to suicide attempters who were admitted to the emergency department of a large teaching hospital in Singapore over a three year period were subjected to analysis. A total of 666 cases were examined (69.2% females; 63.8% Chinese, 15% Malays, 15.8% Indians), ages ranged from 10 years old to 85 years old (Mean = 29.7, Standard Deviation = 16.1). The thematic analysis process that was applied to the textual data elicited key concepts labelled as Relationship issues, Financial strain, Socio-legal-academic—environmental stress, and Physical and mental illness and pain. Interpreted with other recent local research on suicide attempters in Singapore, the findings have implications for informing suicide interventions.

The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming

NASA Astrophysics Data System (ADS)

Betts, R. A.; Cox, P. M.; Collins, M.; Harris, P. P.; Huntingford, C.; Jones, C. D.

A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulated precipitation decrease and forest dieback. Rising atmospheric CO2 is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO2 was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO2 contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO2 and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.

Where Does the Irrigation Water Go? An Estimate of the Contribution of Irrigation to Precipitation Using MERRA

NASA Technical Reports Server (NTRS)

Wei, Jiangfeng; Dirmeyer, Paul A.; Wisser, Dominik; Bosilovich, Michael G.; Mocko, David M.

2013-01-01

Irrigation is an important human activity that may impact local and regional climate, but current climate model simulations and data assimilation systems generally do not explicitly include it. The European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) shows more irrigation signal in surface evapotranspiration (ET) than the Modern-Era Retrospective Analysis for Research and Applications (MERRA) because ERA-Interim adjusts soil moisture according to the observed surface temperature and humidity while MERRA has no explicit consideration of irrigation at the surface. But, when compared with the results from a hydrological model with detailed considerations of agriculture, the ET from both reanalyses show large deficiencies in capturing the impact of irrigation. Here, a back-trajectory method is used to estimate the contribution of irrigation to precipitation over local and surrounding regions, using MERRA with observation-based corrections and added irrigation-caused ET increase from the hydrological model. Results show substantial contributions of irrigation to precipitation over heavily irrigated regions in Asia, but the precipitation increase is much less than the ET increase over most areas, indicating that irrigation could lead to water deficits over these regions. For the same increase in ET, precipitation increases are larger over wetter areas where convection is more easily triggered, but the percentage increase in precipitation is similar for different areas. There are substantial regional differences in the patterns of irrigation impact, but, for all the studied regions, the highest percentage contribution to precipitation is over local land.

Hydrological Storage Length Scales Represented by Remote Sensing Estimates of Soil Moisture and Precipitation

NASA Astrophysics Data System (ADS)

Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara

2018-03-01

The soil water content profile is often well correlated with the soil moisture state near the surface. They share mutual information such that analysis of surface-only soil moisture is, at times and in conjunction with precipitation information, reflective of deeper soil fluxes and dynamics. This study examines the characteristic length scale, or effective depth Δz, of a simple active hydrological control volume. The volume is described only by precipitation inputs and soil water dynamics evident in surface-only soil moisture observations. To proceed, first an observation-based technique is presented to estimate the soil moisture loss function based on analysis of soil moisture dry-downs and its successive negative increments. Then, the length scale Δz is obtained via an optimization process wherein the root-mean-squared (RMS) differences between surface soil moisture observations and its predictions based on water balance are minimized. The process is entirely observation-driven. The surface soil moisture estimates are obtained from the NASA Soil Moisture Active Passive (SMAP) mission and precipitation from the gauge-corrected Climate Prediction Center daily global precipitation product. The length scale Δz exhibits a clear east-west gradient across the contiguous United States (CONUS), such that large Δz depths (>200 mm) are estimated in wetter regions with larger mean precipitation. The median Δz across CONUS is 135 mm. The spatial variance of Δz is predominantly explained and influenced by precipitation characteristics. Soil properties, especially texture in the form of sand fraction, as well as the mean soil moisture state have a lesser influence on the length scale.

Comparison of Ground- and Space-based Radar Observations with Disdrometer Measurements During the PECAN Field Campaign

NASA Astrophysics Data System (ADS)

Torres, A. D.; Rasmussen, K. L.; Bodine, D. J.; Dougherty, E.

2015-12-01

Plains Elevated Convection At Night (PECAN) was a large field campaign that studied nocturnal mesoscale convective systems (MCSs), convective initiation, bores, and low-level jets across the central plains in the United States. MCSs are responsible for over half of the warm-season precipitation across the central U.S. plains. The rainfall from deep convection of these systems over land have been observed to be underestimated by satellite radar rainfall-retrieval algorithms by as much as 40 percent. These algorithms have a strong dependence on the generally unmeasured rain drop-size distribution (DSD). During the campaign, our group measured rainfall DSDs, precipitation fall velocities, and total precipitation in the convective and stratiform regions of MCSs using Ott Parsivel optical laser disdrometers. The disdrometers were co-located with mobile pod units that measured temperature, wind, and relative humidity for quality control purposes. Data from the operational NEXRAD radar in LaCrosse, Wisconsin and space-based radar measurements from a Global Precipitation Measurement satellite overpass on July 13, 2015 were used for the analysis. The focus of this study is to compare DSD measurements from the disdrometers to radars in an effort to reduce errors in existing rainfall-retrieval algorithms. The error analysis consists of substituting measured DSDs into existing quantitative precipitation estimation techniques (e.g. Z-R relationships and dual-polarization rain estimates) and comparing these estimates to ground measurements of total precipitation. The results from this study will improve climatological estimates of total precipitation in continental convection that are used in hydrological studies, climate models, and other applications.

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.

The linkage between geopotential height and monthly precipitation in Iran

NASA Astrophysics Data System (ADS)

Shirvani, Amin; Fadaei, Amir Sabetan; Landman, Willem A.

2018-04-01

This paper investigates the linkage between large-scale atmospheric circulation and monthly precipitation during November to April over Iran. Canonical correlation analysis (CCA) is used to set up the statistical linkage between the 850 hPa geopotential height large-scale circulation and monthly precipitation over Iran for the period 1968-2010. The monthly precipitation dataset for 50 synoptic stations distributed in different climate regions of Iran is considered as the response variable in the CCA. The monthly geopotential height reanalysis dataset over an area between 10° N and 60° N and from 20° E to 80° E is utilized as the explanatory variable in the CCA. Principal component analysis (PCA) as a pre-filter is used for data reduction for both explanatory and response variables before applying CCA. The optimal number of principal components and canonical variables to be retained in the CCA equations is determined using the highest average cross-validated Kendall's tau value. The 850 hPa geopotential height pattern over the Red Sea, Saudi Arabia, and Persian Gulf is found to be the major pattern related to Iranian monthly precipitation. The Pearson correlation between the area averaged of the observed and predicted precipitation over the study area for Jan, Feb, March, April, November, and December months are statistically significant at the 5% significance level and are 0.78, 0.80, 0.82, 0.74, 0.79, and 0.61, respectively. The relative operating characteristic (ROC) indicates that the highest scores for the above- and below-normal precipitation categories are, respectively, for February and April and the lowest scores found for December.

Coherence among climate signals, precipitation, and groundwater.

PubMed

Ghanbari, Reza Namdar; Bravo, Hector R

2011-01-01

Climate signals may affect groundwater level at different time scales in different geographical regions, and those patterns or time scales can be estimated using coherence analysis. This study shows that the synthesis effort required to search for patterns at the physical geography scale is possible, and this approach should be applicable in other regions of the world. The relations between climate signals, Southern Oscillation Index, Pacific Decadal Oscillation, North Atlantic Oscillation, North Pacific Pattern (SOI, PDO, NAO, and NP), precipitation, and groundwater level in three geographical areas of Wisconsin are examined using a three-tiered coherence analysis. In the high frequency band (<4(-1) cycles/year), there is a significant coherence between four climate signals and groundwater level in all three areas. In the low frequency band (>8(-1) to ≤23(-1) cycles/year), we found significant coherence between the SOI and NP signals and groundwater level in the forested area, characterized by shallow wells constructed in sand and gravel aquifers. In the high frequency band, there is significant coherence between the four climate signals and precipitation in all three areas. In the low frequency band, the four climate signals have effect on precipitation in the agricultural area, and SOI and NP have effect on precipitation in the forested and driftless areas. Precipitation affects groundwater level in all three areas, and in high, low and intermediate frequency bands. In the agricultural area, deeper aquifers and a more complex hydrostratigraphy and land use dilute the effect of precipitation on groundwater level for interdecadal frequencies. Copyright © 2010 The Author(s). Journal compilation © 2010 National Ground Water Association.