Spatiotemporal Co-variability of Surface Climate for Renewable Energy across the Contiguous United States: Role of the North Atlantic Subtropical High

NASA Astrophysics Data System (ADS)

Doering, K.; Steinschneider, S.

2017-12-01

The variability of renewable energy supply and drivers of demand across space and time largely determines the energy balance within power systems with a high penetration of renewable technologies. This study examines the joint spatiotemporal variability of summertime climate linked to renewable energy production (precipitation, wind speeds, insolation) and energy demand (temperature) across the contiguous United States (CONUS) between 1948 and 2015. Canonical correlation analysis is used to identify the major modes of joint variability between summer wind speeds and precipitation and related patterns of insolation and temperature. Canonical variates are then related to circulation anomalies to identify common drivers of the joint modes of climate variability. Results show that the first two modes of joint variability between summer wind speeds and precipitation exhibit pan-US dipole patterns with centers of action located in the eastern and central CONUS. Temperature and insolation also exhibit related US-wide dipoles. The relationship between canonical variates and lower-tropospheric geopotential height indicates that these modes are related to variability in the North Atlantic subtropical high (NASH). This insight can inform optimal strategies for siting renewables in an interconnected electric grid, and has implications for the impacts of climate variability and change on renewable energy systems.

Precipitation variability inferred from the annual growth and isotopic composition of tropical trees

NASA Astrophysics Data System (ADS)

Ballantyne, A. P.; Baker, P. A.; Chambers, J. Q.; Villalba, R.

2005-12-01

Here we demonstrate that annual growth and isotopic ratios in tropical trees are responsive to seasonal and annual precipitation variability. We identify several regions of tropical South America characterized by significant relationships between oxygen isotopic ratios (δ 18O) in precipitation and precipitation amount (r = -0.82). Many of these regions are also sensitive to inter-annual variability in the South American Monsoon modulated by the El Niño Southern Oscillation (ENSO). The effectiveness of δ 18O and annual growth of tropical trees as a precipitation proxy is validated by high-resolution sampling of a Tachigali vermelho tree growing near Manaus, Brazil (3.1° S, 60.0° S). Growth in Tachigali spp. was highly correlated with both precipitation and cellulose δ 18O (r = 0.60) and precipitation amount was significantly correlated with δ 18O at a lag of approximately one month (r = 0.56). We also report a multi-proxy record spanning 180 years from Cedrela odorata growing in the Peruvian Amazon near Puerto Maldonado (12.6° S, 69.2° W) revealing a significant relationship between cellulose and monsoon precipitation over the region (r = -0.33). A 150-year record obtained from Polylepis tarapacana growing at Volcan Granada in Northern Argentina (22.0° S, 66.0° W) is also reported with a significant relationship between local monsoon precipitation and a regionally derived ring width index (r = 0.38). Although no significant relationship was revealed between cellulose δ 18O and precipitation in this taxa at this location, separate radii within the same tree revealed a significantly coherent δ 18O signal (r = 0.38). We compared our proxy chronologies with monsoon precipitation reanalysis data for tropical South America, which revealed key features of the South American Monsoon and their sensitivity to ENSO variability.

High resolution reconstruction of monthly autumn and winter precipitation of Iberian Peninsula for last 150 years.

NASA Astrophysics Data System (ADS)

Cortesi, N.; Trigo, R.; González-Hidalgo, J. C.; Ramos, A.

2012-04-01

Precipitation over Iberian Peninsula (IP) presents large values of interannual variability and large spatial contrasts between wet mountainous regions in the north and dry regions in the southern plains. Unlike other European regions, IP was poorly monitored for precipitation during 19th century. Here we present a new approach to fill this gap. A set of 26 atmospheric circulation weather types (Trigo R.M. and DaCamara C.C., 2000) derived from a recent SLP dataset, the EMULATE (European and North Atlantic daily to multidecadal climate variability) Project, was used to reconstruct Iberian monthly precipitation from October to March during 1851-1947. Principal Component Regression Analysis was chosen to develop monthly precipitation reconstruction back to 1851 and calibrated over 1948-2003 period for 3030 monthly precipitation series of high-density homogenized MOPREDAS (Monthly Precipitation Database for Spain and Portugal) database. Validation was conducted over 1920-1947 at 15 key site locations. Results show high model performance for selected months, with a mean coefficient of variation (CV) around 0.6 during validation period. Lower CV values were achieved in western area of IP. Trigo, R. M., and DaCamara, C.C., 2000: "Circulation weather types and their impact on the precipitation regime in Portugal". Int. J. Climatol., 20, 1559-1581.

Repeated and random components in Oklahoma's monthly precipitation record

USDA-ARS?s Scientific Manuscript database

Precipitation across Oklahoma exhibits a high degree of spatial and temporal variability and creates numerous water resources management challenges. The monthly precipitation record of the Central Oklahoma climate division was evaluated in a proof-of-concept to establish whether a simple monthly pre...

Precipitation Storage Efficiency During Fallow in Wheat-Fallow Systems

USDA-ARS?s Scientific Manuscript database

Wheat-fallow production systems arose in order to stabilize widely ranging wheat yields that resulted from highly variable precipitation in the Great Plains. Historically, precipitation storage efficiency (PSE) over the fallow period increased over time as inversion tillage systems used for weed con...

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

PubMed

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

2016-01-01

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

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.

Variability of Precipitation and Evapotranspiration across an Andean Paramo

NASA Astrophysics Data System (ADS)

Jaimes, J. C.; Riveros-Iregui, D.; Avery, W. A.; Gaviria, S.; Peña-Quemba, C.; Herran, G.

2012-12-01

Paramos are alpine grasslands that occur mostly in the Andes Mountains of South America. Typically soils in the paramo have a volcanic origin, which leads to high permeability and high water yield and makes the paramo a reliable drinking water supply for many highland cities. Because hydrological measurements in these humid systems are rare, current understanding of the hydrologic behavior of paramos relies on modeling studies with little validation against ground observations. We present measurements of evapotranspiration (ET) and precipitation (P) across Chingaza Paramo, near Bogotá, Colombia. This paramo supplies water for ~80% of Bogotá's population (a total of 8 million people). Meteorological variables such us air temperature, relative humidity, wind speed, precipitation, and solar radiation were monitored using five weather stations located at various elevations from 3000m to 3600m. Our results show that ET varies from 500 to 700 mm y-1 as a function of elevation, whereas precipitation commonly exceeds ET, ranging between 1500 and 1800 mm y-1. These spatial differences between P and ET make water yield highly variable across this mountainous environment. Our results demonstrate that while paramos play an important role in the hydrologic cycle of tropical environments, understanding their hydrologic behavior requires characterization and monitoring of the pronounced spatial gradients of precipitation and evapotranspiration.

Uncertainty Propagation of Non-Parametric-Derived Precipitation Estimates into Multi-Hydrologic Model Simulations

NASA Astrophysics Data System (ADS)

Bhuiyan, M. A. E.; Nikolopoulos, E. I.; Anagnostou, E. N.

2017-12-01

Quantifying the uncertainty of global precipitation datasets is beneficial when using these precipitation products in hydrological applications, because precipitation uncertainty propagation through hydrologic modeling can significantly affect the accuracy of the simulated hydrologic variables. In this research the Iberian Peninsula has been used as the study area with a study period spanning eleven years (2000-2010). This study evaluates the performance of multiple hydrologic models forced with combined global rainfall estimates derived based on a Quantile Regression Forests (QRF) technique. In QRF technique three satellite precipitation products (CMORPH, PERSIANN, and 3B42 (V7)); an atmospheric reanalysis precipitation and air temperature dataset; satellite-derived near-surface daily soil moisture data; and a terrain elevation dataset are being utilized in this study. A high-resolution, ground-based observations driven precipitation dataset (named SAFRAN) available at 5 km/1 h resolution is used as reference. Through the QRF blending framework the stochastic error model produces error-adjusted ensemble precipitation realizations, which are used to force four global hydrological models (JULES (Joint UK Land Environment Simulator), WaterGAP3 (Water-Global Assessment and Prognosis), ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) and SURFEX (Stands for Surface Externalisée) ) to simulate three hydrologic variables (surface runoff, subsurface runoff and evapotranspiration). The models are forced with the reference precipitation to generate reference-based hydrologic simulations. This study presents a comparative analysis of multiple hydrologic model simulations for different hydrologic variables and the impact of the blending algorithm on the simulated hydrologic variables. Results show how precipitation uncertainty propagates through the different hydrologic model structures to manifest in reduction of error in hydrologic variables.

Timing of climate variability and grassland productivity

PubMed Central

Craine, Joseph M.; Nippert, Jesse B.; Elmore, Andrew J.; Skibbe, Adam M.; Hutchinson, Stacy L.; Brunsell, Nathaniel A.

2012-01-01

Future climates are forecast to include greater precipitation variability and more frequent heat waves, but the degree to which the timing of climate variability impacts ecosystems is uncertain. In a temperate, humid grassland, we examined the seasonal impacts of climate variability on 27 y of grass productivity. Drought and high-intensity precipitation reduced grass productivity only during a 110-d period, whereas high temperatures reduced productivity only during 25 d in July. The effects of drought and heat waves declined over the season and had no detectable impact on grass productivity in August. If these patterns are general across ecosystems, predictions of ecosystem response to climate change will have to account not only for the magnitude of climate variability but also for its timing. PMID:22331914

Synchronous precipitation reduction in the American Tropics associated with Heinrich 2.

PubMed

Medina-Elizalde, Martín; Burns, Stephen J; Polanco-Martinez, Josué; Lases-Hernández, Fernanda; Bradley, Raymond; Wang, Hao-Cheng; Shen, Chuan-Chou

2017-09-11

During the last ice age temperature in the North Atlantic oscillated in cycles known as Dansgaard-Oeschger (D-O) events. The magnitude of Caribbean hydroclimate change associated with D-O variability and particularly with stadial intervals, remains poorly constrained by paleoclimate records. We present a 3.3 thousand-year long stalagmite δ 18 O record from the Yucatan Peninsula (YP) that spans the interval between 26.5 and 23.2 thousand years before present. We estimate quantitative precipitation variability and the high resolution and dating accuracy of this record allow us to investigate how rainfall in the region responds to D-O events. Quantitative precipitation estimates are based on observed regional amount effect variability, last glacial paleotemperature records, and estimates of the last glacial oxygen isotopic composition of precipitation based on global circulation models (GCMs). The new precipitation record suggests significant low latitude hydrological responses to internal modes of climate variability and supports a role of Caribbean hydroclimate in helping Atlantic Meridional Overturning Circulation recovery during D-O events. Significant in-phase precipitation reduction across the equator in the tropical Americas associated with Heinrich event 2 is suggested by available speleothem oxygen isotope records.

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.

Towards an automatic statistical model for seasonal precipitation prediction and its application to Central and South Asian headwater catchments

NASA Astrophysics Data System (ADS)

Gerlitz, Lars; Gafurov, Abror; Apel, Heiko; Unger-Sayesteh, Katy; Vorogushyn, Sergiy; Merz, Bruno

2016-04-01

Statistical climate forecast applications typically utilize a small set of large scale SST or climate indices, such as ENSO, PDO or AMO as predictor variables. If the predictive skill of these large scale modes is insufficient, specific predictor variables such as customized SST patterns are frequently included. Hence statistically based climate forecast models are either based on a fixed number of climate indices (and thus might not consider important predictor variables) or are highly site specific and barely transferable to other regions. With the aim of developing an operational seasonal forecast model, which is easily transferable to any region in the world, we present a generic data mining approach which automatically selects potential predictors from gridded SST observations and reanalysis derived large scale atmospheric circulation patterns and generates robust statistical relationships with posterior precipitation anomalies for user selected target regions. Potential predictor variables are derived by means of a cellwise correlation analysis of precipitation anomalies with gridded global climate variables under consideration of varying lead times. Significantly correlated grid cells are subsequently aggregated to predictor regions by means of a variability based cluster analysis. Finally for every month and lead time, an individual random forest based forecast model is automatically calibrated and evaluated by means of the preliminary generated predictor variables. The model is exemplarily applied and evaluated for selected headwater catchments in Central and South Asia. Particularly the for winter and spring precipitation (which is associated with westerly disturbances in the entire target domain) the model shows solid results with correlation coefficients up to 0.7, although the variability of precipitation rates is highly underestimated. Likewise for the monsoonal precipitation amounts in the South Asian target areas a certain skill of the model could be detected. The skill of the model for the dry summer season in Central Asia and the transition seasons over South Asia is found to be low. A sensitivity analysis by means on well known climate indices reveals the major large scale controlling mechanisms for the seasonal precipitation climate of each target area. For the Central Asian target areas, both, the El Nino Southern Oscillation and the North Atlantic Oscillation are identified as important controlling factors for precipitation totals during moist spring season. Drought conditions are found to be triggered by a warm ENSO phase in combination with a positive phase of the NAO. For the monsoonal summer precipitation amounts over Southern Asia, the model suggests a distinct negative response to El Nino events.

Analysis of the interdecadal variability of summer precipitation in central Japan using a reconstructed 106 year long oxygen isotope record from tree ring cellulose

NASA Astrophysics Data System (ADS)

Kurita, Naoyuki; Nakatsuka, Takeshi; Ohnishi, Keiko; Mitsutani, Takumi; Kumagai, Tomo'omi

2016-10-01

We present a unique proxy for reconstructing the interannual variability of summer precipitation associated with the quasi-stationary front (Baiu front) in central Japan. The rainfall from the Baiu front has a relatively lower oxygen isotopic composition than other types of nonfrontal precipitation. The variability in the oxygen isotopes in summer rainfall is closely related to the Baiu frontal activity. In this study we used a mechanistic tree ring isotope model to reconstruct a 106 year long oxygen isotopic composition of precipitation during the early rainy season (June) based on the oxygen isotopic compositions of the annual rings of Chamaecyparis obtusa Endl trees from central Japan. The year-to-year variations of the isotopes over the most recent 25 years are associated with several teleconnection patterns that often lead to the Baiu precipitation anomalies in central Japan (such as the Pacific-Japan (PJ) pattern, Silk Road pattern, and wave train pattern along the polar jet). Yet none of these external forcing mechanisms apply further back in time. From the 1950s to 1980s, the interannual isotopic variability is predominantly related to local factors such as anomalous intensification/weakening of the Bonin High. Before the 1950s, the variability of the oxygen isotopic composition of precipitation is mainly associated with a wave train pattern along the polar jet. The isotopic variability is predominantly linked to the PJ pattern, while the PJ index is correlated with El Niño-Southern Oscillation. These findings suggest that the teleconnection patterns influencing Baiu precipitation variability vary according to interdecadal time scales during the twentieth century.

El-Niño/Southern Oscillation (ENSO) influences on monthly NO 3 load and concentration, stream flow and precipitation in the Little River Watershed, Tifton, Georgia (GA)

NASA Astrophysics Data System (ADS)

Keener, V. W.; Feyereisen, G. W.; Lall, U.; Jones, J. W.; Bosch, D. D.; Lowrance, R.

2010-02-01

SummaryAs climate variability increases, it is becoming increasingly critical to find predictable patterns that can still be identified despite overall uncertainty. The El-Niño/Southern Oscillation is the best known pattern. Its global effects on weather, hydrology, ecology and human health have been well documented. Climate variability manifested through ENSO has strong effects in the southeast United States, seen in precipitation and stream flow data. However, climate variability may also affect water quality in nutrient concentrations and loads, and have impacts on ecosystems, health, and food availability in the southeast. In this research, we establish a teleconnection between ENSO and the Little River Watershed (LRW), GA., as seen in a shared 3-7 year mode of variability for precipitation, stream flow, and nutrient load time series. Univariate wavelet analysis of the NINO 3.4 index of sea surface temperature (SST) and of precipitation, stream flow, NO 3 concentration and load time series from the watershed was used to identify common signals. Shared 3-7 year modes of variability were seen in all variables, most strongly in precipitation, stream flow and nutrient load in strong El Niño years. The significance of shared 3-7 year periodicity over red noise with 95% confidence in SST and precipitation, stream flow, and NO 3 load time series was confirmed through cross-wavelet and wavelet-coherence transforms, in which common high power and co-variance were computed for each set of data. The strongest 3-7 year shared power was seen in SST and stream flow data, while the strongest co-variance was seen in SST and NO 3 load data. The strongest cross-correlation was seen as a positive value between the NINO 3.4 and NO 3 load with a three-month lag. The teleconnection seen in the LRW between the NINO 3.4 index and precipitation, stream flow, and NO 3 load can be utilized in a model to predict monthly nutrient loads based on short-term climate variability, facilitating management in high risk seasons.

Cross-Regional Assessment Of Coupling And Variability In Precipitation-Runoff Relationships

NASA Astrophysics Data System (ADS)

Carey, S. K.; Tetzlaff, D.; Soulsby, C.; Buttle, J. M.; Laudon, H.; McDonnell, J. J.; McGuire, K. J.; Seibert, J.; Shanley, J. B.

2011-12-01

The higher mid-latitudes of the northern hemisphere are particularly sensitive to change due to the important role the zero-degree isotherm plays in the phase of precipitation and intermediate storage as snow. An international inter-catchment comparison program North-Watch seeks to improve our understanding of the sensitivity of northern catchments to change by examining their hydrological and biogeochemical variability and response. The catchments are located in Sweden (Krycklan), Scotland (Mharcaidh, Girnock and Strontian), the United States (Sleepers River, Hubbard Brook and HJ Andrews) and Canada (Catamaran, Dorset and Wolf Creek). For this study, 8 catchments with 10 continuous years of daily precipitation and runoff data were selected to assess the seasonal coupling of rainfall and runoff and the memory effect of runoff events on the hydrograph at different time scales. To assess the coupling and synchroneity of precipitation, continuous wavelet transforms and wavelet coherence were used. Wavelet spectra identified the relative importance of both annual versus seasonal flows while wavelet coherence was applied to identify over different time scales along the 10-year window how well precipitation and runoff were coupled. For example, while on a given day, precipitation may be closely coupled to runoff, a wet year may not necessarily be a high runoff year in catchments with large storage. Assessing different averaging periods in the variation of daily flows highlights the importance of seasonality in runoff response and the relative influence of rain versus snowmelt on flow magnitude and variability. Wet catchments with limited seasonal precipitation variability (Strontian, Girnock) have precipitation signals more closely coupled with runoff, whereas dryer catchments dominated by snow (Wolf Creek, Krycklan) have strongly coupling only during freshet. Most catchments with highly seasonal precipitation show strong intermittent coupling during their wet season. At longer time scales, some catchments do not exhibit coupling in their input-output relations, which is related to catchment storage.

Identification of weather variables sensitive to dysentery in disease-affected county of China.

PubMed

Liu, Jianing; Wu, Xiaoxu; Li, Chenlu; Xu, Bing; Hu, Luojia; Chen, Jin; Dai, Shuang

2017-01-01

Climate change mainly refers to long-term change in weather variables, and it has significant impact on sustainability and spread of infectious diseases. Among three leading infectious diseases in China, dysentery is exclusively sensitive to climate change. Previous researches on weather variables and dysentery mainly focus on determining correlation between dysentery incidence and weather variables. However, the contribution of each variable to dysentery incidence has been rarely clarified. Therefore, we chose a typical county in epidemic of dysentery as the study area. Based on data of dysentery incidence, weather variables (monthly mean temperature, precipitation, wind speed, relative humidity, absolute humidity, maximum temperature, and minimum temperature) and lagged analysis, we used principal component analysis (PCA) and classification and regression trees (CART) to examine the relationships between the incidence of dysentery and weather variables. Principal component analysis showed that temperature, precipitation, and humidity played a key role in determining transmission of dysentery. We further selected weather variables including minimum temperature, precipitation, and relative humidity based on results of PCA, and used CART to clarify contributions of these three weather variables to dysentery incidence. We found when minimum temperature was at a high level, the high incidence of dysentery occurred if relative humidity or precipitation was at a high level. We compared our results with other studies on dysentery incidence and meteorological factors in areas both in China and abroad, and good agreement has been achieved. Yet, some differences remain for three reasons: not identifying all key weather variables, climate condition difference caused by local factors, and human factors that also affect dysentery incidence. This study hopes to shed light on potential early warnings for dysentery transmission as climate change occurs, and provide a theoretical basis for the control and prevention of dysentery. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Precipitation variability in the Four Corners region USA from 2002 to 2015

NASA Astrophysics Data System (ADS)

Tulley-Cordova, C. L.; Bowen, G. J.; Brady, I.; Bekis, J.

2016-12-01

Due to the arid climate, the Navajo Nation situated in the southwestern United States (US) is sensitive to small changes in precipitation. The Navajo Nation is the largest land based tribe in the US; Navajo residents, wildlife, livestock, and vegetation are highly dependent on water resources including precipitation, surface, ground, and spring waters for vitality. Changes in precipitation directly impacts the Navajo Nation's ecosystem including a variety of interconnected effects such as ground water recharge, frequency of dust migration and strength of winds, flow in ephemeral and perennial streams, plant and animal populations, wildfires, change in vegetative cover and possible alterations in species composition. This study examines hydroclimatic changes during months, seasons, and water years across the Navajo Nation from 2002 to 2015 and how Four Corners USA precipitation variability and trends compares to large-scale atmospheric circulation patterns. Examination of spatial and temporal trends of precipitation variability during this time period can be used to assist an area with limited water management infrastructure with future water planning and help understand a region that has been poorly studied in the past.

Tree-ring-based reconstruction of precipitation in the Bighorn Basin, Wyoming, since 1260 A.D

USGS Publications Warehouse

Gray, S.T.; Fastie, C.L.; Jackson, S.T.; Betancourt, J.L.

2004-01-01

Cores and cross sections from 79 Douglas fir (Pseudotsuga menziesii) and limber pine (Pinus flexilis) trees at four sites in the Bighorn Basin of north-central Wyoming and south-central Montana were used to develop a proxy for annual (June-June) precipitation spanning 1260-1998 A.D. The reconstruction exhibits considerable nonstationarity, and the instrumental era (post-1900) in particular fails to capture the full range of precipitation variability experienced in the past ???750 years. Both single-year and decadal-scale dry events were more severe before 1900. Dry spells in the late thirteenth and sixteenth centuries surpass both magnitude and duration of any droughts in the Bighorn Basin after 1900. Precipitation variability appears to shift to a higher-frequency mode after 1750, with 15-20-yr droughts becoming rare. Comparisons between instrumental and reconstructed values of precipitation and indices of Pacific basin variability reveal that precipitation in the Bighorn Basin generally responds to Pacific forcing in a manner similar to that of the southwestern United States (drier during La Nin??a events), but high country precipitation in areas surrounding the basin displays the opposite response (drier during El Nin??o events). ?? 2004 American Meteorological Society.

Inferring Spatio-temporal Variations in the Risk of Extreme Precipitation in the Western United States from Tree-ring Chronologies

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Ho, M.; Cook, E. R.; Lall, U.

2017-12-01

This work explores how extreme cold-season precipitation dynamics along the west coast of the United States have varied in the past under natural climate variability through an analysis of the moisture anomalies recorded by tree-ring chronologies across the coast and interior of the western U.S. Winters with high total precipitation amounts in the coastal regions are marked by a small number of extreme storms that exhibit distinct spatial patterns of precipitation across the coast and further inland. Building from this observation, this work develops a novel application of dendroclimatic evidence to explore the following questions: a) how is extreme precipitation variability expressed in a network of tree-ring chronologies; b) can this information provide insight on the space-time variability of storm tracks that cause these extreme events; and c) how can the joint variability of extreme precipitation and storm tracks be modeled to develop consistent, multi-centennial reconstructions of both? We use gridded, tree-ring based reconstructions of the summer Palmer Drought Severity Index (PDSI) extending back 500 years within the western U.S. to build and test a novel statistical framework for reconstructing the space-time variability of coastal extreme precipitation and the associated wintertime storm tracks. Within this framework, we (1) identify joint modes of variability of extreme precipitation fields and tree-ring based PDSI reconstructions; (2) relate these modes to previously identified, unique storm track patterns associated with atmospheric rivers (ARs), which are the dominant type of storm that is responsible for extreme precipitation in the region; and (3) determine latitudinal variations of landfalling ARs across the west coast and their relationship to the these joint modes. To our knowledge, this work is the first attempt to leverage information on storm track patterns stored in a network of paleoclimate proxies to improve reconstruction fidelity.

Inferring Spatio-temporal Variations in the Risk of Extreme Precipitation in the Western United States from Tree-ring Chronologies

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Ho, M.; Cook, E. R.; Lall, U.

2016-12-01

This work explores how extreme cold-season precipitation dynamics along the west coast of the United States have varied in the past under natural climate variability through an analysis of the moisture anomalies recorded by tree-ring chronologies across the coast and interior of the western U.S. Winters with high total precipitation amounts in the coastal regions are marked by a small number of extreme storms that exhibit distinct spatial patterns of precipitation across the coast and further inland. Building from this observation, this work develops a novel application of dendroclimatic evidence to explore the following questions: a) how is extreme precipitation variability expressed in a network of tree-ring chronologies; b) can this information provide insight on the space-time variability of storm tracks that cause these extreme events; and c) how can the joint variability of extreme precipitation and storm tracks be modeled to develop consistent, multi-centennial reconstructions of both? We use gridded, tree-ring based reconstructions of the summer Palmer Drought Severity Index (PDSI) extending back 500 years within the western U.S. to build and test a novel statistical framework for reconstructing the space-time variability of coastal extreme precipitation and the associated wintertime storm tracks. Within this framework, we (1) identify joint modes of variability of extreme precipitation fields and tree-ring based PDSI reconstructions; (2) relate these modes to previously identified, unique storm track patterns associated with atmospheric rivers (ARs), which are the dominant type of storm that is responsible for extreme precipitation in the region; and (3) determine latitudinal variations of landfalling ARs across the west coast and their relationship to the these joint modes. To our knowledge, this work is the first attempt to leverage information on storm track patterns stored in a network of paleoclimate proxies to improve reconstruction fidelity.

An assessment of precipitation and surface air temperature over China by regional climate models

NASA Astrophysics Data System (ADS)

Wang, Xueyuan; Tang, Jianping; Niu, Xiaorui; Wang, Shuyu

2016-12-01

An analysis of a 20-year summer time simulation of present-day climate (1989-2008) over China using four regional climate models coupled with different land surface models is carried out. The climatic means, interannual variability, linear trends, and extremes are examined, with focus on precipitation and near surface air temperature. The models are able to reproduce the basic features of the observed summer mean precipitation and temperature over China and the regional detail due to topographic forcing. Overall, the model performance is better for temperature than that of precipitation. The models reasonably grasp the major anomalies and standard deviations over China and the five subregions studied. The models generally reproduce the spatial pattern of high interannual variability over wet regions, and low variability over the dry regions. The models also capture well the variable temperature gradient increase to the north by latitude. Both the observed and simulated linear trend of precipitation shows a drying tendency over the Yangtze River Basin and wetting over South China. The models capture well the relatively small temperature trends in large areas of China. The models reasonably simulate the characteristics of extreme precipitation indices of heavy rain days and heavy precipitation fraction. Most of the models also performed well in capturing both the sign and magnitude of the daily maximum and minimum temperatures over China.

How will wind and water erosion change in drylands in the future?

NASA Astrophysics Data System (ADS)

Okin, G. S.; Sala, O.; Vivoni, E. R.

2017-12-01

Drylands are characterized as much by high spatial and temporal variability as they are by low precipitation. Cover that is patchy at multiple scales allows connectivity for wind and water transport. Vegetation dynamics at interannual scales occurs in the context of community change (including woody encroachment) at decadal scales. Periods of drought alternate with relatively wet periods. Future predictions for the world's drylands are that many will become more arid, but near all will experience greater climate variability. This work explores how future variability will affect transport by wind and water, both of which are crucial elements of biotic-abiotic feedbacks that control community change in drylands. This work is based on long-term observations from the Jornada Long Term Ecological Research (LTER), but with lessons that are applicable elsewhere. We find strong relationships between vegetation community, precipitation and aeolian transport related to changes in connectivity. We further identify strong, scale-dependent relationships between precipitation and runoff. Thus, aeolian transport decreases with increasing annual precipitation and transport by water increases with annual precipitation, with the combined effect that increased variability in annual precipitation is likely to increase both water and wind transport. The consequence of this is that feedbacks associated with community change are likely to strengthen in the future.

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

NASA Astrophysics Data System (ADS)

Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

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.

Improving High-Resolution Weather Forecasts Using the Weather Research and Forecasting (WRF) Model with an Updated Kain–Fritsch Scheme

EPA Science Inventory

Efforts to improve the prediction accuracy of high-resolution (1–10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at ...

Tightening of tropical ascent and high clouds key to precipitation change in a warmer climate

PubMed Central

Su, Hui; Jiang, Jonathan H.; Neelin, J. David; Shen, T. Janice; Zhai, Chengxing; Yue, Qing; Wang, Zhien; Huang, Lei; Choi, Yong-Sang; Stephens, Graeme L.; Yung, Yuk L.

2017-01-01

The change of global-mean precipitation under global warming and interannual variability is predominantly controlled by the change of atmospheric longwave radiative cooling. Here we show that tightening of the ascending branch of the Hadley Circulation coupled with a decrease in tropical high cloud fraction is key in modulating precipitation response to surface warming. The magnitude of high cloud shrinkage is a primary contributor to the intermodel spread in the changes of tropical-mean outgoing longwave radiation (OLR) and global-mean precipitation per unit surface warming (dP/dTs) for both interannual variability and global warming. Compared to observations, most Coupled Model Inter-comparison Project Phase 5 models underestimate the rates of interannual tropical-mean dOLR/dTs and global-mean dP/dTs, consistent with the muted tropical high cloud shrinkage. We find that the five models that agree with the observation-based interannual dP/dTs all predict dP/dTs under global warming higher than the ensemble mean dP/dTs from the ∼20 models analysed in this study. PMID:28589940

Holocene Evolution of Precipitation Patterns in the Southwestern US, Mexico, Central America, and Caribbean: Comparison with Tropical SST Records

NASA Astrophysics Data System (ADS)

Barron, J. A.; Metcalfe, S. E.; Davies, S. J.

2014-12-01

We evaluate proxy reconstructions of Holocene records precipitation in the North American Monsoon region (SW US and northern Mexico) and regions to the south (southern Mexico, Central America, and the Caribbean). Seventy-seven precipitation records are tabulated at 2-3 kyr increments for the past 12 kyr, with results displayed mainly on maps. Sites currently dominated by summer precipitation, coupled with proxy records that distinguish summer vs. winter vegetation are used to estimate summer precipitation. Resulting patterns of precipitation variability are evaluated against SST reconstructions from surrounding tropical seas -eastern tropical Pacific, Gulf of California (GoC), Caribbean, and Gulf of Mexico (GoM), which are source areas for summer precipitation. During the Younger Dryas, ca. 12 ka, widespread drying in southern regions contrasted with evidence for wetter conditions in multiple records from the SW US. By 9 ka wetter conditions had spread to the southern regions, likely reflecting an increased Caribbean low-level jet associated with an enhanced Bermuda High. Pacific westerlies contributed significant winter precipitation to the southwestern US and northernmost Mexico at 9 ka. The modern geographical pattern of summer precipitation was established by 6 ka, as the Bermuda High moved northward following the demise of the Laurentide Ice Sheet. SSTs in the GoC and GoM increased, and the NAM strengthened. Increased regional precipitation differences are apparent by 4 ka, likely reflecting enhanced ENSO variability. Most of the southern region experienced increased precipitation during the Medieval Climate Anomaly (MCA), whereas winter drought dominated in the north. In contrast, much of the Little Ice Age (LIA) was characterized by generally drier conditions in Central America and Mexico, with wetter conditions in the SW US. Results are broadly supportive of enhanced La Niña-like conditions during the MCA vs. increased ENSO variability during the LIA.

Validation of China-wide interpolated daily climate variables from 1960 to 2011

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang

2015-02-01

Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based on the performance of these variables in estimating daily variations, interannual variability, and extreme events. Although longitude, latitude, and elevation data are included in the model, additional information, such as topography and cloud cover, should be integrated into the interpolation algorithm to improve performance in estimating wind speed, atmospheric pressure, and precipitation.

Sensitivity of crop cover to climate variability: insights from two Indian agro-ecoregions.

PubMed

Mondal, Pinki; Jain, Meha; DeFries, Ruth S; Galford, Gillian L; Small, Christopher

2015-01-15

Crop productivity in India varies greatly with inter-annual climate variability and is highly dependent on monsoon rainfall and temperature. The sensitivity of yields to future climate variability varies with crop type, access to irrigation and other biophysical and socio-economic factors. To better understand sensitivities to future climate, this study focuses on agro-ecological subregions in Central and Western India that span a range of crops, irrigation, biophysical conditions and socioeconomic characteristics. Climate variability is derived from remotely-sensed data products, Tropical Rainfall Measuring Mission (TRMM - precipitation) and Moderate Resolution Imaging Spectroradiometer (MODIS - temperature). We examined green-leaf phenologies as proxy for crop productivity using the MODIS Enhanced Vegetation Index (EVI) from 2000 to 2012. Using both monsoon and winter growing seasons, we assessed phenological sensitivity to inter-annual variability in precipitation and temperature patterns. Inter-annual EVI phenology anomalies ranged from -25% to 25%, with some highly anomalous values up to 200%. Monsoon crop phenology in the Central India site is highly sensitive to climate, especially the timing of the start and end of the monsoon and intensity of precipitation. In the Western India site, monsoon crop phenology is less sensitive to precipitation variability, yet shows considerable fluctuations in monsoon crop productivity across the years. Temperature is critically important for winter productivity across a range of crop and management types, such that irrigation might not provide a sufficient buffer against projected temperature increases. Better access to weather information and usage of climate-resilient crop types would play pivotal role in maintaining future productivity. Effective strategies to adapt to projected climate changes in the coming decades would also need to be tailored to regional biophysical and socio-economic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

A proxy for high-resolution regional reanalysis for the Southeast United States: assessment of precipitation variability in dynamically downscaled reanalyses

USGS Publications Warehouse

Stefanova, Lydia; Misra, Vasubandhu; Chan, Steven; Griffin, Melissa; O'Brien, James J.; Smith, Thomas J.

2012-01-01

We present an analysis of the seasonal, subseasonal, and diurnal variability of rainfall from COAPS Land- Atmosphere Regional Reanalysis for the Southeast at 10-km resolution (CLARReS10). Most of our assessment focuses on the representation of summertime subseasonal and diurnal variability.Summer precipitation in the Southeast United States is a particularly challenging modeling problem because of the variety of regional-scale phenomena, such as sea breeze, thunderstorms and squall lines, which are not adequately resolved in coarse atmospheric reanalyses but contribute significantly to the hydrological budget over the region. We find that the dynamically downscaled reanalyses are in good agreement with station and gridded observations in terms of both the relative seasonal distribution and the diurnal structure of precipitation, although total precipitation amounts tend to be systematically overestimated. The diurnal cycle of summer precipitation in the downscaled reanalyses is in very good agreement with station observations and a clear improvement both over their "parent" reanalyses and over newer-generation reanalyses. The seasonal cycle of precipitation is particularly well simulated in the Florida; this we attribute to the ability of the regional model to provide a more accurate representation of the spatial and temporal structure of finer-scale phenomena such as fronts and sea breezes. Over the northern portion of the domain summer precipitation in the downscaled reanalyses remains, as in the "parent" reanalyses, overestimated. Given the degree of success that dynamical downscaling of reanalyses demonstrates in the simulation of the characteristics of regional precipitation, its favorable comparison to conventional newer-generation reanalyses and its cost-effectiveness, we conclude that for the Southeast United states such downscaling is a viable proxy for high-resolution conventional reanalysis.

Analysis of the historical precipitation in the South East Iberian Peninsula at different spatio-temporal scale. Study of the meteorological drought

NASA Astrophysics Data System (ADS)

Fernández-Chacón, Francisca; Pulido-Velazquez, David; Jiménez-Sánchez, Jorge; Luque-Espinar, Juan Antonio

2017-04-01

Precipitation is a fundamental climate variable that has a pronounced spatial and temporal variability on a global scale, as well as at regional and sub-regional scales. Due to its orographic complexity and its latitude the Iberian Peninsula (IP), located to the west of the Mediterranean Basin between the Atlantic Ocean and the Mediterranean Sea, has a complex climate. Over the peninsula there are strong north-south and east-west gradients, as a consequence of the different low-frequency atmospheric patterns, and he overlap of these over the year will be determinants in the variability of climatic variables. In the southeast of the Iberian Peninsula dominates a dry Mediterranean climate, the precipitation is characterized as being an intermittent and discontinuous variable. In this research information coming from the Spain02 v4 database was used to study the South East (SE) IP for the 1971-2010 period with a spatial resolution of 0.11 x 0.11. We analysed precipitation at different time scale (daily, monthly, seasonal, annual,…) to study the spatial distribution and temporal tendencies. The high spatial, intra-annual and inter-annual climatic variability observed makes it necessary to propose a climatic regionalization. In addition, for the identified areas and subareas of homogeneous climate we have analysed the evolution of the meteorological drought for the same period at different time scales. The standardized precipitation index has been used at 12, 24 and 48 month temporal scale. The climatic complexity of the area determines a high variability in the drought characteristics, duration, intensity and frequency in the different climatic areas. This research has been supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 project for the data provided for this study.

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management

USGS Publications Warehouse

Jonas, Jayne L.; Buhl, Deborah A.; Symstad, Amy J.

2015-01-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess 1) the portion of interannual variability of richness and diversity explained by weather, 2) how relationships between these metrics and weather vary among plant assemblages, and 3) which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six datasets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.Read More: http://www.esajournals.org/doi/abs/10.1890/14-1989.1

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management.

PubMed

Jonas, Jayne L; Buhl, Deborah A; Symstad, Amy J

2015-09-01

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess the portion of interannual variability of richness and diversity explained by weather, how relationships between these metrics and weather vary among plant assemblages, and which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six data sets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Retrospective and Prospective Reports of Precipitants to Relapse in Pathological Gambling

ERIC Educational Resources Information Center

Hodgins, David C.; el-Guebaly, Nady

2004-01-01

A prospective design was used to explore the precipitants of relapse in a naturalistic sample of pathological gamblers (N = 101) who had recently quit gambling. Relapse rates were high; only 8% were entirely free of gambling during the 12-month follow-up. Relapses were highly variable but occurred most frequently in the evening, when the person…

Confounding factors in determining causal soil moisture-precipitation feedback

NASA Astrophysics Data System (ADS)

Tuttle, Samuel E.; Salvucci, Guido D.

2017-07-01

Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.

South Asian high and Asian-Pacific-American climate teleconnection

NASA Astrophysics Data System (ADS)

Zhang, Peiqun; Song, Yang; Kousky, Vernon E.

2005-11-01

Growing evidence indicates that the Asian monsoon plays an important role in affecting the weather and climate outside of Asia. However, this active role of the monsoon has not been demonstrated as thoroughly as has the variability of the monsoon caused by various impacting factors such as sea surface temperature and land surface. This study investigates the relationship between the Asian monsoon and the climate anomalies in the Asian-Pacific-American (APA) sector. A hypothesis is tested that the variability of the upper-tropospheric South Asian high (SAH), which is closely associated with the overall heating of the large-scale Asian monsoon, is linked to changes in the subtropical western Pacific high (SWPH), the mid-Pacific trough, and the Mexican high. The changes in these circulation systems cause variability in surface temperature and precipitation in the APA region. A stronger SAH is accompanied by a stronger and more extensive SWPH. The enlargement of the SWPH weakens the mid-Pacific trough. As a result, the southern portion of the Mexican high becomes stronger. These changes are associated with changes in atmospheric teleconnections, precipitation, and surface temperature throughout the APA region. When the SAH is stronger, precipitation increases in southern Asia, decreases over the Pacific Ocean, and increases over the Central America. Precipitation also increases over Australia and central Africa and decreases in the Mediterranean region. While the signals in surface temperature are weak over the tropical land portion, they are apparent in the mid latitudes and over the eastern Pacific Ocean.

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

NASA Astrophysics Data System (ADS)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Regional variation of flow duration curves in the eastern United States: Process-based analyses of the interaction between climate and landscape properties

NASA Astrophysics Data System (ADS)

Chouaib, Wafa; Caldwell, Peter V.; Alila, Younes

2018-04-01

This paper advances the physical understanding of the flow duration curve (FDC) regional variation. It provides a process-based analysis of the interaction between climate and landscape properties to explain disparities in FDC shapes. We used (i) long term measured flow and precipitation data over 73 catchments from the eastern US. (ii) We calibrated the Sacramento model (SAC-SMA) to simulate soil moisture and flow components FDCs. The catchments classification based on storm characteristics pointed to the effect of catchments landscape properties on the precipitation variability and consequently on the FDC shapes. The landscape properties effect was pronounce such that low value of the slope of FDC (SFDC)-hinting at limited flow variability-were present in regions of high precipitation variability. Whereas, in regions with low precipitation variability the SFDCs were of larger values. The topographic index distribution, at the catchment scale, indicated that saturation excess overland flow mitigated the flow variability under conditions of low elevations with large soil moisture storage capacity and high infiltration rates. The SFDCs increased due to the predominant subsurface stormflow in catchments at high elevations with limited soil moisture storage capacity and low infiltration rates. Our analyses also highlighted the major role of soil infiltration rates on the FDC despite the impact of the predominant runoff generation mechanism and catchment elevation. In conditions of slow infiltration rates in soils of large moisture storage capacity (at low elevations) and predominant saturation excess, the SFDCs were of larger values. On the other hand, the SFDCs decreased in catchments of prevalent subsurface stormflow and poorly drained soils of small soil moisture storage capacity. The analysis of the flow components FDCs demonstrated that the interflow contribution to the response was the higher in catchments with large value of slope of the FDC. The surface flow FDC was the most affected by the precipitation as it tracked the precipitation duration curve (PDC). In catchments with low SFDCs, this became less applicable as surface flow FDC diverged from PDC at the upper tail (> 40% of the flow percentile). The interflow and baseflow FDCs illustrated most the filtering effect on the precipitation. The process understanding we achieved in this study is key for flow simulation and assessment in addition to future works focusing on process-based FDC predictions.

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.

Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production

NASA Astrophysics Data System (ADS)

Zhang, Yao; Xiao, Xiangming; Guanter, Luis; Zhou, Sha; Ciais, Philippe; Joiner, Joanna; Sitch, Stephen; Wu, Xiaocui; Nabel, Julia; Dong, Jinwei; Kato, Etsushi; Jain, Atul K.; Wiltshire, Andy; Stocker, Benjamin D.

2016-12-01

Carbon uptake by terrestrial ecosystems is increasing along with the rising of atmospheric CO2 concentration. Embedded in this trend, recent studies suggested that the interannual variability (IAV) of global carbon fluxes may be dominated by semi-arid ecosystems, but the underlying mechanisms of this high variability in these specific regions are not well known. Here we derive an ensemble of gross primary production (GPP) estimates using the average of three data-driven models and eleven process-based models. These models are weighted by their spatial representativeness of the satellite-based solar-induced chlorophyll fluorescence (SIF). We then use this weighted GPP ensemble to investigate the GPP variability for different aridity regimes. We show that semi-arid regions contribute to 57% of the detrended IAV of global GPP. Moreover, in regions with higher GPP variability, GPP fluctuations are mostly controlled by precipitation and strongly coupled with evapotranspiration (ET). This higher GPP IAV in semi-arid regions is co-limited by supply (precipitation)-induced ET variability and GPP-ET coupling strength. Our results demonstrate the importance of semi-arid regions to the global terrestrial carbon cycle and posit that there will be larger GPP and ET variations in the future with changes in precipitation patterns and dryland expansion.

Precipitation and Carbon-Water Coupling Jointly Control the Interannual Variability of Global Land Gross Primary Production

NASA Technical Reports Server (NTRS)

Zhang, Yao; Xiao, Xiangming; Guanter, Luis; Zhou, Sha; Ciais, Philippe; Joiner, Joanna; Sitch, Stephen; Wu, Xiaocui; Nabel, Julian; Dong, Jinwei;

A Study on Temperature and Precipitation Variability in Pre-monsoon Period of 2016 in the Dudh Khola River Valley, Manang, Nepal

NASA Astrophysics Data System (ADS)

Kayastha, R.; Kayastha, R. B.; Chand, M. B.; Armstrong, R. L.

2016-12-01

Meteorological data are the key parameter for deeper and better understanding the local to regional climate variability. Temperature and precipitation are highly dependent on elevation and it is foremost important in water resource management. The runoff from glacierized catchments is greatly influenced by the variation in temperature and precipitation. However, inaccessibility limits the hydro-meteorological data observation in high altitudes. In this study, temperature and precipitation data are observed and analyzed from six stations including two weather stations in different elevation ranging from 1926 to 3908 m a.s.l. in the Dudh Khola River basin, a sub basin of Marsyangdi River basin from March to June 2016 (pre-monsoon period). Clear spatial and temporal variability of temperature lapse rate (TLR) is observed which is related to the extent of humid air. The hourly mean TLR shows highly heterogeneous between the different elevations from - 0.72 o C, -0.51 o C, -0.77 o C, -0.68 to +0.42 o C per 100 m and the hourly linear regression of TLR is - 0.54 o C per 100 m. Similarly, vertical precipitation gradients (PG) between Dharapani & Goa, Goa & Yak Kharka, and Yak Kharka & glacier station are 0.040, 0.037 and 0.032 per meter respectively. Horizontal precipitation gradient from lower station to the higher station in a distance of 16 km is 0.0015 mm per meter. The TLR from the recorded period are less than the environmental lapse rate in the Dudh Khola Valley in pre-monsoon season. From this study it can be concluded that hourly and daily lapse rates and PGs can be used to improve the output of the glacio-hydrological and energy balance modelling in glacierized river basin.

Climate Change of 4°C GlobalWarming above Pre-industrial Levels

NASA Astrophysics Data System (ADS)

Wang, Xiaoxin; Jiang, Dabang; Lang, Xianmei

2018-07-01

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4°C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4°C global warming will occur is 2084. Based on the median results of models that project a 4°C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-tonoise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5°C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the intermodel consistency is better for temperature than for precipitation.

Spatial and temporal patterns of precipitation and stream flow variations in Tigris-Euphrates river basin.

PubMed

Daggupati, Prasad; Srinivasan, Raghavan; Ahmadi, Mehdi; Verma, Deepa

2017-01-01

Tigris and Euphrates river basin (TERB) is one of the largest river basins in the Middle East, and the precipitation (in the form of snowfall) is a major source of streamflow. This study investigates the spatial and temporal variability of precipitation and streamflow in TERB to better understand the hydroclimatic variables and how they varied over time. The precipitation shows a decreasing trend with 1980s being wetter and 2000s being drier. A total of 55 and 40% reduction in high flows in Tigris and Euphrates rivers at T20 and E3 was seen in post-reservoir period. A lag time of 3 to 4 and 5 to 6 months was estimated between peak snowfall and runoff time periods. Decreasing precipitation and streamflow along with several planned dams could hamper the sustainability of several Mesopotamian marshlands that completely depend on the water from the Tigris and Euphrates rivers.

An assessment of differences in gridded precipitation datasets in complex terrain

NASA Astrophysics Data System (ADS)

Henn, Brian; Newman, Andrew J.; Livneh, Ben; Daly, Christopher; Lundquist, Jessica D.

2018-01-01

Hydrologic modeling and other geophysical applications are sensitive to precipitation forcing data quality, and there are known challenges in spatially distributing gauge-based precipitation over complex terrain. We conduct a comparison of six high-resolution, daily and monthly gridded precipitation datasets over the Western United States. We compare the long-term average spatial patterns, and interannual variability of water-year total precipitation, as well as multi-year trends in precipitation across the datasets. We find that the greatest absolute differences among datasets occur in high-elevation areas and in the maritime mountain ranges of the Western United States, while the greatest percent differences among datasets relative to annual total precipitation occur in arid and rain-shadowed areas. Differences between datasets in some high-elevation areas exceed 200 mm yr-1 on average, and relative differences range from 5 to 60% across the Western United States. In areas of high topographic relief, true uncertainties and biases are likely higher than the differences among the datasets; we present evidence of this based on streamflow observations. Precipitation trends in the datasets differ in magnitude and sign at smaller scales, and are sensitive to how temporal inhomogeneities in the underlying precipitation gauge data are handled.

Comparison of Two Grid Refinement Approaches for High Resolution Regional Climate Modeling: MPAS vs WRF

NASA Astrophysics Data System (ADS)

Leung, L.; Hagos, S. M.; Rauscher, S.; Ringler, T.

2012-12-01

This study compares two grid refinement approaches using global variable resolution model and nesting for high-resolution regional climate modeling. The global variable resolution model, Model for Prediction Across Scales (MPAS), and the limited area model, Weather Research and Forecasting (WRF) model, are compared in an idealized aqua-planet context with a focus on the spatial and temporal characteristics of tropical precipitation simulated by the models using the same physics package from the Community Atmosphere Model (CAM4). For MPAS, simulations have been performed with a quasi-uniform resolution global domain at coarse (1 degree) and high (0.25 degree) resolution, and a variable resolution domain with a high-resolution region at 0.25 degree configured inside a coarse resolution global domain at 1 degree resolution. Similarly, WRF has been configured to run on a coarse (1 degree) and high (0.25 degree) resolution tropical channel domain as well as a nested domain with a high-resolution region at 0.25 degree nested two-way inside the coarse resolution (1 degree) tropical channel. The variable resolution or nested simulations are compared against the high-resolution simulations that serve as virtual reality. Both MPAS and WRF simulate 20-day Kelvin waves propagating through the high-resolution domains fairly unaffected by the change in resolution. In addition, both models respond to increased resolution with enhanced precipitation. Grid refinement induces zonal asymmetry in precipitation (heating), accompanied by zonal anomalous Walker like circulations and standing Rossby wave signals. However, there are important differences between the anomalous patterns in MPAS and WRF due to differences in the grid refinement approaches and sensitivity of model physics to grid resolution. This study highlights the need for "scale aware" parameterizations in variable resolution and nested regional models.

Improving synoptic and intraseasonal variability in CFSv2 via stochastic representation of organized convection

NASA Astrophysics Data System (ADS)

Goswami, B. B.; Khouider, B.; Phani, R.; Mukhopadhyay, P.; Majda, A.

2017-01-01

To better represent organized convection in the Climate Forecast System version 2 (CFSv2), a stochastic multicloud model (SMCM) parameterization is adopted and a 15 year climate run is made. The last 10 years of simulations are analyzed here. While retaining an equally good mean state (if not better) as the parent model, the CFS-SMCM simulation shows significant improvement in the synoptic and intraseasonal variability. The CFS-SMCM provides a better account of convectively coupled equatorial waves and the Madden-Julian oscillation. The CFS-SMCM exhibits improvements in northward and eastward propagation of intraseasonal oscillation of convection including the MJO propagation beyond the maritime continent barrier, which is the Achilles Heel for coarse-resolution global climate models (GCMs). The distribution of precipitation events is better simulated in CFSsmcm and spreads naturally toward high-precipitation events. Deterministic GCMs tend to simulate a narrow distribution with too much drizzling precipitation and too little high-precipitation events.

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

NASA Astrophysics Data System (ADS)

Hayashi, Masaki; Farrow, Christopher R.

2014-12-01

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

A 60,000-year record of hydrologic variability in the Central Andes from the hydrogen isotopic composition of leaf waxes in Lake Titicaca sediments

NASA Astrophysics Data System (ADS)

Fornace, Kyrstin L.; Hughen, Konrad A.; Shanahan, Timothy M.; Fritz, Sherilyn C.; Baker, Paul A.; Sylva, Sean P.

2014-12-01

A record of the hydrogen isotopic composition of terrestrial leaf waxes (δDwax) in sediment cores from Lake Titicaca provides new insight into the precipitation history of the Central Andes and controls of South American Summer Monsoon (SASM) variability since the last glacial period. Comparison of the δDwax record with a 19-kyr δD record from the nearby Illimani ice core supports the interpretation that precipitation δD is the primary control on δDwax with a lesser but significant role for local evapotranspiration and other secondary influences on δDwax. The Titicaca δDwax record confirms overall wetter conditions in the Central Andes during the last glacial period relative to a drier Holocene. During the last deglaciation, abrupt δDwax shifts correspond to millennial-scale events observed in the high-latitude North Atlantic, with dry conditions corresponding to the Bølling-Allerød and early Holocene periods and wetter conditions during late glacial and Younger Dryas intervals. We observe a trend of increasing monsoonal precipitation from the early to the late Holocene, consistent with summer insolation forcing of the SASM, but similar hydrologic variability on precessional timescales is not apparent during the last glacial period. Overall, this study demonstrates the relative importance of high-latitude versus tropical forcing as a dominant control on glacial SASM precipitation variability.

Climate dynamics of South America during summer: Connections between the large-scale circulation and regional precipitation

NASA Astrophysics Data System (ADS)

Lenters, Johh Derick

1997-05-01

Relationships between the large-scale circulation and regional precipitation over South America during austral summer are examined using a GCM, linear model, and observational analyses. Emphasis is placed on understanding the origin of upper-tropospheric circulation features such as the Bolivian high and its effects on South American precipitation variability, particularly on the Central Andean Altiplano. Results from the linear model indicate that the Bolivian high and 'Nordeste low' are generated in response to precipitation over the Amazon basin, Central Andes, and South Atlantic convergence zone (SACZ), with African precipitation also playing a crucial role in the formation of the low. The direct mechanical and sensible heating effects of the Andes are minimal, acting only to induce a weak lee trough in midlatitudes and a shallow monsoonal circulation over the Central Andes. In the GCM the effects of the Andes include a strengthening of the Bolivian high and northward shift of the Nordeste low, primarily through changes in the precipitation field. The position of the Bolivian high is primarily determined by Amazonian precipitation and is little affected by the removal of the Andes. Strong subsidence to the west of the high is found to be important for the maintenance of the high's warm core, while large-scale convective overshooting to the east is responsible for a layer of cold air above the high. Observations from eight summer seasons reveal a close relationship between precipitation variability in the Central Andes and the position and intensity of the Bolivian high. The physical mechanisms of this connection are explored using composite, EOF, and correlation techniques. On intraseasonal to interannual timescales, rainy episodes on the Altiplano are found to be associated with warm, moist, poleward flow along the eastern flank of the Andes, often in conjunction with extratropical disturbances and a westward displacement of the SACZ. Corresponding to this northerly advection of warm air is the southward enhancement of the Bolivian high. During dry periods such as the 1987 El Nino, enhanced frontal activity and associated cool, dry, southerly flow east of the Altiplano results in a northward displacement of the Bolivian high.

Does climatic variability influence agricultural land prices under differing uses? The Texas High Plains case

USDA-ARS?s Scientific Manuscript database

The Texas High Plains faces projections of increasing temperature and declining precipitation in the future on account of its semi-arid climate. This research evaluated the impact of climatic variability on agricultural land prices under different land uses in the Texas High Plains, employing the Ri...

Detrital events and hydroclimate variability in the Romanian Carpathians during the mid-to-late Holocene

NASA Astrophysics Data System (ADS)

Longman, Jack; Ersek, Vasile; Veres, Daniel; Salzmann, Ulrich

2017-07-01

The Romanian Carpathians are located at the confluence of three major atmospheric pressure fields: the North Atlantic, the Mediterranean and the Siberian. Despite its importance for understanding past human impact and climate change, high-resolution palaeoenvironmental reconstructions of Holocene hydroclimate variability, and in particular records of extreme precipitation events in the area, are rare. Here we present a 7500-year-long high-resolution record of past climatic change and human impact recorded in a peatbog from the Southern Carpathians, integrating palynological, geochemical and sedimentological proxies. Natural climate fluctuations appear to be dominant until 4500 years before present (yr BP), followed by increasing importance of human impact. Sedimentological and geochemical analyses document regular minerogenic deposition within the bog, linked to periods of high precipitation. Such minerogenic depositional events began 4000 yr BP, with increased depositional rates during the Medieval Warm Period (MWP), the Little Ice Age (LIA) and during periods of societal upheaval (e.g. the Roman conquest of Dacia). The timing of minerogenic events appears to indicate a teleconnection between major shifts in North Atlantic Oscillation (NAO) and hydroclimate variability in southeastern Europe, with increased minerogenic deposition correlating to low NAO index values. By linking the minerogenic deposition to precipitation variability, we state that this link persists throughout the mid-to-late Holocene.

High-resolution projections of 21st century climate over the Athabasca River Basin through an integrated evaluation-classification-downscaling-based climate projection framework

NASA Astrophysics Data System (ADS)

Cheng, Guanhui; Huang, Guohe; Dong, Cong; Zhu, Jinxin; Zhou, Xiong; Yao, Y.

2017-03-01

An evaluation-classification-downscaling-based climate projection (ECDoCP) framework is developed to fill a methodological gap of general circulation models (GCMs)-driven statistical-downscaling-based climate projections. ECDoCP includes four interconnected modules: GCM evaluation, climate classification, statistical downscaling, and climate projection. Monthly averages of daily minimum (Tmin) and maximum (Tmax) temperature and daily cumulative precipitation (Prec) over the Athabasca River Basin (ARB) at a 10 km resolution in the 21st century under four Representative Concentration Pathways (RCPs) are projected through ECDoCP. At the octodecadal scale, temperature and precipitation would increase; after bias correction, temperature would increase with a decreased increment, while precipitation would increase only under RCP 8.5. Interannual variability of climate anomalies would increase from RCPs 4.5, 2.6, 6.0 to 8.5 for temperature and from RCPs 2.6, 4.5, 6.0 to 8.5 for precipitation. Bidecadal averaged climate anomalies would decrease from December-January-February (DJF), March-April-May (MAM), September-October-November (SON) to June-July-August (JJA) for Tmin, from DJF, SON, MAM to JJA for Tmax, and from JJA, MAM, SON to DJF for Prec. Climate projection uncertainties would decrease in May to September for temperature and in November to April for precipitation. Spatial climatic variability would not obviously change with RCPs; climatic anomalies are highly correlated with climate-variable magnitudes. Climate anomalies would decrease from upstream to downstream for temperature, and precipitation would follow an opposite pattern. The north end and the other zones would have colder and warmer days, respectively; precipitation would decrease in the upstream and increase in the remaining region. Climate changes might lead to issues, e.g., accelerated glacier/snow melting, deserving attentions of researchers and the public.

Interannual variability of the atmospheric CO2 growth rate: relative contribution from precipitation and temperature

NASA Astrophysics Data System (ADS)

Wang, J.; Zeng, N.; Wang, M. R.

2015-12-01

The interannual variability (IAV) in atmospheric CO2 growth rate (CGR) is closely connected with the El Niño-Southern Oscillation. However, sensitivities of CGR to temperature and precipitation remain largely uncertain. This paper analyzed the relationship between Mauna Loa CGR and tropical land climatic elements. We find that Mauna Loa CGR lags precipitation by 4 months with a correlation coefficient of -0.63, leads temperature by 1 month (0.77), and correlates with soil moisture (-0.65) with zero lag. Additionally, precipitation and temperature are highly correlated (-0.66), with precipitation leading by 4-5 months. Regression analysis shows that sensitivities of Mauna Loa CGR to temperature and precipitation are 2.92 ± 0.20 Pg C yr-1 K-1 and -0.46 ± 0.07 Pg C yr-1 100 mm-1, respectively. Unlike some recent suggestions, these empirical relationships favor neither temperature nor precipitation as the dominant factor of CGR IAV. We further analyzed seven terrestrial carbon cycle models, from the TRENDY project, to study the processes underlying CGR IAV. All models capture well the IAV of tropical land-atmosphere carbon flux (CFTA). Sensitivities of the ensemble mean CFTA to temperature and precipitation are 3.18 ± 0.11 Pg C yr-1 K-1 and -0.67 ± 0.04 Pg C yr-1 100 mm-1, close to Mauna Loa CGR. Importantly, the models consistently show the variability in net primary productivity (NPP) dominates CGR, rather than soil respiration. Because NPP is largely driven by precipitation, this suggests a key role of precipitation in CGR IAV despite the higher CGR correlation with temperature. Understanding the relative contribution of CO2 sensitivity to precipitation and temperature has important implications for future carbon-climate feedback using such "emergent constraint".

The contributions of local and remote atmospheric moisture fluxes to East Asian precipitation and its variability

NASA Astrophysics Data System (ADS)

Guo, Liang; Klingaman, Nicholas P.; Demory, Marie-Estelle; Vidale, Pier Luigi; Turner, Andrew G.; Stephan, Claudia C.

2018-01-01

We investigate the contribution of the local and remote atmospheric moisture fluxes to East Asia (EA) precipitation and its interannual variability during 1979-2012. We use and expand the Brubaker et al. (J Clim 6:1077-1089,1993) method, which connects the area-mean precipitation to area-mean evaporation and the horizontal moisture flux into the region. Due to its large landmass and hydrological heterogeneity, EA is divided into five sub-regions: Southeast (SE), Tibetan Plateau (TP), Central East (CE), Northwest (NW) and Northeast (NE). For each region, we first separate the contributions to precipitation of local evaporation from those of the horizontal moisture flux by calculating the precipitation recycling ratio: the fraction of precipitation over a region that originates as evaporation from the same region. Then, we separate the horizontal moisture flux across the region's boundaries by direction. We estimate the contributions of the horizontal moisture fluxes from each direction, as well as the local evaporation, to the mean precipitation and its interannual variability. We find that the major contributors to the mean precipitation are not necessarily those that contribute most to the precipitation interannual variability. Over SE, the moisture flux via the southern boundary dominates the mean precipitation and its interannual variability. Over TP, in winter and spring, the moisture flux via the western boundary dominates the mean precipitation; however, variations in local evaporation dominate the precipitation interannual variability. The western moisture flux is the dominant contributor to the mean precipitation over CE, NW and NE. However, the southern or northern moisture flux or the local evaporation dominates the precipitation interannual variability over these regions, depending on the season. Potential mechanisms associated with interannual variability in the moisture flux are identified for each region. The methods and results presented in this study can be readily applied to model simulations, to identify simulation biases in precipitation that relate to the simulated moisture supplies and transport.

Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble

PubMed Central

Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork

2016-01-01

Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment. PMID:27425819

Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble.

PubMed

Jiang, Mingkai; Felzer, Benjamin S; Sahagian, Dork

2016-07-18

Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950-2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040-2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment.

30,000 years of hydroclimatic variability in the coastal southwest United States: regional synthesis and forcings analysis.

NASA Astrophysics Data System (ADS)

Kirby, M. E.

2015-12-01

The coastal southwest United States is characterized by a winter dominated hydroclimate. Far from dependable, this region's supply of winter precipitation is highly variable and often characterized by hydrologic opposites - droughts and floods. Predicting future precipitation and hydrologic dynamics requires a paleoperspective. Here, we present an up-to-date synthesis of hydroclimatic variability over the past 30,000 years. A variety of terrestrial-based studies are examined and compared to understand patterns of regional hydroclimatic change. This comparison is extended into the San Joaquin Basin of California where future climate change will impact the region's agricultural stability and economy. Particularly interesting is the apparent role that Pacific sea surface temperatures (SSTs) play in modulating the region's hydroclimate over a variety of timescales. Are past periods of above average Pacific SSTs analogs for future global warming? If yes, the region might expect an increase in winter precipitation as SSTs rise in response to global warming. However, how this potential precipitation increase is manifest is unknown. For example, will the intensity of precipitation events increase and thus present increased flood hazards and diminished freshwater capture? Finally, we present evidence for changes in the source of winter precipitation over time as well as ecological responses to past hydrologic change.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Understanding the interdecadal variabilities of East Asian summer precipitation: from a perspective of joint influence of oceanic forcings

NASA Astrophysics Data System (ADS)

Zhang, Z.; Sun, X.; Yang, X. Q.

2017-12-01

East Asian summer precipitation (EASP) is highly complicated in both temporal and spatial variabilities at interdecadal time scales, with various time periods and anomalous spatial distribution patterns. The joint influences of three dominant interdecadal signals, i.e., Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO) and Indian Ocean Basin Mode (IOBM), are revealed to be responsible for most of the interdecadal variabilities of EASP in this study, which, however, are not the simply linear combinations of their individual climate effects. Specifically, when PDO and AMO are in antiphase, SST anomalies of the same signs appear in both North Pacific and North Atlantic, the Asian westerly jet (AWJ) is accelerated and acts as a waveguide, favoring a zonally orientated Rossby wave train from North Atlantic to northern East Asia across the mid-high latitude Eurasia. Correspondingly, interdecadal precipitation anomalies exhibit a meridional tripole mode over East China. When PDO and AMO are in phase with oppositely signed SST anomalies in North Pacific and North Atlantic, the waveguide mechanism doesn't work since AWJ is significantly reduced, and the Rossby wave train from North Atlantic travels to South Asia along the great circle path, causing anomalous Indian summer monsoon precipitation (ISMP). In turn, by triggering another Rossby wave trains along both the mid-latitudes and coastal regions of East Asia, the ISMP anomalies induce a meridional dipole mode of interdecadal precipitation anomalies over East China. Through the ISMP and the same dynamical processes, IOBM is more important for the interdecadal precipitation anomalies over northern East Asia.

A Data Centred Method to Estimate and Map Changes in the Full Distribution of Daily Precipitation and Its Exceedances

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2014-12-01

Estimates of how our climate is changing are needed locally in order to inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles or thresholds in distributions of variables such as daily temperature or precipitation. We develop a method[1] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes, to specifically address the challenges presented by 'heavy tailed' distributed variables such as daily precipitation. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the relative amount of precipitation in those extreme precipitation days. Our method is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of precipitation distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily precipitation from specific locations across Europe over the last 60 years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the pattern of change at a given threshold of precipitation and with geographical location. This is model- independent, thus providing data of direct value in model calibration and assessment. Our results identify regionally consistent patterns which, dependent on location, show systematic increase in precipitation on the wettest days, shifts in precipitation patterns to less moderate days and more heavy days, and drying across all days which is of potential value in adaptation planning. [1] S C Chapman, D A Stainforth, N W Watkins, 2013 Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, S. C. Chapman, N. W. Watkins, 2013 Environ. Res. Lett. 8, 034031 [2] Haylock et al. 2008 J. Geophys. Res (Atmospheres), 113, D20119

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

Vertical structure and microphysical characteristics of precipitation on the high terrain and lee side of the Olympic Mountains

NASA Astrophysics Data System (ADS)

Zagrodnik, J. P.; McMurdie, L. A.; Houze, R.

2017-12-01

As mid-latitude cyclones pass over coastal mountain ranges, the processes producing their clouds and precipitation are modified when they encounter complex terrain, leading to a maximum in precipitation fallout on the windward slopes and a minimum on the lee side. The precipitation that does reach the high terrain and lee side of a mountain range can be theoretically determined by a complex interaction between the dynamics of air lifting over the terrain, the thermodynamics of moist air, and the microphysical time required to grow particles large enough to fall out. To date, there have been few observational studies that have focused on the nonlinear microphysical processes contributing to the variability of precipitation that is received on the lee side slopes of a mountain range such as the Olympic Mountains. The 2015-16 Olympic Mountains Experiment (OLYMPEX) collected unprecedented observations on the high terrain and lee side of the Olympic Mountains including frequent soundings on Vancouver Island, dual-polarization Doppler radar, multi-frequency airborne radar, and ground-based particle size and crystal habit observations at the higher elevation Hurricane Ridge site. We utilize these observations to examine the evolution of the vertical structure and microphysical precipitation characteristics over the high terrain and leeside within the context of large-scale dynamic and thermodynamic conditions that evolve during the passage of cold season mid-latitude cyclones. The primary goal is to determine the degree to which the observed variability in lee side precipitation amount and microphysical properties are controlled by variations in temperature, flow speed and direction, shear, and stability associated with characteristic synoptic storm sectors and frontal passages.

Variability of dissolved organic carbon in precipitation during storms at the Shale Hills Critical Zone Observatory

USGS Publications Warehouse

Iavorivska , Lidiia; Boyer, Elizabeth W.; Grimm, Jeffrey W.; Miller, Matthew P.; DeWalle, David R.; Davis, Kenneth J.; Kaye, Margot W.

2017-01-01

Organic compounds are removed from the atmosphere and deposited to the earth's surface via precipitation. In this study, we quantified variations of dissolved organic carbon (DOC) in precipitation during storm events at the Shale Hills Critical Zone Observatory, a forested watershed in central Pennsylvania (USA). Precipitation samples were collected consecutively throughout the storm during 13 events, which spanned a range of seasons and synoptic meteorological conditions, including a hurricane. Further, we explored factors that affect the temporal variability by considering relationships of DOC in precipitation with atmospheric and storm characteristics. Concentrations and chemical composition of DOC changed considerably during storms, with the magnitude of change within individual events being comparable or higher than the range of variation in average event composition among events. While some previous studies observed that concentrations of other elements in precipitation typically decrease over the course of individual storm events, results of this study show that DOC concentrations in precipitation are highly variable. During most storm events concentrations decreased over time, possibly as a result of washing out of the below-cloud atmosphere. However, increasing concentrations that were observed in the later stages of some storm events highlight that DOC removal with precipitation is not merely a dilution response. Increases in DOC during events could result from advection of air masses, local emissions during breaks in precipitation, or chemical transformations in the atmosphere that enhance solubility of organic carbon compounds. This work advances understanding of processes occurring during storms that are relevant to studies of atmospheric chemistry, carbon cycling, and ecosystem responses.

Changes in the intensity of Mediterranean precipitation: a comparison of east/west trends and their causes

NASA Astrophysics Data System (ADS)

Goodess, C. M.; Jones, P. D.

2003-04-01

Changes in the frequency and intensity of precipitation over the last 40 years have been investigated for the Iberian Peninsula and Greece. Over much of the Mediterranean the general tendency is towards decreasing precipitation, but the pattern of change is complex, particularly with respect to extremes. Over most of the Iberian Peninsula, the last 40 years has seen a trend towards more, but less wet rain days. However, in southeast Spain, the reverse has occurred, with more wet days with high precipitation amounts. Over Greece, the main tendency is towards fewer rain days, with little change in rain day amount, which is strongest over the Ionian and Aegean Seas and in winter. A few places, such as Rhodes, do however, show a weak trend towards more intense precipitation events in autumn. The precipitation changes observed over the Iberian Peninsula can, in part, be explained by changes in atmospheric circulation. They are associated with a decrease in the frequency of cyclonic circulation types and increases in the frequency of anticyclonic, easterly and south-easterly types (which can in turn be linked with changes in the intensity of the North Atlantic Oscillation and the frequency and intensity of Mediterranean and Atlantic cyclones). However, precipitation trends simulated by regression models with circulation-type frequency as the predictor variables are weaker than observed. The observed changes in circulation-type frequency over Greece (such as the increase in the frequency of the 'high-precipitation' cyclonic types and decrease in the 'low-precipitation' anticyclonic types) indicate an increase in precipitation. This is in contrast to the observed precipitation decreases. All the regression models underestimate year-to-year variability, and have problems in reproducing the observed trends. The common problems in both regions indicate that different forms of model may be required. The finding that the selected predictor variables are more successful at reproducing the observed precipitation trends in Spain than Greece, indicates different underlying physical processes which require further investigation. Goodess, CM and Jones, PD, 2002: Links between circulation and changes in the characteristics of Iberian precipitation, Int. J. Climatol. 22, 1593-1615. Acknowledgements: This work (http://www.cru.uea.ac.uk/~clareg/nerc.htm) was funded by the Commission of the European Union as part of the ACCORD project and by the UK Natural Environment Research Council.

Evaluating and Quantifying the Climate-Driven Interannual Variability in Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fanwei; Collatz, George James; Pinzon, Jorge E.; Ivanoff, Alvaro

2013-01-01

Satellite observations of surface reflected solar radiation contain informationabout variability in the absorption of solar radiation by vegetation. Understanding thecauses of variability is important for models that use these data to drive land surface fluxesor for benchmarking prognostic vegetation models. Here we evaluated the interannualvariability in the new 30.5-year long global satellite-derived surface reflectance index data,Global Inventory Modeling and Mapping Studies normalized difference vegetation index(GIMMS NDVI3g). Pearsons correlation and multiple linear stepwise regression analyseswere applied to quantify the NDVI interannual variability driven by climate anomalies, andto evaluate the effects of potential interference (snow, aerosols and clouds) on the NDVIsignal. We found ecologically plausible strong controls on NDVI variability by antecedent precipitation and current monthly temperature with distinct spatial patterns. Precipitation correlations were strongest for temperate to tropical water limited herbaceous systemswhere in some regions and seasons 40 of the NDVI variance could be explained byprecipitation anomalies. Temperature correlations were strongest in northern mid- to-high-latitudes in the spring and early summer where up to 70 of the NDVI variance was explained by temperature anomalies. We find that, in western and central North America,winter-spring precipitation determines early summer growth while more recent precipitation controls NDVI variability in late summer. In contrast, current or prior wetseason precipitation anomalies were correlated with all months of NDVI in sub-tropical herbaceous vegetation. Snow, aerosols and clouds as well as unexplained phenomena still account for part of the NDVI variance despite corrections. Nevertheless, this study demonstrates that GIMMS NDVI3g represents real responses of vegetation to climate variability that are useful for global models.

Annual precipitation in the Yellowstone National Park region since AD 1173

USGS Publications Warehouse

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

2007-01-01

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

Annual precipitation in the Yellowstone National Park region since AD 1173

USGS Publications Warehouse

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

2007-01-01

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

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.

Impacts of precipitation variability on plant species and community water stress in a temperate deciduous forest in the central US

DOE PAGES

Gu, Lianhong; Pallardy, Stephen G.; Hosman, Kevin P.; ...

2015-12-11

Variations in precipitation regimes can shift ecosystem structure and function by altering frequency, severity and timing of plant water stress. There is a need for predictively understanding impacts of precipitation regimes on plant water stress in relation to species water use strategies. Here we first formulated two complementary, physiologically-linked measures of precipitation variability (PV) - Precipitation Variability Index (PVI) and Average Recurrence Interval of Effective Precipitation (ARIEP). We then used nine-year continuous measurements of Predawn Leaf Water Potential Integral (PLWPI) in a central US forest to relate PVI and ARIEP to actual plant water availability and comparative water stress responsesmore » of six species with different capacities to regulate their internal water status. We found that PVI and ARIEP explained nearly all inter-annual variations in PLWPI for all species as well as for the community scaled from species measurements. The six species investigated showed differential sensitivities to variations in precipitation regimes. Their sensitivities were reflected more in the responses to PVI and ARIEP than to the mean precipitation rate. Further, they exhibited tradeoffs between responses to low and high PV. Finally, PVI and ARIEP were closely correlated with temporal integrals of positive temperature anomalies and vapor pressure deficit. We suggest that the comparative responses of plant species to PV are part of species-specific water use strategies in a plant community facing the uncertainty of fluctuating precipitation regimes. In conclusion, PVI and ARIEP should be adopted as key indices to quantify physiological drought and the ecological impacts of precipitation regimes in a changing climate.« less

Intraseasonal variability in subtropical South America as depicted by precipitation data

NASA Astrophysics Data System (ADS)

González, P. L. M.; Vera, C. S.; Liebmann, B.; Kiladis, G.

2008-06-01

Daily precipitation data from three stations in subtropical Argentina are used to describe intraseasonal variability (20 90 days) during the austral summer. This variability is compared locally and regionally with that present in outgoing longwave radiation (OLR) data, in order to evaluate the performance of this variable as a proxy for convection in the region. The influence of the intraseasonal activity of the South American Seesaw (SASS) leading convection pattern on precipitation is also explored. Results show that intraseasonal variability explains a significant portion of summer precipitation variance, with a clear maximum in the vicinity of the SASS subtropical center. Correlation analysis reveals that OLR can explain only a small portion of daily precipitation variability, implying that it does not constitute a proper proxy for precipitation on daily timescales. On intraseasonal timescales, though, OLR is able to reproduce the main features of precipitation variability. The dynamical conditions that promote the development of intraseasonal variability in the region are further analyzed for selected summers. Seasons associated with a strong intraseasonal signal in precipitation variability show distinctive wet/dry intraseasonal periods in daily raw data, and are associated with a well defined SASS-like spatial pattern of convection. During these summers, strong large-scale forcing (such as warm El Niño/Southern Oscillation (ENSO) events and/or tropical intraseasonal convective activity), and Rossby-wave-like circulation anomalies extending across the Pacific Ocean, are also observed.

GPM Precipitation Estimates over the Walnut Gulch Experimental Watershed/LTAR site in Southeastern Arizona

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Tan, J.; Petersen, W. A.; Unkrich, C. C.; Demaria, E. M.; Hazenberg, P.; Lakshmi, V.

2017-12-01

Precipitation profiles from the GPM Core Observatory Dual-frequency Precipitation Radar (DPR) form part of the a priori database used in GPM Goddard Profiling (GPROF) algorithm passive microwave radiometer retrievals of rainfall. The GPROF retrievals are in turn used as high quality precipitation estimates in gridded products such as IMERG. Due to the variability in and high surface emissivity of land surfaces, GPROF performs precipitation retrievals as a function of surface classes. As such, different surface types may possess different error characteristics, especially over arid regions where high quality ground measurements are often lacking. Importantly, the emissive properties of land also result in GPROF rainfall estimates being driven primarily by the higher frequency radiometer channels (e.g., > 89 GHz) where precipitation signals are most sensitive to coupling between the ice-phase and rainfall production. In this study, we evaluate the rainfall estimates from the Ku channel of the DPR as well as GPROF estimates from various passive microwave sensors. Our evaluation is conducted at the level of individual satellite pixels (5 to 15 km in diameter), against a dense network of weighing rain gauges (90 in 150 km2) in the USDA-ARS Walnut Gulch Experimental Watershed and Long-Term Agroecosystem Research (LTAR) site in southeastern Arizona. The multiple gauges in each satellite pixel and precise accumulation about the overpass time allow a spatially and temporally representative comparison between the satellite estimates and ground reference. Over Walnut Gulch, both the Ku and GPROF estimates are challenged to delineate between rain and no-rain. Probabilities of detection are relatively high, but false alarm ratios are also high. The rain intensities possess a negative bias across nearly all sensors. It is likely that storm types, arid conditions and the highly variable precipitation regime present a challenge to both rainfall retrieval algorithms. An array of ground-based sensors is being deployed during the 2017 monsoon season to better understand possible reasons for this discrepancy.

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

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

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

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

Basin-scale heterogeneity in Antarctic precipitation and its impact on surface mass variability

DOE PAGES

Fyke, Jeremy; Lenaerts, Jan T. M.; Wang, Hailong

2017-11-15

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

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

Kjellstrom, Erik; Rana, Arun; Grigory, Nikulin; Renate, Wilcke; Hansson, Ulf; Kolax, Michael

2016-04-01

Literature has sufficient evidences of climate change impact all over the world and its impact on various sectors. In light of new advancements made in climate modeling, availability of several climate downscaling approaches, the more robust bias correction methods with varying complexities and strengths, in the present study we performed a systematic evaluation of climate change impact over South-Asia region. We have used different Regional Climate Models (RCMs) (from CORDEX domain), (Global Climate Models GCMs) and gridded observations for the study area to evaluate the models in historical/control period (1980-2010) and changes in future period (2010-2099). Firstly, GCMs and RCMs are evaluated against the Gridded observational datasets in the area using precipitation and temperature as indicative variables. Observational dataset are also evaluated against the reliable set of observational dataset, as pointed in literature. Bias, Correlation, and changes (among other statistical measures) are calculated for the entire region and both the variables. Eventually, the region was sub-divided into various smaller domains based on homogenous precipitation zones to evaluate the average changes over time period. Spatial and temporal changes for the region are then finally calculated to evaluate the future changes in the region. Future changes are calculated for 2 Representative Concentration Pathways (RCPs), the middle emission (RCP4.5) and high emission (RCP8.5) and for both climatic variables, precipitation and temperature. Lastly, Evaluation of Extremes is performed based on precipitation and temperature based indices for whole region in future dataset. Results have indicated that the whole study region is under extreme stress in future climate scenarios for both climatic variables i.e. precipitation and temperature. Precipitation variability is dependent on the location in the area leading to droughts and floods in various regions in future. Temperature is hinting towards a constant increase throughout the region regardless of location.

Quality-by-Design (QbD): An integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and process design space development.

PubMed

Wu, Huiquan; White, Maury; Khan, Mansoor A

2011-02-28

The aim of this work was to develop an integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and design space development. A dynamic co-precipitation process by gradually introducing water to the ternary system of naproxen-Eudragit L100-alcohol was monitored at real-time in situ via Lasentec FBRM and PVM. 3D map of count-time-chord length revealed three distinguishable process stages: incubation, transition, and steady-state. The effects of high risk process variables (slurry temperature, stirring rate, and water addition rate) on both derived co-precipitation process rates and final chord-length-distribution were evaluated systematically using a 3(3) full factorial design. Critical process variables were identified via ANOVA for both transition and steady state. General linear models (GLM) were then used for parameter estimation for each critical variable. Clear trends about effects of each critical variable during transition and steady state were found by GLM and were interpreted using fundamental process principles and Nyvlt's transfer model. Neural network models were able to link process variables with response variables at transition and steady state with R(2) of 0.88-0.98. PVM images evidenced nucleation and crystal growth. Contour plots illustrated design space via critical process variables' ranges. It demonstrated the utility of integrated PAT approach for QbD development. Published by Elsevier B.V.

Investigating the Relationship between Ocean Surface Currents and Seasonal Precipitation in the Western United States

NASA Astrophysics Data System (ADS)

Chiang, F.; AghaKouchak, A.

2017-12-01

While many studies have explored the predictive capabilities of teleconnections associated with North American climate, currently established teleconnections offer limited predictability for rainfall in the Western United States. A recent example was the 2015-16 California drought in which a strong ENSO signal did not lead to above average precipitation as was expected. From an exploration of climate and ocean variables available from satellite data, we hypothesize that ocean currents can provide additional information to explain precipitation variability and improve seasonal predictability on the West Coast. Since ocean currents are influenced by surface wind and temperatures, characterizing connections between currents and precipitation patterns has the potential to further our understanding of coastal weather patterns. For the study, we generated gridded point correlation maps to identify ocean areas with high correlation to precipitation time series corresponding to climate regions in the West Coast region. We also used other statistical measures to evaluate ocean `hot spot' regions with significant correlation to West Coast precipitation. Preliminary results show that strong correlations can be found in the tropical regions of the globe.

A data centred method to estimate and map how the local distribution of daily precipitation is changing

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nick

2014-05-01

Estimates of how our climate is changing are needed locally in order to inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on a method to transform daily observations of precipitation into patterns of local climate change. We develop a method[1] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes, to specifically address the challenges presented by daily precipitation data. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the relative amount of precipitation in those days. Our method is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of precipitation distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily precipitation from specific locations across Europe over the last 60 years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the pattern of change at a given threshold of precipitation and with geographical location. This is model- independent, thus providing data of direct value in model calibration and assessment. Our results show regionally consistent patterns of systematic increase in precipitation on the wettest days, and of drying across all days which is of potential value in adaptation planning. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, 2013, S. C. Chapman, N. W. Watkins, Mapping climate change in European temperature distributions, Environ. Res. Lett. 8, 034031 [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119

Weather and climate applications for rangeland restoration planning

USDA-ARS?s Scientific Manuscript database

Rangeland ecosystems generally have an arid or semi-arid climatology, and are characterized by relatively high variability in seasonal and annual patterns of precipitation. Weather variability during seedling establishment is universally acknowledged as a principal determinant of rangeland seeding...

Performance of near real-time Global Satellite Mapping of Precipitation estimates during heavy precipitation events over northern China

NASA Astrophysics Data System (ADS)

Chen, Sheng; Hu, Junjun; Zhang, Asi; Min, Chao; Huang, Chaoying; Liang, Zhenqing

2018-02-01

This study assesses the performance of near real-time Global Satellite Mapping of Precipitation (GSMaP_NRT) estimates over northern China, including Beijing and its adjacent regions, during three heavy precipitation events from 21 July 2012 to 2 August 2012. Two additional near real-time satellite-based products, the Climate Prediction Center morphing method (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), were used for parallel comparison with GSMaP_NRT. Gridded gauge observations were used as reference for a performance evaluation with respect to spatiotemporal variability, probability distribution of precipitation rate and volume, and contingency scores. Overall, GSMaP_NRT generally captures the spatiotemporal variability of precipitation and shows promising potential in near real-time mapping applications. GSMaP_NRT misplaced storm centers in all three storms. GSMaP_NRT demonstrated higher skill scores in the first high-impact storm event on 21 July 2015. GSMaP_NRT passive microwave only precipitation can generally capture the pattern of heavy precipitation distributions over flat areas but failed to capture the intensive rain belt over complicated mountainous terrain. The results of this study can be useful to both algorithm developers and the scientific end users, providing a better understanding of strengths and weaknesses to hydrologists using satellite precipitation products.

Sensitivity of extreme precipitation to temperature: the variability of scaling factors from a regional to local perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2018-06-01

Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.

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.

Tree-Ring-Based Reconstruction of Precipitation in the Bighorn Basin, Wyoming, since 1260 a.d.

NASA Astrophysics Data System (ADS)

Gray, Stephen T.; Fastie, Christopher L.; Jackson, Stephen T.; Betancourt, Julio L.

2004-10-01

Cores and cross sections from 79 Douglas fir () and limber pine (Pinus flexilis) trees at four sites in the Bighorn Basin of north-central Wyoming and south-central Montana were used to develop a proxy for annual (June June) precipitation spanning 1260 1998 A.D. The reconstruction exhibits considerable nonstationarity, and the instrumental era (post-1900) in particular fails to capture the full range of precipitation variability experienced in the past 750 years. Both single-year and decadal-scale dry events were more severe before 1900. Dry spells in the late thirteenth and sixteenth centuries surpass both magnitude and duration of any droughts in the Bighorn Basin after 1900. Precipitation variability appears to shift to a higher-frequency mode after 1750, with 15 20-yr droughts becoming rare. Comparisons between instrumental and reconstructed values of precipitation and indices of Pacific basin variability reveal that precipitation in the Bighorn Basin generally responds to Pacific forcing in a manner similar to that of the southwestern United States (drier during La Niña events), but high country precipitation in areas surrounding the basin displays the opposite response (drier during El Niño events).

Relationships between interdecadal variability and extreme precipitation events in South America during the monsoon season

NASA Astrophysics Data System (ADS)

Grimm, Alice; Laureanti, Nicole; Rodakoviski, Rodrigo

2016-04-01

This study aims to clarify the impact of interdecadal climate oscillations (periods of 8 years and longer) on the frequency of extreme precipitation events over South America in the monsoon season (austral spring and summer), and determine the influence of these oscillations on the daily precipitation frequency distribution. Interdecadal variability modes of precipitation during the monsoon season are provided by a continental-scale rotated empirical orthogonal function analysis for the 60 years period 1950-2009. The main disclosed modes are robust, since they are reproduced for different periods. They can produce differences around 50% in monthly precipitation between opposite phases. Oceanic and atmospheric anomalous fields associated with these modes indicate that they have physical basis. The first modes in spring and summer display highest correlation with the Interdecadal Pacific Oscillation (IPO) SST mode, while the second modes have strongest correlation with the Atlantic Multidecadal Oscillation (AMO) SST mode. However, there are also other influences on these modes. As the most dramatic consequences of climate variability stem from its influence on the frequency of extreme precipitation events, it is important to also assess this influence, since variations in monthly or seasonal precipitation do not necessarily imply significant alterations in their extreme events. This study seeks to answer the questions: i) Do opposite phases of the main interdecadal modes of seasonal precipitation produce significant anomalies in the frequency of extreme events? ii) Does the interdecadal variability of the frequency of extreme events show similar spatial and temporal structure as the interdecadal variability of the seasonal precipitation? iii) Does the interdecadal variability change the daily precipitation probability distribution between opposite phases? iv) In this case, which ranges of daily precipitation are most affected? The significant anomalies of the extreme events frequency in opposite phases of the interdecadal oscillations display spatial patterns very similar to those of the corresponding modes. In addition, the modes of extreme events frequency bear similarity to the modes of seasonal precipitation, although a complete assessment of this similarity is not possible with the daily data available. The Kolmogorov-Smirnov test is applied to the daily precipitation series for positive and negative phases of the interdecadal modes, in regions with high factor loadings. It shows, with significance level better than 0.01, that daily precipitation from opposite phases pertains to different frequency distributions. Further analyses disclose clearly that there is much greater relative impact of the interdecadal oscillations on the extreme ranges of daily rainfall than in the ranges of moderate and light rainfall. This impact is more linear is spring than in summer. Acknowledgments: This work was supported by: Inter-American Institute for Global Change Research (IAI) CRN3035 which is supported by the US National Science Foundation (Grant GEO-1128040), European Community's Seventh Framework Programme under Grant Agreement n° 212492 (CLARIS LPB), and CNPq-Brazil (National Council for Scientific and Technologic Development).

Orographic precipitation at global and regional scales: Observational uncertainty and evaluation of 25-km global model simulations

NASA Astrophysics Data System (ADS)

Schiemann, Reinhard; Roberts, Charles J.; Bush, Stephanie; Demory, Marie-Estelle; Strachan, Jane; Vidale, Pier Luigi; Mizielinski, Matthew S.; Roberts, Malcolm J.

2015-04-01

Precipitation over land exhibits a high degree of variability due to the complex interaction of the precipitation generating atmospheric processes with coastlines, the heterogeneous land surface, and orography. Global general circulation models (GCMs) have traditionally had very limited ability to capture this variability on the mesoscale (here ~50-500 km) due to their low resolution. This has changed with recent investments in resolution and ensembles of multidecadal climate simulations of atmospheric GCMs (AGCMs) with ~25 km grid spacing are becoming increasingly available. Here, we evaluate the mesoscale precipitation distribution in one such set of simulations obtained in the UPSCALE (UK on PrACE - weather-resolving Simulations of Climate for globAL Environmental risk) modelling campaign with the HadGEM-GA3 AGCM. Increased model resolution also poses new challenges to the observational datasets used to evaluate models. Global gridded data products such as those provided by the Global Precipitation Climatology Project (GPCP) are invaluable for assessing large-scale features of the precipitation distribution but may not sufficiently resolve mesoscale structures. In the absence of independent estimates, the intercomparison of different observational datasets may be the only way to get some insight into the uncertainties associated with these observations. Here, we focus on mid-latitude continental regions where observations based on higher-density gauge networks are available in addition to the global data sets: Europe/the Alps, South and East Asia, and the continental US. The ability of GCMs to represent mesoscale variability is of interest in its own right, as climate information on this scale is required by impact studies. An additional motivation for the research proposed here arises from continuing efforts to quantify the components of the global radiation budget and water cycle. Recent estimates based on radiation measurements suggest that the global mean precipitation/evaporation may be up to 10 Wm-2 (about 0.35 mm day-1) larger than the estimate obtained from GPCP. While the main part of this discrepancy is thought to be due to the underestimation of remotely-sensed ocean precipitation, there is also considerable uncertainty about 'unobserved' precipitation over land, in particular in the form of snow in regions of high latitude/altitude. We aim to contribute to this discussion, at least at a qualitative level, by considering case studies of how area-averaged mountain precipitation is represented in different observational datasets and by HadGEM3-GA3 at different resolutions. Our results show that the AGCM simulates considerably more orographic precipitation at higher resolution. We find this at the global scale both for the winter and summer hemispheres, as well as in several case studies in mid-latitude regions. Gridded observations based on gauge measurements generally capture the mesoscale spatial variability of precipitation, but differ strongly from one another in the magnitude of area-averaged precipitation, so that they are of very limited use for evaluating this aspect of the modelled climate. We are currently conducting a sensitivity experiment (coarse-grained orography in high-resolution HadGEM3) to further investigate the resolution sensitivity seen in the model.

Hydrometeorological daily recharge assessment model (DREAM) for the Western Mountain Aquifer, Israel: Model application and effects of temporal patterns

NASA Astrophysics Data System (ADS)

Sheffer, N. A.; Dafny, E.; Gvirtzman, H.; Navon, S.; Frumkin, A.; Morin, E.

2010-05-01

Recharge is a critical issue for water management. Recharge assessment and the factors affecting recharge are of scientific and practical importance. The purpose of this study was to develop a daily recharge assessment model (DREAM) on the basis of a water balance principle with input from conventional and generally available precipitation and evaporation data and demonstrate the application of this model to recharge estimation in the Western Mountain Aquifer (WMA) in Israel. The WMA (area 13,000 km2) is a karst aquifer that supplies 360-400 Mm3 yr-1 of freshwater, which constitutes 20% of Israel's freshwater and is highly vulnerable to climate variability and change. DREAM was linked to a groundwater flow model (FEFLOW) to simulate monthly hydraulic heads and spring flows. The models were calibrated for 1987-2002 and validated for 2003-2007, yielding high agreement between calculated and measured values (R2 = 0.95; relative root-mean-square error = 4.8%; relative bias = 1.04). DREAM allows insights into the effect of intra-annual precipitation distribution factors on recharge. Although annual precipitation amount explains ˜70% of the variability in simulated recharge, analyses with DREAM indicate that the rainy season length is an important factor controlling recharge. Years with similar annual precipitation produce different recharge values as a result of temporal distribution throughout the rainy season. An experiment with a synthetic data set exhibits similar results, explaining ˜90% of the recharge variability. DREAM represents significant improvement over previous recharge estimation techniques in this region by providing near-real-time recharge estimates that can be used to predict the impact of climate variability on groundwater resources at high temporal and spatial resolution.

Assimilating Non-linear Effects of Customized Large-Scale Climate Predictors on Downscaled Precipitation over the Tropical Andes

NASA Astrophysics Data System (ADS)

Molina, J. M.; Zaitchik, B. F.

2016-12-01

Recent findings considering high CO2 emission scenarios (RCP8.5) suggest that the tropical Andes may experience a massive warming and a significant precipitation increase (decrease) during the wet (dry) seasons by the end of the 21st century. Variations on rainfall-streamflow relationships and seasonal crop yields significantly affect human development in this region and make local communities highly vulnerable to climate change and variability. We developed an expert-informed empirical statistical downscaling (ESD) algorithm to explore and construct robust global climate predictors to perform skillful RCP8.5 projections of in-situ March-May (MAM) precipitation required for impact modeling and adaptation studies. We applied our framework to a topographically-complex region of the Colombian Andes where a number of previous studies have reported El Niño-Southern Oscillation (ENSO) as the main driver of climate variability. Supervised machine learning algorithms were trained with customized and bias-corrected predictors from NCEP reanalysis, and a cross-validation approach was implemented to assess both predictive skill and model selection. We found weak and not significant teleconnections between precipitation and lagged seasonal surface temperatures over El Niño3.4 domain, which suggests that ENSO fails to explain MAM rainfall variability in the study region. In contrast, series of Sea Level Pressure (SLP) over American Samoa -likely associated with the South Pacific Convergence Zone (SPCZ)- explains more than 65% of the precipitation variance. The best prediction skill was obtained with Selected Generalized Additive Models (SGAM) given their ability to capture linear/nonlinear relationships present in the data. While SPCZ-related series exhibited a positive linear effect in the rainfall response, SLP predictors in the north Atlantic and central equatorial Pacific showed nonlinear effects. A multimodel (MIROC, CanESM2 and CCSM) ensemble of ESD projections revealed an increased variability and a positive and significant trend in the MAM precipitation mean in the next decades, with accentuated changes and projection uncertainty after 2050. ESD traces (2050-2100) from MIROC presented the highest changes in the precipitation mean ( 60%) when compared with the observations.

Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections

NASA Astrophysics Data System (ADS)

Tan, Xuezhi; Gan, Thian Yew; Chen, Shu; Liu, Bingjun

2018-05-01

Climate change and large-scale climate patterns may result in changes in probability distributions of climate variables that are associated with changes in the mean and variability, and severity of extreme climate events. In this paper, we applied a flexible framework based on the Bayesian spatiotemporal quantile (BSTQR) model to identify climate changes at different quantile levels and their teleconnections to large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Pacific-North American (PNA). Using the BSTQR model with time (year) as a covariate, we estimated changes in Canadian winter precipitation and their uncertainties at different quantile levels. There were some stations in eastern Canada showing distributional changes in winter precipitation such as an increase in low quantiles but a decrease in high quantiles. Because quantile functions in the BSTQR model vary with space and time and assimilate spatiotemporal precipitation data, the BSTQR model produced much spatially smoother and less uncertain quantile changes than the classic regression without considering spatiotemporal correlations. Using the BSTQR model with five teleconnection indices (i.e., SOI, PDO, PNA, NP and NAO) as covariates, we investigated effects of large-scale climate patterns on Canadian winter precipitation at different quantile levels. Winter precipitation responses to these five teleconnections were found to occur differently at different quantile levels. Effects of five teleconnections on Canadian winter precipitation were stronger at low and high than at medium quantile levels.

Characterization of increased persistence and intensity of precipitation in the northeastern United States

NASA Astrophysics Data System (ADS)

Guilbert, Justin; Betts, Alan K.; Rizzo, Donna M.; Beckage, Brian; Bomblies, Arne

2015-03-01

We present evidence of increasing persistence in daily precipitation in the northeastern United States that suggests that global circulation changes are affecting regional precipitation patterns. Meteorological data from 222 stations in 10 northeastern states are analyzed using Markov chain parameter estimates to demonstrate that a significant mode of precipitation variability is the persistence of precipitation events. We find that the largest region-wide trend in wet persistence (i.e., the probability of precipitation in 1 day and given precipitation in the preceding day) occurs in June (+0.9% probability per decade over all stations). We also find that the study region is experiencing an increase in the magnitude of high-intensity precipitation events. The largest increases in the 95th percentile of daily precipitation occurred in April with a trend of +0.7 mm/d/decade. We discuss the implications of the observed precipitation signals for watershed hydrology and flood risk.

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.

Interannual rainfall variability over China in the MetUM GA6 and GC2 configurations

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas P.; Vidale, Pier Luigi; Turner, Andrew G.; Demory, Marie-Estelle; Guo, Liang

2018-05-01

Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyse the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ˜ 200, 90 and 40 km in the zonal direction at the equator, respectively) are analysed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China but improve with finer resolution and coupling. Empirical orthogonal teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal mean time series. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

How Do Microphysical Processes Influence Large-Scale Precipitation Variability and Extremes?

DOE PAGES

Hagos, Samson; Ruby Leung, L.; Zhao, Chun; ...

2018-02-10

Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less

How Do Microphysical Processes Influence Large-Scale Precipitation Variability and Extremes?

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

Hagos, Samson; Ruby Leung, L.; Zhao, Chun

Convection permitting simulations using the Model for Prediction Across Scales-Atmosphere (MPAS-A) are used to examine how microphysical processes affect large-scale precipitation variability and extremes. An episode of the Madden-Julian Oscillation is simulated using MPAS-A with a refined region at 4-km grid spacing over the Indian Ocean. It is shown that cloud microphysical processes regulate the precipitable water (PW) statistics. Because of the non-linear relationship between precipitation and PW, PW exceeding a certain critical value (PWcr) contributes disproportionately to precipitation variability. However, the frequency of PW exceeding PWcr decreases rapidly with PW, so changes in microphysical processes that shift the columnmore » PW statistics relative to PWcr even slightly have large impacts on precipitation variability. Furthermore, precipitation variance and extreme precipitation frequency are approximately linearly related to the difference between the mean and critical PW values. Thus observed precipitation statistics could be used to directly constrain model microphysical parameters as this study demonstrates using radar observations from DYNAMO field campaign.« less

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

NASA Astrophysics Data System (ADS)

Faulk, S.; Moon, S.; Mitchell, J.; Lora, J. M.

2016-12-01

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

High marsh foraminiferal assemblages' response to intra-decadal and multi-decadal precipitation variability, between 1934 and 2010 (Minho, NW Portugal)

NASA Astrophysics Data System (ADS)

Fatela, Francisco; Moreno, João; Leorri, Eduardo; Corbett, Reide

2014-10-01

Foraminiferal assemblages of Caminha tidal marshes have been studied since 2002 revealing a peculiar dominance of brackish species, such as Haplophragmoides manilaensis, Haplophragmoides wilberti, Haplophragmoides sp., Pseudothurammina limnetis and Trochamminita salsa/irregularis in the high marshes of the Minho and the Coura lower estuaries. The assemblage composition reflects low salinity conditions, despite the short distance to the estuarine mouth (~ 4 km). However, in May 2010, the presence of salt marsh species Trochammina inflata and Jadammina macrescens became very significant, likely a result of 5 consecutive dry years and a corresponding salinity rise in sediment pore water. Correspondence analysis (CA) groups the surface samples according to their marsh zone, showing a positive correlation with the submersion time of each sampling point. The brackish and normal salinity foraminiferal species appear separated in the CA. This observation was applied to the top 10 cm of a high marsh sediment core that corresponds to the period of instrumental record of precipitation and river flow in the Minho region. We found that river flow strongly correlates with precipitation in the Lima and Minho basins. The longer precipitation record was, therefore, used to interpret the foraminiferal assemblages' variability. Three main phases were distinguished along ca. 80 years of precipitation data: 1) negative anomalies from 1934 to 1957; 2) positive anomalies from 1958 to 1983; and 3) negative anomalies from 1984 to 2010. This last dryer period exhibits the precipitation maximum and the greatest amplitude of rainfall values. High marsh foraminifera reveals a fast response to these short-term shifts; low salinity species relative abundance increases when precipitation increases over several decades, as well as in the same decade, in the years of heavy rainfall of dryer periods. High marsh foraminifera records the increase of freshwater flooding and seepage by 1) decreasing abundance and 2) increasing the dominance of low salinity species. On the other hand, low precipitation over ca. 5 years increases the assemblage productivity and the relative abundance of normal salinity species. The positive correlation found between winter precipitation and the NAO winter index indicates that the Minho region is a part of the North Atlantic climate dynamics and demonstrates that the foraminiferal record from Caminha high marsh may be applied in high-resolution studies of SW Europe climate evolution.

Analysis and trends of precipitation lapse rate and extreme indices over north Sikkim eastern Himalayas under CMIP5ESM-2M RCPs experiments

NASA Astrophysics Data System (ADS)

Singh, Vishal; Goyal, Manish Kumar

2016-01-01

This paper draws attention to highlight the spatial and temporal variability in precipitation lapse rate (PLR) and precipitation extreme indices (PEIs) through the mesoscale characterization of Teesta river catchment, which corresponds to north Sikkim eastern Himalayas. A PLR rate is an important variable for the snowmelt runoff models. In a mountainous region, the PLR could be varied from lower elevation parts to high elevation parts. In this study, a PLR was computed by accounting elevation differences, which varies from around 1500 m to 7000 m. A precipitation variability and extremity were analysed using multiple mathematical functions viz. quantile regression, spatial mean, spatial standard deviation, Mann-Kendall test and Sen's estimation. For this reason, a daily precipitation, in the historical (years 1980-2005) as measured/observed gridded points and projected experiments for the 21st century (years 2006-2100) simulated by CMIP5 ESM-2 M model (Coupled Model Intercomparison Project Phase 5 Earth System Model 2) employing three different radiative forcing scenarios (Representative Concentration Pathways), utilized for the research work. The outcomes of this study suggest that a PLR is significantly varied from lower elevation to high elevation parts. The PEI based analysis showed that the extreme high intensity events have been increased significantly, especially after 2040s. The PEI based observations also showed that the numbers of wet days are increased for all the RCPs. The quantile regression plots showed significant increments in the upper and lower quantiles of the various extreme indices. The Mann-Kendall test and Sen's estimation tests clearly indicated significant changing patterns in the frequency and intensity of the precipitation indices across all the sub-basins and RCP scenario in an intra-decadal time series domain. The RCP8.5 showed extremity of the projected outcomes.

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.

ARM Cloud Aerosol Precipitation Experiment (ACAPEX) Science Plan

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

Leung, L. R.; Prather, K.; Ralph, R.

The western U.S. receives precipitation predominantly during the cold season when storms approach from the Pacific Ocean. The snowpack that accumulates during winter storms provides about 70-90% of water supply for the region. Understanding and modeling the fundamental processes that govern the large precipitation variability and extremes in the western U.S. is a critical test for the ability of climate models to predict the regional water cycle, including floods and droughts. Two elements of significant importance in predicting precipitation variability in the western U.S. are atmospheric rivers and aerosols. Atmospheric rivers (ARs) are narrow bands of enhanced water vapor associatedmore » with the warm sector of extratropical cyclones over the Pacific and Atlantic oceans. Because of the large lower-tropospheric water vapor content, strong atmospheric winds and neutral moist static stability, some ARs can produce heavy precipitation by orographic enhancement during landfall on the U.S. West Coast. While ARs are responsible for a large fraction of heavy precipitation in that region during winter, much of the rest of the orographic precipitation occurs in post-frontal clouds, which are typically quite shallow, with tops just high enough to pass the mountain barrier. Such clouds are inherently quite susceptible to aerosol effects on both warm rain and ice precipitation-forming processes.« less

Hydroclimatic variability in the Lake Mondsee region and its relationships with large-scale climate anomaly patterns

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Swierczynski, Tina; Brauer, Achim; Kämpf, Lucas; Czymzik, Markus

2017-04-01

Flood triggered detrital layers in varved sediments of Lake Mondsee, located at the northern fringe of the European Alps (47°48'N,13°23'E), provide an important archive of regional hydroclimatic variability during the mid- to late Holocene. To improve the interpretation of the flood layer record in terms of large-scale climate variability, we investigate the relationships between observational hydrological records from the region, like the Mondsee lake level, the runoff of the lake's main inflow Griesler Ache, with observed precipitation and global climate patterns. The lake level shows a strong positive linear trend during the observational period in all seasons. Additionally, lake level presents important interannual to multidecadal variations. These variations are associated with distinct seasonal atmospheric circulation patterns. A pronounced anomalous anticyclonic center over the Iberian Peninsula is associated with high lake levels values during winter. This center moves southwestward during spring, summer and autumn. In the same time, a cyclonic anomaly center is recorded over central and western Europe. This anomalous circulation extends southwestward from winter to autumn. Similar atmospheric circulation patterns are associated with river runoff and precipitation variability from the region. High lake levels are associated with positive local precipitation anomalies in all seasons as well as with negative local temperature anomalies during spring, summer and autumn. A correlation analysis reveals that lake level, runoff and precipitation variability is related to large-scale sea surface temperature anomaly patterns in all seasons suggesting a possible impact of large-scale climatic modes, like the North Atlantic Oscillation and Atlantic Multidecadal Oscillation on hydroclimatic variability in the Lake Mondsee region. The results presented in this study can be used for a more robust interpretation of the long flood layer record from Lake Mondsee sediments in terms of regional and large-scale climate variability during the past.

The Primacy of Multidecadal to Centennial Variability Over Late Holocene Forced Change of the Asian Monsoon on the Southern Tibetan Plateau

NASA Astrophysics Data System (ADS)

Conroy, J. L.; Hudson, A. M.; Overpeck, J. T.; Liu, K. B.; Luo, W.; Cole, J. E.

2016-12-01

The nature of multidecadal to centennial variability of the Asian monsoon remains largely unknown. Here we use the sediment record from a closed-basin lake in southern Tibet, Ngamring Tso, to assess summer monsoon precipitation from 4100 cal yr BP to present. The first principal component of the Ngamring Tso grain size record correlates significantly with observed June-September precipitation. From CE 1940-2007, grain size decreased with increasing summer precipitation and increased with decreasing summer precipitation. Satellite images of Ngamring Tso suggest precipitation-induced changes in lake depth or area likely govern grain size variability. Prolonged periods of weak summer monsoon precipitation occurred from 2800-2600 cal yr BP, 2500-2300 cal yr BP, and 1600-400 cal yr BP. A trend toward increased summer precipitation began around 1000 cal yr BP, with above-average summer precipitation from 400 cal yr BP to present, peaking between 200-100 cal yr BP. Dry and wet periods are coincident with dry and wet periods in other south-central Tibetan lake sediment records and with regional proxies of the ISM and EASM, indicating south-central Tibet is influenced by both monsoon subsystems. 20th century precipitation variability in southern Tibet falls within the range of natural variability in the last 4100 years, and does not show a clear trend of increasing precipitation as projected by models. Instead, it appears that poorly understood internal modes of monsoon variability remained influential throughout the last 4100 years. Substantial multidecadal to centennial-scale variability will thus complicate our ability to project future anthropogenic changes in the region's monsoon precipitation.

Interdecadal Connection Between Artic Temperature and Summer Precipitation Over the Yangtze River Valley in the CMIP5 Historical Simulations

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

Li, Yuefeng; Leung, Lai-Yung R.; Xiao, Ziniu

2013-10-01

This study assesses the ability of the Phase 5 Coupled Model Intercomparison Project (CMIP5) simulations in capturing the interdecadal precipitation enhancement over the Yangtze River valley (YRV) and investigates the contributions of Arctic warming to the interdecadal variability of the East Asian summer monsoon rainfall. Six CMIP5 historical simulations including models from Canada (CCCma), China (BCC), Germany (MPI-M), Japan (MRI), United Kingdom (MOHC), and United States (NCAR) are used. The NCEP/NCAR reanalysis and observed precipitation are also used for comparison. Among the six CMIP5 simulations, only CCCma can approximately simulate the enhancement of interdecadal summer precipitation over the YRV inmore » 1990-2005 relative to 1960-1975, and the relationships between the summer precipitation with surface temperature (Ts), the 850hPa winds, and 500hPa height field (H500), and between Ts and H500 using regression, correlation, and SVD analyses. It is found that CCCma can reasonably simulate the interdecadal surface warming over the boreal mid-to high latitudes and the Arctic in winter, spring and summer. The summer Baikal blocking appears to be the bridge that links the winter and spring surface warming over the mid-to high latitude and Arctic with the enhancement of summer precipitation over the YRV. Models that missed some or all of these relationships found in CCCma and the reanalysis failed to simulate the interdecadal enhancement of precipitation over the YRV. This points to the importance of high latitude and Arctic processes on interdecadal variability of the East Asian summer monsoon and the challenge for global climate models to correctly simulate the linkages.« less

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

Precipitation and shortwave radiation play important roles in climatic, hydrological and biogeochemical cycles. Several global and regional forcing data sets currently provide historical estimates of these two variables over China, including the Global Land Data Assimilation System (GLDAS), the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the China Meteorological Forcing Dataset (CMFD). The CN05.1 precipitation data set, a gridded analysis based on CMA gauge observations, also provides high-resolution historical precipitation data for China. In this study, we present an intercomparison of precipitation and shortwave radiation data from CN05.1, CMFD, CLDAS and GLDAS during 2008-2014. We also validate all four data sets against independent ground station observations. All four forcing data sets capture the spatial distribution of precipitation over major land areas of China, although CLDAS indicates smaller annual-mean precipitation amounts than CN05.1, CMFD or GLDAS. Time series of precipitation anomalies are largely consistent among the data sets, except for a sudden decrease in CMFD after August 2014. All forcing data indicate greater temporal variations relative to the mean in dry regions than in wet regions. Validation against independent precipitation observations provided by the Ministry of Water Resources (MWR) in the middle and lower reaches of the Yangtze River indicates that CLDAS provides the most realistic estimates of spatiotemporal variability in precipitation in this region. CMFD also performs well with respect to annual mean precipitation, while GLDAS fails to accurately capture much of the spatiotemporal variability and CN05.1 contains significant high biases relative to the MWR observations. Estimates of shortwave radiation from CMFD are largely consistent with station observations, while CLDAS and GLDAS greatly overestimate shortwave radiation. All three forcing data sets capture the key features of the spatial distribution, but estimates from CLDAS and GLDAS are systematically higher than those from CMFD over most of mainland China. Based on our evaluation metrics, CLDAS slightly outperforms GLDAS. CLDAS is also closer than GLDAS to CMFD with respect to temporal variations in shortwave radiation anomalies, with substantial differences among the time series. Differences in temporal variations are especially pronounced south of 34° N. Our findings provide valuable guidance for a variety of stakeholders, including land-surface modelers and data providers.

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.

Interannual variability of the atmospheric CO2 growth rate: roles of precipitation and temperature

NASA Astrophysics Data System (ADS)

Wang, Jun; Zeng, Ning; Wang, Meirong

2016-04-01

The interannual variability (IAV) in atmospheric CO2 growth rate (CGR) is closely connected with the El Niño-Southern Oscillation. However, sensitivities of CGR to temperature and precipitation remain largely uncertain. This paper analyzed the relationship between Mauna Loa CGR and tropical land climatic elements. We find that Mauna Loa CGR lags precipitation by 4 months with a correlation coefficient of -0.63, leads temperature by 1 month (0.77), and correlates with soil moisture (-0.65) with zero lag. Additionally, precipitation and temperature are highly correlated (-0.66), with precipitation leading by 4-5 months. Regression analysis shows that sensitivities of Mauna Loa CGR to temperature and precipitation are 2.92 ± 0.20 PgC yr-1 K-1 and -0.46 ± 0.07 PgC yr-1 100 mm-1, respectively. Unlike some recent suggestions, these empirical relationships favor neither temperature nor precipitation as the dominant factor of CGR IAV. We further analyzed seven terrestrial carbon cycle models, from the TRENDY project, to study the processes underlying CGR IAV. All models capture well the IAV of tropical land-atmosphere carbon flux (CFTA). Sensitivities of the ensemble mean CFTA to temperature and precipitation are 3.18 ± 0.11 PgC yr-1 K-1 and -0.67 ± 0.04 PgC yr-1 100 mm-1, close to Mauna Loa CGR. Importantly, the models consistently show the variability in net primary productivity (NPP) dominates CGR, rather than heterotrophic respiration. Because previous studies have proved that NPP is largely driven by precipitation in tropics, it suggests a key role of precipitation in CGR IAV despite the higher CGR correlation with temperature. Understanding the relative contribution of CO2 sensitivity to precipitation and temperature has important implications for future carbon-climate feedback using such ''emergent constraint''.

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.

Timing of floods in southeastern China: Seasonal properties and potential causes

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Gu, Xihui; Singh, Vijay P.; Shi, Peijun; Luo, Ming

2017-09-01

Flood hazards and flood risks in southeastern China have been causing increasing concerns due to dense population and highly-developed economy. This study attempted to address changes of seasonality, timing of peak floods and variability of occurrence date of peak floods using circular statistical methods and the modified Mann-Kendall trend detection method. The causes of peak flood changes were also investigated. Results indicated that: (1) floods were subject to more seasonality and temporal clustering when compared to precipitation extremes. However, seasonality of floods and extreme precipitation was subject to spatial heterogeneity in northern Guangdong. Similar changing patterns of peak floods and extreme precipitation were found in coastal regions; (2) significant increasing/decreasing seasonality, but no confirmed spatial patterns, were observed for peak floods and extreme precipitation. Peak floods in northern Guangdong province had decreasing variability, but had larger variability in coastal regions; (3) tropical cyclones had remarkable impacts on extreme precipitation changes in coastal regions of southeastern China, and peak floods as well. The landfalling of tropical cyclones was decreasing and concentrated during June-September; this is the major reason for earlier but enhanced seasonality of peak floods in coastal regions. This study sheds new light on flood behavior in coastal regions in a changing environment.

Climatic and ecological controls on variability of fire activity in the tropics and subtropics derived from satellite data

NASA Astrophysics Data System (ADS)

van der Werf, G. R.; Randerson, J. T.; Giglio, L.; Gobron, N.; Dolman, H. J.

2006-12-01

El Nino-Southern Oscillation-linked variations in biomass burning emissions substantially contribute to interannual variability in the growth rate of many trace gases, yet ecological and climatic controls on fire activity are not well known. We used satellite-derived datasets of biomass burning, precipitation rates, and net primary production (NPP) in the tropics and subtropics during 1998 through 2005 to investigate the factors that regulate interannual variability in fire emissions. In many xeric regions that have low levels of NPP, we found a positive relationship between precipitation, NPP, and fire activity, implying that fire in these regions is limited to years when precipitation allows for the build-up of sufficient biomass or fuel loads to allow fire spread. This was most evident in regions where mean annual precipitation was below approximately 600 mm / year, including xeric regions of Africa and Northern Australia. In contrast, in areas of the tropics undergoing active deforestation, including, Indonesia, Central America, and parts of South America we found a significant negative correlation between precipitation and fire activity during the dry season. This implies that human use of fire in these regions in the deforestation process is at least partly limited by periods when high moisture levels limit ignition and fire activity.

Flexible stocking strategies for adapting to climatic variability

USDA-ARS?s Scientific Manuscript database

As a result of precipitation-induced variability on forage production, ranchers have difficulty matching animal demand with forage availability in their operations. Flexible stocking strategies could more effectively use extra forage in highly productive years and limit risk of overgrazing during dr...

Climate change impacts on northwestern and intermountain United States rangelands

Treesearch

Jeanne C. Chambers; Mike Pellant

2008-01-01

Our focus is on the Pacific Northwest and Intermountain Region including the Great Basin, Columbia Plateau, Colorado Plateau, and surrounding areas. The climate of this large, arid to semiarid region is defined by generally low and highly variable precipitation. Much of the yearly precipitation arrives as winter snow because most of the moisture comes as frontal storms...

Geographic overview: Climate, phenology, and disturbance regimes in steppe and desert communities

Treesearch

B. J. Weddell

1996-01-01

In midwestern steppes, precipitation peaks in summer, whereas west of the Rocky Mountains, steppes are characterized by summer drought. In western deserts, the amount of precipitation is highly variable. These different climatic regimes result in differences in prevalence of and resilience to disturbances such as herbivory, and differences in susceptibility to invasion...

Extreme precipitation event over North China in August 2010: observations, monthly forecasting, and link to intra-seasonal variability of the Silk-Road wave-train across Eurasia

NASA Astrophysics Data System (ADS)

Orsolini, Yvan; Zhang, Ling; Peters, Dieter; Fraedrich, Klaus

2014-05-01

Forecast of regional precipitation events at the sub-seasonal timescale remains a big challenge for operational global prediction systems. Over the Far East in summer, climate and precipitation are strongly influenced by the fluctuating western Pacific subtropical high (WPSH) and strong precipitation is often associated with southeasterly low-level wind that brings moist-laden air from the southern China seas. The WPSH variability is partly influenced by quasi-stationary wave-trains propagating eastwards from Europe across Asia along the two westerly jets: the Silk-Road wave-train along the Asian jet at mid-latitudes and, on a more northern route, the polar wave-train along the sub-polar jet. While the Silk-Road wave-train appears as a robust, internal mode of variability in seasonal predictions models, its predictability is very low on the sub-seasonal to seasonal time scale. A case in point is the unusual summer of 2010, when China experienced its worst seasonal flooding for a decade, triggered by unusually prolonged and severe monsoonal rains. In addition that summer was also characterized by record-breaking heat wave over Eastern Europe and Russia as well as catastrophic monsoonal floods in Pakistan 2010. The impact of the latter circulation anomalies on the precipitation further east over China, has been little explored. Here, we examine the role and the actual predictability of the Silk-Road wave-train, and its impact on precipitation over Northeastern China throughout August 2010, using the high-resolution IFS forecast model of ECMWF, realistic initialized and run in an ensemble mode. We demonstrate that the forecast failure with regard to flooding and extreme precipitation over Northeastern China in August 2010 is linked to the failure to represent intra-seasonal variations of the Silk-Road wave-train and the associated intensification of the WPSH.

Assessing Precipitation Isotope Variations during Atmospheric River Events to Reveal Dominant Atmospheric/Hydrologic Processes

NASA Astrophysics Data System (ADS)

McCabe-Glynn, S. E.; Johnson, K. R.; Yoshimura, K.; Buenning, N. H.; Welker, J. M.

2015-12-01

Extreme precipitation events across the Western US commonly associated with atmospheric rivers (ARs), whereby extensive fluxes of moisture are transported from the subtropics, can result in major damage and are projected by most climate models to increase in frequency and severity. However, they are difficult to project beyond ~ten days and the location of landfall and topographically induced precipitation is even more uncertain. Water isotopes, often used to reconstruct past rainfall variability, are useful natural tracers of atmospheric hydrologic processes. Because of the typical tropical and sub-tropical origins, ARs can carry unique water isotope (δ18O and δ2H, d-excess) signatures that can be utilized to provide source and process information that can lead to improving AR predictions. Recent analysis of the top 10 weekly precipitation total samples from Sequoia National Park, CA, of which 9 contained AR events, shows a high variability in the isotopic values. NOAA Hysplit back trajectory analyses reveals a variety of trajectories and varying latitudinal source regions contributed to moisture delivered to this site, which may explain part of the high variability (δ2H = -150.03 to -49.52 ‰, δ18O = -19.27 to -7.20 ‰, d-excess = 4.1 to 25.8). Here we examine the top precipitation totals occurring during AR events and the associated isotopic composition of precipitation samples from several sites across the Western US. We utilize IsoGSM, an isotope-enabled atmospheric general circulation model, to characterize the hydrologic processes and physical dynamics contributing to the observed isotopic variations. We investigate isotopic influences from moisture source location, AR speed, condensation height, and associated temperature. We explore the dominant controls on spatial and temporal variations of the isotopic composition of AR precipitation which highlights different physical processes for different AR events.

Oilfield scales: controls on precipitation and crystal morphology of barite (barium sulphate)

NASA Astrophysics Data System (ADS)

Stark, A. I. R.; Wogelius, R. A.; Vaughan, D. J.

2003-04-01

The precipitation and subsequent build up of barite (barium sulphate) inside extraction tubing presents a costly problem for off shore oil wells which use seawater to mobilize oil during hydrocarbon recovery. Mixing of reservoir formation water containing Ba2+ ions and seawater containing SO_42- ions results in barite precipitation within the reservoir well-bore region and piping. Great effort has been expended in designing strategies to minimize scale formation but details of the reaction mechanism and sensitivity to thermodynamic variables are poorly constrained. Furthermore, few detailed studies have been carried out under simulated field conditions. Hence an experimental programme was designed to study barite formation under environmentally relevant conditions with control of several system variables during the precipitation reaction. Synthetic sea-water and formation-water brines containing sodium sulphate and barium chloride, respectively, were mixed to induce BaSO_4 precipitation. Experiments were carried out at high temperature (100^oC) and high pressure (500 bars) in double rocking autoclave bombs. Barite formation as a function of the addition of calcium, magnesium, and a generic phosphonate based scale inhibitor was investigated whilst maintaining constant pH, temperature and ionic strength (0.5159). Additional experiments were performed at ambient conditions for comparison. Data concerning nucleation, growth rates, and crystal morphology were obtained. ICP-AES data from the supernatant product solutions showed considerable variation in quantity of barium sulphate precipitated as a function of the listed experimental variables. For example, ESEM analysis of barium sulphate crystals showed a dramatic shift in crystal habit from the typical tabular habit produced in control experiments; experiments performed in the presence of foreign cations produced more equant crystals, while those experiments completed in the presence of the phosphonate scale inhibitor produced precipitates with distorted anhedral shapes. Based on these preliminary results, further experiments which monitor rate and morphology as a function of Ba/Ca ratio, ionic strength, and ion activity product for barite will also be completed.

A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part I: Interannual variability

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas Pappas; Vidale, Pier Luigi; Turner, Andrew George; Demory, Marie-Estelle; Guo, Liang

2018-06-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. To improve its understanding and prediction, many studies have associated precipitation variability with particular causes for specific seasons and regions. Here, a consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to 1951-2007 high-resolution precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. The EOT method is validated by the reproduction of known relationships to the El Niño Southern Oscillation (ENSO): high positive correlations with ENSO are found in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that wintertime rainfall variability along the southeast coast is associated with anomalous convection over the tropical eastern Atlantic and communicated to China through a zonal wavenumber-three Rossby wave. Furthermore, spring rainfall variability in the Yangtze valley is related to upper-tropospheric midlatitude perturbations that are part of a Rossby wave pattern with its origin in the North Atlantic. A circumglobal wave pattern in the northern hemisphere is also associated with autumn precipitation variability in eastern areas. The analysis is objective, comprehensive, and produces timeseries that are tied to specific locations in China. This facilitates the interpretation of associated dynamical processes, is useful for understanding the regional hydrological cycle, and allows the results to serve as a benchmark for assessing general circulation models.

Precipitation-productivity Relation in Grassland in Northern China: Investigations at Multiple Spatiotemporal Scales

NASA Astrophysics Data System (ADS)

Hu, Z.

2017-12-01

Climate change is predicted to cause dramatic variability in precipitation regime, not only in terms of change in annual precipitation amount, but also in precipitation seasonal distribution and precipitation event characteristics (high frenquency extrem precipitation, larger but fewer precipitation events), which combined to influence productivity of grassland in arid and semiarid regions. In this study, combining remote sensing products with in-situ measurements of aboveground net primary productivity (ANPP) and gross primary productivity (GPP) data from eddy covariance system in grassland of northern China, we quantified the effects of spatio-temporal vairation in precipitation on productivity from local sites to region scale. We found that, for an individual precipitation event, the duration of GPP-response to the individual precipitation event and the maximum absolute GPP response induced by the individual precipitation event increased linearly with the size of precipitation events. Comparison of the productivity-precipitation relationships between multi-sites determined that the predominant characteristics of precipitation events (PEC) that affected GPP differed remarkably between the water-limited temperate steppe and the temperature-limited alpine meadow. The number of heavy precipitation events (>10 mm d-1) was the most important PEC to impact GPP in the temperate steppe through affecting soil moisture at different soil profiles, while precipitation interval was the factor that affected GPP most in the alpine meadow via its effects on temperature. At the region scale, shape of ANPP-precipitation relationship varies with distinct spatial scales, and besides annual precipitation, precipitation seasonal distribution also has comparable impacts on spatial variation in ANPP. Temporal variability in ANPP was lower at both the dry and wet end, and peaked at a precipitation of 243.1±3.5mm, which is the transition region between typical steppe and desert steppe. Our work has important implications to obtain an advanced understanding of productivity-response of grassland ecosystems to altered precipitation regimes.

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers.

PubMed

Varela, Sara; Lima-Ribeiro, Matheus S; Terribile, Levi Carina

2015-01-01

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12-BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/.

A Short Guide to the Climatic Variables of the Last Glacial Maximum for Biogeographers

PubMed Central

Varela, Sara; Lima-Ribeiro, Matheus S.; Terribile, Levi Carina

2015-01-01

Ecological niche models are widely used for mapping the distribution of species during the last glacial maximum (LGM). Although the selection of the variables and General Circulation Models (GCMs) used for constructing those maps determine the model predictions, we still lack a discussion about which variables and which GCM should be included in the analysis and why. Here, we analyzed the climatic predictions for the LGM of 9 different GCMs in order to help biogeographers to select their GCMs and climatic layers for mapping the species ranges in the LGM. We 1) map the discrepancies between the climatic predictions of the nine GCMs available for the LGM, 2) analyze the similarities and differences between the GCMs and group them to help researchers choose the appropriate GCMs for calibrating and projecting their ecological niche models (ENM) during the LGM, and 3) quantify the agreement of the predictions for each bioclimatic variable to help researchers avoid the environmental variables with a poor consensus between models. Our results indicate that, in absolute values, GCMs have a strong disagreement in their temperature predictions for temperate areas, while the uncertainties for the precipitation variables are in the tropics. In spite of the discrepancies between model predictions, temperature variables (BIO1-BIO11) are highly correlated between models. Precipitation variables (BIO12- BIO19) show no correlation between models, and specifically, BIO14 (precipitation of the driest month) and BIO15 (Precipitation Seasonality (Coefficient of Variation)) show the highest level of discrepancy between GCMs. Following our results, we strongly recommend the use of different GCMs for constructing or projecting ENMs, particularly when predicting the distribution of species that inhabit the tropics and the temperate areas of the Northern and Southern Hemispheres, because climatic predictions for those areas vary greatly among GCMs. We also recommend the exclusion of BIO14 and BIO15 from ENMs because those variables show a high level of discrepancy between GCMs. Thus, by excluding them, we decrease the level of uncertainty of our predictions. All the climatic layers produced for this paper are freely available in http://ecoclimate.org/. PMID:26068930

Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim

NASA Astrophysics Data System (ADS)

Quintana-Seguí, Pere; Turco, Marco; Herrera, Sixto; Miguez-Macho, Gonzalo

2017-04-01

Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980-2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

Precipitation, density, and population dynamics of desert bighorn sheep on San Andres National Wildlife Refuge, New Mexico

USGS Publications Warehouse

Bender, L.C.; Weisenberger, M.E.

2005-01-01

Understanding the determinants of population size and performance for desert bighorn sheep (Ovis canadensis mexicana) is critical to develop effective recovery and management strategies. In arid environments, plant communities and consequently herbivore populations are strongly dependent upon precipitation, which is highly variable seasonally and annually. We conducted a retrospective exploratory analysis of desert bighorn sheep population dynamics on San Andres National Wildlife Refuge (SANWR), New Mexico, 1941-1976, by modeling sheep population size as a function of previous population sizes and precipitation. Population size and trend of desert bighorn were best and well described (R 2=0.89) by a model that included only total annual precipitation as a covariate. Models incorporating density-dependence, delayed density-dependence, and combinations of density and precipitation were less informative than the model containing precipitation alone (??AlCc=8.5-22.5). Lamb:female ratios were positively related to precipitation (current year: F1,34=7.09, P=0.012; previous year: F1,33=3.37, P=0.075) but were unrelated to population size (current year. F1,34=0.04, P=0.843; previous year: F1,33 =0.14, P=0.715). Instantaneous population rate of increase (r) was related to population size (F1,33=5.55; P=0.025). Precipitation limited populations of desert bighorn sheep on SANWR primarily in a density-independent manner by affecting production or survival of lambs, likely through influences on forage quantity and quality. Habitat evaluations and recovery plans for desert bighorn sheep need to consider fundamental influences on desert bighorn populations such as precipitation and food, rather than focus solely on proximate issues such as security cover, predation, and disease. Moreover, the concept of carrying capacity for desert bighorn sheep may need re-evaluation in respect to highly variable (CV =35.6%) localized precipitation patterns. On SANWR carrying capacity for desert bighorn sheep was zero when total annual precipitation was <28.2 cm.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

Winter (DJF) precipitation over Northwest India (NWI) is very important for the cultivation of Rabi crops. Thus, an accurate estimation of high-resolution observations, evaluation of high-resolution numerical models, and understanding the local variability trends are essential. The objective of this study is to verify the quality of a new high spatial resolution (0.25° × 0.25°) gridded daily precipitation data set of India Meteorological Department (IMD1) over NWI during winter. An intercomparison with four existing precipitation data sets at 0.5° × 0.5° of IMD (IMD2), 1° × 1° of IMD (IMD3), 0.25° × 0.25° of APHRODITE (APRD1), and 0.5° × 0.5° of APHRODITE (APRD1) resolution during a common period of 1971-2003 is done. The evaluation of data quality of these five data sets against available 26 station observations is carried out, and the results clearly indicate that all the five data sets reasonably agreed with the station observation. However, the errors are relatively more in all the five data sets over Jammu and Kashmir-related four stations (Srinagar, Drass, Banihal top, and Dawar), while these errors are less in the other stations. It may be due to the lack of station observations over the region. The quality of IMD1 data set over NWI for winter precipitation is reasonably well than the other data sets. The intercomparison analysis suggests that the climatological mean, interannual variability, and coefficient of variation from IMD1 are similar with other data sets. Further, the analysis extended to the India meteorological subdivisions over the region. This analysis indicates overestimation in IMD3 and underestimation in APRD1 and APRD2 over Jammu and Kashmir, Himachal Pradesh, and NWI as a whole, whereas IMD2 is closer to IMD1. Moreover, all the five data sets are highly correlated (>0.5) among them at 99.9% confidence level for all subdivisions. It is remarkably noticed that multicategorical (light precipitation, moderate precipitation, heavy precipitation, and very heavy precipitation) skill score of accuracy (>0.8) for the four data sets against IMD1 is good for all the subdivisions as well as NWI and is more in IMD2. IMD1 performs well in capturing the relationships of winter precipitation with climate indices such as Nino 3.4 region sea surface temperature, Southern Oscillation Index, Arctic Oscillation, and North Atlantic Oscillation. The results conclude that IMD1 is useful to understand the variability trends at the local climate scale and its global teleconnections.

Zonal wind indices to reconstruct United States winter precipitation during El Niño

NASA Astrophysics Data System (ADS)

Farnham, D. J.; Steinschneider, S.; Lall, U.

2017-12-01

The highly discussed 2015/16 El Niño event, which many likened to the similarly strong 1997/98 El Niño event, led to precipitation impacts over the continental United States (CONUS) inconsistent with general expectations given past events and model-based forecasts. This presents a challenge for regional water managers and others who use seasonal precipitation forecasts who previously viewed El Niño events as times of enhanced confidence in seasonal water availability and flood risk forecasts. It is therefore useful to understand the extent to which wintertime CONUS precipitation during El Niño events can be explained by seasonal sea surface temperature heating patterns and the extent to which the precipitation is a product of natural variability. In this work, we define two seasonal indices based on the zonal wind field spanning from the eastern Pacific to the western Atlantic over CONUS that can explain El Niño precipitation variation spatially throughout CONUS over 11 historic El Niño events from 1950 to 2016. The indices reconstruct El Niño event wintertime (Jan-Mar) gridded precipitation over CONUS through cross-validated regression much better than the traditional ENSO sea surface temperature indices or other known modes of variability. Lastly, we show strong relationships between sea surface temperature patterns and the phases of the zonal wind indices, which in turn suggests that some of the disparate CONUS precipitation during El Niño events can be explained by different heating patterns. The primary contribution of this work is the identification of intermediate variables (in the form of zonal wind indices) that can facilitate further studies into the distinct hydroclimatic response to specific El Niño events.

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

The forcing of monthly precipitation variability over Southwest Asia during the Boreal cold season

USGS Publications Warehouse

Hoell, Andrew; Shukla, Shraddhanand; Barlow, Mathew; Cannon, Forest; Kelley, Colin; Funk, Christopher C.

2015-01-01

Southwest Asia, deemed as the region containing the countries of Afghanistan, Iran, Iraq and Pakistan, is water scarce and receives nearly 75% of its annual rainfall during8 the boreal cold season of November-April. The forcing of Southwest Asia precipitation has been previously examined for the entire boreal cold season from the perspective of climate variability originating over the Atlantic and tropical Indo-Pacific Oceans. Here, we examine the inter-monthly differences in precipitation variability over Southwest Asia and the atmospheric conditions directly responsible in forcing monthly November-April precipitation. Seasonally averaged November-April precipitation over Southwest Asia is significantly correlated with sea surface temperature (SST) patterns consistent with Pacific Decadal Variability (PDV), the El Nino-Southern Oscillation (ENSO) and the warming trend of SST (Trend). On the contrary, the precipitation variability during individual months of November-April are unrelated and are correlated with SST signatures that include PDV, ENSO and Trend in different combinations. Despite strong inter-monthly differences in precipitation variability during November- April over Southwest Asia, similar atmospheric circulations, highlighted by a stationary equivalent barotropic Rossby wave centered over Iraq, force the monthly spatial distributions of precipitation. Tropospheric waves on the eastern side of the equivalent barotropic Rossby wave modifies the flux of moisture and advects the mean temperature gradient, resulting in temperature advection that is balanced by vertical motions over Southwest Asia. The forcing of monthly Southwest Asia precipitation by equivalent barotropic Rossby waves is different than the forcing by baroclinic Rossby waves associated with tropically-forced-only modes of climate variability.

Detection of the relationship between peak temperature and extreme precipitation

NASA Astrophysics Data System (ADS)

Yu, Y.; Liu, J.; Zhiyong, Y.

2017-12-01

Under the background of climate change and human activities, the characteristics and pattern of precipitation have changed significantly in many regions. As the political and cultural center of China, the structure and character of precipitation in Jingjinji District has varied dramatically in recent years. In this paper, the daily precipitation data throughout the period 1960-2013 are selected for analyzing the spatial-temporal variability of precipitation. The results indicate that the frequency and intensity of precipitation presents an increasing trend. Based on the precipitation data, the maximum, minimum and mean precipitation in different temporal and spatial scales is calculated respectively. The temporal and spatial variation of temperature is obtained by using statistical methods. The relationship between temperature and precipitation in different range is analyzed. The curve relates daily precipitation extremes with local temperatures has a peak structure, increasing at the low-medium range of temperature variations but decreasing at high temperatures. The relationship between extreme precipitation is stronger in downtown than that in suburbs.

Holocene hydrologic variation at Lake Titicaca, Bolivia/Peru, and its relationship to North Atlantic climate variation

NASA Astrophysics Data System (ADS)

Baker, P. A.; Fritz, S. C.; Garland, J.; Ekdahl, E.

2005-10-01

A growing number of sites in the Northern Hemisphere show centennial- to millennial-scale climate variation that has been correlated with change in solar variability or with change in North Atlantic circulation. However, it is unclear how (or whether) these oscillations in the climate system are manifest in the Southern Hemisphere because of a lack of sites with suitably high sampling resolution. In this paper, we reconstruct the lake-level history of Lake Titicaca, using the carbon isotopic content of sedimentary organic matter, to evaluate centennial- to millennial-scale precipitation variation and its phasing relative to sites in the Northern Hemisphere. The pattern and timing of lake-level change in Lake Titicaca is similar to the ice-rafted debris record of Holocene Bond events, demonstrating a possible coupling between precipitation variation on the Altiplano and North Atlantic sea-surface temperatures (SSTs). The cold periods of the Holocene Bond events correspond with periods of increased precipitation on the Altiplano. Holocene precipitation variability on the Altiplano is anti-phased with respect to precipitation in the Northern Hemisphere monsoon region. More generally, the tropical Andes underwent large changes in precipitation on centennial-to-millennial timescales during the Holocene.

Impact of Variable SST on Simulated Warm Season Precipitation

NASA Astrophysics Data System (ADS)

Saleeby, S. M.; Cotton, W. R.

2007-05-01

The Colorado State University - Regional Atmospheric Modeling System (CSU-RAMS) is being used to examine the variability in monsoon-related warm season precipitation over Mexico and the United States due to variability in SST. Given recent improvements and increased resolution in satellite derived SSTs it is pertinent to examine the sensitivity of the RAMS model to the variety of SST data sources that are available. In particular, we are examining this dependence across continental scales over the full warm season, as well as across the regional scale centered around the Gulf of California on time scales of individual surge events. In this study we performed an ensemble of simulations that include the 2002, 2003, and 2004 warm seasons with use of the Climatology, Reynold's, AVHRR, and MODIS SSTs. From the seasonal 90-day simulations with 30km grid spacing, it was found that variations in surface latent heat flux are directly linked to differences in SST. Regions with cooler (warmer) SST have decreased (increased) moisture flux from the ocean which is in proportion to the magnitude of the SST difference. Over the eastern Pacific, differences in low-level horizontal moisture flux show a general trend toward reduced fluxes over cooler waters and very little inland impact. Over the Gulf of Mexico, however, there is substantial variability for each dataset comparison, despite having only limited variability among the SST data. Causes of this unexpected variability are not straight-forward. Precipitation impacts are greatest near the southern coast of Mexico and along the Sierra Madres. Precipitation variability over the CONUS is rather chaotic and is limited to areas impacted by the Gulf of Mexico or monsoon convection. Another unexpected outcome is the lack of variability in areas near the northern Gulf of California where SST and latent heat flux variability is a maximum. From the 7-day surge period simulations at 7km grid spacing, we found that SST differences on the higher resolution nested grid reveal fine scale variability that is otherwise smoothed out or unapparent on the coarser grid. Unlike the coarse grid, the latent heat flux, temperature, and moisture transport differences on the fine grid reveal an inland impact. This is likely due to fine scale variability in onshore moisture transport and sea- breeze circulations which may alter monsoonal convection and precipitation. However, only the largest SST differences (spatially and in magnitude) tend to invoke large, coherent responses in moisture flux. The SST variability at high resolution produces relatively large differences in precipitation that are focused along the slopes of the SMO, with a tendency toward greater variability along the western slope adjacent to the coast. The precipitation differences are of fine resolution, with variability of +/- 30 mm (over 5 days) along the length of the SMO. Variability on the fine grid also invokes precipitation changes over AZ/NM that are not resolved on the coarse grid. Vertical cross-sections examined along the GoC during the surge episode revealed variations in the moisture and temperature structure of the surge. The cooler SSTs in the climatological dataset produced the greatest variability compared to the other datasets. The surge produced from climatology SSTs was nearly 5g/kg drier and up to 4°C cooler compared to surges influenced by the SST datasets. The overall northward propagation of the surge appeared unaffected by the SSTs.

The role of internal variability in prolonging the California drought

NASA Astrophysics Data System (ADS)

Buenning, N. H.; Stott, L. D.

2015-12-01

The current drought in California has been one of the driest on record. Using atmospheric general circulation models (AGCMs), recent studies have demonstrated that the low precipitation anomalies observed during the first three winters of the current drought are mostly attributable to changes in sea surface temperature (SST) and sea ice forcing. Here we show through AGCM simulations that the fourth and latest winter of the current drought is not attributable to SST and sea ice forcing, but instead a consequence of higher internal variability. Using the Global Spectral Model (GSM) we demonstrate how the surface forcing reproduces dry conditions over California for the first three winters of the current drought, similar to what other models produced. However, when forced with the SST and sea ice conditions for the winter of 2014-2015, GSM robustly simulates high precipitation conditions over California. This significantly differs with observed precipitation anomalies, which suggests a model deficiency or large influence of internal variability within the climate system during the winter of 2014-2015. Ensemble simulations with 234 realizations reveal that the surface forcing created a broader range of precipitation possibilities over California. Thus, the surface forcing caused a greater degree of internal variations, which was driven by a reduced latitudinal temperature gradient and amplified planetary waves over the Pacific. Similar amplified waves are also seen in 21st century climate projections of upper-level geopotential heights, suggesting that 21st century precipitation over California will become more variable and increasingly difficult to predict on seasonal timescales. When an El Nino pattern is applied to the surface forcing the precipitation further increases and the variance amongst model realizations is reduced, which indicates a strong likelihood of an anomalously wet 2015-2016 winter season.

The Schaake shuffle: A method for reconstructing space-time variability in forecasted precipitation and temperature fields

USGS Publications Warehouse

Clark, M.R.; Gangopadhyay, S.; Hay, L.; Rajagopalan, B.; Wilby, R.

2004-01-01

A number of statistical methods that are used to provide local-scale ensemble forecasts of precipitation and temperature do not contain realistic spatial covariability between neighboring stations or realistic temporal persistence for subsequent forecast lead times. To demonstrate this point, output from a global-scale numerical weather prediction model is used in a stepwise multiple linear regression approach to downscale precipitation and temperature to individual stations located in and around four study basins in the United States. Output from the forecast model is downscaled for lead times up to 14 days. Residuals in the regression equation are modeled stochastically to provide 100 ensemble forecasts. The precipitation and temperature ensembles from this approach have a poor representation of the spatial variability and temporal persistence. The spatial correlations for downscaled output are considerably lower than observed spatial correlations at short forecast lead times (e.g., less than 5 days) when there is high accuracy in the forecasts. At longer forecast lead times, the downscaled spatial correlations are close to zero. Similarly, the observed temporal persistence is only partly present at short forecast lead times. A method is presented for reordering the ensemble output in order to recover the space-time variability in precipitation and temperature fields. In this approach, the ensemble members for a given forecast day are ranked and matched with the rank of precipitation and temperature data from days randomly selected from similar dates in the historical record. The ensembles are then reordered to correspond to the original order of the selection of historical data. Using this approach, the observed intersite correlations, intervariable correlations, and the observed temporal persistence are almost entirely recovered. This reordering methodology also has applications for recovering the space-time variability in modeled streamflow. ?? 2004 American Meteorological Society.

Trends and variability of daily precipitation extremes during 1960-2012 in the Yangtze River Basin, China

USDA-ARS?s Scientific Manuscript database

Trends and variability of extreme precipitation events are important for water-related disaster prevention and mitigation as well as water resource management. Based on daily precipitation dataset from 143 meteorological stations in the Yangtze River Basin (YRB), a suite of precipitation indices rec...

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

The tropical rainforests of the Guianas, north of the Amazon, are home to several Amerindian communities, hold high levels of biodiversity and, importantly, remain some of the world's most pristine and intact rainforests. Not only do they have important functions in the global carbon cycle, but they regulate the local and regional climate and help generate rain over vast distances. Despite their significance however, the climate and hydrology of this region is poorly understood. It is important to establish the current climate regime of the area as a baseline against which any impacts of future climate change or deforestation can be measured but observed historical climate datasets are generally sparse and of low quality. Here we examine the available precipitation and temperature datasets for the region and derive tentative precipitation and temperature maps focussed on Guyana. To overcome the limitations in the inadequate observational data coverage we also make use of a reanalysis dataset from the European Centre for Medium-range Weather Forecasts (ECMWF). The ECMWF ERA40 dataset comprises a spatially consistent global historical climate for the period 1957-2002 at a ~125 km2 (1.125 degree) resolution at the equator and is particularly valuable for establishing the climate of data-poor areas. Once validated for the area of interest, ERA40 is used to determine the precipitation and temperature regime of the Guianas. Grid-cell by grid-cell analysis provides a complete picture of spatial patterns of averaged monthly precipitation variability across the area, vital for establishing a basis from which to compare any future effects of climate change. This is the first comprehensive study of the recent historical climate and its variability in this area, placing a new hydroclimate monitoring and research program at the Iwokrama International Centre for Rainforest Conservation and Development, Guyana, into the broader climate context. Mean differences (biases) and annual average spatial correlations are examined between modelled ERA40 and observed time series comparing the seasonal cycles and the yearly, monthly and monthly anomaly time series. This is to evaluate if the reanalysis data correctly reproduces the areally averaged observed mean annual precipitation, interannual variability and seasonal precipitation cycle over the region. Results show that reanalysis precipitation for the region compares favourably with areally averaged observations where available, although the model underestimates precipitation in some zones of higher elevation. Also ERA40 data is slightly positively biased along the coast and negatively biased inland. Comparisons between observed and modelled data show that although correlations of annual time series are low (<0.6), correlations of monthly time series reach 0.8 demonstrating that the model captures much of the seasonal variation in precipitation. However correlations between monthly precipitation anomalies, where the averaged seasonal cycle has been removed from the comparison, are lower (< 0.6). As precipitation observations are not assimilated into the reanalysis these results provide a good validation of model performance. The seasonal cycle of precipitation is found to be highly variable across the region. Two wet-seasons (June and December) occur in northern Guyana which relate to the twice yearly passage of the inter-tropical convergence zone whereas a single wet season (April-August) occurs in the savannah zone, which stretches from Venezuela through the southern third of Guyana. The climate transition zone lies slightly north of the distinctive forest-savannah boundary which suggests that the boundary may be highly sensitive to future alterations in climate, such as those due to climate change or deforestation.

Comparative Evaluation of Performances of Two Versions of NCEP Climate Forecast System in Predicting Winter Precipitation over India

NASA Astrophysics Data System (ADS)

Nageswararao, M. M.; Mohanty, U. C.; Nair, Archana; Ramakrishna, S. S. V. S.

2016-06-01

The precipitation during winter (December through February) over India is highly variable in terms of time and space. Maximum precipitation occurs over the Himalaya region, which is important for water resources and agriculture sectors over the region and also for the economy of the country. Therefore, in the present global warming era, the realistic prediction of winter precipitation over India is important for planning and implementing agriculture and water management strategies. The National Centers for Environmental Prediction (NCEP) issued the operational prediction of climatic variables in monthly to seasonal scale since 2004 using their first version of fully coupled global climate model known as Climate Forecast System (CFSv1). In 2011, a new version of CFS (CFSv2) was introduced with the incorporation of significant changes in older version of CFS (CFSv1). The new version of CFS is required to compare in detail with the older version in the context of simulating the winter precipitation over India. Therefore, the current study presents a detailed analysis on the performance of CFSv2 as compared to CFSv1 for the winter precipitation over India. The hindcast runs of both CFS versions from 1982 to 2008 with November initial conditions are used and the model's precipitation is evaluated with that of India Meteorological Department (IMD). The models simulated wind and geopotential height against the National Center for Atmospheric Research (NCEP-NCAR) reanalysis-2 (NNRP2) and remote response patterns of SST against Extended Reconstructed Sea Surface Temperatures version 3b (ERSSTv3b) are examined for the same period. The analyses of winter precipitation revealed that both the models are able to replicate the patterns of observed climatology; interannual variability and coefficient of variation. However, the magnitude is lesser than IMD observation that can be attributed to the model's inability to simulate the observed remote response of sea surface temperatures to all India winter precipitation. Of the two, CFSv1 is appreciable in capturing year-to-year variations in observed winter precipitation while CFSv2 failed in simulating the same. CFSv1 has accounted for less mean bias and RMSE errors along with good correlations and index of agreements than CFSv2 for predicting winter precipitation over India. In addition, the CFSv1 is also having a high probability of detection in predicting different categories (normal, excess and deficit) of observed winter precipitation over India.

Influence of Climate Oscillations on Extreme Precipitation in Texas

NASA Astrophysics Data System (ADS)

Bhatia, N.; Singh, V. P.; Srivastav, R. K.

2016-12-01

Much research in the field of hydroclimatology is focusing on the impact of climate variability on hydrologic extremes. Recent studies show that the unique geographical location and the enormous areal extent, coupled with extensive variations in climate oscillations, have intensified the regional hydrologic cycle of Texas. The state-wide extreme precipitation events can actually be attributed to sea-surface pressure and temperature anomalies, such as Bermuda High and Jet Streams, which are further triggered by such climate oscillations. This study aims to quantify the impact of five major Atlantic and Pacific Ocean related climate oscillations: (i) Atlantic Multidecadal Oscillation (AMO), (ii) North Atlantic Oscillation (NAO), (iii) Pacific Decadal Oscillation (PDO), (iv) Pacific North American Pattern (PNA), and (v) Southern Oscillation Index (SOI), on extreme precipitation in Texas. Their respective effects will be determined for both climate divisions delineated by the National Climatic Data Centre (NCDC) and climate regions defined by the Köppen Climate Classification System. This study will adopt a weighted correlation approach to attain the robust correlation coefficients while addressing the regionally variable data outliers for extreme precipitation. Further, the variation of robust correlation coefficients across Texas is found to be related to the station elevation, historical average temperature, and total precipitation in the months of extremes. The research will shed light on the relationship between precipitation extremes and climate variability, thus aiding regional water boards in planning, designing, and managing the respective systems as per the future climate change.

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.

Climatology of extreme daily precipitation in Colorado and its diverse spatial and seasonal variability

USGS Publications Warehouse

Mahoney, Kelly M.; Ralph, F. Martin; Walter, Klaus; Doesken, Nolan; Dettinger, Michael; Gottas, Daniel; Coleman, Timothy; White, Allen

2015-01-01

The climatology of Colorado’s historical extreme precipitation events shows a remarkable degree of seasonal and regional variability. Analysis of the largest historical daily precipitation totals at COOP stations across Colorado by season indicates that the largest recorded daily precipitation totals have ranged from less than 60 mm day−1 in some areas to more than 250 mm day−1 in others. East of the Continental Divide, winter events are rarely among the top 10 events at a given site, but spring events dominate in and near the foothills; summer events are most common across the lower-elevation eastern plains, while fall events are most typical for the lower elevations west of the Divide. The seasonal signal in Colorado’s central mountains is complex; high-elevation intense precipitation events have occurred in all months of the year, including summer, when precipitation is more likely to be liquid (as opposed to snow), which poses more of an instantaneous flood risk. Notably, the historic Colorado Front Range daily rainfall totals that contributed to the damaging floods in September 2013 occurred outside of that region’s typical season for most extreme precipitation (spring–summer). That event and many others highlight the fact that extreme precipitation in Colorado has occurred historically during all seasons and at all elevations, emphasizing a year-round statewide risk.

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

Bae, Soo Ya; Jeong, Jaein I.; Park, R.

We examine the effect of anthropogenic aerosols on the weekly variability of precipitation in Korea in summer 2004 by using Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models. We con-duct two WRF simulations including a baseline simulation with empirically based cloud condensation nuclei (CCN) number concentrations and a sensitivity simulation with our implementation to account for the effect of aerosols on CCN number concentrations. The first simulation underestimates observed precipitation amounts, particularly in northeastern coastal areas of Korea, whereas the latter shows higher precipitation amounts that are in better agree-ment with the observations. In addition, themore » sensitivity model with the aerosol effects reproduces the observed weekly variability, particularly for precipitation frequency with a high R at 0.85, showing 20% increase of precipita-tion events during the weekend than those during weekdays. We find that the aerosol effect results in higher CCN number concentrations during the weekdays and a three-fold increase of the cloud water mixing ratio through en-hanced condensation. As a result, the amount of warm rain is generally suppressed because of the low auto-conversion process from cloud water to rain water under high aerosol conditions. The inefficient conversion, how-ever, leads to higher vertical development of clouds in the mid-atmosphere with stronger updrafts in the sensitivity model, which increases by 21% cold-phase hydrometeors including ice, snow, and graupel relative to the baseline model and ultimately results in higher precipitation amounts in summer.« less

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 high intensity precipitation from 16 Regional climate models over a meso-scale catchment in the Midlands Regions of England

NASA Astrophysics Data System (ADS)

Wetterhall, F.; He, Y.; Cloke, H.; Pappenberger, F.; Freer, J.; Wilson, M.; McGregor, G.

2009-04-01

Local flooding events are often triggered by high-intensity rain-fall events, and it is important that these can be correctly modelled by Regional Climate Models (RCMs) if the results are to be used in climate impact assessment. In this study, daily precipitation from 16 RCMs was compared with observations over a meso-scale catchment in the Midlands Region of England. The RCM data was provided from the European research project ENSEMBLES and the precipitation data from the UK MetOffice. The RCMs were all driven by reanalysis data from the ERA40 dataset over the time period 1961-2000. The ENSEMBLES data is on the spatial scale of 25 x 25 km and it was disaggregated onto a 5 x 5 km grid over the catchment and compared with interpolated observational data with the same resolution. The mean precipitation was generally underestimated by the ENSEMBLES data, and the maximum and persistence of high intensity rainfall was even more underestimated. The inter-annual variability was not fully captured by the RCMs, and there was a systematic underestimation of precipitation during the autumn months. The spatial pattern in the modelled precipitation data was too smooth in comparison with the observed data, especially in the high altitudes in the western part of the catchment where the high precipitation usually occurs. The RCM outputs cannot reproduce the current high intensity precipitation events that are needed to sufficiently model extreme flood events. The results point out the discrepancy between climate model output and the high intensity precipitation input needs for hydrological impact modelling.

Global characteristics of stream flow seasonality and variability

USGS Publications Warehouse

Dettinger, M.D.; Diaz, Henry F.

2000-01-01

Monthly stream flow series from 1345 sites around the world are used to characterize geographic differences in the seasonality and year-to-year variability of stream flow. Stream flow seasonality varies regionally, depending on the timing of maximum precipitation, evapotranspiration, and contributions from snow and ice. Lags between peaks of precipitation and stream flow vary smoothly from long delays in high-latitude and mountainous regions to short delays in the warmest sectors. Stream flow is most variable from year to year in dry regions of the southwest United States and Mexico, the Sahel, and southern continents, and it varies more (relatively) than precipitation in the same regions. Tropical rivers have the steadiest flows. El Nin??o variations are correlated with stream flow in many parts of the Americas, Europe, and Australia. Many stream flow series from North America, Europe, and the Tropics reflect North Pacific climate, whereas series from the eastern United States, Europe, and tropical South America and Africa reflect North Atlantic climate variations.

High resolution reconstruction of monthly precipitation of Iberian Peninsula using circulation weather types

NASA Astrophysics Data System (ADS)

Cortesi, N.; Trigo, R.; Gonzalez-Hidalgo, J. C.; Ramos, A. M.

2012-06-01

Precipitation over the Iberian Peninsula (IP) is highly variable and shows large spatial contrasts between wet mountainous regions, to the north, and dry regions in the inland plains and southern areas. In this work, a high-density monthly precipitation dataset for the IP was coupled with a set of 26 atmospheric circulation weather types (Trigo and DaCamara, 2000) to reconstruct Iberian monthly precipitation from October to May with a very high resolution of 3030 precipitation series (overall mean density one station each 200 km2). A stepwise linear regression model with forward selection was used to develop monthly reconstructed precipitation series calibrated and validated over 1948-2003 period. Validation was conducted by means of a leave-one-out cross-validation over the calibration period. The results show a good model performance for selected months, with a mean coefficient of variation (CV) around 0.6 for validation period, being particularly robust over the western and central sectors of IP, while the predicted values in the Mediterranean and northern coastal areas are less acute. We show for three long stations (Lisbon, Madrid and Valencia) the comparison between model and original data as an example to how these models can be used in order to obtain monthly precipitation fields since the 1850s over most of IP for this very high density network.

Regional simulation of interannual variability over South America

NASA Astrophysics Data System (ADS)

Misra, V.; Dirmeyer, P. A.; Kirtman, B. P.; Juang, H.-M. Henry; Kanamitsu, M.

2002-08-01

Three regional climate simulations covering the austral summer season during three contrasting phases of the El Niño-Southern Oscillation cycle were conducted with the Regional Spectral Model (RSM) developed at the National Centers for Environmental Prediction (NCEP). The simulated interannual variability of precipitation over the Amazon River Basin, the Intertropical Convergence Zone, the Pacific and Atlantic Ocean basins, and extratropical South America compare reasonably well with observations. The RSM optimally filters the peturbations about a time-varying base field, thereby enhancing the information content of the global NCEP reanalysis. The model is better than the reanalysis in reproducing the observed interannual variability of outgoing longwave radiation at both high frequencies (3-30 days) and intraseasonal (30-60 days) scales. The low-level jet shows a peak in its speed in 1998 and a minimum in the 1999 simulations. The lag correlation of the jet index with convection over various areas in continental South America indicates that the jet induces precipitation over the Pampas region downstream. A detailed moisture budget was conducted over various subregions. This budget reveals that moisture flux convergence determines most of the interannual variability of precipitation over the Amazon Basin, the Atlantic Intertropical Convergence Zone, and the Nordeste region of Brazil. However, both surface evaporation and surface moisture flux convergence were found to be critical in determining the interannual variability of precipitation over the southern Pampas, Gran Chaco area, and the South Atlantic Convergence Zone.

Region-Specific Sensitivity of Anemophilous Pollen Deposition to Temperature and Precipitation

PubMed Central

Donders, Timme H.; Hagemans, Kimberley; Dekker, Stefan C.; de Weger, Letty A.; de Klerk, Pim; Wagner-Cremer, Friederike

2014-01-01

Understanding relations between climate and pollen production is important for several societal and ecological challenges, importantly pollen forecasting for pollinosis treatment, forensic studies, global change biology, and high-resolution palaeoecological studies of past vegetation and climate fluctuations. For these purposes, we investigate the role of climate variables on annual-scale variations in pollen influx, test the regional consistency of observed patterns, and evaluate the potential to reconstruct high-frequency signals from sediment archives. A 43-year pollen-trap record from the Netherlands is used to investigate relations between annual pollen influx, climate variables (monthly and seasonal temperature and precipitation values), and the North Atlantic Oscillation climate index. Spearman rank correlation analysis shows that specifically in Alnus, Betula, Corylus, Fraxinus, Quercus and Plantago both temperature in the year prior to (T-1), as well as in the growing season (T), are highly significant factors (TApril rs between 0.30 [P<0.05[ and 0.58 [P<0.0001]; TJuli-1 rs between 0.32 [P<0.05[ and 0.56 [P<0.0001]) in the annual pollen influx of wind-pollinated plants. Total annual pollen prediction models based on multiple climate variables yield R2 between 0.38 and 0.62 (P<0.0001). The effect of precipitation is minimal. A second trapping station in the SE Netherlands, shows consistent trends and annual variability, suggesting the climate factors are regionally relevant. Summer temperature is thought to influence the formation of reproductive structures, while temperature during the flowering season influences pollen release. This study provides a first predictive model for seasonal pollen forecasting, and also aides forensic studies. Furthermore, variations in pollen accumulation rates from a sub-fossil peat deposit are comparable with the pollen trap data. This suggests that high frequency variability pollen records from natural archives reflect annual past climate variability, and can be used in palaeoecological and -climatological studies to bridge between population- and species-scale responses to climate forcing. PMID:25133631

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.

Scaling Linguistic Characterization of Precipitation Variability

NASA Astrophysics Data System (ADS)

Primo, C.; Gutierrez, J. M.

2003-04-01

Rainfall variability is influenced by changes in the aggregation of daily rainfall. This problem is of great importance for hydrological, agricultural and ecological applications. Rainfall averages, or accumulations, are widely used as standard climatic parameters. However different aggregation schemes may lead to the same average or accumulated values. In this paper we present a fractal method to characterize different aggregation schemes. The method provides scaling exponents characterizing weekly or monthly rainfall patterns for a given station. To this aim, we establish an analogy with linguistic analysis, considering precipitation as a discrete variable (e.g., rain, no rain). Each weekly, or monthly, symbolic precipitation sequence of observed precipitation is then considered as a "word" (in this case, a binary word) which defines a specific weekly rainfall pattern. Thus, each site defines a "language" characterized by the words observed in that site during a period representative of the climatology. Then, the more variable the observed weekly precipitation sequences, the more complex the obtained language. To characterize these languages, we first applied the Zipf's method obtaining scaling histograms of rank ordered frequencies. However, to obtain significant exponents, the scaling must be maintained some orders of magnitude, requiring long sequences of daily precipitation which are not available at particular stations. Thus this analysis is not suitable for applications involving particular stations (such as regionalization). Then, we introduce an alternative fractal method applicable to data from local stations. The so-called Chaos-Game method uses Iterated Function Systems (IFS) for graphically representing rainfall languages, in a way that complex languages define complex graphical patterns. The box-counting dimension and the entropy of the resulting patterns are used as linguistic parameters to quantitatively characterize the complexity of the patterns. We illustrate the high climatological discrimination power of the linguistic parameters in the Iberian peninsula, when compared with other standard techniques (such as seasonal mean accumulated precipitation). As an example, standard and linguistic parameters are used as inputs for a clustering regionalization method, comparing the resulting clusters.

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.

Analysis of a Small Vigorous Mesoscale Convective System in a Low-Shear Environment. Pt. 1; Formation, Echo Structure and Lightning Behavior

NASA Technical Reports Server (NTRS)

Knupp, Kevin; Geerts, Bart; Goodman, Steven J.

1997-01-01

The precipitation output was highly variable due to the transient nature of the intense convective elements. This result is attributed to the high Richardson number (175) of the environment, which is much higher than that of the typical MCS environment. The development of the stratiform precipitation was accomplished locally (in situ), and not be advection of from the convective region. In situ charging of the stratiform region is also supported by the observations.

Precipitation variability within the West Pacific Warm Pool over the past 120 ka: Evidence from the Davao Gulf, southern Philippines

NASA Astrophysics Data System (ADS)

Fraser, Nicholas; Kuhnt, Wolfgang; Holbourn, Ann; Bolliet, Timothé; Andersen, Nils; Blanz, Thomas; Beaufort, Luc

2014-11-01

Proxy records of hydrologic variability in the West Pacific Warm Pool (WPWP) have revealed wide-scale changes in past convective activity in response to orbital and suborbital climate forcings. However, attributing proxy responses to regional changes in WPWP hydrology versus local variations in precipitation requires independent records linking the terrestrial and marine realms. We present high-resolution stable isotope, UK'37 sea surface temperature, X-ray fluorescence (XRF) core scanning, and coccolithophore-derived paleoproductivity records covering the past 120 ka from International Marine Global Change (IMAGES) Program Core MD06-3075 (6°29'N, 125°50'E, water depth 1878 m), situated in the Davao Gulf on the southern side of Mindanao. XRF-derived log(Fe/Ca) records provide a robust proxy for runoff-driven sedimentary discharge from Mindanao, while past changes in local productivity are associated with variable freshwater runoff and stratification of the surface layer. Significant precessional-scale variability in sedimentary discharge occurred during marine isotope stage (MIS) 5, with peaks in discharge contemporaneous with Northern Hemisphere summer insolation minima. We attribute these changes to the latitudinal migration of the Intertropical Convergence Zone (ITCZ) over the WPWP together with variability in the strength of the Walker circulation acting on precessional timescales. Between 60 and 15 ka sedimentary discharge at Mindanao was muted, displaying little orbital- or millennial-scale variability, likely in response to weakened precessional insolation forcing and lower sea level driving increased subsidence of air masses over the exposed Sunda Shelf. These results highlight the high degree of local variability in the precipitation response to past climate changes in the WPWP.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Assessing changes in extreme convective precipitation from a damage perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Tye, M. R.

2016-12-01

Projected increases in high-intensity short-duration convective precipitation are expected even in regions that are likely to become more arid. Such high intensity precipitation events can trigger hazardous flash floods, debris flows and landslides that put people and local assets at risk. However, the assessment of local scale precipitation extremes is hampered by its high spatial and temporal variability. In addition to which, not only are extreme events rare, but such small scale events are likely to be underreported where they don't coincide with the observation network. Rather than focus solely on the convective precipitation, understanding the characteristics of these extremes which drive damage may be more effective to assess future risks. Two sources of data are used in this study. First, sub-daily precipitation observations over the Southern Alps enable an examination of seasonal and regional patterns in high-intensity convective precipitation and their relationship with weather types. Secondly, reports of private loss and damage on a household scale are used to identify which events are most damaging, or what conditions potentially enhance the vulnerability to these extremes.This study explores the potential added value from including recorded loss and damage data to understand the risks from summertime convective precipitation events. By relating precipitation generating weather types to the severity of damage we hope to develop a mechanism to assess future risks. A further benefit would be to identify from damage reports the likely occurrence of precipitation extremes where no direct observations are available and use this information to validate remotely sensed observations.

Empirical meaning of DTM multifractal parameters in the precipitation context

NASA Astrophysics Data System (ADS)

Portilla Farfan, Freddy; Valencia, Jose Luis; Villeta, Maria; Tarquis, Ana M.; Saa-Requejo, Antonio

2015-04-01

The main objective of this research is to interpret the multifractal parameters in the case of precipitation series from an empirical approach. In order to do so nineteen precipitation series were generated with a daily precipitation simulator derived from year and month estimations and considering the classical statistics, used commonly in hydrology studies, from actual data of four Spanish rain gauges located in a gradient from NW to SE. For all generated series the multifractal parameters were estimated following the technique DTM (Double Trace Moments) developed by Lavalle et al. (1993) and the variations produced considered. The results show the following conclusions: 1. The intermittency, C1, increases when precipitation is concentrating for fewer days, making it more variable, or when increasing its concentration on maximum monthly precipitation days, while it is not affected due to the modification in the variability in the number of days rained. 2. Multifractility, α, increases with the number of rainy days and the variability of the precipitation, yearly as well as monthly, as well as with the concentration of precipitation on the maximum monthly precipitation day. 3. The maximum probable singularity, γs, increases with the concentration of rain on the day of the maximum monthly precipitation and the variability in yearly and monthly level. 4. The non-conservative degree, H, depends on the number of rainy days that appear on the series and secondly on the general variability of the rain. References Lavallée D., S. Lovejoy, D. Schertzer and P. Ladoy, 1993. Nonlinear variability and landscape topography: analysis and simulation. In: Fractals in Geography (N. Lam and L. De Cola, Eds.) Prentice Hall, Englewood Cliffs, 158-192.

Atmospheric River Importance to Extratropical Climate and Hydrology

NASA Astrophysics Data System (ADS)

Nash, D.; Waliser, D. E.; Guan, B.; Ye, H.; Ralph, F. M.

2017-12-01

Atmospheric Rivers (ARs) are narrow, long, water vapor rich corridors of the atmosphere that are responsible for over 90% of the poleward moisture transport across mid-latitudes and into high latitudes. This suggests a crucial role for ARs in helping establish the extra-tropical atmospheric water budget and hydroclimate variability. However, the contribution of ARs to the extra-tropical atmospheric water budget has yet to be quantified, including impacts on water vapor transport and storage, and precipitation. This study characterizes the roles of AR related atmospheric transport on combined and individual atmospheric water budget variables over extratropical regions of both hemispheres based on MERRA2 reanalysis products during 1997-2014. Results show that poleward water vapor transport related to ARs is strongly related to changes in water vapor storage and especially precipitation in higher latitudes in both hemispheres, with the relationship dependent on averaging period. For example, for the annual cycle climatology, both AR transport and local evaporation support the variation in precipitation. However, on monthly time scales, the water budget at higher latitudes tends to be dominated by the balance between AR transport and precipitation. On pentad and daily time scales, AR transport is related to both precipitation and water vapor storage changes. These results indicate the important role of the episodic, extreme moisture transports associated with ARs in helping establish the high latitude water and energy cycles, and associated hydroclimate.

Environmental variation and macrofauna response in a coastal area influenced by land runoff

NASA Astrophysics Data System (ADS)

Akoumianaki, Ioanna; Papaspyrou, Sokratis; Kormas, Konstantinos Ar.; Nicolaidou, Artemis

2013-11-01

Macrofauna community interactions with environmental variables in the water column (salinity, temperature, turbidity, transparency, suspended particulate matter, particulate organic matter, choloroplastic pigments) and in the sediment (granulometric variables, organic carbon and pigments) were investigated in a coastal area with high land runoff due to riverine and temporary stream discharges (Greece, Aegean Sea, Maliakos Gulf). Samples were taken along a distance-depositional gradient from the river mouth to the open sea at eight stations, at times of different precipitation regime from August 2000 to May 2001. The physical variables, such as transparency and median grain size, generally increased seawards, and parallelled the depositional gradient as opposed to measures of food inputs and hydrodynamic regime. High environmental heterogeneity was observed during peak precipitation. The total number of species increased seawards and from August (122 species) to May (170 species). Maximum abundance also increased from August (4953 m-2) to May (10,220 individuals m-2), irrespective of distance from river mouth. Species belonging to different functional groups, as to recolonization, feeding, motility and substrate preferences, coexisted at all times indicating high functional diversity. Non-parametric multivariate regression showed that at times of low, rising and falling precipitation 78-81% of community variation was explained by environmental variables, indicating that macrofauna distribution and species composition respond to food inputs and sediment characteristics. During peak land runoff the community-environment relationship weakened (57% of the variability explained). The diversity of functional traits of the most abundant species indicates that the macrofauna community can absorb the impact of increased turbidity, sedimentation and current-driven dispersion. The study offers baseline information for the integrated coastal zone management in microtidal areas with high land runoff under Mediterranean-type climate conditions. During peak land runoff the community-environment relationship weakened (57% of the variability explained) whilst species distribution ranges increased. The study shows that the functional diversity in the study area prior to high discharge period enable macrofauna community to absorb the impact of increased turbidity, sedimentation and current-driven dispersion. The study offers baseline information for the impact of high land runoff in microtidal areas under Mediterranean-type climate conditions.

Climatic controls of vegetation vigor in four contrasting forest types of India--evaluation from National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer datasets (1990-2000).

PubMed

Prasad, V Krishna; Anuradha, E; Badarinath, K V S

2005-09-01

Ten-day advanced very high resolution radiometer images from 1990 to 2000 were used to examine spatial patterns in the normalized difference vegetation index (NDVI) and their relationships with climatic variables for four contrasting forest types in India. The NDVI signal has been extracted from homogeneous vegetation patches and has been found to be distinct for deciduous and evergreen forest types, although the mixed-deciduous signal was close to the deciduous ones. To examine the decadal response of the satellite-measured vegetation phenology to climate variability, seven different NDVI metrics were calculated using the 11-year NDVI data. Results suggested strong spatial variability in forest NDVI metrics. Among the forest types studied, wet evergreen forests of north-east India had highest mean NDVI (0.692) followed by evergreen forests of the Western Ghats (0.529), mixed deciduous forests (0.519) and finally dry deciduous forests (0.421). The sum of NDVI (SNDVI) and the time-integrated NDVI followed a similar pattern, although the values for mixed deciduous forests were closer to those for evergreen forests of the Western Ghats. Dry deciduous forests had higher values of inter-annual range (RNDVI) and low mean NDVI, also coinciding with a high SD and thus a high coefficient of variation (CV) in NDVI (CVNDVI). SNDVI has been found to be high for wet evergreen forests of north-east India, followed by evergreen forests of the Western Ghats, mixed deciduous forests and dry deciduous forests. Further, the maximum NDVI values of wet evergreen forests of north-east India (0.624) coincided with relatively high annual total precipitation (2,238.9 mm). The time lags had a strong influence in the correlation coefficients between annual total rainfall and NDVI. The correlation coefficients were found to be comparatively high (R2=0.635) for dry deciduous forests than for evergreen forests and mixed deciduous forests, when the precipitation data with a lag of 30 days was correlated against NDVI. Using multiple regression approach models were developed for individual forest types using 16 different climatic indices. A high proportion of the temporal variance (>90%) has been accounted for by three of the precipitation parameters (maximum precipitation, precipitation of the wettest quarter and driest quarter) and two of the temperature parameters (annual mean temperature and temperature of the coldest quarter) for mixed deciduous forests. Similarly, in the case of deciduous forests, four precipitation parameters and three temperature parameters explained nearly 83.6% of the variance. These results suggest differences in the relationship between NDVI and climatic variables based upon the time of growing season, time interval and climatic indices over which they were summed. These results have implications for forest cover mapping and monitoring in tropical regions of India.

Modeling the Spatial and Temporal Variation of Monthly and Seasonal Precipitation on the Nevada Test Site and Vicinity, 1960-2006

USGS Publications Warehouse

Blainey, Joan B.; Webb, Robert H.; Magirl, Christopher S.

2007-01-01

The Nevada Test Site (NTS), located in the climatic transition zone between the Mojave and Great Basin Deserts, has a network of precipitation gages that is unusually dense for this region. This network measures monthly and seasonal variation in a landscape with diverse topography. Precipitation data from 125 climate stations on or near the NTS were used to spatially interpolate precipitation for each month during the period of 1960 through 2006 at high spatial resolution (30 m). The data were collected at climate stations using manual and/or automated techniques. The spatial interpolation method, applied to monthly accumulations of precipitation, is based on a distance-weighted multivariate regression between the amount of precipitation and the station location and elevation. This report summarizes the temporal and spatial characteristics of the available precipitation records for the period 1960 to 2006, examines the temporal and spatial variability of precipitation during the period of record, and discusses some extremes in seasonal precipitation on the NTS.

Variability of East Asian summer monsoon precipitation during the Holocene and possible forcing mechanisms

NASA Astrophysics Data System (ADS)

Lu, Fuzhi; Ma, Chunmei; Zhu, Cheng; Lu, Huayu; Zhang, Xiaojian; Huang, Kangyou; Guo, Tianhong; Li, Kaifeng; Li, Lan; Li, Bing; Zhang, Wenqing

2018-03-01

Projecting how the East Asian summer monsoon (EASM) rainfall will change with global warming is essential for human sustainability. Reconstructing Holocene climate can provide critical insight into its forcing and future variability. However, quantitative reconstructions of Holocene summer precipitation are lacking for tropical and subtropical China, which is the core region of the EASM influence. Here we present high-resolution annual and summer rainfall reconstructions covering the whole Holocene based on the pollen record at Xinjie site from the lower Yangtze region. Summer rainfall was less seasonal and 30% higher than modern values at 10-6 cal kyr BP and gradually declined thereafter, which broadly followed the Northern Hemisphere summer insolation. Over the last two millennia, however, the summer rainfall has deviated from the downward trend of summer insolation. We argue that greenhouse gas forcing might have offset summer insolation forcing and contributed to the late Holocene rainfall anomaly, which is supported by the TraCE-21 ka transient simulation. Besides, tropical sea-surface temperatures could modulate summer rainfall by affecting evaporation of seawater. The rainfall pattern concurs with stalagmite and other proxy records from southern China but differs from mid-Holocene rainfall maximum recorded in arid/semiarid northern China. Summer rainfall in northern China was strongly suppressed by high-northern-latitude ice volume forcing during the early Holocene in spite of high summer insolation. In addition, the El Niño/Southern Oscillation might be responsible for droughts of northern China and floods of southern China during the late Holocene. Furthermore, quantitative rainfall reconstructions indicate that the Paleoclimate Modeling Intercomparison Project (PMIP) simulations underestimate the magnitude of Holocene precipitation changes. Our results highlight the spatial and temporal variability of the Holocene EASM precipitation and potential forcing mechanisms, which are very helpful for calibration of paleoclimate models and prediction of future precipitation changes in East Asia in the scenario of global warming.

Tree-ring based reconstruction of spring hydroclimate variability in the Caucasus

NASA Astrophysics Data System (ADS)

Martin-Benito, Dario; Köse, Nesibe; Güner, Tuncay; Pederson, Neil

2015-04-01

The Caucasus region has been identified as one of the most prominent biodiversity hotspots in the world. The region experiences recurrent droughts that not only affect natural vegetation but also the agriculturally-based economies in the Caucasus. Across northeastern Turkey and the Caucasus region, instrumental records providing information on climate variability are generally scarce. Thus the magnitude and frequency of past droughts in this biologically important region are less known. Additionally, despite the increase of climate reconstructions in the past decades for many parts of Europe and Asia, relatively little work has been done to understand hydroclimate variability in the Caucasus region. Nearly all efforts in the region have focused on the Mediterranean part of Turkey and the Middle East region. We developed new tree-ring width chronologies from different elevation sites in northeastern Turkey with the goal to reconstruct annually-resolved estimates of temperature and hydroclimate across the region. We developed the first reconstruction of spring hydroclimate variability for the Caucasus and the southeastern Black Sea Region since 1750 CE using a nested procedure. Despite the high mean annual precipitation in the region, our reconstruction accounted for over 45% of May-June precipitation variability from 1925 to 2006. We observed no evidence of a decrease in spring precipitation during the recent decades. However, we do see a decrease in precipitation variability over the last 75 years with respect to previous periods that, at this time, does not appear to be related to sample replication. Although our reconstructed precipitation shows important similarities with previous work from Mediterranean and northern Turkey, we find distinct drought periods are also evident suggesting a wider range of climate dynamics in the broader Black Sea region than what has been previously identified. Distinct episodes of drought at the larger scales could have important implications for the dynamics of ecosystems prior to and after the 20th century.

Sampling of the Diurnal Cycle of Precipitation using TRMM

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Bell, Thomas L.; Xu, Li-Ming; Starr, David OC. (Technical Monitor)

2001-01-01

We examine the temporal sampling of tropical regions using observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR). We conclude that PR estimates at any one hour, even using three years of data, are inadequate to describe the diurnal cycle of precipitation over regions smaller than 12 degrees, due to high spatial variability in sampling. We show that the optimum period of accumulation is four hours. Diurnal signatures display half as much sampling error when averaged over four hours of local time. A similar pattern of sampling variability is found in the TMI data, despite the TMI's wider swath and increased sampling. These results are verified using an orbital model. The sensitivity of the sampling to satellite altitude is presented, as well as sampling patterns at the new TRMM altitude of 402.5 km.

A Vertical Census of Precipitation Characteristics using Ground-based Dual-polarimetric Radar Data

NASA Astrophysics Data System (ADS)

Wolff, D. B.; Petersen, W. A.; Marks, D. A.; Pippitt, J. L.; Tokay, A.; Gatlin, P. N.

2017-12-01

Characterization of the vertical structure/variability of precipitation and resultant microphysics is critical in providing physical validation of space-based precipitation retrievals. In support of NASAs Global Precipitation Measurement (GPM) mission Ground Validation (GV) program, NASA has invested in a state-of-art dual-polarimetric radar known as NPOL. NPOL is routinely deployed on the Delmarva Peninsula in support of NASAs GPM Precipitation Research Facility (PRF). NPOL has also served as the backbone of several GPM field campaigns in Oklahoma, Iowa, South Carolina and most recently in the Olympic Mountains in Washington state. When precipitation is present, NPOL obtains very high-resolution vertical profiles of radar observations (e.g. reflectivity (ZH) and differential reflectivity (ZDR)), from which important particle size distribution parameters are retrieved such as the mass-weight mean diameter (Dm) and the intercept parameter (Nw). These data are then averaged horizontally to match the nadir resolution of the dual-frequency radar (DPR; 5 km) on board the GPM satellite. The GPM DPR, Combined, and radiometer algorithms (such as GPROF) rely on functional relationships built from assumed parametric relationships and/or retrieved parameter profiles and spatial distributions of particle size (PSD), water content, and hydrometeor phase within a given sample volume. Thus, the NPOL-retrieved profiles provide an excellent tool for characterization of the vertical profile structure and variability during GPM overpasses. In this study, we will use many such overpass comparisons to quantify an estimate of the true sub-IFOV variability as a function of hydrometeor and rain type (convective or stratiform). This presentation will discuss the development of a relational database to help provide a census of the vertical structure of precipitation via analysis and correlation of reflectivity, differential reflectivity, mean-weight drop diameter and the normalized intercept parameter of the gamma drop size distribution.

Increasing influence of air temperature on upper Colorado River streamflow

USGS Publications Warehouse

Woodhouse, Connie A.; Pederson, Gregory T.; Morino, Kiyomi; McAfee, Stephanie A.; McCabe, Gregory J.

2016-01-01

This empirical study examines the influence of precipitation, temperature, and antecedent soil moisture on upper Colorado River basin (UCRB) water year streamflow over the past century. While cool season precipitation explains most of the variability in annual flows, temperature appears to be highly influential under certain conditions, with the role of antecedent fall soil moisture less clear. In both wet and dry years, when flow is substantially different than expected given precipitation, these factors can modulate the dominant precipitation influence on streamflow. Different combinations of temperature, precipitation, and soil moisture can result in flow deficits of similar magnitude, but recent droughts have been amplified by warmer temperatures that exacerbate the effects of relatively modest precipitation deficits. Since 1988, a marked increase in the frequency of warm years with lower flows than expected, given precipitation, suggests continued warming temperatures will be an increasingly important influence in reducing future UCRB water supplies.

Study of continuous precipitation of ADU for the implantation in the pilot installation at the Atomic Energy Institute, Brazil. Estudo de precipitacao continua de DUA para a implantacao na instalacao piloto CEQ-IEA (in Portuguese)

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

Araujo, Jose Adroalado de

1974-05-15

The paper deals with the ammonium diuranate continuous precipitation with a high chemical purity degree from uranyl nitrate solutions, using 1.2 and 2.4 ammonium hydroxide solutions and gaseous NH{sub 3} as a precipitating agent. The precipitations were carried out in a continuous procedure with one and two stages. The variables studied were the NH[sub 4}OH solutions concentration, ADU precipitation curve, the flow rate of reactants, the temperature of the precipitation, pH of the suspended ADU, and ammonium diuranate filtrability. The experimental work performed and the data obtained permitted the design of a chemical reactor for the continuous nuclear grade ADUmore » precipitation at the Chemical Engineering Department of the Atomic Energy Institute of Sao Paulo.« less

Precipitation thresholds and drought-induced tree die-off: Insights from patterns of Pinus edulis mortality along an environmental stress gradient

Treesearch

Michael J. Clifford; Patrick D. Royer; Neil S. Cobb; David D. Breshears; Paulette L. Ford

2013-01-01

Recent regional tree die-off events appear to have been triggered by a combination of drought and heat - referred to as 'global-change-type drought'. To complement experiments focused on resolving mechanisms of drought-induced tree mortality, an evaluation of how patterns of tree die-off relate to highly spatially variable precipitation is needed....

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).

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).

Improvement of high floods predictability in the Red River of the North basin using combined remote-sensed, gauge-based and assimilated precipitation data

NASA Astrophysics Data System (ADS)

Semenova, O.; Restrepo, P. J.

2011-12-01

The Red River of the North basin (USA) is considered to be under high risk of flood danger, having experienced serious flooding during the last few years. The region climate can be characterized as cold and, during winter, it exhibits continuous snowcover modified by wind redistribution. High-hazard runoff regularly occurs as a major spring snowmelt event resulting from the relatively rapid release of water from the snowpack on frozen soils. Although in summer/autumn most rainfall occurs from convective storms over small areas and does not generate dangerous floods, the pre-winter state of the soils may radically influence spring maximum flows. Large amount of artificial agricultural tiles and numerous small post-glacial depressions influencing the redistribution of runoff complicates the predictions of high floods. In such conditions any hydrological model would not be successful without proper precipitation input. In this study the simulation of runoff processes for two watersheds in the basin of the Red River of the North, USA, was undertaken using the Hydrograph model developed at the State Hydrological Institute (St. Petersburg, Russia). The Hydrograph is a robust process-based model, where the processes have a physical basis combined with some strategic conceptual simplifications that give it the ability to be applied in the conditions of low information availability. It accounts for the processes of frost and thaw of soils, snow redistribution and depression storage impacts. The assessment of the model parameters was conducted based on the characteristics of soil and vegetation cover. While performing the model runs, the parameters of depression storage and the parameters of different types of flow were manually calibrated to reproduce the observed flow. The model provided satisfactory simulation results in terms not only of river runoff but also variable sates of soil like moisture and temperature over a simulation period 2005 - 2010. For experimental runs precipitation from different sources was used as forcing data to the hydrological model: 1) data of ground meteorological stations; 2) the Snow Data Assimilation System (SNODAS) products containing several variables: snow water equivalent, snow depth, solid and liquid precipitation; 3) MAPX precipitation data which is mean areal precipitation for a watershed calculated using the radar- and gauge-based information. The results demonstrated that in the conditions of high uncertainty of model parameters combining precipitation information from different sources (the SNODAS precipitation in winter with the MAPX precipitation in summer) significantly improves the model performance and predictability of high floods.

An analysis of the daily precipitation variability in the Himalayan orogen using a statistical parameterisation and its potential in driving landscape evolution models with stochastic climatic forcing

NASA Astrophysics Data System (ADS)

Deal, Eric; Braun, Jean

2015-04-01

A current challenge in landscape evolution modelling is to integrate realistic precipitation patterns and behaviour into longterm fluvial erosion models. The effect of precipitation on fluvial erosion can be subtle as well as nonlinear, implying that changes in climate (e.g. precipitation magnitude or storminess) may have unexpected outcomes in terms of erosion rates. For example Tucker and Bras (2000) show theoretically that changes in the variability of precipitation (storminess) alone can influence erosion rate across a landscape. To complicate the situation further, topography, ultimately driven by tectonic uplift but shaped by erosion, has a major influence on the distribution and style of precipitation. Therefore, in order to untangle the coupling between climate, erosion and tectonics in an actively uplifting orogen where fluvial erosion is dominant it is important to understand how the 'rain dial' used in a landscape evolution model (LEM) corresponds to real precipitation patterns. One issue with the parameterisation of rainfall for use in an LEM is the difference between the timescales for precipitation (≤ 1 year) and landscape evolution (> 103 years). As a result, precipitation patterns must be upscaled before being integrated into a model. The relevant question then becomes: What is the most appropriate measure of precipitation on a millennial timescale? Previous work (Tucker and Bras, 2000; Lague, 2005) has shown that precipitation can be properly upscaled by taking into account its variable nature, along with its average magnitude. This captures the relative size and frequency of extreme events, ensuring a more accurate characterisation of the integrated effects of precipitation on erosion over long periods of time. In light of this work, we present a statistical parameterisation that accurately models the mean and daily variability of ground based (APHRODITE) and remotely sensed (TRMM) precipitation data in the Himalayan orogen with only a few parameters. We also demonstrate over what spatial and temporal scales this parameterisation applies and is stable. Applying the parameterisation over the Himalayan orogen reveals large-scale strike-perpendicular gradients in precipitation variability in addition to the long observed strike-perpendicular gradient in precipitation magnitude. This observation, combined with the theoretical work mentioned above, suggests that variability is an integral part of the interaction between climate and erosion. References Bras, R. L., & Tucker, G. E. (2000). A stochastic approach to modeling the role of rainfall variability in drainage basin evolution. Water Resources Research, 36(7), 1953-1964. doi:10.1029/2000WR900065 Lague, D. (2005). Discharge, discharge variability, and the bedrock channel profile. Journal of Geophysical Research, 110(F4), F04006. doi:10.1029/2004JF000259

Loch Vale Watershed Long-Term Ecological Research and Monitoring Program: Quality Assurance Report, 2003-09

USGS Publications Warehouse

Richer, Eric E.; Baron, Jill S.

2011-01-01

The Loch Vale watershed project is a long-term research and monitoring program located in Rocky Mountain National Park that addresses watershed-scale ecosystem processes, particularly as they respond to atmospheric deposition and climate variability. Measurements of precipitation depth, precipitation chemistry, discharge, and surface-water quality are made within the watershed and elsewhere in Rocky Mountain National Park. As data collected for the program are used by resource managers, scientists, policy makers, and students, it is important that all data collected in Loch Vale watershed meet high standards of quality. In this report, data quality was evaluated for precipitation, discharge, and surface-water chemistry measurements collected during 2003-09. Equipment upgrades were made at the Loch Vale National Atmospheric Deposition Program monitoring site to improve precipitation measurements and evaluate variability in precipitation depth and chemistry. Additional solar panels and batteries have been installed to improve the power supply, and data completeness, at the NADP site. As a result of equipment malfunction, discharge data for the Loch Outlet were estimated from October 18, 2005, to August 17, 2006. Quality-assurance results indicate that more than 98 percent of all surface-water chemistry measurements were accurate and precise. Records that did not meet quality criteria were removed from the database. Measurements of precipitation depth, precipitation chemistry, discharge, and surface-water quality were all sufficiently complete and consistent to support project data needs.

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

USGS Publications Warehouse

Griffin, Eleanor R.; Friedman, Jonathan M.

2017-01-01

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

Improved Hourly and Sub-Hourly Gauge Data for Assessing Precipitation Extremes in the U.S.

NASA Astrophysics Data System (ADS)

Lawrimore, J. H.; Wuertz, D.; Palecki, M. A.; Kim, D.; Stevens, S. E.; Leeper, R.; Korzeniewski, B.

2017-12-01

The NOAA/National Weather Service (NWS) Fischer-Porter (F&P) weighing bucket precipitation gauge network consists of approximately 2000 stations that comprise a subset of the NWS Cooperative Observers Program network. This network has operated since the mid-20th century, providing one of the longest records of hourly and 15-minute precipitation observations in the U.S. The lengthy record of this dataset combined with its relatively high spatial density, provides an important source of data for many hydrological applications including understanding trends and variability in the frequency and intensity of extreme precipitation events. In recent years NOAA's National Centers for Environmental Information initiated an upgrade of its end-to-end processing and quality control system for these data. This involved a change from a largely manual review and edit process to a fully automated system that removes the subjectivity that was previously a necessary part of dataset quality control and processing. An overview of improvements to this dataset is provided along with the results of an analysis of observed variability and trends in U.S. precipitation extremes since the mid-20th century. Multi-decadal trends in many parts of the nation are consistent with model projections of an increase in the frequency and intensity of heavy precipitation in a warming world.

Evaluating the response of Lake Prespa (SW Balkan) to future climate change projections from a high-resolution model

NASA Astrophysics Data System (ADS)

van der Schriek, Tim; Varotsos, Konstantinos V.; Giannakopoulos, Christos

2017-04-01

The Mediterranean stands out globally due to its sensitivity to (future) climate change. Projections suggest that the Balkans will experience precipitation and runoff decreases of up to 30% by 2100. However, these projections show large regional spatial variability. Mediterranean lake-wetland systems are particularly threatened by projected climate changes that compound increasingly intensive human impacts (e.g. water extraction, drainage, pollution and dam-building). Protecting the remaining systems is extremely important for supporting global biodiversity. This protection should be based on a clear understanding of individual lake-wetland hydrological responses to future climate changes, which requires fine-resolution projections and a good understanding of the impact of hydro-climate variability on individual lakes. Climate change may directly affect lake level (variability), volume and water temperatures. In turn, these variables influence lake-ecology, habitats and water quality. Land-use intensification and water abstraction multiply these climate-driven changes. To date, there are no projections of future water level and -temperature of individual Mediterranean lakes under future climate scenarios. These are, however, of crucial importance to steer preservation strategies on the relevant catchment-scale. Here we present the first projections of water level and -temperature of the Prespa Lakes covering the period 2071-2100. These lakes are of global significance for biodiversity, and of great regional socio-economic importance as a water resource and tourist attraction. Impact projections are assessed by the Regional Climate Model RCA4 of the Swedish Meteorological and Hydrological Institute (SMHI) driven by the Max Planck Institute for Meteorology global climate model MPI-ESM-LR under two RCP future emissions scenarios, the RCP4.5 and the RCP8.5, with the simulations carried out in the framework of EURO-CORDEX. Temperature, evapo(transpi)ration and precipitation over the Prespa catchment were simulated with this high horizontal resolution (12 × 12 km) regional climate model. Lake temperatures were derived from surface temperatures based on physical models, while water levels were calculated with the lake water balance model. Climate simulations indicate that annual- and wet season catchment precipitation does not significantly change by the end of the century. The median precipitation decreases, while precipitation variability increases. The percentage of annual precipitation falling in the wet season increases by 5-10%, indicating a stronger seasonality in the precipitation regime. Summer (lake) temperatures and lake surface evaporation will rise significantly under both explored climate change scenarios. Lake impact projections indicate that evaporation changes will cause the water level of Lake Megali Prespa to fall by 5m to 840-839m. The increased precipitation variability will cause large inter-annual water level fluctuations. Average water level may fall even further if: (1) drier summers lead to more water abstraction for irrigation, and (2) there is a reduction in winter snowfall/accumulation and thus less discharge. These findings are of key importance for developing sustainable lake water resource management in a region that is highly vulnerable to future climate change and already experiences significant water stress. Research paves the way for innovative management adaptation strategies focussed on decreasing water abstraction, for example through introducing smart irrigation and selecting more water efficient crops.

Evaporation, precipitation, and associated salinity changes at a humid, subtropical estuary

USGS Publications Warehouse

Sumner, D.M.; Belaineh, G.

2005-01-01

The distilling effect of evaporation and the diluting effect of precipitation on salinity at two estuarine sites in the humid subtropical setting of the Indian River Lagoon, Florida, were evaluated based on daily evaporation computed with an energy-budget method and measured precipitation. Despite the larger magnitude of evaporation (about 1,580 mm yr-1) compared to precipitation (about 1,180 mm yr-1) between February 2002 and January 2004, the variability of monthly precipitation induced salinity changes was more than twice the variability of evaporation induced changes. Use of a constant, mean value of evaporation, along with measured values of daily precipitation, were sufficient to produce simulated salinity changes that contained little monthly (root-mean-square error = 0.33??? mo-1 and 0.52??? mo-1 at the two sites) or cumulative error (<1??? yr-1) compared to simulations that used computed daily values of evaporation. This result indicates that measuring the temporal variability in evaporation may not be critical to simulation of salinity within the lagoon. Comparison of evaporation and precipitation induced salinity changes with measured salinity changes indicates that evaporation and precipitation explained only 4% of the changes in salinity within a flow-through area of the lagoon; surface water and ocean inflows probably accounted for most of the variability in salinity at this site. Evaporation and precipitation induced salinity changes explained 61% of the variability in salinity at a flow-restricted part of the lagoon. ?? 2005 Estuarine Research Federation.

Changes in temporal variability of precipitation over land due to anthropogenic forcings

DOE PAGES

Konapala, Goutam; Mishra, Ashok; Leung, L. Ruby

2017-02-02

This study investigated the anthropogenic influence on the temporal variability of annual precipitation for the period 1950-2005 as simulated by the CMIP5 models. The temporal variability of both annual precipitation amount (PRCPTOT) and intensity (SDII) was first measured using a metric of statistical dispersion called the Gini coefficient. Comparing simulations driven by both anthropogenic and natural forcings (ALL) with simulations of natural forcings only (NAT), we quantified the anthropogenic contributions to the changes in temporal variability at global, continental and sub-continental scales as a relative difference of the respective Gini coefficients of ALL and NAT. Over the period of 1950-2005,more » our results indicate that anthropogenic forcings have resulted in decreased uniformity (i.e., increase in unevenness or disparity) in annual precipitation amount and intensity at global as well as continental scales. In addition, out of the 21 sub-continental regions considered, 14 (PRCPTOT) and 17 (SDII) regions showed significant anthropogenic influences. The human impacts are generally larger for SDII compared to PRCTOT, indicating that the temporal variability of precipitation intensity is generally more susceptible to anthropogenic influence than precipitation amount. Lastly, the results highlight that anthropogenic activities have changed not only the trends but also the temporal variability of annual precipitation, which underscores the need to develop effective adaptation management practices to address the increased disparity.« less

Interannual variability in the extent of wetland-stream connectivity within the Prairie Pothole Region

Treesearch

Melanie Vanderhoof; Laurie Alexander

2016-01-01

The degree of hydrological connectivity between wetland systems and downstream receiving waters can be expected to influence the volume and variability of stream discharge. The Prairie Pothole Region contains a high density of depressional wetland features, a consequence of glacial retreat. Spatial variability in wetland density, drainage evolution, and precipitation...

The effects of precipitation variability on C4 photosynthesis, net primary production and soil respiration in a Chihuahuan desert grassland

Treesearch

Michell L. Thomey

2012-01-01

Although the Earth's climate system has always been inherently variable, the magnitude and rate of anthropogenic climate change is subjecting ecosystems and the populations that they contain to novel environmental conditions. Because water is the most limiting resource, arid-semiarid ecosystems are likely to be highly responsive to future climate variability. The...

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009

NASA Astrophysics Data System (ADS)

Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui

2014-01-01

Using time series of moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data from 2000 to 2009, we assessed decadal vegetation dynamics across Canada and examined the relationship between NDVI and climatic variables (precipitation and temperature). The Palmer drought severity index and vapor pressure difference (VPD) were used to relate the vegetation changes to the climate, especially in cases of drought. Results indicated that MODIS NDVI measurements provided a dynamic picture of interannual variation in Canadian vegetation patterns. Greenness declined in 2000, 2002, and 2009 and increased in 2005, 2006, and 2008. Vegetation dynamics varied across regions during the period. Most forest land shows little change, while vegetation in the ecozone of Pacific Maritime, Prairies, and Taiga Shield shows more dynamics than in the others. Significant correlations were found between NDVI and the climatic variables. The variation of NDVI resulting from climatic variability was more highly correlated to temperature than to precipitation in most ecozones. Vegetation grows better with higher precipitation and temperature in almost all ecozones. However, vegetation grows worse under higher temperature in the Prairies ecozone. The annual changes in NDVI corresponded well with the change in VPD in most ecozones.

Soil Organic Matter Stabilization via Mineral Interactions in Forest Soils with Varying Saturation Frequency

NASA Astrophysics Data System (ADS)

Possinger, A. R.; Inagaki, T.; Bailey, S. W.; Kogel-Knabner, I.; Lehmann, J.

2017-12-01

Soil carbon (C) interaction with minerals and metals through surface adsorption and co-precipitation processes is important for soil organic C (SOC) stabilization. Co-precipitation (i.e., the incorporation of C as an "impurity" in metal precipitates as they form) may increase the potential quantity of mineral-associated C per unit mineral surface compared to surface adsorption: a potentially important and as yet unaccounted for mechanism of C stabilization in soil. However, chemical, physical, and biological characterization of co-precipitated SOM as such in natural soils is limited, and the relative persistence of co-precipitated C is unknown, particularly under dynamic environmental conditions. To better understand the relationships between SOM stabilization via organometallic co-precipitation and environmental variables, this study compares mineral-SOM characteristics across a forest soil (Spodosol) hydrological gradient with expected differences in co-precipitation of SOM with iron (Fe) and aluminum (Al) due to variable saturation frequency. Soils were collected from a steep, well-drained forest soil transect with low, medium, and high frequency of water table intrusion into surface soils (Hubbard Brook Experimental Forest, Woodstock, NH). Lower saturation frequency soils generally had higher C content, C/Fe, C/Al, and other indicators of co-precipitation interactions resulting from SOM complexation, transport, and precipitation, an important process of Spodosol formation. Preliminary Fe X-ray Absorption Spectroscopic (XAS) characterization of SOM and metal chemistry in low frequency profiles suggest co-precipitation of SOM in the fine fraction (<20 µm). Short-term (10d) aerobic incubation of high and low saturation frequency soils showed greater SOC mineralization per unit soil C for low saturation frequency (i.e., higher co-precipitation) soils; however, increased mineralization may be attributed to non-mineral associated fractions of SOM. Further work to identify the component of SOM contributing to rapid mineralization using 13C-labeled substrates will link the observed chemical characteristics (13C-NMR, C K-edge XANES, and Fe XAS) of mineral-organic associations resulting from varying saturation frequency with mechanisms driving mineralization processes.

Impact of Urbanization on Spatial Variability of Rainfall-A case study of Mumbai city with WRF Model

NASA Astrophysics Data System (ADS)

Mathew, M.; Paul, S.; Devanand, A.; Ghosh, S.

2015-12-01

Urban precipitation enhancement has been identified over many cities in India by previous studies conducted. Anthropogenic effects such as change in land cover from hilly forest areas to flat topography with solid concrete infrastructures has certain effect on the local weather, the same way the greenhouse gas has on climate change. Urbanization could alter the large scale forcings to such an extent that it may bring about temporal and spatial changes in the urban weather. The present study investigate the physical processes involved in urban forcings, such as the effect of sudden increase in wind velocity travelling through the channel space in between the dense array of buildings, which give rise to turbulence and air mass instability in urban boundary layer and in return alters the rainfall distribution as well as rainfall initiation. A numerical model study is conducted over Mumbai metropolitan city which lies on the west coast of India, to assess the effect of urban morphology on the increase in number of extreme rainfall events in specific locations. An attempt has been made to simulate twenty extreme rainfall events that occurred over the summer monsoon period of the year 2014 using high resolution WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) model to assess the urban land cover mechanisms that influences precipitation variability over this spatially varying urbanized region. The result is tested against simulations with altered land use. The correlation of precipitation with spatial variability of land use is found using a detailed urban land use classification. The initial and boundary conditions for running the model were obtained from the global model ECMWF(European Centre for Medium Range Weather Forecast) reanalysis data having a horizontal resolution of 0.75 °x 0.75°. The high resolution simulations show significant spatial variability in the accumulated rainfall, within a few kilometers itself. Understanding the spatial variability of precipitation will help in the planning and management of the built environment more efficiently.

Decadal variability of precipitation over Western North America

USGS Publications Warehouse

Cayan, D.R.; Dettinger, M.D.; Diaz, Henry F.; Graham, N.E.

1998-01-01

Decadal (>7- yr period) variations of precipitation over western North America account for 20%-50% of the variance of annual precipitation. Spatially, the decadal variability is broken into several regional [O(1000 km)] components. These decadal variations are contributed by fluctuations in precipitation from seasons of the year that vary from region to region and that are not necessarily concentrated in the wettest season(s) alone. The precipitation variations are linked to various decadal atmospheric circulation and SST anomaly patterns where scales range from regional to global scales and that emphasize tropical or extratropical connections, depending upon which precipitation region is considered. Further, wet or dry decades are associated with changes in frequency of at least a few short-period circulation 'modes' such as the Pacific-North American pattern. Precipitation fluctuations over the southwestern United States and the Saskatchewan region of western Canada are associated with extensive shifts of sea level pressure and SST anomalies, suggesting that they are components of low-frequency precipitation variability from global-scale climate proceses. Consistent with the global scale of its pressure and SST connection, the Southwest decadal precipitation is aligned with opposing precipitation fluctuations in northern Africa.Decadal (>7-yr period) variations of precipitation over western North America account for 20%-50% of the variance of annual precipitation. Spatially, the decadal variability is broken into several regional [O(1000 km)] components. These decadal variations are contributed by fluctuations in precipitation from seasons of the year that vary from region to region and that are not necessarily concentrated in the wettest season(s) alone. The precipitation variations are linked to various decadal atmospheric circulation and SST anomaly patterns where scales range from regional to global scales and that emphasize tropical or extratropical connections, depending upon which precipitation region is considered. Further, wet or dry decades are associated with changes in frequency of at least a few short-period circulation `modes' such as the Pacific-North American pattern. Precipitation fluctuations over the southwestern United States and the Saskatchewan region of western Canada are associated with extensive shifts of sea level pressure and SST anomalies, suggesting that they are components of low-frequency precipitation variability from global-scale climate processes. Consistent with the global scale of its pressure and SST connection, the Southwest decadal precipitation is aligned with opposing precipitation fluctuations in northern Africa.

Climate variability decreases species richness and community stability in a temperate grassland.

PubMed

Zhang, Yunhai; Loreau, Michel; He, Nianpeng; Wang, Junbang; Pan, Qingmin; Bai, Yongfei; Han, Xingguo

2018-06-26

Climate change involves modifications in both the mean and the variability of temperature and precipitation. According to global warming projections, both the magnitude and the frequency of extreme weather events are increasing, thereby increasing climate variability. The previous studies have reported that climate warming tends to decrease biodiversity and the temporal stability of community primary productivity (i.e., community stability), but the effects of the variability of temperature and precipitation on biodiversity, community stability, and their relationship have not been clearly explored. We used a long-term (from 1982 to 2014) field data set from a temperate grassland in northern China to explore the effects of the variability of mean temperature and total precipitation on species richness, community stability, and their relationship. Results showed that species richness promoted community stability through increases in asynchronous dynamics across species (i.e., species asynchrony). Both species richness and species asynchrony were positively associated with the residuals of community stability after controlling for its dependence on the variability of mean temperature and total precipitation. Furthermore, the variability of mean temperature reduced species richness, while the variability of total precipitation decreased species asynchrony and community stability. Overall, the present study revealed that species richness and species asynchrony promoted community stability, but increased climate variability may erode these positive effects and thereby threaten community stability.

Long-term limnological data from the larger lakes of Yellowstone National Park, Wyoming, USA

USGS Publications Warehouse

Theriot, E.C.; Fritz, S.C.; Gresswell, Robert E.

1997-01-01

Long-term limnological data from the four largest lakes in Yellowstone National Park (Yellowstone, Lewis, Shoshone, Heart) are used to characterize their limnology and patterns of temporal and spatial variability. Heart Lake has distinctively high concentrations of dissolved materials, apparently reflecting high thermal inputs. Shoshone and Lewis lakes have the highest total SiO2 concentrations (averaging over 23.5 mg L-1), apparently as a result of the rhyolitic drainage basins. Within Yellowstone Lake spatial variability is low and ephemeral for most measured variables, except that the Southeast Arm has lower average Na concentrations. Seasonal variation is evident for Secchi transparency, pH, and total-SiO2 and probably reflects seasonal changes in phytoplankton biomass and productivity. Total dissolved solids (TDS) and total-SiO2 generally show a gradual decline from the mid-1970s through mid-1980s, followed by a sharp increase. Ratios of Kjeldahl-N to total-PO4 (KN:TP) suggest that the lakes, especially Shoshone, are often nitrogen limited. Kjeldahl-N is positively correlated with winter precipitation, but TP and total-SiO2 are counterintuitively negatively correlated with precipitation. We speculate that increased winter precipitation, rather than watershed fires, increases N-loading which, in turn, leads to increased demand for TP and total SiO2.

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

NASA Astrophysics Data System (ADS)

Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

2017-10-01

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

Vegetation and environmental controls on soil respiration in a pinon-juniper woodland

Treesearch

Sandra A. White

2008-01-01

Soil respiration (RS) responds to changes in plant and microbial activity and environmental conditions. In arid ecosystems of the southwestern USA, soil moisture exhibits large fluctuations because annual and seasonal precipitation inputs are highly variable, with increased variability expected in the future. Patterns of soil moisture, and periodic severe drought, are...

First field-based observations of δ2H and δ18O values of precipitation and other water bodies in the Mongolian Gobi desert

NASA Astrophysics Data System (ADS)

Burnik Šturm, Martina; Ganbaatar, Oyunsaikhan; Voigt, Christian C.; Kaczensky, Petra

2017-04-01

Hydrogen (δ2H) and oxygen (δ18O) isotope values of water are widely used to track the global hydrological cycle and the global δ2H and δ18O patterns of precipitation are increasingly used in studies on animal migration, forensics, food authentication and traceability studies. However, δ2H and δ18O values of precipitation spanning one or more years are available for only a few 100 locations worldwide and for many remote areas such as Mongolia data are still scarce. We obtained the first field-based δ2H and δ18O isotope data of event-based precipitation, rivers and other water bodies in the extreme environment of the Dzungarian Gobi desert in SW Mongolia, covering a period of 16 months (1). Our study area is located over 450 km north-east from the nearest IAEA GNIP station (Fukang station, China) from which it is separated by a mountain range at the international border between China and Mongolia. Isotope values of the collected event-based precipitation showed and extreme range and a high seasonal variability with higher and more variable values in summer and lower in winter. The high variability could not be explained by different origin of air masses alone (i.e. NW polar winds over Russia or westerlies over Central Asia; analyzed using back-trajectory HYSPLIT model), but is likely a result of a combination of different processes affecting the isotope values of precipitation in this area. The calculated field-based local meteoric water line (LMWL, δ2H=(7.42±0.16)δ18O-(23.87±3.27)) showed isotopic characteristics of precipitation in an arid region. We observed a slight discrepancy between the filed based and modelled (Online Isotope in Precipitation Calculator, OIPC) LMWL which highlighted the difficulty of modelling the δ2H and δ18O values for areas with extreme climatic conditions and thus emphasized the importance of collecting long-term field-based data. The collected isotopic data of precipitation and other water bodies provide a basis for future studies in this largely understudied region. (1)Burnik Šturm M., Ganbaatar O., Voigt C.C., Kaczensky P. (2016) First field-based observations of δ2H and δ18O values of precipitation, rivers and other water bodies in the Dzungarian Gobi, SW Mongolia. Isotopes in Environmental and Health Studies, doi: 10.1080/10256016.2016.1231184

An underestimated role of precipitation frequency in regulating summer soil moisture

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

Wu, Chaoyang; Chen, Jing M.; Pumpanen, Jukka

2012-04-26

Soil moisture induced droughts are expected to become more frequent under future global climate change. Precipitation has been previously assumed to be mainly responsible for variability in summer soil moisture. However, little is known about the impacts of precipitation frequency on summer soil moisture, either interannually or spatially. To better understand the temporal and spatial drivers of summer drought, 415 site yr measurements observed at 75 flux sites world wide were used to analyze the temporal and spatial relationships between summer soil water content (SWC) and the precipitation frequencies at various temporal scales, i.e., from half-hourly, 3, 6, 12 andmore » 24 h measurements. Summer precipitation was found to be an indicator of interannual SWC variability with r of 0.49 (p < 0.001) for the overall dataset. However, interannual variability in summer SWC was also significantly correlated with the five precipitation frequencies and the sub-daily precipitation frequencies seemed to explain the interannual SWC variability better than the total of precipitation. Spatially, all these precipitation frequencies were better indicators of summer SWC than precipitation totals, but these better performances were only observed in non-forest ecosystems. Our results demonstrate that precipitation frequency may play an important role in regulating both interannual and spatial variations of summer SWC, which has probably been overlooked or underestimated. However, the spatial interpretation should carefully consider other factors, such as the plant functional types and soil characteristics of diverse ecoregions.« less

Reequilibration of fluid inclusions in low-temperature calcium-carbonate cement

NASA Astrophysics Data System (ADS)

Goldstein, Robert H.

1986-09-01

Calcium-carbonate cements precipitated in low-temperature, near-surface, vadose environments contain fluid inclusions of variable vapor-to-liquid ratios that yield variable homogenization temperatures. Cements precipitated in low-temperature, phreatic environments contain one-phase, all-liquid fluid inclusions. Neomorphism of unstable calcium-carbonate phases may cause reequilibration of fluid inclusions. Stable calcium-carbonate cements of low-temperature origin, which have been deeply buried, contain fluid inclusions of variable homogenization temperature and variable salt composition. Most inclusion fluids are not representative of the fluids present during cement growth and are more indicative of burial pore fluids. Therefore, low-temperature fluid inclusions probably reequilibrate with burial fluids during progressive burial. Reequilibration is likely caused by high internal pressures in inclusions which result in hydrofracturing. The resulting fluid-inclusion population could contain a nearly complete record of burial fluids in which a particular rock has been bathed. *Present address: Department of Geology, University of Kansas, Lawrence, Kansas 66045

Spatio-Temporal Changes In Non-Extreme Precipitation Variability Over North America

NASA Astrophysics Data System (ADS)

Roque, S.

2016-12-01

Precipitation variability encompasses attributes associated with the sequencing and duration of events of the full range of magnitudes. However, climate change studies have largely focused on extreme events. Using analyses of long-term weather station data we show that high frequency events, such as fraction of wet days in a year and average duration of wet and dry periods, are undergoing significant changes across North America. The median increase in fraction of wet days in a year indicates that in 2010, North America experienced an additional 11 days of precipitation compared to 1960 (when the median number of wet days was 96), and wet periods that were 0.14 days longer than those in 1960 (when the median was 1.78 days). Further, these changes in high-frequency precipitation are more prevalent and larger than those associated with extremes. Such trends also exist for events of a range of magnitudes. Results reveal the existence of localized clusters with opposing trends to that of broader geographic variation, which illustrates the role of microclimate and other drivers of trends. Such hitherto unknown patterns have the potential to significantly inform our characterization of the resilience and vulnerability of a broad range of ecosystems, and agricultural and socio-economic systems. They can also set new benchmarks for climate model assessments.

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.

Boreal spring precipitation variability in the cold arid western Himalaya during the last millennium, regional linkages, and socio-economic implications

NASA Astrophysics Data System (ADS)

Yadava, Akhilesh K.; Bräuning, Achim; Singh, Jayendra; Yadav, Ram R.

2016-07-01

Precipitation in the monsoon shadow zone of the western Himalayan region, largely under the influence of mid-latitude westerlies, is the dominant regional socioeconomic driver. Current knowledge of long-term regional precipitation variability is scarce due to spatially and temporally limited weather and high-resolution proxy climate records. We developed the first boreal spring precipitation reconstruction for the western Himalaya covering the last millennium (1030-2011 C.E.). The annually resolved reconstruction is based on a large tree-ring data set of Himalayan cedar (Cedrus deodara) and neoza pine (Pinus gerardiana) from 16 ecologically homogeneous moisture stressed settings in Kinnaur, western Indian Himalaya. The precipitation reconstruction revealed persistent long-term spring droughts from the 12th to early 16th century C.E. and pluvial from the late 16th century C.E. to recent decades. The late 15th and early 16th centuries (1490-1514 C.E.) displayed the driest episode, with precipitation being ∼15% lower than the long-term mean. The early 19th century (1820-1844 C.E.) was the wettest period of the past millennium, with mean precipitation ∼13% above the long-term mean. The reconstructed boreal spring precipitation from the western Himalaya revealed large-scale consistency with hydrological records from westerly dominated regions in Central Asia, indicating synoptic-scale changes in atmospheric circulation during the major part of the Medieval and Little Ice Age periods. Protracted droughts in Central Asia could have caused severe contraction of the regional economy, as indicated by striking coherence of reconstructed drought periods and historic social upheavals and invasions of India from Central and Western Asian invaders. Vulnerability to climatic extremes underpins the need to develop a better understanding of the temporal and spatial variability in regional hydroclimate in order to devise viable water resource management plans.

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

Impact of internal variability on projections of Sahel precipitation change

NASA Astrophysics Data System (ADS)

Monerie, Paul-Arthur; Sanchez-Gomez, Emilia; Pohl, Benjamin; Robson, Jon; Dong, Buwen

2017-11-01

The impact of the increase of greenhouse gases on Sahelian precipitation is very uncertain in both its spatial pattern and magnitude. In particular, the relative importance of internal variability versus external forcings depends on the time horizon considered in the climate projection. In this study we address the respective roles of the internal climate variability versus external forcings on Sahelian precipitation by using the data from the CESM Large Ensemble Project, which consists of a 40 member ensemble performed with the CESM1-CAM5 coupled model for the period 1920-2100. We show that CESM1-CAM5 is able to simulate the mean and interannual variability of Sahel precipitation, and is representative of a CMIP5 ensemble of simulations (i.e. it simulates the same pattern of precipitation change along with equivalent magnitude and seasonal cycle changes as the CMIP5 ensemble mean). However, CESM1-CAM5 underestimates the long-term decadal variability in Sahel precipitation. For short-term (2010-2049) and mid-term (2030-2069) projections the simulated internal variability component is able to obscure the projected impact of the external forcing. For long-term (2060-2099) projections external forcing induced change becomes stronger than simulated internal variability. Precipitation changes are found to be more robust over the central Sahel than over the western Sahel, where climate change effects struggle to emerge. Ten (thirty) members are needed to separate the 10 year averaged forced response from climate internal variability response in the western Sahel for a long-term (short-term) horizon. Over the central Sahel two members (ten members) are needed for a long-term (short-term) horizon.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

Evaluation of High Resolution IMERG Satellite Precipitation over the Global Oceans using OceanRAIN

NASA Astrophysics Data System (ADS)

Kucera, P. A.; Klepp, C.

2017-12-01

Precipitation is a key parameter of the essential climate variables in the Earth System that is a key variable in the global water cycle. Observations of precipitation over oceans is relatively sparse. Satellite observations over oceans is the only viable means of measuring the spatially distribution of precipitation. In an effort to improve global precipitation observations, the research community has developed a state of the art precipitation dataset as part of the NASA/JAXA Global Precipitation Measurement (GPM) program. The satellite gridded product that has been developed is called Integrated Multi-satelliE Retrievals for GPM (IMERG), which has a maximum spatial resolution of 0.1º x 0.1º and temporal 30 minute. Even with the advancements in retrievals, there is a need to quantify uncertainty of IMERG precipitation estimates especially over oceans. To address this need, the OceanRAIN dataset has been used to create a comprehensive database to compare IMERG products. The OceanRAIN dataset was created using observations from the ODM-470 optical disdrometer that has been deployed on 12 research vessels worldwide with 6 long-term installations operating in all climatic regions, seasons and ocean basins. More than 6 million data samples have been collected on the OceanRAIN program. These data were matched to IMERG grids for the study period of 15 March 2014-01 April 2017. This evaluation produced over 1500 matched IMERG-OceanRAIN pairs of precipitation observed at the surface. These matched pairs were used to evaluate the performance of IMERG stratified by different latitudinal bands and precipitation regimes. The presentation will provide an overview of the study and summary of evaluation results.

Long-term growth-increment chronologies reveal diverse influences of climate forcing on freshwater and forest biota in the Pacific Northwest

USGS Publications Warehouse

Black, Bryan A.; Dunham, Jason B.; Blundon, Brett W.; Brim-Box, Jayne; Tepley, Alan J.

2015-01-01

Analyses of how organisms are likely to respond to a changing climate have focused largely on the direct effects of warming temperatures, though changes in other variables may also be important, particularly the amount and timing of precipitation. Here, we develop a network of eight growth-increment width chronologies for freshwater mussel species in the Pacific Northwest, United States and integrate them with tree-ring data to evaluate how terrestrial and aquatic indicators respond to hydroclimatic variability, including river discharge and precipitation. Annual discharge averaged across water years (October 1–September 30) was highly synchronous among river systems and imparted a coherent pattern among mussel chronologies. The leading principal component of the five longest mussel chronologies (1982–2003; PC1mussel) accounted for 47% of the dataset variability and negatively correlated with the leading principal component of river discharge (PC1discharge; r = −0.88; P < 0.0001). PC1mussel and PC1discharge were closely linked to regional wintertime precipitation patterns across the Pacific Northwest, the season in which the vast majority of annual precipitation arrives. Mussel growth was also indirectly related to tree radial growth, though the nature of the relationships varied across the landscape. Negative correlations occurred in forests where tree growth tends to be limited by drought while positive correlations occurred in forests where tree growth tends to be limited by deep or lingering snowpack. Overall, this diverse assemblage of chronologies illustrates the importance of winter precipitation to terrestrial and freshwater ecosystems and suggests that a complexity of climate responses must be considered when estimating the biological impacts of climate variability and change.

Long-term growth-increment chronologies reveal diverse influences of climate forcing on freshwater and forest biota in the Pacific Northwest.

PubMed

Black, Bryan A; Dunham, Jason B; Blundon, Brett W; Brim-Box, Jayne; Tepley, Alan J

2015-02-01

Analyses of how organisms are likely to respond to a changing climate have focused largely on the direct effects of warming temperatures, though changes in other variables may also be important, particularly the amount and timing of precipitation. Here, we develop a network of eight growth-increment width chronologies for freshwater mussel species in the Pacific Northwest, United States and integrate them with tree-ring data to evaluate how terrestrial and aquatic indicators respond to hydroclimatic variability, including river discharge and precipitation. Annual discharge averaged across water years (October 1-September 30) was highly synchronous among river systems and imparted a coherent pattern among mussel chronologies. The leading principal component of the five longest mussel chronologies (1982-2003; PC1(mussel)) accounted for 47% of the dataset variability and negatively correlated with the leading principal component of river discharge (PC1(discharge); r = -0.88; P < 0.0001). PC1(mussel) and PC1(discharge) were closely linked to regional wintertime precipitation patterns across the Pacific Northwest, the season in which the vast majority of annual precipitation arrives. Mussel growth was also indirectly related to tree radial growth, though the nature of the relationships varied across the landscape. Negative correlations occurred in forests where tree growth tends to be limited by drought while positive correlations occurred in forests where tree growth tends to be limited by deep or lingering snowpack. Overall, this diverse assemblage of chronologies illustrates the importance of winter precipitation to terrestrial and freshwater ecosystems and suggests that a complexity of climate responses must be considered when estimating the biological impacts of climate variability and change. © 2014 John Wiley & Sons Ltd.

Weather extremes and the Romans - A marine palynological perspective on Italian temperature and precipitation between 200 BC and 500 AD

NASA Astrophysics Data System (ADS)

Zonneveld, Karin; Clotten, Caroline; Chen, Liang

2015-04-01

Sediments of a tephra-dated marine sediment core located at the distal part of the Po-river discharge plume (southern Italy) have been studied with a three annual resolution. Based on the variability in the dinoflagellate cyst content detailed reconstructions have been established of variability in precipitation related river discharge rates and local air temperature. Furthermore about the variability in distort water quality has been reconstructed. We show that both precipitation and temperature signals vary in tune with cyclic changes in solar insolation. On top of these cyclic changes, short term extremes in temperature and precipitation can be observed that can be interpreted to reflect periods of local weather extremes. Comparison of our reconstructions with historical information suggest that times of high temperatures and maximal precipitation corresponds to the period of maximal expansion of the Roman Empire. We have strong indications that at this time discharge waters might have contained higher nutrient concentrations compared to previous and later time intervals suggesting anthropogenic influence of the water quality. First pilot-results suggest that the decrease in temperature reconstructed just after the "Roman Optimum" corresponds to an increase in numbers of armored conflicts between the Roman and German cultures. Furthermore we observe a resemblance in timing of short-term intervals with cold weather spells during the early so called "Dark-Age-Period" to correspond to epidemic/pandemic events in Europe.

Atmospheric inputs of organic matter to a forested watershed: Variations from storm to storm over the seasons

NASA Astrophysics Data System (ADS)

Iavorivska, Lidiia; Boyer, Elizabeth W.; Miller, Matthew P.; Brown, Michael G.; Vasilopoulos, Terrie; Fuentes, Jose D.; Duffy, Christopher J.

2016-12-01

The objectives of this study were to determine the quantity and chemical composition of precipitation inputs of dissolved organic carbon (DOC) to a forested watershed; and to characterize the associated temporal variability. We sampled most precipitation that occurred from May 2012 through August 2013 at the Susquehanna Shale Hills Critical Zone Observatory (Pennsylvania, USA). Sub-event precipitation samples (159) were collected sequentially during 90 events; covering various types of synoptic meteorological conditions in all climatic seasons. Precipitation DOC concentrations and rates of wet atmospheric DOC deposition were highly variable from storm to storm, ranging from 0.3 to 5.6 mg C L-1 and from 0.5 to 32.8 mg C m-2 h-1, respectively. Seasonally, storms in spring and summer had higher concentrations of DOC and more optically active organic matter than in winter. Higher DOC concentrations resulted from weather types that favor air advection, where cold frontal systems, on average, delivered more than warm/stationary fronts and northeasters. A mixed modeling statistical approach revealed that factors related to storm properties, emission sources, and to the chemical composition of the atmosphere could explain more than 60% of the storm to storm variability in DOC concentrations. This study provided observations on changes in dissolved organic matter that can be useful in modeling of atmospheric oxidative chemistry, exploring relationships between organics and other elements of precipitation chemistry, and in considering temporal changes in ecosystem nutrient balances and microbial activity.

Understanding the impact of ENSO on the variability and sources of moisture for precipitation in mainland southeast Asia during the onset of the Indian summer monsoon.

NASA Astrophysics Data System (ADS)

Li, Y.; Jones, D. B. A.; Dyer, E.; Nusbaumer, J. M.; Noone, D.

2017-12-01

Seasonal variation of precipitation in mainland southeast Asia (SEA) is dominated by the Indian summer monsoon system and the western Pacific winter monsoon system, while the interannual variability of precipitation in this region can be related to remote variability, such as variations in sea surface temperatures in the Pacific Ocean associated with El Niño Southern Oscillation (ENSO) events. Here we use a version of the Community Earth System Model (CESM1.2) with water tagging capability, to examine the impact of ENSO on precipitation in mainland Southeast Asia during the onset of the Indian summer monsoon. In the model, water is tagged as it is evaporated from geographically defined regions and tracked through phase changes in the atmosphere until it is precipitated. The model simulates well the seasonal variability in SEA precipitation as captured by multiple observational data sets, and the variations in precipitation during the monsoon onset is well correlated with the Oceanic Niño Index. We examine the changes in the large-scale atmospheric circulation associated with El Niño and La Niña conditions, and the implication of these changes for moisture transport to SEA. In particular, we quantify the relative ENSO-induced changes in the local and Pacific and Indian Ocean moisture sources for SEA precipitation. We also assess the changes in the moisture source regions over the seasonal cycle to obtain an understanding of the variability in the moisture sources for SEA precipitation from seasonal to interannual time scales.

Intercomparison of model response and internal variability across climate model ensembles

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Ganguly, Auroop R.

2017-10-01

Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

USGS Publications Warehouse

Christensen, L.; Tague, C.L.; Baron, Jill S.

2008-01-01

Transpiration is an important component of soil water storage and stream-flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro-Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R2 = 0.32 and 0.29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200-1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800-2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150-2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600-4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright ?? 2008 John Wiley & Sons, Ltd.

(In)Consistent estimates of changes in relative precipitation in an European domain over the last 350 years

NASA Astrophysics Data System (ADS)

Bothe, Oliver; Wagner, Sebastian; Zorita, Eduardo

2015-04-01

How did regional precipitation change in past centuries? We have potentially three sources of information to answer this question: There are, especially for Europe, a number of long records of local station precipitation; documentary records and natural archives of past environmental variability serve as proxy records for empirical reconstructions; in addition, simulations with coupled climate models or Earth System Models provide estimates on the spatial structure of precipitation variability. However, instrumental records rarely extend back to the 18th century, reconstructions include large uncertainties, and simulation skill is often still unsatisfactory for precipitation. Thus, we can only seek to answer to which extent the three sources provide a consistent picture of past regional precipitation changes. This presentation describes the (lack of) consistency in describing changes of the distributional properties of seasonal precipitation between the different data sources. We concentrate on England and Wales since there are two recent reconstructions and a long observation based record available for this domain. The season of interest is an extended spring (March, April, May, June, July, MAMJJ) over the past 350 years. The main simulated data stem from a regional simulation for the European domain with CCLM driven at its lateral boundaries with conditions provided by a MPI-ESM COSMOS simulation for the last millennium using a high-amplitude solar forcing. A number of simulations for the past 1000 years from the Paleoclimate Modelling Intercomparison Project Phase III provide additional information. We fit a Weibull distribution to the available data sets following the approach for calculating standardized precipitation indices. We do so over 51 year moving windows to assess the consistency of changes in the distributional properties. Changes in the percentiles for severe (and extreme) dry or wet conditions and in the Weibull standard deviations of precipitation estimates are generally not consistent among the different data sets. Only few common signals are evident. Even the relatively strong exogenous forcing history of the late 18th and early 19th century appears to have only small effects on the precipitation distributions. The reconstructions differ systematically from the long instrumental data in displaying much stronger variability compared to the observations over their common period. Distributional properties for both data sets show to some extent opposite evolutions. The reconstructions do not reliably represent the distributions in specific periods but rather reflect low-frequency changes in the mean plus a certain amount of noise. Moreover, also multi-model simulations do not agree on the changes over this period. The lack of consistent simulated relations under purely naturally forced and internal variability on multi-decadal time-scales therefore questions our ability to conclude on dynamical inferences about regional climate variability in the PMIP3 ensemble and, in turn, in climate simulations in general. The potentially opposite evolution of reconstructions and instrumental data for the chosen domain further hampers reconciling available information about past regional precipitation variability in England and Wales. However, we find some possibly surprising but encouraging agreement between the observed data and the regional simulation.

Rainfall pattern variability as climate change impact in The Wallacea Region

NASA Astrophysics Data System (ADS)

Pujiastuti, I.; Nurjani, E.

2018-04-01

The objective of the study is to observe the characteristic variability of rainfall pattern in the city located in every rainfall type, local (Kendari), monsoon (Manado), and equatorial (Palu). The result will be compared to determine which has the most significantly precipitation changing due to climate change impact. Rainfall variability in Indonesia illustrates precipitation variation thus the important variability is the variability of monthly rainfall. Monthly precipitation data for the period of 1961-2010 are collected from Indonesian Agency for Meteorological, Climatological, and Geophysical Agency. This data is calculated with the normal test statistical method to analyze rainfall variability. The result showed the pattern of trend and variability of rainfall in every city with the own characteristic which determines the rainfall type. Moreover, there is comparison of rainfall pattern changing between every rainfall type. This information is useful for climate change mitigation and adaptation strategies especially in water resource management form precipitation as well as the occurrence of meteorological disasters.

Convergence of Dynamic Vegetation Net Productivity Responses to Precipitation Variability from 10 Years of MODIS EVI

USDA-ARS?s Scientific Manuscript database

According to Global Climate Models (GCMs) the occurrence of extreme events of precipitation will be more frequent in the future. Therefore, important challenges arise regarding climate variability, which are mainly related to the understanding of ecosystem responses to changes in precipitation patte...

Response of progressive hillslope deformation to precipitation

Treesearch

Robert R. Ziemer

1984-01-01

Abstract - To document a relationship between progressive hillslope deformation and precipitation, boreholes on the Redwood Creek basin in northern California were surveyed semiannually from 1974 to 1982. Regressions were calculated between borehole displacement and an antecedent precipitation index (API) variable. Values for the API variable were obtained by summing...

Impacts of precipitation and temperature trends on different time scales on the water cycle and water resource availability in mountainous Mediterranean catchments.

NASA Astrophysics Data System (ADS)

José Pérez-Palazón, María; Pimentel, Rafael; Herrero, Javier; José Polo, María

2017-04-01

Climatology trends, precipitation and temperature variations condition the hydrological evolution of the river flow response at basin and sub-basin scales. The link between both climate and flow trends is crucial in mountainous areas, where small variations in temperature can produce significant impacts on precipitation (occurrence as rainfall or snowfall), snowmelt and evaporation, and consequently very different flow signatures. This importance is greater in semiarid regions, where the high variability of the climatic annual and seasonal regimes usually amplifies this impact on river flow. The Sierra Nevada National Park (Southern Spain), with altitudes ranging from 2000 to 3500 m.a.s.l., is part of the global climate change observatories network and a clear example of snow regions in a semiarid environment. This mountain range is head of different catchments, being the Guadalfeo River Basin one of the most influenced by the snow regime. This study shows the observed 55-year (1961-2015) trends of annual precipitation and daily mean temperature, and the associated impacts on snowfall and snow persistence, and the resulting trend of the annual river flow in the Guadalfeo River Basin (Southern Spain), a semiarid abrupt mountainous area (up to 3450 m a.s.l.) facing the Mediterranean Sea where the Alpine and Mediterranean climates coexist in a domain highly influenced by the snow regime, and a significant seasonality in the flow regime. The annual precipitation and annual daily mean temperature experimented a decreasing trend of 2.05 mm/year and an increasing trend of 0.037 °C/year, respectively, during the study period, with a high variability on a decadal basis. However, the torrential precipitation events are more frequent in the last few years of the study period, with an apparently increasing associated dispersion. The estimated annual snowfall trend shows a decreasing trend of 0.24 mm/year, associated to the decrease of precipitation rather than to temperature increase. From the analyses of river flow observations and hydrological modelling, these trends result in an estimated decreasing annual trend of the mean river inflow to reservoirs of 0.091 m3/s, which is equivalent to a mean loss of 2.87 hm3/year during the study period. Nonetheless, these results are associated to a high variability of both extreme values and the annual and decadal values. Moreover, the decrease of the annual inflow is approximately a 25% higher than the loss of precipitation, due to the impact on the different water fluxes from the snowpack associated to the enhanced torrential behaviour of both snowfall/rainfall occurrence and snow persistence. The results show the complexity of hydrological processes in Mediterranean regions, especially under the snow influence, and point out to a significant shift in the precipitation and temperature regime, and thus on the snow-affected hydrological variables in the study area, with a decrease of the available water resource volume in the medium and long term. However, on an annual basis, years with an intense snowfall regime but mild and longer dry periods result in a significant increase of the annual river flow and water storage. Reservoir operation criteria and water allocation should undergo a revision based on hydrological modelling of the snow regions and scenario analysis.

Beyond the NAO: Dynamics and Precipitation Implications of the Azores High Since AD 800

NASA Astrophysics Data System (ADS)

Thatcher, D.; Wanamaker, A. D.; Denniston, R. F.; Asmerom, Y.; Ummenhofer, C.; Polyak, V. J.; Haws, J.; Gillikin, D. P.

2016-12-01

Atmospheric circulation in the North Atlantic region during the last millennium, particularly the state of the North Atlantic Oscillation (NAO), a system closely tied to regional precipitation dynamics, remains the subject of considerable debate in both proxy- and model-based studies. It has been suggested that the winter NAO was in a persistently positive state during the Medieval Climate Anomaly (MCA; AD 850-1250), resulting in increased precipitation across much of northern Europe and decreased rainfall across Iberia. However, besides changes in atmospheric circulation and precipitation dynamics that could be associated with an altered mean state of the NAO, relatively little attention has been given to atmospheric dynamics, namely the intensity and location, of the subtropical high system (Azores High, the southern node of the NAO) in driving hydroclimate in Iberia. Presented here is a continuous, precisely dated, and sub-decadally-resolved stalagmite isotopic and elemental time series from Buraca Gloriosa (BG) cave, western Portugal, situated within the center of the Azores High at the southern node of the NAO, which preserves evidence of regional hydroclimate from approximately AD 800 to the present. Stalagmite oxygen and carbon isotopic values and magnesium/calcium ratios primarily reflect effective moisture and reveal generally dry conditions during the MCA with a rapid shift to wetter conditions during the Little Ice Age (LIA; AD 1250-1850) at this location. Our proxy data reveal that substantial short-term hydroclimate variability characterized the last 1200 years. They support the hypothesis that while an intensified, semi-persistent subtropical high (and likely positive NAO state) characterized much of the MCA, the NAO remained variable over this time period. Climate model results also suggest that the Azores High pressure system both migrated southward and weakened from the MCA into the LIA.

Spatio-temporal variability of several eco-precipitation indicators in China

NASA Astrophysics Data System (ADS)

Guo, B. B.; Zhang, J.; Wang, F.

2016-12-01

Climate change is expected to have large impacts on the eco-hydrological processes. Precipitation as one of the most important meteorological factors is a significant parameter in ecohydrology. Many studies and precipitation indexes focused on the long-term precipitation variability have been put forward. However, these former studies did not consider the vegetation response and these indexes could not reflect it efficiently. Eco-precipitation indicators reflecting the features and patterns of precipitations and serving as significant input parameters of eco-hydrological models are of paramount significance to the studies of these models. Therefore we proposed 4 important eco-precipitation indicators—Precipitation Variability Index (PVI), Precipitation Occurrence Rate (λ), Mean Precipitation Depth (1/θ) and Annual Precipitation (AP). The PVI index depicts the precipitation variability with a value of zero for perfectly uniform and increases as precipitation events become more sporadic. The λ, 1/θ and AP depict the precipitation frequency, intensity and annual amount, respectively. With large precipitation and vegetation discrepancies, China is selected as a study area. Firstly, these indicators are calculated separately with 55-years (1961-2015) daily precipitation time-series from 693 weather stations in China. Then, the temporal trend is analyzed through Mann-Kendall (MK) test and parametric t-test in annual time scale. Furthermore, the spatial distribution is analyzed through the spatial interpolation tools ANUsplin. The result shows that: (1) 1/θ increased significantly (4.59cm/10yr) while λ decreased significantly (1.54 days/10yr), which means there is an increasing trend of extreme precipitation events; (2)there is a significant downward trend of PVI, which means the rhythm of precipitation has a uniform and concentrated trend; (3) AP increased insignificantly (0.57mm/10yr); and (4)the MK test of these indicators shows that there is saltation of λ and 1/θ with a saltation point in the year 1997 and 1992, respectively. This study indicates that uniform and concentrated extreme precipitation significantly increased in China under the climate change, which brings severer challenge in constructing eco-hydrological models to make rational countermeasures.

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.

Estimating historical groundwater levels based on relations with hydrologic and meteorological variables in the U.S. glacial aquifer system

NASA Astrophysics Data System (ADS)

Dudley, R. W.; Hodgkins, G. A.; Nielsen, M. G.; Qi, S. L.

2018-07-01

A number of previous studies have examined relations between groundwater levels and hydrologic and meteorological variables over parts of the glacial aquifer system, but systematic analyses across the entire U.S. glacial aquifer system are lacking. We tested correlations between monthly groundwater levels measured at 1043 wells in the U.S. glacial aquifer system considered to be minimally influenced by human disturbance and selected hydrologic and meteorological variables with the goal of extending historical groundwater records where there were strong correlations. Groundwater levels in the East region correlated most strongly with short-term (1 and 3 month) averages of hydrologic and meteorological variables, while those in the Central and West Central regions yielded stronger correlations with hydrologic and meteorological variables averaged over longer time intervals (6-12 months). Variables strongly correlated with high and low annual groundwater levels were identified as candidate records for use in statistical linear models as a means to fill in and extend historical high and low groundwater levels respectively. Overall, 37.4% of study wells meeting data criteria had successful models for high and (or) low groundwater levels; these wells shared characteristics of relatively higher local precipitation, higher local land-surface slope, lower amounts of clay within the surficial sediments, and higher base-flow index. Streamflow and base flow served as explanatory variables in about two thirds of both high- and low-groundwater-level models in all three regions, and generally yielded more and better models compared to precipitation and Palmer Drought Severity Index. The use of variables such as streamflow with substantially longer and more complete records than those of groundwater wells provide a means for placing contemporary groundwater levels in a longer historical context and can support site-specific analyses such as groundwater modeling.

Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

2016-01-01

An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

Climate Downscaling over Nordeste, Brazil, Using the NCEP RSM97.

NASA Astrophysics Data System (ADS)

Sun, Liqiang; Ferran Moncunill, David; Li, Huilan; Divino Moura, Antonio; de Assis de Souza Filho, Francisco

2005-02-01

The NCEP Regional Spectral Model (RSM), with horizontal resolution of 60 km, was used to downscale the ECHAM4.5 AGCM (T42) simulations forced with observed SSTs over northeast Brazil. An ensemble of 10 runs for the period January-June 1971-2000 was used in this study. The RSM can resolve the spatial patterns of observed seasonal precipitation and capture the interannual variability of observed seasonal precipitation as well. The AGCM bias in displacement of the Atlantic ITCZ is partially corrected in the RSM. The RSM probability distribution function of seasonal precipitation anomalies is in better agreement with observations than that of the driving AGCM. Good potential prediction skills are demonstrated by the RSM in predicting the interannual variability of regional seasonal precipitation. The RSM can also capture the interannual variability of observed precipitation at intraseasonal time scales, such as precipitation intensity distribution and dry spells. A drought index and a flooding index were adopted to indicate the severity of drought and flooding conditions, and their interannual variability was reproduced by the RSM. The overall RSM performance in the downscaled climate of the ECHAM4.5 AGCM is satisfactory over Nordeste. The primary deficiency is a systematic dry bias for precipitation simulation.

Norwegian fjord sediments reveal NAO related winter temperature and precipitation changes of the past 2800 years

NASA Astrophysics Data System (ADS)

Faust, Johan; Fabian, Karl; Giraudeau, Jacques; Knies, Jochen

2016-04-01

The North Atlantic Oscillation (NAO) is the leading mode of atmospheric circulation variability in the North Atlantic region. Associated shifts of storm tracks, precipitation and temperature patterns affect energy supply and demand, fisheries and agricultural, as well as marine and terrestrial ecological dynamics. Long-term NAO reconstructions are crucial to better understand NAO variability in its response to climate forcing factors, and assess predictability and possible shifts associated with ongoing climate change. Fjord deposits have a great potential for providing high-resolution sedimentary records that reflect local terrestrial and marine processes and, therefore, offer unique opportunities for the investigation of sedimentological and geochemical climatically induced processes. A recent study of instrumental time series revealed NAO as main factor for a strong relation between winter temperature, precipitation and river discharge in central Norway over the past 50 years. Here we use the gained knowledge to establish the first high resolution NAO proxy record from marine sediments. By comparing geochemical measurements from a short sediment core with instrumental data we show that marine primary productivity proxies are sensitive to NAO changes. Conditioned on a stationary relation between our climate proxy and the NAO we establish the first high resolution NAO proxy record (NAO-TFJ) from marine sediments covering the past 2,800 years. The NAO-TFJ shows distinct co-variability with climate changes over Greenland, solar activity and Northern Hemisphere glacier dynamics as well as climatically associated paleo-demographic trends.

Heterogeneous Sensitivity of Tropical Precipitation Extremes during Growth and Mature Phases of Atmospheric Warming

NASA Astrophysics Data System (ADS)

Parhi, P.; Giannini, A.; Lall, U.; Gentine, P.

2016-12-01

Assessing and managing risks posed by climate variability and change is challenging in the tropics, from both a socio-economic and a scientific perspective. Most of the vulnerable countries with a limited climate adaptation capability are in the tropics. However, climate projections, particularly of extreme precipitation, are highly uncertain there. The CMIP5 (Coupled Model Inter- comparison Project - Phase 5) inter-model range of extreme precipitation sensitivity to the global temperature under climate change is much larger in the tropics as compared to the extra-tropics. It ranges from nearly 0% to greater than 30% across models (O'Gorman 2012). The uncertainty is also large in historical gauge or satellite based observational records. These large uncertainties in the sensitivity of tropical precipitation extremes highlight the need to better understand how tropical precipitation extremes respond to warming. We hypothesize that one of the factors explaining the large uncertainty is due to differing sensitivities during different phases of warming. We consider the `growth' and `mature' phases of warming under climate variability case- typically associated with an El Niño event. In the remote tropics (away from tropical Pacific Ocean), the response of the precipitation extremes during the two phases can be through different pathways: i) a direct and fast changing radiative forcing in an atmospheric column, acting top-down due to the tropospheric warming, and/or ii) an indirect effect via changes in surface temperatures, acting bottom-up through surface water and energy fluxes. We also speculate that the insights gained here might be useful in interpreting the large sensitivity under climate change scenarios, since the physical mechanisms during the two warming phases under climate variability case, have some correspondence with an increasing and stabilized green house gas emission scenarios.

Contemporary Model Fidelity over the Maritime Continent: Examination of the Diurnal Cycle, Synoptic, Intraseasonal and Seasonal Variability

NASA Astrophysics Data System (ADS)

Baranowski, D.; Waliser, D. E.; Jiang, X.

2016-12-01

One of the key challenges in subseasonal weather forecasting is the fidelity in representing the propagation of the Madden-Julian Oscillation (MJO) across the Maritime Continent (MC). In reality both propagating and non-propagating MJO events are observed, but in numerical forecast the latter group largely dominates. For this study, comprehensive model performances are evaluated using metrics that utilize the mean precipitation pattern and the amplitude and phase of the diurnal cycle, with a particular focus on the linkage between a model's local MC variability and its fidelity in representing propagation of the MJO and equatorial Kelvin waves across the MC. Subseasonal to seasonal variability of mean precipitation and its diurnal cycle in 20 year long climate simulations from over 20 general circulation models (GCMs) is examined to benchmark model performance. Our results show that many models struggle to represent the precipitation pattern over complex Maritime Continent terrain. Many models show negative biases of mean precipitation and amplitude of its diurnal cycle; these biases are often larger over land than over ocean. Furthermore, only a handful of models realistically represent the spatial variability of the phase of the diurnal cycle of precipitation. Models tend to correctly simulate the timing of the diurnal maximum of precipitation over ocean during local solar time morning, but fail to acknowledge influence of the land, with the timing of the maximum of precipitation there occurring, unrealistically, at the same time as over ocean. The day-to-day and seasonal variability of the mean precipitation follows observed patterns, but is often unrealistic for the diurnal cycle amplitude. The intraseasonal variability of the amplitude of the diurnal cycle of precipitation is mainly driven by model's ability (or lack of) to produce eastward propagating MJO-like signal. Our results show that many models tend to decrease apparent air-sea contrast in the mean precipitation and diurnal cycle of precipitation patterns over the Maritime Continent. As a result, the complexity of those patterns is heavily smoothed, to such an extent in some models that the Maritime Continent features and imprint is almost unrecognizable relative to the eastern Indian Ocean or Western Pacific.

Winter North Atlantic Oscillation impact on European precipitation and drought under climate change

NASA Astrophysics Data System (ADS)

Tsanis, I.; Tapoglou, E.

2018-01-01

The North Atlantic Oscillation (NAO) is responsible for the climatic variability in the Northern Hemisphere, in particular, in Europe and is related to extreme events, such as droughts. The purpose of this paper is to study the correlation between precipitation and winter (December-January-February-March (DJFM)) NAO both for the historical period (1951-2000) and two future periods (2001-2050 and 2051-2100). NAO is calculated for these three periods by using sea level pressure, while precipitation data from seven climate models following the representative concentration pathway (RCP) 8.5 are also used in this study. An increasing trend in years with positive DJFM NAO values in the future is defined by this data, along with higher average DJFM NAO values. The correlation between precipitation and DJFM NAO is high, especially in the Northern (high positive) and Southern Europe (high negative). Therefore, higher precipitation in Northern Europe and lower precipitation in Southern Europe are expected in the future. Cross-spectral analysis between precipitation and DJFM NAO time series in three different locations in Europe revealed the best coherence in a dominant cycle between 3 and 4 years. Finally, the maximum drought period in terms of consecutive months with drought is examined in these three locations. The results can be used for strategic planning in a sustainable water resources management plan, since there is a link between drought events and NAO.

High-Resolution Modeling of ENSO-Induced Precipitation in the Tropical Andes: Implications for Proxy Interpretation.

NASA Astrophysics Data System (ADS)

Kiefer, J.; Karamperidou, C.

2017-12-01

Clastic sediment flux into high-elevation Andean lakes is controlled by glacial processes and soil erosion caused by high precipitation events, making these lakes suitable archives of past climate. To wit, sediment records from Laguna Pallcacocha in Ecuador have been interpreted as proxies of ENSO variability, owing to increased precipitation in the greater region during El Niño events. However, the location of the lake's watershed, the presence of glaciers, and the different impacts of ENSO on precipitation in the eastern vs western Andes have challenged the suitability of the Pallcacocha record as an ENSO proxy. Here, we employ WRF, a high-resolution regional mesoscale weather prediction model, to investigate the circulation dynamics, sources of moisture, and resulting precipitation response in the L. Pallcacocha region during different flavors of El Niño and La Niña events, and in the presence or absence of ice caps. In patricular, we investigate Eastern Pacific (EP), Central Pacific (CP), coastal El Niño, and La Niña events. We validate the model simulations against spatially interpolated station measurements and reanalysis data. We find that during EP events, moisture is primarily advected from the Pacific, whereas during CP events, moisture primarily originates from the Atlantic. More moisture is available during EP events, which implies higher precipitation rates. Furthermore, we find that precipitation during EP events is mostly non-convective in contrast to primarily convective precipitation during CP events. Finally, a synthesis of the sedimentary record and the EP:CP ratio of accumulated precipitation and specific humidity in the L. Pallcacocha region allows us to assess whether past changes in the relative frequency of the two ENSO flavors may have been recorded in paleoclimate archives in this region.

Evaluate Hydrologic Response on Spatiotemporal Characteristics of Rainfall Using High Resolution Radar Rainfall Data and WRF-Hydro Model

NASA Astrophysics Data System (ADS)

Gao, S.; Fang, N. Z.

2017-12-01

A previously developed Dynamic Moving Storm (DMS) generator is a multivariate rainfall model simulating the complex nature of precipitation field: spatial variability, temporal variability, and storm movement. Previous effort by the authors has investigated the sensitivity of DMS parameters on corresponding hydrologic responses by using synthetic storms. In this study, the DMS generator has been upgraded to generate more realistic precipitation field. The dependence of hydrologic responses on rainfall features was investigated by dissecting the precipitation field into rain cells and modifying their spatio-temporal specification individually. To retrieve DMS parameters from radar rainfall data, rain cell segmentation and tracking algorithms were respectively developed and applied on high resolution radar rainfall data (1) to spatially determine the rain cells within individual radar image and (2) to temporally analyze their dynamic behavior. Statistics of DMS parameters were established by processing a long record of rainfall data (10 years) to keep the modification on real storms within the limit of regional climatology. Empirical distributions of the DMS parameters were calculated to reveal any preferential pattern and seasonality. Subsequently, the WRF-Hydro model forced by the remodeled and modified precipitation was used for hydrologic simulation. The study area was the Upper Trinity River Basin (UTRB) watershed, Texas; and two kinds of high resolution radar data i.e. the Next-Generation Radar (NEXRAD) level III Digital Hybrid Reflectivity (DHR) product and Multi-Radar Multi-Sensor (MRMS) precipitation rate product, were utilized to establish parameter statistics and to recreate/remodel historical events respectively. The results demonstrated that rainfall duration is a significant linkage between DMS parameters and their hydrologic impacts—any combination of spatiotemporal characteristics that keep rain cells longer over the catchment will produce higher peak discharge.

Compound effects of temperature and precipitation in making droughts more frequent in Marathwada, India

NASA Astrophysics Data System (ADS)

Mondal, A.; Zachariah, M.; Achutarao, K. M.; Otto, F. E. L.

2017-12-01

The Marathwada region in Maharashtra, India is known to suffer significantly from agrarian crisis including farmer suicides resulting from persistent droughts. Drought monitoring in India is commonly based on univariate indicators that consider the deficiency in precipitation alone. However, droughts may involve complex interplay of multiple physical variables, necessitating an integrated, multivariate approach to analyse their behaviour. In this study, we compare the behaviour of drought characteristics in Marathwada in the recent years as compared to the first half of the twentieth century, using a joint precipitation and temperature-based Multivariate Standardized Drought Index (MSDI). Drought events in the recent times are found to exhibit exceptional simultaneous anomalies of high temperature and precipitation deficits in this region, though studies on precipitation alone show that these events are within the range of historically observed variability. Additionally, we also develop multivariate copula-based Severity-Duration-Frequency (SDF) relationships for droughts in this region and compare their natures pre- and post- 1950. Based on multivariate return periods considering both temperature and precipitation anomalies, as well as the severity and duration of droughts, it is found that droughts have become more frequent in the post-1950 period. Based on precipitation alone, such an observation cannot be made. This emphasizes the sensitivity of droughts to temperature and underlines the importance of considering compound effects of temperature and precipitation in order to avoid an underestimation of drought risk. This observation-based analysis is the first step towards investigating the causal mechanisms of droughts, their evolutions and impacts in this region, particularly those influenced by anthropogenic climate change.

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.

Describing rainfall in northern Australia using multiple climate indices

NASA Astrophysics Data System (ADS)

Wilks Rogers, Cassandra Denise; Beringer, Jason

2017-02-01

Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño-Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

Evaluation of a Mesoscale Convective System in Variable-Resolution CESM

NASA Astrophysics Data System (ADS)

Payne, A. E.; Jablonowski, C.

2017-12-01

Warm season precipitation over the Southern Great Plains (SGP) follows a well observed diurnal pattern of variability, peaking at night-time, due to the eastward propagation of mesoscale convection systems that develop over the eastern slopes of the Rockies in the late afternoon. While most climate models are unable to adequately capture the organization of convection and characteristic pattern of precipitation over this region, models with high enough resolution to explicitly resolve convection show improvement. However, high resolution simulations are computationally expensive and, in the case of regional climate models, are subject to boundary conditions. Newly developed variable resolution global climate models strike a balance between the benefits of high-resolution regional climate models and the large-scale dynamics of global climate models and low computational cost. Recently developed parameterizations that are insensitive to the model grid scale provide a way to improve model performance. Here, we present an evaluation of the newly available Cloud Layers Unified by Binormals (CLUBB) parameterization scheme in a suite of variable-resolution CESM simulations with resolutions ranging from 110 km to 7 km within a regionally refined region centered over the SGP Atmospheric Radiation Measurement (ARM) site. Simulations utilize the hindcast approach developed by the Department of Energy's Cloud-Associated Parameterizations Testbed (CAPT) for the assessment of climate models. We limit our evaluation to a single mesoscale convective system that passed over the region on May 24, 2008. The effects of grid-resolution on the timing and intensity of precipitation, as well as, on the transition from shallow to deep convection are assessed against ground-based observations from the SGP ARM site, satellite observations and ERA-Interim reanalysis.

Climate Variability during the TRMM Era: Relationships between TRMM Precipitation and Upper-Tropospheric Hydrometeors

NASA Technical Reports Server (NTRS)

Robertson, Franklin

2008-01-01

Tropical rainfall as seen by the TRMM radar has multiple scales of organization, one prominent example of which is mesoscale deep convection that supports the production of strong, widespread anvil systems important to the planet's water and energy balance. TRMM PR precipitation retrievals (i.e. the 2A25 algorithm) are reliable down to rates below 1.0 mm/h which captures the majority of near-surface rainfall. However, much of the precipitating hydrometeor mass above the freezing level in these anvil systems may be associated with particles where TRMM PR s/n is low. In out analysis we are examining the question of 'What portions of the total hydrometeor spectrum can we see individually with TRMM, CloudSat, high frequency passive microwave (e.g. AMSU-B, MHS) and MODIS'. This will allow us to pursue fundamental issues of precipitation, efficiency, maintenance of upper-troposheric humidity, and cloud forcing variability in the tropical climate system. We do this by generating frequency distributions of ice water content (IWC), integrated IWC (IWP), and precipitation as appropriate for these sensors and relate these to TRMM near-surface rainfall. Joint frequency distributions are developed from more limited coincidence between TRMM and these sensors. We interpret these results in terms of a climate regime descriptor and as an index of precipitation efficiency for tropical rain systems.

The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter

USGS Publications Warehouse

Hoell, Andrew; Funk, Christopher C.; Mathew Barlow,

2015-01-01

Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving how we simulate climate extremes as we enter a warmer (and often drier) world in the coming centuries; if climate models underestimate low-frequency variability, we will underestimate the risk of future abrupt change and extreme events, such as megadroughts.

Validation of High Resolution IMERG Satellite Precipitation over the Global Oceans using OceanRAIN

NASA Astrophysics Data System (ADS)

Kucera, Paul; Klepp, Christian

2017-04-01

Precipitation is a key parameter of the essential climate variables in the Earth System that is a key variable in the global water cycle. Observations of precipitation over oceans is relatively sparse. Satellite observations over oceans is the only viable means of measuring the spatially distribution of precipitation. In an effort to improve global precipitation observations, the research community has developed a state of the art precipitation dataset as part of the NASA/JAXA Global Precipitation Measurement (GPM) program. The satellite gridded product that has been developed is called Integrated Multi-satelliE Retrievals for GPM (IMERG), which has a maximum spatial resolution of 0.1° x 0.1° and temporal 30 minute. Even with the advancements in retrievals, there is a need to quantify uncertainty of IMERG especially over oceans. To address this need, the OceanRAIN dataset has been used to create a comprehensive database to compare IMERG products. The OceanRAIN dataset was collected using an ODM-470 optical disdrometer that has been deployed on 12 research vessels worldwide with 6 long-term installations operating in all climatic regions, seasons and ocean basins. More than 5.5 million data samples have been collected on the OceanRAIN program. These data were matched to IMERG grids for the study period of 15 March 2014-31 January 2016. This evaluation produced over a 1000 matched pairs with precipitation observed at the surface. These matched pairs were used to evaluate the performance of IMERG for different latitudinal bands and precipitation regimes. The presentation will provide an overview of the study and summary of evaluation results.

The sensitivity of WRF daily summertime simulations over West Africa to alternative parameterizations. Part 2: Precipitation.

PubMed

Noble, Erik; Druyan, Leonard M; Fulakeza, Matthew

2016-01-01

This paper evaluates the performance of the Weather and Research Forecasting (WRF) model as a regional-atmospheric model over West Africa. It tests WRF sensitivity to 64 configurations of alternative parameterizations in a series of 104 twelve-day September simulations during eleven consecutive years, 2000-2010. The 64 configurations combine WRF parameterizations of cumulus convection, radiation, surface-hydrology, and PBL. Simulated daily and total precipitation results are validated against Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) data. Particular attention is given to westward-propagating precipitation maxima associated with African Easterly Waves (AEWs). A wide range of daily precipitation validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve time-longitude correlations (against GPCP) of between 0.35-0.42 and spatiotemporal variability amplitudes only slightly higher than observed estimates. A parallel simulation by the benchmark Regional Model-v.3 achieves a higher correlation (0.52) and realistic spatiotemporal variability amplitudes. The largest favorable impact on WRF precipitation validation is achieved by selecting the Grell-Devenyi convection scheme, resulting in higher correlations against observations than using the Kain-Fritch convection scheme. Other parameterizations have less obvious impact. Validation statistics for optimized WRF configurations simulating the parallel period during 2000-2010 are more favorable for 2005, 2006, and 2008 than for other years. The selection of some of the same WRF configurations as high scorers in both circulation and precipitation validations supports the notion that simulations of West African daily precipitation benefit from skillful simulations of associated AEW vorticity centers and that simulations of AEWs would benefit from skillful simulations of convective precipitation.

The sensitivity of WRF daily summertime simulations over West Africa to alternative parameterizations. Part 2: Precipitation

PubMed Central

Noble, Erik; Druyan, Leonard M.; Fulakeza, Matthew

2018-01-01

This paper evaluates the performance of the Weather and Research Forecasting (WRF) model as a regional-atmospheric model over West Africa. It tests WRF sensitivity to 64 configurations of alternative parameterizations in a series of 104 twelve-day September simulations during eleven consecutive years, 2000–2010. The 64 configurations combine WRF parameterizations of cumulus convection, radiation, surface-hydrology, and PBL. Simulated daily and total precipitation results are validated against Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) data. Particular attention is given to westward-propagating precipitation maxima associated with African Easterly Waves (AEWs). A wide range of daily precipitation validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve time-longitude correlations (against GPCP) of between 0.35–0.42 and spatiotemporal variability amplitudes only slightly higher than observed estimates. A parallel simulation by the benchmark Regional Model-v.3 achieves a higher correlation (0.52) and realistic spatiotemporal variability amplitudes. The largest favorable impact on WRF precipitation validation is achieved by selecting the Grell-Devenyi convection scheme, resulting in higher correlations against observations than using the Kain-Fritch convection scheme. Other parameterizations have less obvious impact. Validation statistics for optimized WRF configurations simulating the parallel period during 2000–2010 are more favorable for 2005, 2006, and 2008 than for other years. The selection of some of the same WRF configurations as high scorers in both circulation and precipitation validations supports the notion that simulations of West African daily precipitation benefit from skillful simulations of associated AEW vorticity centers and that simulations of AEWs would benefit from skillful simulations of convective precipitation. PMID:29563651

Global Precipitation Patterns Associated with ENSO and Tropical Circulations

NASA Technical Reports Server (NTRS)

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

1999-01-01

Tropical precipitation and the accompanying latent heat release is the engine that drives the global circulation. An increase or decrease in rainfall in the tropics not only leads to the local effects of flooding or drought, but contributes to changes in the large scale circulation and global climate system. Rainfall in the tropics is highly variable, both seasonally (monsoons) and interannually (ENSO). Two experimental observational data sets, developed under the auspices of the Global Precipitation Climatology Project (GPCP), are used in this study to examine the relationships between global precipitation and ENSO and extreme monsoon events over the past 20 years. The V2x79 monthly product is a globally complete, 2.5 deg x 2.5 deg, satellite-gauge merged data set that covers the period 1979 to the present. Indices based on patterns of satellite-derived rainfall anomalies in the Pacific are used to analyze the teleconnections between ENSO and global precipitation, with emphasis on the monsoon systems. It has been well documented that dry (wet) Asian monsoons accompany warm (cold) ENSO events. However, during the summer seasons of the 1997/98 ENSO the precipitation anomalies were mostly positive over India and the Bay of Bengal, which may be related to an epoch-scale variability in the Asian monsoon circulation. The North American monsoon may be less well linked to ENSO, but a positive precipitation anomaly was observed over Mexico around the September following the 1997/98 event. For the twenty-year record, precipitation and SST patterns in the tropics are analyzed during wet and dry monsoons. For the Asian summer monsoon, positive rainfall anomalies accompany two distinct patterns of tropical precipitation and a warm Indian Ocean. Negative anomalies coincide with a wet Maritime Continent.

Geographically weighted regression based methods for merging satellite and gauge precipitation

NASA Astrophysics Data System (ADS)

Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

2018-03-01

Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

Relative Contribution of Monsoon Precipitation and Pumping to Changes in Groundwater Storage in India

NASA Technical Reports Server (NTRS)

Asoka, Akarsh; Gleeson, Tom; Wada, Yoshihide; Mishra, Vimal

2017-01-01

The depletion of groundwater resources threatens food and water security in India. However, the relative influence of groundwater pumping and climate variability on groundwater availability and storage remains unclear. Here we show from analyses of satellite and local well data spanning the past decade that long-term changes in monsoon precipitation are driving groundwater storage variability in most parts of India either directly by changing recharge or indirectly by changing abstraction. We find that groundwater storage has declined in northern India at the rate of 2 cm/yr and increased by 1 to 2 cm/yr in southern India between 2002 and 2013. We find that a large fraction of the total variability in groundwater storage in north-central and southern India can be explained by changes in precipitation. Groundwater storage variability in northwestern India can be explained predominantly by variability in abstraction for irrigation, which is in turn influenced by changes in precipitation. Declining precipitation in northern India is linked to Indian Ocean warming, suggesting a previously unrecognized teleconnection between ocean temperatures and groundwater storage.

Classification and Space-Time Analysis of Precipitation Events in Manizales, Caldas, Colombia.

NASA Astrophysics Data System (ADS)

Suarez Hincapie, J. N.; Vélez, J.; Romo Melo, L.; Chang, P.

2015-12-01

Manizales is a mid-mountain Andean city located near the Nevado del Ruiz volcano in west-central Colombia, this location exposes it to earthquakes, floods, landslides and volcanic eruptions. It is located in the intertropical convergence zone (ITCZ) and presents a climate with a bimodal rainfall regime (Cortés, 2010). Its mean annual rainfall is 2000 mm, one may observe precipitation 70% of the days over a year. This rain which favors the formation of large masses of clouds and the presence of macroclimatic phenomenon as "El Niño South Oscillation", has historically caused great impacts in the region (Vélez et al, 2012). For example the geographical location coupled with rain events results in a high risk of landslides in the city. Manizales has a hydrometeorological network of 40 stations that measure and transmit data of up to eight climate variables. Some of these stations keep 10 years of historical data. However, until now this information has not been used for space-time classification of precipitation events, nor has the meteorological variables that influence them been thoroughly researched. The purpose of this study was to classify historical events of rain in an urban area of Manizales and investigate patterns of atmospheric behavior that influence or trigger such events. Classification of events was performed by calculating the "n" index of the heavy rainfall, describing the behavior of precipitation as a function of time throughout the event (Monjo, 2009). The analysis of meteorological variables was performed using statistical quantification over variable time periods before each event. The proposed classification allowed for an analysis of the evolution of rainfall events. Specially, it helped to look for the influence of different meteorological variables triggering rainfall events in hazardous areas as the city of Manizales.

50 years of change at 14 headwater snowmelt-dominated watersheds in Wyoming

NASA Astrophysics Data System (ADS)

Voutchkova, D. D.; Miller, S. N.

2017-12-01

Wyoming is a headwater state contributing to the water resources of four major US basins: Columbia River, Colorado River, Great Basin, and Missouri River. Most of the annual precipitation in this semi-arid state is received at high elevations as snow. Water availability for drinking water supply, reservoir storage, industrial, agricultural, and ecological needs - all depends on the variable and potentially changing annual snowmelt. Thus, characterizing snowmelt and snowmelt-dominated runoff variability and change at high-elevation headwater watersheds in Wyoming is of utmost importance. Next to quantifying variability and changes in total precipitation, snow-water equivalent (SWE), annual runoff and low flows at 14 selected and representative high-elevation watersheds during the previous 50 years, we also explore past watershed disturbances. Wildfires, forest management (e.g. timber harvest), and recent bark beetle outbakes have altered the vegetation and potentially the hydrology of these high-elevation watersheds. We present a synthesis and trend analysis of 49-75 complete water years (wy) of daily streamflow data for 14 high-elevation watersheds, 25-36 complete wy of daily SWE and precipitation data for the closest SNOTEL stations, and spatiotemporal data on burned areas for 20 wy, tree mortality for 18 wy, timber harvest during the 20th century, as well as overview on legacy tie-drive related distrbances. These results are discussed with respect to the differing watershed characteristics in order to present a spectrum of possible hydrologic responses. The importance of our work lies in extending our understanding of snowmelt headwater annual runoff and low-flow dynamics in Wyoming specifically. Such regional synthesis would inform and facilitate water managers and planners both at local state-wide level, but also in the intermountain US West.

Multi-Decadal to Millennial Scale Holocene Hydrologic Variation in the Southern Hemisphere Tropics of South America

NASA Astrophysics Data System (ADS)

Ekdahl, E. J.; Fritz, S. C.; Baker, P. A.; Burns, S. J.; Coley, K.; Rigsby, C. A.

2005-12-01

Numerous sites in the Northern Hemisphere show multi-decadal to millennial scale climate variation during the Holocene, many of which have been correlated with changes in atmospheric radiocarbon production or with changes in North Atlantic oceanic circulation. The manifestation of such climate variability in the hydrology of the Southern Hemisphere tropics of South America is unclear, because of the limited number of records at suitably high resolution. In the Lake Titicaca drainage basin of Bolivia and Peru, high-resolution lacustrine records reveal the overall pattern of Holocene lake-level change, the influence of precessional forcing of the South American Summer Monsoon, and the effects of high-frequency climate variability in records of lake productivity and lake ecology. Precessional forcing of regional precipitation is evident in the Lake Titicaca basin as a massive (ca. 85 m) mid-Holocene decline in lake level beginning about 7800 cal yr BP and a subsequent rise in lake level after 4000 cal yr BP. Here we show that multi-decadal to millennial-scale climate variability, superimposed upon the envelope of change at orbital time scales, is similar in timing and pattern to the ice-rafted debris record of Holocene Bond events in the North Atlantic. A high-resolution carbon isotopic record from Lake Titicaca that spans the entire Holocene suggests that cold intervals of Holocene Bond events are periods of increased precipitation, thus indicating an anti-phasing of precipitation variation on the Altiplano relative to the Northern Hemisphere tropics. A similar pattern of variation is also evident in high-resolution (2-30 yr spacing) diatom and geochemical records that span the last 7000 yr from two smaller lakes, Lagos Umayo and Lagunillas, in the Lake Titicaca drainage basin.

Using Empirical Orthogonal Teleconnections to Analyze Interannual Precipitation Variability in China

NASA Astrophysics Data System (ADS)

Stephan, C.; Klingaman, N. P.; Vidale, P. L.; Turner, A. G.; Demory, M. E.; Guo, L.

2017-12-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. A consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. It produces known teleconnections, that include high positive correlations with ENSO in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that variability along the southeast coast in winter, in the Yangtze valley in spring, and in eastern China in autumn, are associated with extratropical Rossby wave trains. The same analysis is applied to six climate simulations of the Met Office Unified Model with and without air-sea coupling and at various horizontal resolutions of 40, 90 and 200 km. All simulations reproduce the observed patterns of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are all patterns associated with the observed physical mechanism. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. Finer resolution does not improve the fidelity of these patterns or their associated mechanisms. Evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient; attention must be paid to associated mechanisms.

Calibration and validation of CSM-CROPGRO-cotton model using lysimeter data in the Texas High Plains

USDA-ARS?s Scientific Manuscript database

The Texas High Plains (THP) is one of the most important food and fiber producing regions in the Ogallala Aquifer Region, currently facing rapid decline of groundwater levels. Predicated climate extremes and high temporal variability in growing season precipitation in the future may demand growers t...

Lake oxygen isotopes as recorders of North American Rocky Mountain hydroclimate: Holocene patterns and variability at multi-decadal to millennial time scales

USGS Publications Warehouse

Anderson, Lesleigh; Max Berkelhammer,; Barron, John A.; Steinman, Byron A.; Finney, Bruce P.; Abbott, Mark B.

2016-01-01

Lake sediment oxygen isotope records (calcium carbonate-δ18O) in the western North American Cordillera developed during the past decade provide substantial evidence of Pacific ocean–atmosphere forcing of hydroclimatic variability during the Holocene. Here we present an overview of 18 lake sediment δ18O records along with a new compilation of lake water δ18O and δ2H that are used to characterize lake sediment sensitivity to precipitation-δ18O in contrast to fractionation by evaporation. Of the 18 records, 14 have substantial sensitivity to evaporation. Two records reflect precipitation-δ18O since the middle Holocene, Jellybean and Bison Lakes, and are geographically positioned in the northern and southern regions of the study area. Their comparative analysis indicates a sequence of time-varying north–south precipitation-δ18O patterns that is evidence for a highly non-stationary influence by Pacific ocean–atmosphere processes on the hydroclimate of western North America. These observations are discussed within the context of previous research on North Pacific precipitation-δ18O based on empirical and modeling methods. The Jellybean and Bison Lake records indicate that a prominent precipitation-δ18O dipole (enriched-north and depleted-south) was sustained between ~ 3.5 and 1.5 ka, which contrasts with earlier Holocene patterns, and appears to indicate the onset of a dominant tropical control on North Pacific ocean–atmosphere dynamics. This remains the state of the system today. Higher frequency reversals of the north–south precipitation-δ18O dipole between ~ 2.5 and 1.5 ka, and during the Medieval Climate Anomaly and the Little Ice Age, also suggest more varieties of Pacific ocean–atmosphere modes than a single Pacific Decadal Oscillation (PDO) type analogue. Results indicate that further investigation of precipitation-δ18O patterns on short (observational) and long (Holocene) time scales is needed to improve our understanding of the processes that drive regional precipitation-δ18O responses to Pacific ocean–atmosphere variability, which in turn, will lead to a better understanding of internal Pacific ocean–atmosphere variability and its response to external climate forcing mechanisms.

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Climatic and physiographic controls of spatial variability in surface water balance over the contiguous United States using the Budyko relationship

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Ficklin, Darren L.

2017-09-01

The geographic variability in the partitioning of precipitation into surface runoff (Q) and evapotranspiration (ET) is fundamental to understanding regional water availability. The Budyko equation suggests this partitioning is strictly a function of aridity, yet observed deviations from this relationship for individual watersheds impede using the framework to model surface water balance in ungauged catchments and under future climate and land use scenarios. A set of climatic, physiographic, and vegetation metrics were used to model the spatial variability in the partitioning of precipitation for 211 watersheds across the contiguous United States (CONUS) within Budyko's framework through the free parameter ω. A generalized additive model found that four widely available variables, precipitation seasonality, the ratio of soil water holding capacity to precipitation, topographic slope, and the fraction of precipitation falling as snow, explained 81.2% of the variability in ω. The ω model applied to the Budyko equation explained 97% of the spatial variability in long-term Q for an independent set of watersheds. The ω model was also applied to estimate the long-term water balance across the CONUS for both contemporary and mid-21st century conditions. The modeled partitioning of observed precipitation to Q and ET compared favorably across the CONUS with estimates from more sophisticated land-surface modeling efforts. For mid-21st century conditions, the model simulated an increase in the fraction of precipitation used by ET across the CONUS with declines in Q for much of the eastern CONUS and mountainous watersheds across the western United States.

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

The El Nino-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with Coupled General Circulation Models (CGCMs) to investigate how regional precipitation in the 21st century may be affected by changes in both ENSO-driven precipitation variability and slowly-evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of 20th century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in 21st century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with 20th century observations and more stationary during the 21st century. Finally, the model-predicted 21st century rainfall response to cENSO is decomposed into the sum of three terms: 1) the 21st century change in the mean state of precipitation; 2) the historical precipitation response to the cENSO pattern; and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

CMIP5 model simulations of Ethiopian Kiremt-season precipitation: current climate and future changes

NASA Astrophysics Data System (ADS)

Li, Laifang; Li, Wenhong; Ballard, Tristan; Sun, Ge; Jeuland, Marc

2016-05-01

Kiremt-season (June-September) precipitation provides a significant water supply for Ethiopia, particularly in the central and northern regions. The response of Kiremt-season precipitation to climate change is thus of great concern to water resource managers. However, the complex processes that control Kiremt-season precipitation challenge the capability of general circulation models (GCMs) to accurately simulate precipitation amount and variability. This in turn raises questions about their utility for predicting future changes. This study assesses the impact of climate change on Kiremt-season precipitation using state-of-the-art GCMs participating in the Coupled Model Intercomparison Project Phase 5. Compared to models with a coarse resolution, high-resolution models (horizontal resolution <2°) can more accurately simulate precipitation, most likely due to their ability to capture precipitation induced by topography. Under the Representative Concentration Pathway (RCP) 4.5 scenario, these high-resolution models project an increase in precipitation over central Highlands and northern Great Rift Valley in Ethiopia, but a decrease in precipitation over the southern part of the country. Such a dipole pattern is attributable to the intensification of the North Atlantic subtropical high (NASH) in a warmer climate, which influences Ethiopian Kiremt-season precipitation mainly by modulating atmospheric vertical motion. Diagnosis of the omega equation demonstrates that an intensified NASH increases (decreases) the advection of warm air and positive vorticity into the central Highlands and northern Great Rift Valley (southern part of the country), enhancing upward motion over the northern Rift Valley but decreasing elsewhere. Under the RCP 4.5 scenario, the high-resolution models project an intensification of the NASH by 15 (3 × 105 m2 s-2) geopotential meters (stream function) at the 850-hPa level, contributing to the projected precipitation change over Ethiopia. The influence of the NASH on Kiremt-season precipitation becomes more evident in the future due to the offsetting effects of two other major circulation systems: the East African Low-level Jet (EALLJ) and the Tropical Easterly Jet (TEJ). The high-resolution models project a strengthening of the EALLJ, but a weakening of the TEJ. Future changes in the EALLJ and TEJ will drive this precipitation system in opposite directions, leading to small or no net changes in precipitation in Ethiopia.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

Konapala, Goutam; Mishra, Ashok; Leung, L. Ruby

This study investigated the anthropogenic influence on the temporal variability of annual precipitation for the period 1950-2005 as simulated by the CMIP5 models. The temporal variability of both annual precipitation amount (PRCPTOT) and intensity (SDII) was first measured using a metric of statistical dispersion called the Gini coefficient. Comparing simulations driven by both anthropogenic and natural forcings (ALL) with simulations of natural forcings only (NAT), we quantified the anthropogenic contributions to the changes in temporal variability at global, continental and sub-continental scales as a relative difference of the respective Gini coefficients of ALL and NAT. Over the period of 1950-2005,more » our results indicate that anthropogenic forcings have resulted in decreased uniformity (i.e., increase in unevenness or disparity) in annual precipitation amount and intensity at global as well as continental scales. In addition, out of the 21 sub-continental regions considered, 14 (PRCPTOT) and 17 (SDII) regions showed significant anthropogenic influences. The human impacts are generally larger for SDII compared to PRCTOT, indicating that the temporal variability of precipitation intensity is generally more susceptible to anthropogenic influence than precipitation amount. Lastly, the results highlight that anthropogenic activities have changed not only the trends but also the temporal variability of annual precipitation, which underscores the need to develop effective adaptation management practices to address the increased disparity.« less

Global precipitation measurement (GPM)

NASA Astrophysics Data System (ADS)

Neeck, Steven P.; Flaming, Gilbert M.; Adams, W. James; Smith, Eric A.

2001-12-01

The National Aeronautics and Space Administration (NASA) is studying options for future space-based missions for the EOS Follow-on Era (post 2003), building upon the measurements made by Pre-EOS and EOS First Series Missions. One mission under consideration is the Global Precipitation Measurement (GPM), a cooperative venture of NASA, Japan, and other international partners. GPM will capitalize on the experience of the highly successful Tropical Rainfall Measurement Mission (TRMM). Its goal is to extend the measurement of rainfall to high latitudes with high temporal frequency, providing a global data set every three hours. A reference concept has been developed consisting of an improved TRMM-like primary satellite with precipitation radar and microwave radiometer to make detailed and accurate estimates of the precipitation structure and a constellation of small satellites flying compact microwave radiometers to provide the required temporal sampling of highly variable precipitation systems. Considering that DMSP spacecraft equipped with SSMIS microwave radiometers, successor NPOESS spacecraft equipped with CMIS microwave radiometers, and other relevant international systems are expected to be in operation during the timeframe of the reference concept, the total number of small satellites required to complete the constellation will be reduced. A nominal plan is to begin implementation in FY'03 with launches in 2007. NASA is presently engaged in advanced mission studies and advanced instrument technology development related to the mission.

Increased Spatial Variability and Intensification of Extreme Monsoon Rainfall due to Urbanization.

PubMed

Paul, Supantha; Ghosh, Subimal; Mathew, Micky; Devanand, Anjana; Karmakar, Subhankar; Niyogi, Dev

2018-03-02

While satellite data provides a strong robust signature of urban feedback on extreme precipitation; urbanization signal is often not so prominent with station level data. To investigate this, we select the case study of Mumbai, India and perform a high resolution (1 km) numerical study with Weather Research and Forecasting (WRF) model for eight extreme rainfall days during 2014-2015. The WRF model is coupled with two different urban schemes, the Single Layer Urban Canopy Model (WRF-SUCM), Multi-Layer Urban Canopy Model (WRF-MUCM). The differences between the WRF-MUCM and WRF-SUCM indicate the importance of the structure and characteristics of urban canopy on modifications in precipitation. The WRF-MUCM simulations resemble the observed distributed rainfall. WRF-MUCM also produces intensified rainfall as compared to the WRF-SUCM and WRF-NoUCM (without UCM). The intensification in rainfall is however prominent at few pockets of urban regions, that is seen in increased spatial variability. We find that the correlation of precipitation across stations within the city falls below statistical significance at a distance greater than 10 km. Urban signature on extreme precipitation will be reflected on station rainfall only when the stations are located inside the urban pockets having intensified precipitation, which needs to be considered in future analysis.

Precipitation event tracking reveals that precipitation characteristics respond differently under seasonal, interannual, and anthropogenic forcing

NASA Astrophysics Data System (ADS)

Chen, C.; Chang, W.; Kong, W.; Wang, J.; Kotamarthi, V. R.; Stein, M.; Moyer, E. J.

2017-12-01

Change in precipitation characteristics is an especially concerning potential impact of climate change, and both model and observational studies suggest that increases in precipitation intensity are likely. However, studies to date have focused on mean accumulated precipitation rather than on the characteristics of individual events. We report here on a study using a novel rainstorm identification tracking algorithm (Chang et al. 2016) that allows evaluating changes in spatio-temporal characteristics of events. We analyze high-resolution precipitation from dynamically downscaled regional climate simulations over the continental U.S. (WRF driven by CCSM4) of present and future climate conditions. We show that precipitation events show distinct characteristic changes for natural seasonal and interannual variations and for anthropogenic greenhouse-gas forcing. In all cases, wetter seasons/years/future climate states are associated with increased precipitation intensity, but other precipitation characteristics respond differently to the different drivers. For example, under anthropogenic forcing, future wetter climate states involve smaller individual event sizes (partially offsetting their increased intensity). Under natural variability, however, wetter years involve larger mean event sizes. Event identification and tracking algorithms thus allow distinguishing drivers of different types of precipitation changes, and in relating those changes to large-scale processes.

Extreme precipitation variability, forage quality and large herbivore diet selection in arid environments

USGS Publications Warehouse

Cain, James W.; Gedir, Jay V.; Marshal, Jason P.; Krausman, Paul R.; Allen, Jamison D.; Duff, Glenn C.; Jansen, Brian; Morgart, John R.

2017-01-01

Nutritional ecology forms the interface between environmental variability and large herbivore behaviour, life history characteristics, and population dynamics. Forage conditions in arid and semi-arid regions are driven by unpredictable spatial and temporal patterns in rainfall. Diet selection by herbivores should be directed towards overcoming the most pressing nutritional limitation (i.e. energy, protein [nitrogen, N], moisture) within the constraints imposed by temporal and spatial variability in forage conditions. We investigated the influence of precipitation-induced shifts in forage nutritional quality and subsequent large herbivore responses across widely varying precipitation conditions in an arid environment. Specifically, we assessed seasonal changes in diet breadth and forage selection of adult female desert bighorn sheep Ovis canadensis mexicana in relation to potential nutritional limitations in forage N, moisture and energy content (as proxied by dry matter digestibility, DMD). Succulents were consistently high in moisture but low in N and grasses were low in N and moisture until the wet period. Nitrogen and moisture content of shrubs and forbs varied among seasons and climatic periods, whereas trees had consistently high N and moderate moisture levels. Shrubs, trees and succulents composed most of the seasonal sheep diets but had little variation in DMD. Across all seasons during drought and during summer with average precipitation, forages selected by sheep were higher in N and moisture than that of available forage. Differences in DMD between sheep diets and available forage were minor. Diet breadth was lowest during drought and increased with precipitation, reflecting a reliance on few key forage species during drought. Overall, forage selection was more strongly associated with N and moisture content than energy content. Our study demonstrates that unlike north-temperate ungulates which are generally reported to be energy-limited, N and moisture may be more nutritionally limiting for desert ungulates than digestible energy.

Tree Ring Analyses Unlock a Century of Hydroclimatic Variability Across the Himalayas

NASA Astrophysics Data System (ADS)

Brunello, C. F.; Andermann, C.; Helle, G.; Comiti, F.; Tonon, G.; Hovius, N.

2017-12-01

Climate change has altered precipitation patterns and impacted the spatio-temporal distribution and availability of water in high mountain environments. For example, intensification of the Indian Summer Monsoon (ISM) increases the potential for moisture laden air to breach the Himalayan orographic barrier and penetrate into the arid, elevated southern Tibetan Plateau, with geomorphological and hydrological consequences. Such trends should be considered against a solid background, but a consistent record of centennial monsoon dynamics in the trans-Himalayan region has never been developed. Instrumental data are sparse and only cover a limited time period as well as remotely sensed information. Meanwhile, models have major systematic bias and substantial uncertainty in reproducing ISM interannual variability. In this context, hydro-climatic proxies, such as oxygen stable isotope ratios in cellulose of tree rings, are a valuable source of data, especially because isotope mass spectroscopy can unlock yearly resolved information by tracing the isotopic signature (18O) stored within each growth ring. Here we present three centennial records of monsoon dynamics, along a latitudinal transect, spanning a pronounced precipitation gradient across the Himalayan orogen. Three sites were selected along the Kali Gandaki valley in the central Himalayas (Nepal), this valley connects the wet, monsoon dominated Gangetic plain with the arid Tibetan Plateau. Our transect covers the sensitive northern end of the precipitation gradient, located in the upper part of the catchment. Our results show that inter-annual variation of monsoon strength can be reconstructed by tree ring δ18O. The inferred monsoon dynamics are compared against independent constraints on precipitation, snow cover and river discharge. Different water sources contribute disproportionally at the three sites, reflecting spatial and temporal shifts of the westerlies and the Indian summer monsoon. These two dominant sources of humidity are complemented by recycled continental circulation characterizing pre-monsoon rainfall. Our yearly resolved records of monsoon strength provide insights into anomalous hydro-climatic years and highlight the importance of precipitation variability for the hydrological processes in high mountain regions.

Hydroclimatic Controls on Agroecosystem Resiliency in the Northern High Plains

NASA Astrophysics Data System (ADS)

Munoz-Arriola, F.; Amaranto, A.; Solomatine, D.; Corzo, G.

2016-12-01

Water-controlled ecosystems play a critical role in sustaining intensive food production. More frequent and intense droughts and extreme precipitation challenge genetic progresses to increase crop yields. This work aims to identify the agroecosystem's resiliency to droughts and extreme precipitation in the Northern High Plains (NHP). NHP is characterized by its extensive use of groundwater to fulfill crop irrigation requirements. Groundwater "subsidizes" water deficits and supports intensification of crop production. However, it is unclear how sensitive are agroecosystems to hydroclimatological variations at large-scale, which may affect water discharge and recharge at basin scale and crop production at field scale. Our objective is to develop diagnostic and prognostic conceptual models for groundwater withdrawals in response to climate variability and consumptive use of water. The present study is located in the irrigated agricultural areas of the NHP. We use observed changes in the water table as tracers to changes natural forcing (i.e. observed precipitation) and anthropogenic water demands (i.e. simulated evapotranspiration) though the development of two different diagnostic/prognostic models using Artificial Neural Network (ANN) and Support Vector Machine (SVM). Water-table data was obtained from the Nebraska Geological Survey, and gridded daily hydroclimatic data from Livneh et al (2015), which together with MODIS-LAI provided the inputs for a Variable Infiltration Capacity model to simulate evapotranspiration at a 1/16th degree resolution. A regionalization procedure based on K-Clustering was applied to precipitation data (1950-2013) to identify areas of common and natural variability. Inconsistent output and input sampling frequencies used a time adaptation algorithm to assist the training of the ANN and SVM models. Results showed that both the ANN and the SVM diagnose and predicted ground water. Selected dry and wet (identified Extreme-Precipitation-Event) years are evaluated to isolate hydroclimate and water management drivers and resilient agroecosystems. This methodology will contribute to identify areas of physical vulnerability and agroecosystem resiliency.

Reconstructing climate variability using tree rings and glacier fluctuations in the southern Chilean Andes

NASA Astrophysics Data System (ADS)

Aravena, Juan-Carlos

This thesis investigates climate variability in southern South America (south of 40°S) during the last 400 years using instrumental data, tree rings and glacier fluctuations. The dominant spatial and temporal patterns of a network of 25 homogeneous instrumental rainfall records were analyzed and used to define four regional precipitation series (1950-2000): northwestern Patagonia, central Patagonia, Patagonian plains-Atlantic, and southern Patagonia. Time series analysis of these regional patterns shows marked decadal variability for northwestern and central Patagonia, 3-7 year oscillations for Patagonian plains-Atlantic region, and a strong biannual oscillatory mode for southern Patagonia. Regional rainfall appears to be strongly influenced by Antarctic circulation modes (Antarctic Oscillation Index) while the ENSO influence on rainfall variability is less evident. Highly significant correlation of precipitation on the west coast of Patagonia with the pressure gradient between the subtropical eastern Pacific and the high-latitude south eastern Pacific is confirmed. A new network of 18 tree-ring chronologies from Pilgerodendron uviferum, an endemic conifer, was developed from sites along the western flank of the southern Andes. Highly significant series inter-correlation values ranged between 0.44 and 0.629 while mean sensitivity values ranged between 0.186 and 0.252. The series have relatively few missing rings (0.77-0.12% in individual chronologies). The oldest Pilgerodendron sampled to date was 859 years old while the chronology length ranged between 239 and 633 years. Ring-width series are correlated with precipitation but there were difficulties developing strong precipitation/ring-width relationships for individual stations/sites. However, two regional rainfall reconstructions were developed based on the inverse correlation between Pilgerodendron radial growth and the precipitation of northwestern and southern Patagonia. The reconstruction for spring-early summer in northwestern Patagonia extends from AD 1600 to 2002, and only explains 14% of the variance in the instrumental record. The southern Patagonia summer-autumn precipitation reconstruction (1600 to 2000) explains 40% of the total variance. Both reconstructed series show oscillatory modes for periodicities between 2 and 4 years and between 20 and 40 years. Droughts recognized in the reconstructed northwestern Patagonia precipitation series coincide with several other precipitation reconstructions of south-central Chile and Argentina over the last 400 years. "Little Ice Age" glacier fluctuations were examined at Mount San Lorenzo (47°30'S) and Santa Ines Island (53°45'S) in southern Chile using dendroglaciologic, geomorphic and historical (documentary, photographic) evidence. At Mount San Lorenzo the glacial advances occurred between 1600 and the late 1800s-early 1900s. At Santa Ines Island, the oldest glacial advance is dated ca. AD 1675 at Alejandro Glacier. Minimum age estimates ca. AD 1758, 1840-45 and 1895-1910 are common to Alejandro and Beatriz glaciers suggesting synchronous glacial activity. Glaciers have been receding at both sites during the last half of the 20th century. Radiocarbon dates from peat at Beatriz Glacier on Santa Ines Island indicate that the seventeenth century advance was the most extensive in the last 5,300 years in this area. Comparison between these glacier histories and climatic reconstructions for the last 400 years shows that glaciers from both study areas respond to a combination of temperature and precipitation. Future work involving a multi-criteria approach to date these moraines should include examination of soils, volcanic tephras and lake deposits within moraines, together with other dating tools to improve the dating control of the glacier histories. Keywords. Precipitation, homogeneity analysis, atmospheric circulation, Pilgerodendron uviferum, tree rings, time series analysis, climate variability, Southern South America, glaciers, dendroglaciology, Little Ice Age.

Drivers of annual to decadal streamflow variability in the lower Colorado River Basin

NASA Astrophysics Data System (ADS)

Lambeth-Beagles, R. S.; Troch, P. A.

2010-12-01

The Colorado River is the main water supply to the southwest region. As demand reaches the limit of supply in the southwest it becomes increasingly important to understand the dynamics of streamflow in the Colorado River and in particular the tributaries to the lower Colorado River. Climate change may pose an additional threat to the already-scarce water supply in the southwest. Due to the narrowing margin for error, water managers are keen on extending their ability to predict streamflow volumes on a mid-range to decadal scale. Before a predictive streamflow model can be developed, an understanding of the physical drivers of annual to decadal streamflow variability in the lower Colorado River Basin is needed. This research addresses this need by applying multiple statistical methods to identify trends, patterns and relationships present in streamflow, precipitation and temperature over the past century in four contributing watersheds to the lower Colorado River. The four watersheds selected were the Paria, Little Colorado, Virgin/Muddy, and Bill Williams. Time series data over a common period from 1906-2007 for streamflow, precipitation and temperature were used for the initial analysis. Through statistical analysis the following questions were addressed: 1) are there observable trends and patterns in these variables during the past century and 2) if there are trends or patterns, how are they related to each other? The Mann-Kendall test was used to identify trends in the three variables. Assumptions regarding autocorrelation and persistence in the data were taken into consideration. Kendall’s tau-b test was used to establish association between any found trends in the data. Initial results suggest there are two primary processes occurring. First, statistical analysis reveals significant upward trends in temperatures and downward trends in streamflow. However, there appears to be no trend in precipitation data. These trends in streamflow and temperature speak to increasing evaporation and transpiration processes. Second, annual variability in streamflow is not statistically correlated with annual temperature variability but appears to be highly correlated with annual precipitation variability. This implies that on a year-to-year basis, changes in streamflow volumes are directly affected by precipitation and not temperature. Future development of a predictive streamflow model will need to take into consideration these two processes to obtain accurate results. In order to extend predictive skill to the multi-year scale relationships between precipitation, temperature and persistent climate indices such as the Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation and El Nino/Southern Oscillation will need to be examined.

Assessing Global Water Storage Variability from GRACE: Trends, Seasonal Cycle, Subseasonal Anomalies and Extremes.

PubMed

Humphrey, Vincent; Gudmundsson, Lukas; Seneviratne, Sonia I

Throughout the past decade, the Gravity Recovery and Climate Experiment (GRACE) has given an unprecedented view on global variations in terrestrial water storage. While an increasing number of case studies have provided a rich overview on regional analyses, a global assessment on the dominant features of GRACE variability is still lacking. To address this, we survey key features of temporal variability in the GRACE record by decomposing gridded time series of monthly equivalent water height into linear trends, inter-annual, seasonal, and subseasonal (intra-annual) components. We provide an overview of the relative importance and spatial distribution of these components globally. A correlation analysis with precipitation and temperature reveals that both the inter-annual and subseasonal anomalies are tightly related to fluctuations in the atmospheric forcing. As a novelty, we show that for large regions of the world high-frequency anomalies in the monthly GRACE signal, which have been partly interpreted as noise, can be statistically reconstructed from daily precipitation once an adequate averaging filter is applied. This filter integrates the temporally decaying contribution of precipitation to the storage changes in any given month, including earlier precipitation. Finally, we also survey extreme dry anomalies in the GRACE record and relate them to documented drought events. This global assessment sets regional studies in a broader context and reveals phenomena that had not been documented so far.

Rainfall Variability, Adaptation through Irrigation, and Sustainable Management of Water Resources in India

NASA Astrophysics Data System (ADS)

Fishman, R.

2013-12-01

Most studies of the impact of climate change on agriculture account for shifts in temperature and total seasonal (or monthly) precipitation. However, climate change is also projected to increase intra-seasonal precipitation variability in many parts of the world. To provide first estimates of the potential impact, I paired daily rainfall and rice yield data during the period 1970-2004, from across India, where about a fifth of the world's rice is produced, and yields have always been highly dependent on the erratic monsoon rainfall. Multivariate regression models revealed that the number of rainless days during the wet season has a statistically robust negative impact on rice yields that exceeds that of total seasonal rainfall. Moreover, a simulation of climate change impacts found that the negative impact of the projected increase in the number of rainless days will trump the positive impact of the projected increase in total precipitation, and reverse the net precipitation effect on rice production from positive (+3%) to negative (-10%). The results also indicate that higher irrigation coverage is correlated with reduced sensitivity to rainfall variability, suggesting the expansion of irrigation can effectively adapt agriculture to these climate change impacts. However, taking into account limitations on water resource availability in India, I calculate that under current irrigation practices, sustainable use of water can mitigate less than a tenth of the impact.

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.

Atmospheric inputs of organic matter to a forested watershed: Variations from storm to storm over the seasons

USGS Publications Warehouse

Iavorivska , Lidiia; Boyer, Elizabeth W.; Miller, Matthew P.; Brown, Michael G.; Vasilopoulos , Terrie; Fuentes, Jose D.; Duffy, Christopher J.

2016-01-01

The objectives of this study were to determine the quantity and chemical composition of precipitation inputs of dissolved organic carbon (DOC) to a forested watershed; and to characterize the associated temporal variability. We sampled most precipitation that occurred from May 2012 through August 2013 at the Susquehanna Shale Hills Critical Zone Observatory (Pennsylvania, USA). Sub-event precipitation samples (159) were collected sequentially during 90 events; covering various types of synoptic meteorological conditions in all climatic seasons. Precipitation DOC concentrations and rates of wet atmospheric DOC deposition were highly variable from storm to storm, ranging from 0.3 to 5.6 mg C L−1 and from 0.5 to 32.8 mg C m−2 h−1, respectively. Seasonally, storms in spring and summer had higher concentrations of DOC and more optically active organic matter than in winter. Higher DOC concentrations resulted from weather types that favor air advection, where cold frontal systems, on average, delivered more than warm/stationary fronts and northeasters. A mixed modeling statistical approach revealed that factors related to storm properties, emission sources, and to the chemical composition of the atmosphere could explain more than 60% of the storm to storm variability in DOC concentrations. This study provided observations on changes in dissolved organic matter that can be useful in modeling of atmospheric oxidative chemistry, exploring relationships between organics and other elements of precipitation chemistry, and in considering temporal changes in ecosystem nutrient balances and microbial activity.

Disruption, not displacement: Environmental variability and temporary migration in Bangladesh

PubMed Central

Gray, Clark; Yunus, Mohammad; Emch, Michael

2018-01-01

Mass migration is one of the most concerning potential outcomes of global climate change. Recent research into environmentally induced migration suggests that relationship is much more complicated than originally posited by the ‘environmental refugee’ hypothesis. Climate change is likely to increase migration in some cases and reduce it in others, and these movements will more often be temporary and short term than permanent and long term. However, few large-sample studies have examined the evolution of temporary migration under changing environmental conditions. To address this gap, we measure the extent to which temperature, precipitation, and flooding can predict temporary migration in Matlab, Bangladesh. Our analysis incorporates high-frequency demographic surveillance data, a discrete time event history approach, and a range of sociodemographic and contextual controls. This approach reveals that migration declines immediately after flooding but quickly returns to normal. In contrast, optimal precipitation and high temperatures have sustained positive effects on temporary migration that persist over one to two year periods. Building on previous studies of long-term migration, these results challenge the common assumption that flooding, precipitation extremes and high temperatures will consistently increase temporary migration. Instead, our results are consistent with a livelihoods interpretation of environmental migration in which households draw on a range of strategies to cope with environmental variability. PMID:29375196

Disruption, not displacement: Environmental variability and temporary migration in Bangladesh.

PubMed

Call, Maia A; Gray, Clark; Yunus, Mohammad; Emch, Michael

2017-09-01

Mass migration is one of the most concerning potential outcomes of global climate change. Recent research into environmentally induced migration suggests that relationship is much more complicated than originally posited by the 'environmental refugee' hypothesis. Climate change is likely to increase migration in some cases and reduce it in others, and these movements will more often be temporary and short term than permanent and long term. However, few large-sample studies have examined the evolution of temporary migration under changing environmental conditions. To address this gap, we measure the extent to which temperature, precipitation, and flooding can predict temporary migration in Matlab, Bangladesh. Our analysis incorporates high-frequency demographic surveillance data, a discrete time event history approach, and a range of sociodemographic and contextual controls. This approach reveals that migration declines immediately after flooding but quickly returns to normal. In contrast, optimal precipitation and high temperatures have sustained positive effects on temporary migration that persist over one to two year periods. Building on previous studies of long-term migration, these results challenge the common assumption that flooding, precipitation extremes and high temperatures will consistently increase temporary migration. Instead, our results are consistent with a livelihoods interpretation of environmental migration in which households draw on a range of strategies to cope with environmental variability.

America's water: Agricultural water demands and the response of groundwater

NASA Astrophysics Data System (ADS)

Ho, M.; Parthasarathy, V.; Etienne, E.; Russo, T. A.; Devineni, N.; Lall, U.

2016-07-01

Agricultural, industrial, and urban water use in the conterminous United States (CONUS) is highly dependent on groundwater that is largely drawn from nonsurficial wells (>30 m). We use a Demand-Sensitive Drought Index to examine the impacts of agricultural water needs, driven by low precipitation, high agricultural water demand, or a combination of both, on the temporal variability of depth to groundwater across the CONUS. We characterize the relationship between changes in groundwater levels, agricultural water deficits relative to precipitation during the growing season, and winter precipitation. We find that declines in groundwater levels in the High Plains aquifer and around the Mississippi River Valley are driven by groundwater withdrawals used to supplement agricultural water demands. Reductions in agricultural water demands for crops do not, however, lead to immediate recovery of groundwater levels due to the demand for groundwater in other sectors in regions such as Utah, Maryland, and Texas.

Disdrometer-based C-Band Radar Quantitative Precipitation Estimation (QPE) in a highly complex terrain region in tropical Colombia.

NASA Astrophysics Data System (ADS)

Sepúlveda, J.; Hoyos Ortiz, C. D.

2017-12-01

An adequate quantification of precipitation over land is critical for many societal applications including agriculture, hydroelectricity generation, water supply, and risk management associated with extreme events. The use of rain gauges, a traditional method for precipitation estimation, and an excellent one, to estimate the volume of liquid water during a particular precipitation event, does not allow to fully capture the highly spatial variability of the phenomena which is a requirement for almost all practical applications. On the other hand, the weather radar, an active remote sensing sensor, provides a proxy for rainfall with fine spatial resolution and adequate temporary sampling, however, it does not measure surface precipitation. In order to fully exploit the capabilities of the weather radar, it is necessary to develop quantitative precipitation estimation (QPE) techniques combining radar information with in-situ measurements. Different QPE methodologies are explored and adapted to local observations in a highly complex terrain region in tropical Colombia using a C-Band radar and a relatively dense network of rain gauges and disdrometers. One important result is that the expressions reported in the literature for extratropical locations are not representative of the conditions found in the tropical region studied. In addition to reproducing the state-of-the-art techniques, a new multi-stage methodology based on radar-derived variables and disdrometer data is proposed in order to achieve the best QPE possible. The main motivation for this new methodology is based on the fact that most traditional QPE methods do not directly take into account the different uncertainty sources involved in the process. The main advantage of the multi-stage model compared to traditional models is that it allows assessing and quantifying the uncertainty in the surface rain rate estimation. The sub-hourly rainfall estimations using the multi-stage methodology are realistic compared to observed data in spite of the many sources of uncertainty including the sampling volume, the different physical principles of the sensors, the incomplete understanding of the microphysics of precipitation and, the most important, the rapidly varying droplet size distribution.

Mid to late-Holocene diatom microfossils and geochemical proxies as evidence for paleoclimate in the Hudson River estuary, New York

NASA Astrophysics Data System (ADS)

Gurung, D.; McHugh, C. M.; Kenna, T. C.; Burckle, L.

2009-05-01

New methodologies that combine the use of microfossil diatom assemblages, and elemental geochemistry (bromine (Br)) are being developed to assess late Holocene climatic variability in estuaries. The main idea is that in an estuary the saltwater wedge fluctuates in response to the volume of fluvial discharge that depends on surface runoff from precipitation and melting of snow (spring freshet). During times of high precipitation the saltwater wedge is pushed seaward. In contrast, during times of drought the saltwater wedge moves landward into the estuary. The Hudson River estuary in New York was flooded by marine waters in the early Holocene and at present its sedimentation patterns are in a state of dynamic equilibrium. Guided by high-resolution multibeam bathymetry, sediment cores (˜6 m in length) were recovered from the oligohaline parts of the estuary where discharge and precipitation changes have more impact on the saltwater wedge fluctuations. In those cores that showed continuous sedimentation, diatom assemblages and Br (ppm) were studied and used as proxies for salinity. Diatom assemblages (marine, freshwater and brackish) were identified and counted and Br (ppm) was measured by X-ray fluorescence spectrometry with an Innov-X portable system. The results were calibrated to an Pb-210 age model and compared with instrumental data of precipitation, river discharge, and Palmer Drought Severity Index (PDSI), The results obtained from two different locations show that marine diatom abundance and Br content correlate with periods of high precipitation during 1992-1988; 1985-1980; 1976-1968; 1962-1958; and increase with periods of low precipitation or droughts in 1987-1985; 1980-1975; 1967-1962; 1943-1938. The mid to late Holocene record shows a variability on the scale of ˜300 to 400 years similar to that obtained by Cronin et al. (2003) for Chesapeake Bay and related to the North Atlantic Oscillation. From 1992 to the present, both marine diatoms and Br ppm increase dramatically and do not correlate to the precipitation record. This increase in salinity is observed in all the cores and could be the result of relative sea level rise into the estuary.

Bayesian inference of uncertainties in precipitation-streamflow modeling in a snow affected catchment

NASA Astrophysics Data System (ADS)

Koskela, J. J.; Croke, B. W. F.; Koivusalo, H.; Jakeman, A. J.; Kokkonen, T.

2012-11-01

Bayesian inference is used to study the effect of precipitation and model structural uncertainty on estimates of model parameters and confidence limits of predictive variables in a conceptual rainfall-runoff model in the snow-fed Rudbäck catchment (142 ha) in southern Finland. The IHACRES model is coupled with a simple degree day model to account for snow accumulation and melt. The posterior probability distribution of the model parameters is sampled by using the Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm and the generalized likelihood function. Precipitation uncertainty is taken into account by introducing additional latent variables that were used as multipliers for individual storm events. Results suggest that occasional snow water equivalent (SWE) observations together with daily streamflow observations do not contain enough information to simultaneously identify model parameters, precipitation uncertainty and model structural uncertainty in the Rudbäck catchment. The addition of an autoregressive component to account for model structure error and latent variables having uniform priors to account for input uncertainty lead to dubious posterior distributions of model parameters. Thus our hypothesis that informative priors for latent variables could be replaced by additional SWE data could not be confirmed. The model was found to work adequately in 1-day-ahead simulation mode, but the results were poor in the simulation batch mode. This was caused by the interaction of parameters that were used to describe different sources of uncertainty. The findings may have lessons for other cases where parameterizations are similarly high in relation to available prior information.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Quantitative precipitation estimates for the northeastern Qinghai-Tibetan Plateau over the last 18,000 years

NASA Astrophysics Data System (ADS)

Li, Jianyong; Dodson, John; Yan, Hong; Cheng, Bo; Zhang, Xiaojian; Xu, Qinghai; Ni, Jian; Lu, Fengyan

2017-05-01

Quantitative information regarding the long-term variability of precipitation and vegetation during the period covering both the Late Glacial and the Holocene on the Qinghai-Tibetan Plateau (QTP) is scarce. Herein, we provide new and numerical reconstructions for annual mean precipitation (PANN) and vegetation history over the last 18,000 years using high-resolution pollen data from Lakes Dalianhai and Qinghai on the northeastern QTP. Hitherto, five calibration techniques including weighted averaging, weighted average-partial least squares regression, modern analogue technique, locally weighted weighted averaging regression, and maximum likelihood were first employed to construct robust inference models and to produce reliable PANN estimates on the QTP. The biomization method was applied for reconstructing the vegetation dynamics. The study area was dominated by steppe and characterized with a highly variable, relatively dry climate at 18,000-11,000 cal years B.P. PANN increased since the early Holocene, obtained a maximum at 8000-3000 cal years B.P. with coniferous-temperate mixed forest as the dominant biome, and thereafter declined to present. The PANN reconstructions are broadly consistent with other proxy-based paleoclimatic records from the northeastern QTP and the northern region of monsoonal China. The possible mechanisms behind the precipitation changes may be tentatively attributed to the internal feedback processes of higher latitude (e.g., North Atlantic) and lower latitude (e.g., subtropical monsoon) competing climatic regimes, which are primarily modulated by solar energy output as the external driving force. These findings may provide important insights into understanding the future Asian precipitation dynamics under the projected global warming.

Weather observations on Whistler Mountain during five storms

NASA Astrophysics Data System (ADS)

Thériault, Julie M.; Rasmussen, Kristen L.; Fisico, Teresa; Stewart, Ronald E.; Joe, Paul; Gultepe, Ismail; Clément, Marilys; Isaac, George A.

2014-01-01

A greater understanding of precipitation formation processes over complex terrain near the west coast of British Colombia will contribute to many relevant applications, such as climate studies, local hydrology, transportation, and winter sport competition. The phase of precipitation is difficult to determine because of the warm and moist weather conditions experienced during the wintertime in coastal mountain ranges. The goal of this study is to investigate the wide range of meteorological conditions that generated precipitation on Whistler Mountain from 4-12 March 2010 during the SNOW-V10 field campaign. During this time period, five different storms were documented in detail and were associated with noticeably different meteorological conditions in the vicinity of Whistler Mountain. New measurement techniques, along with the SNOW-V10 instrumentation, were used to obtain in situ observations during precipitation events along the Whistler mountainside. The results demonstrate a high variability of weather conditions ranging from the synoptic-scale to the macro-scale. These weather events were associated with a variation of precipitation along the mountainside, such as events associated with snow, snow pellets, and rain. Only two events associated with a rain-snow transition along the mountainside were observed, even though above-freezing temperatures along the mountainside were recorded 90 % of the time. On a smaller scale, these events were also associated with a high variability of snowflake types that were observed simultaneously near the top of Whistler Mountain. Overall, these detailed observations demonstrate the importance of understanding small-scale processes to improve observational techniques, short-term weather prediction, and longer-term climate projections over mountainous regions.

Winter westerly disturbance dynamics and precipitation in the western Himalaya and Karakoram: a wave-tracking approach

NASA Astrophysics Data System (ADS)

Cannon, Forest; Carvalho, Leila M. V.; Jones, Charles; Norris, Jesse

2016-07-01

Extratropical cyclones, including winter westerly disturbances (WWD) over central Asia, are fundamental features of the atmosphere that maintain energy, momentum, and moisture at global scales while intimately linking large-scale circulation to regional-scale meteorology. Within high mountain Asia, WWD are the primary contributor to regional precipitation during winter. In this work, we present a novel WWD tracking methodology, which provides an inventory of location, timing, intensity, and duration of events, allowing for a comprehensive study of the factors that relate WWD to orographic precipitation, on an individual event basis and in the aggregate. We identify the relationship between the strength of disturbances, the state of the background environment during their propagation, and precipitation totals in the Karakoram/western Himalaya. We observe significant differences in convective and mechanical instability contributions to orographic precipitation as a function of the relationship between the intensity of WWD and the background temperature and moisture fields, which exhibit strong intraseasonal variability. Precipitation is primarily orographically forced during intense WWD with strong cross-barrier winds, while weaker WWD with similar precipitation totals are observed to benefit from enhanced instability due to high moisture content and temperature at low levels, occurring primarily in the late winter/premonsoon. The contribution of these factors is observed to fluctuate on a per-case basis, indicating important influences of intraseasonal oscillations and tropical-extratropical interactions on regional precipitation.

Daily rainfall statistics of TRMM and CMORPH: A case for trans-boundary Gandak River basin

NASA Astrophysics Data System (ADS)

Kumar, Brijesh; Patra, Kanhu Charan; Lakshmi, Venkat

2016-07-01

Satellite precipitation products offer an opportunity to evaluate extreme events (flood and drought) for areas where rainfall data are not available or rain gauge stations are sparse. In this study, daily precipitation amount and frequency of TRMM 3B42V.7 and CMORPH products have been validated against daily rain gauge precipitation for the monsoon months (June-September or JJAS) from 2005-2010 in the trans-boundary Gandak River basin. The analysis shows that the both TRMM and CMORPH can detect rain and no-rain events, but they fail to capture the intensity of rainfall. The detection of precipitation amount is strongly dependent on the topography. In the plains areas, TRMM product is capable of capturing high-intensity rain events but in the hilly regions, it underestimates the amount of high-intensity rain events. On the other hand, CMORPH entirely fails to capture the high-intensity rain events but does well with low-intensity rain events in both hilly regions as well as the plain region. The continuous variable verification method shows better agreement of TRMM rainfall products with rain gauge data. TRMM fares better in the prediction of probability of occurrence of high-intensity rainfall events, but it underestimates intensity at high altitudes. This implies that TRMM precipitation estimates can be used for flood-related studies only after bias adjustment for the topography.

Reconstructing Hydrologic Variability in Southwestern North America Using Speleothem Proxies and Precipitation Isotopes from California

NASA Astrophysics Data System (ADS)

McCabe-Glynn, Staryl

Precipitation in southwestern North America has exhibited significant natural variability over the past few thousand years. This variability has been attributed to sea surface temperature regimes in the Pacific and Atlantic oceans, and to the attendant shifts in atmospheric circulation patterns. In particular, decadal variability in the North Pacific has influenced precipitation in this region during the twentieth century, but links to earlier droughts and pluvials are unclear. Here I assess these links using delta18 O measurements from a speleothem from southern California that spans AD 854-- 2007. I show that variations in the oxygen isotopes of the speleothem correlate to sea surface temperatures in the Kuroshio Extension region of the North Pacific, which affect the atmospheric trajectory and isotopic composition of moisture reaching the study site. Interpreting our speleothem data as a record of sea surface temperatures in the Kuroshio Extension, I find a strong 22-year periodicity, suggesting a persistent solar influence on North Pacific decadal variability. A comparison with tree-ring records of precipitation during the past millennium shows that some droughts occurred during periods of warmth in the Kuroshio Extension, similar to the instrumental record. However, other droughts did not and instead were likely influenced by other factors. The carbon isotope record indicates drier conditions are associated with higher delta13C values and may be a suitable proxy for reconstructing past drought variability. More research is needed to determine the controls on trace element concentrations. Finally, I find a significant increase in sea surface temperature variability over the past 150 years, which may reflect an influence of greenhouse gas concentrations on variability in the North Pacific. While drought is a common feature of climate in this region, most climate models also project extreme precipitation events to increase in frequency and severity because the climate changes largely due to increased water vapor content in a warmer atmosphere. I also utilize precipitation data and isotopic analysis from precipitation samples collected weekly from near the cave site at Giant Forest, Sequoia National Park, California, from 2001 to 2011, to analyze climate mode patterns during extreme precipitation events and to construct an isotopic data base of precipitation samples. Composite maps indicate extreme precipitation weeks consist of a weaker Aleutian Low, coupled with a deep low pressure cell located northwest of California and enhanced subtropical moisture. I find extreme precipitation weeks occur more often during the La Nina phase and less during the positive Eastern Pacific (EP) phase or during the Central Pacific (CP) neutral phase at our site. Analyses of climate mode patterns and precipitation amounts indicate that when the negative Arctic Oscillation (AO), negative and neutral Pacific North American pattern (PNA), and positive Southern Oscillation Index (SOI) (La Nina) are in sync, the maximum amount of precipitation anomalies are distributed along the Western US. Additionally, the central or eastern Pacific location of El Nino Southern Oscillation sea surface temperature anomalies can further enhance predictive capabilities of the landfall location of extreme precipitation.

Precipitation in a boiling soup: is microphysics driving the statistical properties of intense turbulent convection?

NASA Astrophysics Data System (ADS)

Parodi, A.; von Hardenberg, J.; Provenzale, A.

2012-04-01

Intense precipitation events are often associated with strong convective phenomena in the atmosphere. A deeper understanding of how microphysics affects the spatial and temporal variability of convective processes is relevant for many hydro-meteorological applications, such as the estimation of rainfall using remote sensing techniques and the ability to predict severe precipitation processes. In this paper, high-resolution simulations (0.1-1 km) of an atmosphere in radiative-convective equilibrium are performed using the Weather Research and Forecasting (WRF) model by prescribing different microphysical parameterizations. The dependence of fine-scale spatio-temporal properties of convective structures on microphysical details are investigated and the simulation results are compared with the known properties of radar maps of precipitation fields. We analyze and discuss similarities and differences and, based also on previous results on the dependence of precipitation statistics on the raindrop terminal velocity, try to draw some general inferences.

Carbon Dioxide Physiological Forcing Dominates Projected Eastern Amazonian Drying

NASA Astrophysics Data System (ADS)

Richardson, T. B.; Forster, P. M.; Andrews, T.; Boucher, O.; Faluvegi, G.; Fläschner, D.; Kasoar, M.; Kirkevâg, A.; Lamarque, J.-F.; Myhre, G.; Olivié, D.; Samset, B. H.; Shawki, D.; Shindell, D.; Takemura, T.; Voulgarakis, A.

2018-03-01

Future projections of east Amazonian precipitation indicate drying, but they are uncertain and poorly understood. In this study we analyze the Amazonian precipitation response to individual atmospheric forcings using a number of global climate models. Black carbon is found to drive reduced precipitation over the Amazon due to temperature-driven circulation changes, but the magnitude is uncertain. CO2 drives reductions in precipitation concentrated in the east, mainly due to a robustly negative, but highly variable in magnitude, fast response. We find that the physiological effect of CO2 on plant stomata is the dominant driver of the fast response due to reduced latent heating and also contributes to the large model spread. Using a simple model, we show that CO2 physiological effects dominate future multimodel mean precipitation projections over the Amazon. However, in individual models temperature-driven changes can be large, but due to little agreement, they largely cancel out in the model mean.

Terrestrial precipitation and soil moisture: A case study over southern Arizona and data development

NASA Astrophysics Data System (ADS)

Stillman, Susan

Quantifying climatological precipitation and soil moisture as well as interannual variability and trends requires extensive observation. This work focuses on the analysis of available precipitation and soil moisture data and the development of new ways to estimate these quantities. Precipitation and soil moisture characteristics are highly dependent on the spatial and temporal scales. We begin at the point scale, examining hourly precipitation and soil moisture at individual gauges. First, we focus on the Walnut Gulch Experimental Watershed (WGEW), a 150 km2 area in southern Arizona. The watershed has been measuring rainfall since 1956 with a very high density network of approximately 0.6 gauges per km2. Additionally, there are 19 soil moisture probes at 5 cm depth with data starting in 2002. In order to extend the measurement period, we have developed a water balance model which estimates monsoon season (Jul-Sep) soil moisture using only precipitation for input, and calibrated so that the modeled soil moisture fits best with the soil moisture measured by each of the 19 probes from 2002-2012. This observationally constrained soil moisture is highly correlated with the collocated probes (R=0.88), and extends the measurement period from 10 to 56 years and the number of gauges from 19 to 88. Then, we focus on the spatiotemporal variability within the watershed and the ability to estimate area averaged quantities. Spatially averaged precipitation and observationally constrained soil moisture from the 88 gauges is then used to evaluate various gridded datasets. We find that gauge-based precipitation products perform best followed by reanalyses and then satellite-based products. Coupled Model Intercomparison Project Phase 5 (CMIP5) models perform the worst and overestimate cold season precipitation while offsetting the monsoon peak precipitation forward or backward by a month. Satellite-based soil moisture is the best followed by land data assimilation systems and reanalyses. We show that while WGEW is small compared to the grid size of many of the evaluated products, unlike scaling from point to area, the effect of scaling from smaller to larger area is small. Finally, we focus on global precipitation. Global monthly gauge based precipitation data has become widely available in recent years and is necessary for analyzing the climatological and anomaly precipitation fields as well as for calibrating and evaluating other gridded products such as satellite-based and modeled precipitation. However, frequency and intensity of precipitation are also important in the partitioning of water and energy fluxes. Therefore, because daily and sub-daily observed precipitation is limited to recent years, the number of raining days per month (N) is needed. We show that the only currently available long-term N product, developed by the Climate Research Unit (CRU), is deficient in certain areas, particularly where CRU gauge data is sparse. We then develop a new global 110-year N product, which shows significant improvement over CRU using three regional daily precipitation products with far more gauges than are used in CRU.

Response of lake chemistry to atmospheric deposition and climate in selected Class I wilderness areas in the western United States, 1993-2009

USGS Publications Warehouse

Mast, M. Alisa

2011-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Forest Service, Air Resource Management, conducted a study to evaluate long-term trends in lake-water chemistry for 64 high-elevation lakes in selected Class I wilderness areas in Colorado, Idaho, Utah, and Wyoming during 1993 to 2009. Understanding how and why lake chemistry is changing in mountain areas is essential for effectively managing and protecting high-elevation aquatic ecosystems. Trends in emissions, atmospheric deposition, and climate variables (air temperature and precipitation amount) were evaluated over a similar period of record. A main objective of the study was to determine if changes in atmospheric deposition of contaminants in the Rocky Mountain region have resulted in measurable changes in the chemistry of high-elevation lakes. A second objective was to investigate linkages between lake chemistry and air temperature and precipitation to improve understanding of the sensitivity of mountain lakes to climate variability.

Circulation controls of the spatial structure of maximum daily precipitation over Poland

NASA Astrophysics Data System (ADS)

Stach, Alfred

2015-04-01

Among forecasts made on the basis of global and regional climatic models is one of a high probability of an increase in the frequency and intensity of extreme precipitation events. Learning the regularities underlying the recurrence and spatial extent of extreme precipitation is obviously of great importance, both economic and social. The main goal of the study was to analyse regularities underlying spatial and temporal variations in monthly Maximum Daily Precipitation Totals (MDPTs) observed in Poland over the years 1956-1980. These data are specific because apart from being spatially discontinuous, which is typical of precipitation, they are also non-synchronic. The main aim of the study was accomplished via several detailed goals: • identification and typology of the spatial structure of monthly MDPTs, • determination of the character and probable origin of events generating MDPTs, and • quantitative assessment of the contribution of the particular events to the overall MDPT figures. The analysis of the spatial structure of MDPTs was based on 300 models of spatial structure, one for each of the analysed sets of monthly MDPTs. The models were built on the basis of empirical anisotropic semivariograms of normalised data. In spite of their spatial discontinuity and asynchronicity, the MDPT data from Poland display marked regularities in their spatial pattern that yield readily to mathematical modelling. The MDPT field in Poland is usually the sum of the outcomes of three types of processes operating at various spatial scales: local (<10-20 km), regional (50-150 km), and supra-regional (>200 km). The spatial scales are probably connected with a convective/ orographic, a frontal and a 'planetary waves' genesis of high precipitation. Their contributions are highly variable. Generally predominant, however, are high daily precipitation totals with a spatial extent of 50 to 150 km connected with mesoscale phenomena and the migration of atmospheric fronts (35-38%). The spatial extent of areas of high local-scale precipitation usually varies at random, especially in the warm season. At supra-local scales, structures of repetitive size predominate. Eight types of anisotropic structures of monthly MDPTs were distinguished. To identify them, an analysis was made of semivariance surface similarities. The types differ not only in the level and direction of anisotropy, but also in the number and type of elementary components, which is evidence of genetic differences in precipitation. Their appearance shows a significant seasonal variability, so the most probable supposition was that temporal variations in the MDPT pattern were connected with circulation conditions: the type and direction of inflow of air masses. This hypothesis was validated by testing differences in the frequency of occurrence of Grosswetterlagen circulation situations in the months belonging to the distinguished types of the spatial MDPT pattern.

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

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

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE PAGES

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai; ...

2016-07-14

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Trends in the precipitation and crystallization behavior of supersaturated aqueous solutions of poorly water-soluble drugs assessed using synchrotron radiation.

PubMed

Raina, Shweta A; Van Eerdenbrugh, Bernard; Alonzo, David E; Mo, Huaping; Zhang, Geoff G Z; Gao, Yi; Taylor, Lynne S

2015-06-01

Amorphous materials are high-energy solids that can potentially enhance the bioavailability of poorly soluble compounds. A major impediment to their widespread use as a formulation platform is the tendency of amorphous materials to crystallize. The aim of this study was to evaluate the relative crystallization tendency of six structural analogues belonging to the dihydropyridine class, in an aqueous environment in the absence and presence of polymers, using wide-angle X-ray scattering synchrotron radiation and polarized light microscopy. The crystallization behavior of precipitates generated from supersaturated solutions of the active pharmaceutical ingredients was found to be highly variable ranging from immediate to several hours in the absence of polymers. Polymers with intermediate hydrophilicity/hydrophobicity were found to substantially delay crystallization, whereas strongly hydrophilic or hydrophobic polymers were largely ineffective. Nuclear magnetic resonance spectroscopy experiments supported the supposition that polymers need to have affinity for both the drug-rich precipitate and the aqueous phase in order to be effective crystallization inhibitors. This study highlights the variability in the crystallization tendency of different compounds and provides insight into the mechanism of inhibition by polymeric additives. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Modeling the influence of precipitation and nitrogen deposition on forest understory fuel connectivity in Sierra Nevada mixed-conifer forest

Treesearch

M. Hurteau; M. North; T. Foines

2009-01-01

Climate change models for California’s Sierra Nevada predict greater inter-annual variability in precipitation over the next 50 years. These increases in precipitation variability coupled with increases in nitrogen deposition fromfossil fuel consumption are likely to result in increased productivity levels and significant increases in...

Decadal variations in the strength of ENSO teleconnections with precipitation in the western United States

USGS Publications Warehouse

McCabe, G.J.; Dettinger, M.D.

1999-01-01

Changing patterns of correlations between the historical average June-November Southern Oscillation Index (SOI) and October-March precipitation totals for 84 climate divisions in the western US indicate a large amount of variability in SOI/precipitation relations on decadal time scales. Correlations of western US precipitation with SOI and other indices of tropical El Nino-Southern Oscillation (ENSO) processes were much weaker from 1920 to 1950 than during recent decades. This variability in teleconnections is associated with the character of tropical air-sea interactions as indexed by the number of out-of-phase SOI/tropical sea surface temperature (SST) episodes, and with decadal variability in the North Pacific Ocean as indexed by the Pacific Decadal Oscillation (PDO). ENSO teleconnections with precipitation in the western US are strong when SOI and NINO3 are out-of-phase and PDO is negative. ENSO teleconnections are weak when SOI and NINO3 are weakly correlated and PDO is positive. Decadal modes of tropical and North Pacific Ocean climate variability are important indicators of periods when ENSO indices, like SOI, can be used as reliable predictors of winter precipitation in the US.

Relative contributions of mean-state shifts and ENSO-driven variability to precipitation changes in a warming climate

DOE PAGES

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; ...

2015-12-18

The El Niño–Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change.more » Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. Lastly, by examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.« less

Variability modes of precipitation along a Central Mediterranean area and their relations with ENSO, NAO, and other climatic patterns

NASA Astrophysics Data System (ADS)

Kalimeris, Anastasios; Ranieri, Ezio; Founda, Dimitra; Norrant, Caroline

2017-12-01

This study analyses a century-long set of precipitation time series in the Central Mediterranean (encompassing the Greek Ionian and the Italian Puglia regions) and investigates the statistically significant modes of the interannual precipitation variability using efficient methods of spectral decomposition. The statistical relations and the possible physical couplings between the detected modes and the global or hemispheric patterns of climatic variability (the El Niño Southern Oscillation or ENSO, the North Atlantic Oscillation or NAO, the East Atlantic or EA, the Scandinavian or SCAND, and others) were examined in the time-frequency domain and low-order synchronization events were sought. Significant modes of precipitation variability were detected in the Taranto Gulf and the southern part of the Greek Ionian region at the sub-decadal scales (mostly driven by the SCAND pattern) and particularly at the decadal and quasi-decadal scales, where strong relations found with the ENSO activity (under complex implications of EA and NAO) prior to the 1930s or after the early-1970s. The precipitation variations in the Adriatic stations of Puglia are dominated by significant bi-decadal modes which found to be coherent with the ENSO activity and also weakly related with the Atlantic Ocean sea surface temperature intrinsic variability. Additionally, important discontinuities characterize the evolution of precipitation in certain stations of the Taranto Gulf and the Greek Ionian region during the early-1960s and particularly during the early-1970s, followed by significant reductions in the mean annual precipitation. These discontinuities seem to be associated with regional effects of NAO and SCAND, probably combined with the impact of the 1970s climatic shift in the Pacific and the ENSO variability.

Tolerance adaptation and precipitation changes complicate latitudinal patterns of climate change impacts.

PubMed

Bonebrake, Timothy C; Mastrandrea, Michael D

2010-07-13

Global patterns of biodiversity and comparisons between tropical and temperate ecosystems have pervaded ecology from its inception. However, the urgency in understanding these global patterns has been accentuated by the threat of rapid climate change. We apply an adaptive model of environmental tolerance evolution to global climate data and climate change model projections to examine the relative impacts of climate change on different regions of the globe. Our results project more adverse impacts of warming on tropical populations due to environmental tolerance adaptation to conditions of low interannual variability in temperature. When applied to present variability and future forecasts of precipitation data, the tolerance adaptation model found large reductions in fitness predicted for populations in high-latitude northern hemisphere regions, although some tropical regions had comparable reductions in fitness. We formulated an evolutionary regional climate change index (ERCCI) to additionally incorporate the predicted changes in the interannual variability of temperature and precipitation. Based on this index, we suggest that the magnitude of climate change impacts could be much more heterogeneous across latitude than previously thought. Specifically, tropical regions are likely to be just as affected as temperate regions and, in some regions under some circumstances, possibly more so.

Circulation and rainfall climatology of a 10-year (1979 - 1988) integration with the Goddard Laboratory for atmospheres general circulation model

NASA Technical Reports Server (NTRS)

Kim, J.-H.; Sud, Y. C.

1993-01-01

A 10-year (1979-1988) integration of Goddard Laboratory for Atmospheres (GLA) general circulation model (GCM) under Atmospheric Model Intercomparison Project (AMIP) is analyzed and compared with observation. The first momentum fields of circulation variables and also hydrological variables including precipitation, evaporation, and soil moisture are presented. Our goals are (1) to produce a benchmark documentation of the GLA GCM for future model improvements; (2) to examine systematic errors between the simulated and the observed circulation, precipitation, and hydrologic cycle; (3) to examine the interannual variability of the simulated atmosphere and compare it with observation; and (4) to examine the ability of the model to capture the major climate anomalies in response to events such as El Nino and La Nina. The 10-year mean seasonal and annual simulated circulation is quite reasonable compared to the analyzed circulation, except the polar regions and area of high orography. Precipitation over tropics are quite well simulated, and the signal of El Nino/La Nina episodes can be easily identified. The time series of evaporation and soil moisture in the 12 biomes of the biosphere also show reasonable patterns compared to the estimated evaporation and soil moisture.

Effects of baseline conditions on the simulated hydrologic response to projected climate change

USGS Publications Warehouse

Koczot, Kathryn M.; Markstrom, Steven L.; Hay, Lauren E.

2011-01-01

Changes in temperature and precipitation projected from five general circulation models, using one late-twentieth-century and three twenty-first-century emission scenarios, were downscaled to three different baseline conditions. Baseline conditions are periods of measured temperature and precipitation data selected to represent twentieth-century climate. The hydrologic effects of the climate projections are evaluated using the Precipitation-Runoff Modeling System (PRMS), which is a watershed hydrology simulation model. The Almanor Catchment in the North Fork of the Feather River basin, California, is used as a case study. Differences and similarities between PRMS simulations of hydrologic components (i.e., snowpack formation and melt, evapotranspiration, and streamflow) are examined, and results indicate that the selection of a specific time period used for baseline conditions has a substantial effect on some, but not all, hydrologic variables. This effect seems to be amplified in hydrologic variables, which accumulate over time, such as soil-moisture content. Results also indicate that uncertainty related to the selection of baseline conditions should be evaluated using a range of different baseline conditions. This is particularly important for studies in basins with highly variable climate, such as the Almanor Catchment.

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

Stable Isotopes of Precipitation During Tropical Sumatra Squalls in Singapore

NASA Astrophysics Data System (ADS)

He, Shaoneng; Goodkin, Nathalie F.; Kurita, Naoyuki; Wang, Xianfeng; Rubin, Charles Martin

2018-04-01

Sumatra Squalls, organized bands of thunderstorms, are the dominant mesoscale convective systems during the intermonsoon and southwest monsoon seasons in Singapore. To understand how they affect precipitation isotopes, we monitored the δ value of precipitation daily and continuously (every second and integrated over 30 s) during all squalls in 2015. We found that precipitation δ18O values mainly exhibit a "V"-shape pattern and less commonly a "W"-shape pattern. Variation in δ18O values during a single event is about 1 to 6‰ with the lowest values mostly observed in the stratiform zone, which agrees with previous observations and modeling simulations. Reevaporation can significantly affect δ values, especially in the last stage of the stratiform zone. Daily precipitation is characterized by periodic negative shifts in δ value, largely associated with the squalls rather than moisture source change. The shifts can be more than 10‰, larger than intraevent variation. Initial δ18O values of events are highly variable, and those with the lowest values also have the lowest initial values. Therefore, past convective activities in the upwind area can significantly affect the δ18O, and convection at the sampling site has limited contribution to isotopic variability. A significant correlation between precipitation δ18O value and regional outgoing longwave radiation and rainfall in the Asian monsoon region and western Pacific suggests that regional organized convection probably drives stable isotopic compositions of precipitation. A drop in the frequency of the squalls in 2015 is related to weak organized convection in the region caused by El Niño.

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

NASA Astrophysics Data System (ADS)

Wen, Xiaohu; Wu, Xiaoqing; Gao, Meng

2017-11-01

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

Use of dynamical downscaling to improve the simulation of Central U.S. warm season precipitation in CMIP5 models

NASA Astrophysics Data System (ADS)

Harding, Keith J.; Snyder, Peter K.; Liess, Stefan

2013-11-01

supporting exceptionally productive agricultural lands, the Central U.S. is susceptible to severe droughts and floods. Such precipitation extremes are expected to worsen with climate change. However, future projections are highly uncertain as global climate models (GCMs) generally fail to resolve precipitation extremes. In this study, we assess how well models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate summer means, variability, extremes, and the diurnal cycle of Central U.S. summer rainfall. Output from a subset of historical CMIP5 simulations are used to drive the Weather Research and Forecasting model to determine whether dynamical downscaling improves the representation of Central U.S. rainfall. We investigate which boundary conditions influence dynamically downscaled precipitation estimates and identify GCMs that can reasonably simulate precipitation when downscaled. The CMIP5 models simulate the seasonal mean and variability of summer rainfall reasonably well but fail to resolve extremes, the diurnal cycle, and the dynamic forcing of precipitation. Downscaling to 30 km improves these characteristics of precipitation, with the greatest improvement in the representation of extremes. Additionally, sizeable diurnal cycle improvements occur with higher (10 km) resolution and convective parameterization disabled, as the daily rainfall peak shifts 4 h closer to observations than 30 km resolution simulations. This lends greater confidence that the mechanisms responsible for producing rainfall are better simulated. Because dynamical downscaling can more accurately simulate these aspects of Central U.S. summer rainfall, policymakers can have added confidence in dynamically downscaled rainfall projections, allowing for more targeted adaptation and mitigation.

Covariability of seasonal temperature and precipitation over the Iberian Peninsula in high-resolution regional climate simulations (1001-2099)

NASA Astrophysics Data System (ADS)

Fernández-Montes, S.; Gómez-Navarro, J. J.; Rodrigo, F. S.; García-Valero, J. A.; Montávez, J. P.

2017-04-01

Precipitation and surface temperature are interdependent variables, both as a response to atmospheric dynamics and due to intrinsic thermodynamic relationships and feedbacks between them. This study analyzes the covariability of seasonal temperature (T) and precipitation (P) across the Iberian Peninsula (IP) using regional climate paleosimulations for the period 1001-1990, driven by reconstructions of external forcings. Future climate (1990-2099) was simulated according to SRES scenarios A2 and B2. These simulations enable exploring, at high spatial resolution, robust and physically consistent relationships. In winter, positive P-T correlations dominate west-central IP (Pearson correlation coefficient ρ = + 0.43, for 1001-1990), due to prevalent cold-dry and warm-wet conditions, while this relationship weakens and become negative towards mountainous, northern and eastern regions. In autumn, negative correlations appear in similar regions as in winter, whereas for summer they extend also to the N/NW of the IP. In spring, the whole IP depicts significant negative correlations, strongest for eastern regions (ρ = - 0.51). This is due to prevalent frequency of warm-dry and cold-wet modes in these regions and seasons. At the temporal scale, regional correlation series between seasonal anomalies of temperature and precipitation (assessed in 31 years running windows in 1001-1990) show very large multidecadal variability. For winter and spring, periodicities of about 50-60 years arise. The frequency of warm-dry and cold-wet modes appears correlated with the North Atlantic Oscillation (NAO), explaining mainly co-variability changes in spring. For winter and some regions in autumn, maximum and minimum P-T correlations appear in periods with enhanced meridional or easterly circulation (low or high pressure anomalies in the Mediterranean and Europe). In spring and summer, the Atlantic Multidecadal Oscillation shows some fingerprint on the frequency of warm/cold modes. For future scenarios, an intensification of the negative P-T relationship is generally found, as a result of an increased frequency of the warm-dry mode.

Seasonal precipitation extreme indices in mainland Portugal: trends and variability in the period 1941-2007

NASA Astrophysics Data System (ADS)

Santo, Fátima E.; Ramos, Alexandre M.; de Lima, M. Isabel P.; Trigo, Ricardo M.

2013-04-01

Changes in the precipitation regimes are expected to be accompanied by variations in the occurrence of extreme events, which in turn could be related to low frequency variability. The impact on the society and environment requires that the regional specificities are understood. For mainland Portugal, this work reports the results of the analysis of trends in selected precipitation indices calculated from daily precipitation data from 57 meteorological stations, recorded in the period 1941-2007; additionally we have also investigated the correlations between these indices and several modes of low frequency variability over the area. We focus on exploring regional differences and seasonal variations in the intensity, frequency and duration of extreme precipitation events. The precipitation indices were assessed at the seasonal scale and calculated at both the station and regional scales. Results sometimes highlight marked changes in seasonal precipitation and show that: i) trends in spring and autumn have opposite signals: statistically significant drying trends in the spring are accompanied by a reduction in precipitation extremes; in autumn, wetting trends are detected for all precipitation indices, although overall they are not significant at the 5% level; ii) there seems to be a tendency for a reduction in the duration of the rainy season; iii) the North Atlantic Oscillation (NAO) is the mode of variability that has the highest influence on precipitation extremes over mainland Portugal, particularly in the winter and autumn, and is one of the most important teleconnection patterns in all seasons. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) through project STORMEx FCOMP-01-0124-FEDER-019524 (PTDC/AAC-CLI/121339/2010).

Understanding climate variability and global climate change using high-resolution GCM simulations

NASA Astrophysics Data System (ADS)

Feng, Xuelei

In this study, three climate processes are examined using long-term simulations from multiple climate models with increasing horizontal resolutions. These simulations include the European Center for Medium-range Weather Forecasts (ECMWF) atmospheric general circulation model (AGCM) runs forced with observed sea surface temperatures (SST) (the Athena runs) and a set of coupled ocean-atmosphere seasonal hindcasts (the Minerva runs). Both sets of runs use different AGCM resolutions, the highest at 16 km. A pair of the Community Climate System Model (CCSM) simulations with ocean general circulation model (OGCM) resolutions at 100 and 10 km are also examined. The higher resolution CCSM run fully resolves oceanic mesoscale eddies. The resolution influence on the precipitation climatology over the Gulf Stream (GS) region is first investigated. In the Athena simulations, the resolution increase generates enhanced mean GS precipitation moderately in both large-scale and sub-scale rainfalls in the North Atlantic, with the latter more tightly confined near the oceanic front. However, the non-eddy resolving OGCM in the Minerva runs simulates a weaker oceanic front and weakens the mean GS precipitation response. On the other hand, an increase in CCSM oceanic resolutions from non-eddy-resolving to eddy resolving regimes greatly improves the model's GS precipitation climatology, resulting in both stronger intensity and more realistic structure. Further analyses show that the improvement of the GS precipitation climatology due to resolution increases is caused by the enhanced atmospheric response to an increased SST gradient near the oceanic front, which leads to stronger surface convergence and upper level divergence. Another focus of this study is on the global warming impacts on precipitation characteristic changes using the high-resolution Athena simulations under the SST forcing from the observations and a global warming scenario. As a comparison, results from the coarse resolution simulation are also analyzed to examine the dependence on resolution. The increasing rates of globally averaged precipitation amount for the high and low resolution simulations are 1.7%/K-1 and 1.8%/K-1, respectively. The sensitivities for heavy, moderate, light and drizzle rain are 6.8, -1.2, 0.0, 0.2%/K-1 for low and 6.3, -1.5, 0.4, -0.2%/K -1 for high resolution simulations. The number of rainy days decreases in a warming scenario, by 3.4 and 4.2 day/year-1, respectively. The most sensitive response of 6.3-6.8%/K-1 for the heavy rain approaches that of the 7%/K-1 for the Clausius-Clapeyron scaling limit. During the twenty-first century simulation, the increases in precipitation are larger over high latitude and wet regions in low and mid-latitudes. Over the dry regions, such as the subtropics, the precipitation amount and frequency decrease. There is a higher occurrence of low and heavy rain from the tropics to mid-latitudes at the expense of the decreases in the frequency of moderate rain. In the third part, the inter-annual variability of the northern hemisphere storm tracks is examined. In the Athena simulations, the leading modes of the observed storm track variability are reproduced realistically by all runs. In general, the fluctuations of the model storm tracks in the North Pacific and Atlantic basins are largely independent of each other. Within each basin, the variations are characterized by the intensity change near the climatological center and the meridional shift of the storm track location. These two modes are associated with major teleconnection patterns of the low frequency atmospheric variations. These model results are not sensitive to resolution. Using the Minerva hindcast initialized in November, it is shown that a portion of the winter (December-January) storm track variability is predictable, mainly due to the influences of the atmospheric wave trains induced by the El Nino and Southern Oscillation.

The Centennial Trends Greater Horn of Africa precipitation dataset.

PubMed

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

2015-01-01

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

The Centennial Trends Greater Horn of Africa precipitation dataset

USGS Publications Warehouse

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

2015-01-01

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

Long-term trends and variability of total and extreme precipitation in Thailand

NASA Astrophysics Data System (ADS)

Limsakul, Atsamon; Singhruck, Patama

2016-03-01

Based on quality-controlled daily station data, long-term trends and variability of total and extreme precipitation indices during 1955-2014 were examined for Thailand. An analysis showed that while precipitation events have been less frequent across most of Thailand, they have become more intense. Moreover, the indices measuring the magnitude of intense precipitation events indicate a trend toward wetter conditions, with heavy precipitation contributing a greater fraction to annual totals. One consequence of this change is the increased frequency and severity of flash floods as recently evidenced in many parts of Thailand. On interannual-to-interdecadal time scales, significant relationships between variability of precipitation indices and the indices for the state of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) were found. These results provide additional evidence that large-scale climate phenomena in the Pacific Ocean are remote drivers of variability in Thailand's total and extreme precipitation. Thailand tended to have greater amounts of precipitation and more extreme events during La Niña years and the PDO cool phase, and vice versa during El Niño years and the PDO warm phase. Another noteworthy finding is that in 2011 Thailand experienced extensive flooding in a year characterized by exceptionally extreme precipitation events. Our results are consistent with the regional studies for the Asia-Pacific Network. However, this study provides a more detailed picture of coherent trends at a station scale and documents changes that have occurred in the twenty-first century, both of which help to inform decisions concerning effective management strategies.

Relative Contribution of Monsoon Precipitation and Pumping to Changes in Groundwater Storage in India

NASA Astrophysics Data System (ADS)

A, A.; Gleeson, T. P.; Wada, Y.; Mishra, V.

2017-12-01

The availability and depletion of groundwater resources - a possible threat to food and water security - are impacted by both pumping and climate variability, although the relative importance of these two drivers is rarely quantified. Here we show that long-term change in the monsoon precipitation is a major driver of groundwater storage variability in most parts of India either directly by changing recharge or indirectly by changing abstraction. GRACE and observation well data show that groundwater storage has declined in north India with a rate of 2 cm/year and increased in the south India by 1 to 2 cm/year during the period of 2002-2013. A large fraction of total variability in groundwater storage is influenced by precipitation in northcentral and southern India. Groundwater storage variability in the northwestern India is mainly explained by variability in abstraction for irrigation, which is influenced by precipitation. Declines in precipitation in north India is linked with the Indian Ocean warming, suggesting a previously unrecognised teleconnection between ocean temperatures and groundwater storage. These results have strong implications for management of groundwater resources under current and future climate conditions in India.

Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation

NASA Astrophysics Data System (ADS)

Harzallah, A.; Rocha de Aragão, J. O.; Sadourny, R.

1996-08-01

The relationship between interannual variability of rainfall in north-east Brazil and tropical sea-surface temperature is studied using observations and model simulations. The simulated precipitation is the average of seven independent realizations performed using the Laboratoire de Météorologie Dynamique atmospheric general model forced by the 1970-1988 observed sea-surface temperature. The model reproduces very well the rainfall anomalies (correlation of 091 between observed and modelled anomalies). The study confirms that precipitation in north-east Brazil is highly correlated to the sea-surface temperature in the tropical Atlantic and Pacific oceans. Using the singular value decomposition method, we find that Nordeste rainfall is modulated by two independent oscillations, both governed by the Atlantic dipole, but one involving only the Pacific, the other one having a period of about 10 years. Correlations between precipitation in north-east Brazil during February-May and the sea-surface temperature 6 months earlier indicate that both modes are essential to estimate the quality of the rainy season.

Improved intraseasonal variability in the NASA GEOS AGCM with 2-moment microphysics and a shallow cumulus parameterization

NASA Astrophysics Data System (ADS)

Arnold, N.; Barahona, D.

2017-12-01

Atmospheric general circulation models (AGCMs) have long struggled to realistically represent tropical intraseasonal variability. Here we report progress in simulating the Madden Julian Oscillation (MJO) with the NASA Goddard Earth Observing System (GEOS) AGCM, in free-running simulations utilizing a new two-moment microphysics scheme and the University of Washington shallow cumulus parameterization. Lag composites of intraseasonal signals show significantly improved eastward propagation over the Indian Ocean and maritime region, with increased eastward precipitation variance and more coherent large-scale structure. The dynamics of the MJO are analyzed using a vertically resolved moisture budget, assuming weak temperature gradient conditions. We find that positive longwave radiative heating anomalies associated with high clouds contribute to low-level ascent and moistening, coincident with intraseasonal precipitation anomalies. Horizontal advection generally damps intraseasonal moisture anomalies, but at some longitudes contributes to their eastward tendency. Shallow convection is enhanced to the east of the intraseasonal precipitation maximum, and its associated moistening of the lower free troposphere encourages eastward propagation of deep convection.

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.

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.

Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Cloud Classification System

NASA Astrophysics Data System (ADS)

Hong, Yang

Precipitation estimation from satellite information (VISIBLE , IR, or microwave) is becoming increasingly imperative because of its high spatial/temporal resolution and board coverage unparalleled by ground-based data. After decades' efforts of rainfall estimation using IR imagery as basis, it has been explored and concluded that the limitations/uncertainty of the existing techniques are: (1) pixel-based local-scale feature extraction; (2) IR temperature threshold to define rain/no-rain clouds; (3) indirect relationship between rain rate and cloud-top temperature; (4) lumped techniques to model high variability of cloud-precipitation processes; (5) coarse scales of rainfall products. As continuing studies, a new version of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN), called Cloud Classification System (CCS), has been developed to cope with these limitations in this dissertation. CCS includes three consecutive components: (1) a hybrid segmentation algorithm, namely Hierarchically Topographical Thresholding and Stepwise Seeded Region Growing (HTH-SSRG), to segment satellite IR images into separated cloud patches; (2) a 3D feature extraction procedure to retrieve both pixel-based local-scale and patch-based large-scale features of cloud patch at various heights; (3) an ANN model, Self-Organizing Nonlinear Output (SONO) network, to classify cloud patches into similarity-based clusters, using Self-Organizing Feature Map (SOFM), and then calibrate hundreds of multi-parameter nonlinear functions to identify the relationship between every cloud types and their underneath precipitation characteristics using Probability Matching Method and Multi-Start Downhill Simplex optimization techniques. The model was calibrated over the Southwest of United States (100°--130°W and 25°--45°N) first and then adaptively adjusted to the study region of North America Monsoon Experiment (65°--135°W and 10°--50°N) using observations from Geostationary Operational Environmental Satellite (GOES) IR imagery, Next Generation Radar (NEXRAD) rainfall network, and Tropical Rainfall Measurement Mission (TRMM) microwave rain rate estimates. CCS functions as a distributed model that first identifies cloud patches and then dispatches different but the best matching cloud-precipitation function for each cloud patch to estimate instantaneous rain rate at high spatial resolution (4km) and full temporal resolution of GOES IR images (every 30-minute). Evaluated over a range of spatial and temporal scales, the performance of CCS compared favorably with GOES Precipitation Index (GPI), Universal Adjusted GPI (UAGPI), PERSIANN, and Auto-Estimator (AE) algorithms, consistently. Particularly, the large number of nonlinear functions and optimum IR-rain rate thresholds of CCS model are highly variable, reflecting the complexity of dominant cloud-precipitation processes from cloud patch to cloud patch over various regions. As a result, CCS can more successfully capture variability in rain rate at small scales than existing algorithms and potentially provides rainfall product from GOES IR-NEXARD-TRMM TMI (SSM/I) at 0.12° x 0.12° and 3-hour resolution with relative low standard error (˜=3.0mm/hr) and high correlation coefficient (˜=0.65).

Ozone Climatology for Portsmouth, NH 1978-2002

NASA Astrophysics Data System (ADS)

Wake, C. P.; Miller, S. T.

2003-12-01

Hourly ozone mixing ratios have been monitored in Portsmouth, NH since 1978 for the typical "summer" ozone season (April to October) by the New Hampshire Department of Environmental Services. This 25 year record provides the basis to investigate seasonal variability in daily summertime ozone levels in Portsmouth NH and evaluate the relationship between ozone mixing ratios, temperature, precipitation, and the state of El Niño/Southern Oscillation. The overall goal of this research is to identify significant relationships between high ozone days and a suite of climate variables. The mean daily ozone mixing ratio in Portsmouth from 1977 through 2002 was 40 ppbv (sd 17 ppbv) with a mean of 6 days per summer when maxiumum 8 hour ozone levels exceed the 80 ppbv level. The highest ozone levels usually occur during June, July and August (with a peak in July), but high ozone days also occur May and September. April and October rarely experience high ozone. High ozone in coastal New Hampshire (and for most of New England) occurs predominantly on days when maximum temperatures are above 85 oF, although there are also may hot days when ozone levels do not reach elevated levels. Analysis of the relationship between number of days per year when 8 hour ozone is greater than 80 ppbv and maximum temperatures are greater than 85 oF indicates that there is a positive correlation (r = 0.60). Surprisingly, there is not a strong inverse relationship between ozone days and precipitation. For example, over the last 25 years, 1988 clearly stands out with 20 days with maximum 8 hour ozone above 80 ppbv. However, 1988 also experienced considerable precipitation in July and August (14.1 inches compared to the climatological mean of 6.7 inches) and relatively few days without precipitation (38 compared to the climatological mean of 44). There are differences in temperature, precipitation, and ozone levels in Portsmouth during years that are classified as El Ni¤o and neutral, compared to La Nina years. However, we have only experienced one strong La Nina year in the past 25 years, so the results must be viewed with caution. The La Nina year (1988) experience high ozone and more frequent hot days, as well as double the average precipitation. El Niño years experience slightly warmer, dryer and experience more frequent ozone days, although they are not significantly different from neutral years. Our results indicate that hot summers are indeed related to higher than average ozone levels, although there is considerable variability in this relationship. There does not appear to be a consistent ozone - precipitation relationship. Further work is needed to define these relationships for a larger number of stations throughout New England and also for comparison to broader synoptic to hemispheric circulation patterns and sea surface temperatures.

Multi-scale impacts of the Pacific SST and PDO on the summer precipitation of North-Central China from 1870 to 2002

NASA Astrophysics Data System (ADS)

Bi, Shuoben; Qu, Ying; Bi, Shengjie; Wu, Weiting; Jiang, Tingting

2018-05-01

Climate variability has become a hot topic worldwide in recent years. Although large numbers of climate data series have been reconstructed based on hundreds to thousands, or even tens of thousands, of years, our understanding of this problem is still controversial. We use the precipitation index (PI) series to study the periodicity of the precipitation in northern China from 1870 to 2002 and explore the climate variability on a large timescale. The analysis shows that the precipitation has periods of 2.27-3.03, 7.14, 10.00, 11.11, 12.50, 14.29, 16.67, 20.00, and 25.00 a. Based on complete ensemble empirical mode decomposition (CEEMD), the Pacific sea surface temperature (SST) and Pacific interdecadal oscillation (PDO) are decomposed into different frequencies. The results show that the SST and PDO have interannual to interdecadal periodicity. To determine the impact of the Pacific SST and PDO on the PI, we make use of the cross wavelet power spectrum and wavelet coherency spectrum to analyze their period relation and reveal their periodic change characteristics; it is found that different bands of the Pacific SST, PDO, and PI have high power.

Tropical Pacific forcing on decadal-to-centennial NAO-dominated precipitation variability in northern Mediterranean over the past 6500 years

NASA Astrophysics Data System (ADS)

Hu, H. M.; Shen, C. C.; Michel, V.; Jiang, X.; Mii, H. S.; Wang, Y.; Valensi, P.

2017-12-01

We present a multi-annual-resolved absolute-dated stalagmite-inferred precipitation record, with age precision as good as ±2 years, from northern Italy, to reflect North Atlantic Oscillation (NAO) dynamics since 6.5 ka (thousand years ago, before 1950 C.E.). Our record features millennial precipitation fluctuations punctuated by several centennial-scale drought periods centered at 5.6, 6.2, 4.2, 3.0 and 2.3 ka. The phase relationship with previous NAO-sensitive records suggests a multi-millennial southward migration of the northern Westerlies and enhanced NAO variability from the middle- to late-Holocene. We also found the multi-decadal to centennial rainfall amount could dramatically vary within few decades, possibly affecting ancient Mediterranean civilizations. Concurrence between northern Mediterranean precipitation and western tropical Pacific sea surface temperature records suggests the remote forcing on this NAO-dominated rainfall. We argue that the irregular NAO change nowadays could be related to high frequency of El Niño-Southern Oscillation events and might cause an inevitable abrupt hydroclimate change and irreparable impacts on the regional human society in the near future.

Interannual variability of the frontal activity in the Southern Hemisphere: relationship with atmospheric circulation and precipitation over southern South America

NASA Astrophysics Data System (ADS)

Blázquez, Josefina; Solman, Silvina A.

2017-04-01

The interannual variability of the frontal activity over the western Southern Hemisphere and its linkage with the variability of the atmospheric circulation and precipitation over southern South America is studied. The analysis is focused on the austral winter and spring seasons. The frontal activity is represented by an index defined as the product between the horizontal gradient of temperature and the relative vorticity at 850 hPa (FI) and is computed from the ERA Interim and NCEP2 reanalysis. For the two seasons the main mode of variability of FI, as depicted by the first Empirical Orthogonal Function, presents centres of action located in the southern part of the western Southern Hemisphere. This pattern is present in the two reanalysis datasets. The correlation coefficients between the principal component of the leading mode of FI and the two main modes of the 500 hPa geopotential height indicate that both the ENSO-mode and the SAM modulate the leading pattern of FI in winter while during the spring season the ENSO-mode controls the FI variability. The variability of the FI has a robust influence on the interannual variability of precipitation over southern South America and adjacent oceans. Over the continent, it was found that the pattern of precipitation anomalies associated with the variability of the FI depicts significant signals over southeastern South America (SESA), centre and south of Chile for winter and over SESA and southeastern Brazil for spring and agrees with the pattern of the leading mode of precipitation variability over southern South America.

The Relationship between Hydroclimatic Variables and Faecal Indicator Bacteria in River Basins in Pakistan and Bangladesh

NASA Astrophysics Data System (ADS)

Hofstra, Nynke; Shahid Iqbal, M.; Majedul Islam, M. M.

2016-04-01

Water contaminated with pathogenic bacteria causing diarrhoea poses a health risk to the population. Worldwide, diarrhoea is the 3rd leading cause of death. A changing climate may increase the concentration of pathogens in surface water. Increased temperature will mostly increase the inactivation of pathogens and therefore decrease the surface water concentration. Increased precipitation may dilute contaminated water, but may also increase the runoff of pathogens into the surface water. Decreased precipitation may have the opposite effect. Moreover, increased chance of extreme precipitation events and increased risk of floods may also increase the runoff of pathogens into the surface water. The net balance of these effects is uncertain. The objective of our study is to quantify the relationship between hydroclimatic variables (surface air and water temperature, precipitation and runoff) and faecal indicator bacteria (FIB, E. coli and Enterococci) in two rivers in Pakistan and Bangladesh. In these countries health problems are large, particularly in annual periods of flood. We studied FIB instead of pathogens, because of the costs associated with pathogen measurements. The relationship between FIB and hydroclimatic variables is expected to be comparable to the relationship between pathogens and hydroclimatic variables. For both regions the FIB concentrations have been monitored for two years between 2013 and 2015 at several points in the rivers. Concentrations of FIB in Kabul (Pakistan) and Betna (Bangladesh) river basins are very high (up to 5.2 log10 cfu/100ml). Due to a broken waste water treatment system of the city of Peshawar, concentrations are higher in Kabul than in the Betna river. All hydroclimatic variables positively correlate with FIB. An unexpected positive relation with temperature can be explained by the fact that temperature and discharge increase at the same time and possibly FIB growth. The positive relation with precipitation and discharge shows that not the dilution, but the increased runoff of FIB is more important. Regression models for each of the measurement locations in Kabul river show that water temperature, discharge and precipitation together explain a large part of the variance (R2 equals 0.72-0.94) for E. coli. The regression model for Betna river comprises water temperature and discharge and for E. coli R2=0.47 and for Enterococci R2=0.49. We can conclude that FIB concentrations increase with increasing temperature and particularly precipitation and discharge. We expect pathogen concentrationss to increase in a similar way and would therefore expect increased health risk due to climate change in Kabul and Betna river basins.

On the fall 2010 Enhancements of the Global Precipitation Climatology Centre's Data Sets

NASA Astrophysics Data System (ADS)

Becker, A. W.; Schneider, U.; Meyer-Christoffer, A.; Ziese, M.; Finger, P.; Rudolf, B.

2010-12-01

Precipitation is meanwhile a top listed parameter on the WMO GCOS list of 44 essential climate variables (ECV). This is easily justified by its crucial role to sustain any form of life on earth as major source of fresh water, its major impact on weather, climate, climate change and related issues of society’s adaption to the latter. Finally its occurrence is highly variable in space and time thus bearing the potential to trigger major flood and draught related disasters. Since its start in 1989 the Global precipitation Climatology Centre (GPCC) performs global analyses of monthly precipitation for the earth’s land-surface on the basis of in-situ measurements. The effort was inaugurated as part of the Global Precipitation Climatology Project of the WMO World Climate Research Program (WCRP). Meanwhile, the data set has continuously grown both in temporal coverage (original start of the evaluation period was 1986), as well as extent and quality of the underlying data base. The number of stations involved in the related data base has approximately doubled in the past 8 years by trespassing the 40, 60 and 80k thresholds in 2002, 2006 and 2010. Core data source of the GPCC analyses are the data from station networks operated by the National Meteorological Services worldwide; data deliveries have been received from ca. 190 countries. The GPCC integrates also other global precipitation data collections (i.e. FAO, CRU and GHCN), as well as regional data sets. Currently the Africa data set from S. Nicholson (Univ. Tallahassee) is integrated. As a result of these efforts the GPCC holds the worldwide largest and most comprehensive collection of precipitation data, which is continuously updated and extended. Due to the high spatial-temporal variability of precipitation, even its global analysis requires this high number of stations to provide for a sufficient density of measurement data on almost any place on the globe. The acquired data sets are pre-checked, reformatted and then imported into a relational data base, where they are archived separately in source specific slots, thus allowing an inter-comparison of data from the different sources. Any time new data sets are imported to the data base the metadata in the input data set are compared to those already available in the data base. In case of discrepancies (e.g. deviating coordinates), external geographical sources of information are utilized to decide whether a correction of the metadata in the data base is required or not, thus resulting in a perpetual improvement of the station meta data. The presentation shall give an account on the four major products derived from the GPCC data base, which are two near real-time ones comprising the precipitation data retrieved from the GTS, and two offline products that allow for hydro-climatological assessments. The real-time products are used for example to calibrate Satellite based precipitation measurements. To illustrate the potential of the offline (Full Data) products we will present an asessment of the strong 2010 La Nina season that has apparently caused severe weather patterns world wide, including the flood disasters in Pakistan and Wuhan, China.

Long Term Ground Based Precipitation Data Analysis in California's 7 Climate Divisions: Spatial and Temporal Variability

NASA Astrophysics Data System (ADS)

Rodriguez, L.; El-Askary, H. M.; Rakovski, C.; Allai, M.

2015-12-01

California is an area of diverse topography and has what many scientists call a Mediterranean climate. Various precipitation patterns exist due to El Niño Southern Oscillation (ENSO) which can cause abnormal precipitation or droughts. As temperature increases mainly due to the increase of CO2 in the atmosphere, it is rapidly changing the climate of not only California but the world. An increase in temperature is leading to droughts in certain areas as other areas are experiencing heavy rainfall/flooding. Droughts in return are providing a foundation for fires harming the ecosystem and nearby population. Various natural hazards can be induced due to the coupling effects from inconsistent precipitation patterns and vice versa. Using wavelets and ARIMA modeling, we were able to identify anomalies of high precipitation and droughts within California's 7 climate divisions using NOAA's hourly precipitation data from rain gauges and compared the results with modeled data, SOI, PDO, and AMO. The identification of anomalies can be used to compare and correct remote sensing measurements of precipitation and droughts.

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.

Diverse multi-decadal changes in streamflow within a rapidly urbanizing region

NASA Astrophysics Data System (ADS)

Diem, Jeremy E.; Hill, T. Chee; Milligan, Richard A.

2018-01-01

The impact of urbanization on streamflow depends on a variety of factors (e.g., climate, initial land cover, inter-basin transfers, water withdrawals, wastewater effluent, etc.). The purpose of this study is to examine trends in streamflow from 1986 to 2015 in a range of watersheds within the rapidly urbanizing Atlanta, GA metropolitan area. This study compares eight watersheds over three decades, while minimizing the influence of inter-annual precipitation variability. Population and land-cover data were used to analyze changes over approximately twenty years within the watersheds. Precipitation totals for the watersheds were estimated using precipitation totals at nearby weather stations. Multiple streamflow variables, such as annual streamflow, frequencies of high-flow days (HFDs), flashiness, and precipitation-adjusted streamflow, for the eight streams were calculated using daily streamflow data. Variables were tested for significant trends from 1986 to 2015 and significant differences between 1986-2000 and 2001-2015. Flashiness increased for all streams without municipal water withdrawals, and the four watersheds with the largest increase in developed land had significant increases in flashiness. Significant positive trends in precipitation-adjusted mean annual streamflow and HFDs occurred for the two watersheds (Big Creek and Suwanee Creek) that experienced the largest increases in development, and these were the only watersheds that went from majority forest land in 1986 to majority developed land in 2015. With a disproportionate increase in HFD occurrence during summer, Big Creek and Suwannee Creek also had a reduction in intra-annual variability of HFD occurrence. Watersheds that were already substantially developed at the beginning of the period and did not have wastewater discharge had declining streamflow. The most urbanized watershed (Peachtree Creek) had a significant decrease in streamflow, and a possible cause of the decrease was increasing groundwater infiltration into sewers. The impacts of urbanization on streamflow within the metropolitan area have undoubtedly been felt by a wide of range of communities.

Variability, trends, and drivers of regional fluctuations in Australian fire activity

NASA Astrophysics Data System (ADS)

Earl, Nick; Simmonds, Ian

2017-07-01

Throughout the world fire regimes are determined by climate, vegetation, and anthropogenic factors, and they have great spatial and temporal variability. The availability of high-quality satellite data has revolutionized fire monitoring, allowing for a more consistent and comprehensive evaluation of temporal and spatial patterns. Here we utilize a satellite based "active fire" (AF) product to statistically analyze 2001-2015 variability and trends in Australian fire activity and link this to precipitation and large-scale atmospheric structures (namely, the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD)) known to have potential for predicting fire activity in different regions. It is found that Australian fire activity is decreasing (during summer (December-February)) or stable, with high temporal and spatial variability. Eastern New South Wales (NSW) has the strongest decreasing trend (to the 1% confidence level), especially during the winter (JJA) season. Other significantly decreasing areas are Victoria/NSW, Tasmania, and South-east Queensland. These decreasing fire regions are relatively highly populated, so we suggest that the declining trends are due to improved fire management, reducing the size and duration of bush fires. Almost half of all Australian AFs occur during spring (September-November). We show that there is considerable potential throughout Australia for a skillful forecast for future season fire activity based on current and previous precipitation activity, ENSO phase, and to a lesser degree, the IOD phase. This is highly variable, depending on location, e.g., the IOD phase is for more indicative of fire activity in southwest Western Australia than for Queensland.

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.

Hydroclimate variability in NE Brazil over the last 2K

NASA Astrophysics Data System (ADS)

Giselle, Utida; Ioanna, Bouloubassi; Francisco, Cruz; Enno, Schefuβ; Abdel, Sifeddine; Vincent, Klein; Johan, Etourneau; Renata, Zocatelli; André, Zular; Hai, Cheng; Laurence, Edwards R.

2016-04-01

Precipitation associated with the South American Summer Monsoon (SASM) and the Intertropical Convergence Zone (ITCZ) supplies more than 70% of tropical South America's annual precipitation and is fundamental in sustaining the water regime for regional socioeconomic activities. Motivated by the fact that the greatest uncertainty in model projections of future precipitation trends lies in the tropics, and particularly in South America, a number of recent proxy and modeling studies have aimed at understanding SASM spatiotemporal variability regarding its dynamics, driving mechanisms and teleconnections. Exact reconstructions of past meridional ITCZ displacements (timing, sign, amplitude), however, are currently lacking, mainly because of the paucity of suited high-resolution archives. This restricts our ability to assess regional rainfall variability at decadal to centennial timescales, especially in the hydroclimatic-sensitive semi-arid Nordeste, needed to understand the interactions between SASM and ITCZ and to evaluate the impact of Pacific-Atlantic climate interactions on the regional rainfall variability at decadal/multi-decadal scale. Here we present two new and complementary high-resolution records of past precipitation over the last 2K from the north area of Nordeste, an area ideally located to track fluctuations in the southernmost edge of ITCZ movement. We present a new δO18 record from a local speleothem and combine it, for the first time, with δD analyses of wax lipids in well-dated sediments from a nearby lake. The two independent records show a remarkable similarity and are characterized by strong decadal to multidecadal variability as well as century-scale changes. The period 250-450 yrs CE appears as the wettest phase over the last 2K, while the Medieval Climate Anomaly (MCA) is characterized by extremely dry conditions. Following the MCA, the Little Ice Age (LIA) is a relatively wetter phase. The data document fluctuations of southern meridional ITCZ movements during the last millennium that compare well with available records of fluctuations in northern ITCZ extension (Cariaco Basin). Comparisons to proxy records from tropical South America regions affected by the SASM and the South America Convergence Zone (SACZ) allow evaluating the SAMS/SACZ-ITCZ linkages. Furthermore, the data are discussed in terms of the role of the Atlantic and Pacific modes of variability in modulating regional hydroclimate.

Streamflow characteristics and trends in New Jersey, water years 1897-2003

USGS Publications Warehouse

Watson, Kara M.; Reiser, Robert G.; Nieswand, Steven P.; Schopp, Robert D.

2005-01-01

Streamflow statistics were computed for 111 continuous-record streamflow-gaging stations with 20 or more years of continuous record and for 500 low-flow partial-record stations, including 66 gaging stations with less than 20 years of continuous record. Daily mean streamflow data from water year 1897 through water year 2001 were used for the computations at the gaging stations. (The water year is the 12-month period, October 1 through September 30, designated by the calendar year in which it ends). The characteristics presented for the long-term continuous-record stations are daily streamflow, harmonic mean flow, flow frequency, daily flow durations, trend analysis, and streamflow variability. Low-flow statistics for gaging stations with less than 20 years of record and for partial-record stations were estimated by correlating base-flow measurements with daily mean flows at long-term (more than 20 years) continuous-record stations. Instantaneous streamflow measurements through water year 2003 were used to estimate low-flow statistics at the partial-record stations. The characteristics presented for partial-record stations are mean annual flow; harmonic mean flow; and annual and winter low-flow frequency. The annual 1-, 7-, and 30-day low- and high-flow data sets were tested for trends. The results of trend tests for high flows indicate relations between upward trends for high flows and stream regulation, and high flows and development in the basin. The relation between development and low-flow trends does not appear to be as strong as for development and high-flow trends. Monthly, seasonal, and annual precipitation data for selected long-term meteorological stations also were tested for trends to analyze the effects of climate. A significant upward trend in precipitation in northern New Jersey, Climate Division 1 was identified. For Climate Division 2, no general increase in average precipitation was observed. Trend test results indicate that high flows at undeveloped, unregulated sites have not been affected by the increase in average precipitation. The ratio of instantaneous peak flow to 3-day mean flow, ratios of flow duration, ratios of high-flow/low-flow frequency, and coefficient of variation were used to define streamflow variability. Streamflow variability was significantly greater among the group of gaging stations located outside the Coastal Plain than among the group of gaging stations located in the Coastal Plain.

Impacts of the EA and SCA patterns on the 20th century NAO-winter precipitation relationship in Europe

NASA Astrophysics Data System (ADS)

Comas-Bru, Laia; McDermott, Frank

2013-04-01

Much of the 20th century multi-decadal variability in the NAO-winter precipitation relationship over the N. Atlantic / European sector can be ascribed to the combined effects of the North Atlantic Oscillation (NAO) and either the East Atlantic pattern (EA) or the Scandinavian pattern (SCA). The NAO, EA and SCA indices employed here are defined as the three leading vectors of the cross-correlation matrix calculated from monthly sea-level pressure anomalies for 138 complete winters from the 20CRv2 dataset (Compo et al., 2011). Winter precipitation data over Europe for the entire 20th century is derived from the high resolution CRU-TS3.1 climate dataset (Mitchell and Jones, 2005). Here we document for the first time, that different NAO/EA and NAO/SCA combinations systematically influence winter precipitation conditions in Europe as a consequence of NAO dipole migrations. We find that the zero-correlated line of the NAO-winter precipitation relationship migrates southwards when the EA is in the opposite phase to the NAO. This can be related to a south-westwards migration of the NAO dipole under these conditions, as shown by teleconnectivity maps. Similarly, a clockwise movement of the NAO-winter climate correlated areas occurs when the phase of the SCA is opposite to that of the NAO, reflecting a clockwise movement of the NAO dipole under these conditions. An important implication of these migrations is that they influence the spatial and temporal stationarity of climate-NAO relationships. As a result, the link between winter precipitation patterns and the NAO is not straightforward in some regions such as the southern UK, Ireland and France. For instance, much of the inter-annual variability in the N-S winter precipitation gradient in the UK, originally attributed to inter-annual and inter-decadal variability of the NAO, reflects the migration of the NAO dipole, linked to linear combinations of the NAO and the EA. Our results indicate that when the N-S winter precipitation gradient is accentuated by the occurrence of a positive EA during positive NAO winters, drier conditions than normal are found in the southern UK. This is consistent, for example, with the severe winter drought of 1976, when computed NAO and EA indices were both positive (0.97 and 1.87, respectively), illustrating the modulating effect of NAO/EA combinations on winter precipitation patterns in the southern UK. References: Compo GP et al. 2011. The Twentieth Century Reanalysis Project. Quarterly Journal of the Royal Meteorological Society, 137 (654), 1-28. Mitchell TD, Jones PD. 2005. An improved method for constructing a database of monthly climate observations and associated high-resolution grids. International Journal of Climatology, 25, 693-712.

Impact of climate variability on runoff in the north-central United States

USGS Publications Warehouse

Ryberg, Karen R.; Lin, Wei; Vecchia, Aldo V.

2014-01-01

Large changes in runoff in the north-central United States have occurred during the past century, with larger floods and increases in runoff tending to occur from the 1970s to the present. The attribution of these changes is a subject of much interest. Long-term precipitation, temperature, and streamflow records were used to compare changes in precipitation and potential evapotranspiration (PET) to changes in runoff within 25 stream basins. The basins studied were organized into four groups, each one representing basins similar in topography, climate, and historic patterns of runoff. Precipitation, PET, and runoff data were adjusted for near-decadal scale variability to examine longer-term changes. A nonlinear water-balance analysis shows that changes in precipitation and PET explain the majority of multidecadal spatial/temporal variability of runoff and flood magnitudes, with precipitation being the dominant driver. Historical changes in climate and runoff in the region appear to be more consistent with complex transient shifts in seasonal climatic conditions than with gradual climate change. A portion of the unexplained variability likely stems from land-use change.

Long-term climate patterns in Alaskan surface temperature and precipitation and their biological consequences

USGS Publications Warehouse

Simpson, James J.; Hufford, Gary L.; Fleming, Michael D.; Berg, Jared S.; Ashton, J.B.

2002-01-01

Mean monthly climate maps of Alaskan surface temperature and precipitation produced by the parameter-elevation regression on independent slopes model (PRISM) were analyzed. Alaska is divided into interior and coastal zones with consistent but different climatic variability separated by a transition region; it has maximum interannual variability but low long-term mean variability. Pacific decadal oscillation (PDO)- and El Nino Southern Oscillation (ENSO)-type events influence Alaska surface temperatures weakly (1-2/spl deg/C) statewide. PDO has a stronger influence than ENSO on precipitation but its influence is largely localized to coastal central Alaska. The strongest influence of Arctic oscillation (AO) occurs in northern and interior Alaskan precipitation. Four major ecosystems are defined. A major eco-transition zone occurs between the interior boreal forest and the coastal rainforest. Variability in insolation, surface temperature, precipitation, continentality, and seasonal changes in storm track direction explain the mapped ecosystems. Lack of westward expansion of the interior boreal forest into the western shrub tundra is influenced by the coastal marine boundary layer (enhanced cloud cover, reduced insolation, cooler surface and soil temperatures).

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

NASA Astrophysics Data System (ADS)

Frauenfeld, O. W.; Chen, L.

2013-12-01

Precipitation represents an important link between the atmosphere, hydrosphere, and biosphere and is thus a key component of the climate system. As indicated by the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), global surface air temperatures increased by 0.74°C during the 20th century, with further warming of 0.2°C/decade projected by the 2030s. Projected changes in precipitation, however, are much more variable, and exhibit more complex temporal and spatial patterns. This presentation focuses on precipitation variability based on 20 general circulation models (GCMs) participating in the fifth coupled model intercomparison project (CMIP5). Specifically, we focus on China and provide a comprehensive evaluation of the CMIP5 models compared to historical 20th century precipitation variability from two observational precipitation products: the University of East Anglia's Climatic Research Unit (CRU) time series (TS) dataset version 3.10, and the Global Precipitation Climatology Centre (GPCC) version 6. We also reassess the performance of the third CMIP (CMIP3) to quantify potential improvements in CMIP5 over the previous generation of GCMs. Finally, we provide 21st century precipitation projections for China based on three representative concentration pathways (RCP): RCP 8.5, 4.5, and 2.6. These future precipitation projections are presented in light of the observed 20th century biases in the models. We find that CMIP5 models are able to better reproduce the general spatial pattern of observed 20th century precipitation than CMIP3. However, for China as a whole, the annual precipitation magnitude is overestimated in CMIP5, more so than in CMIP3. This smaller overestimation in CMIP3 was primarily driven by a large underestimation of summer precipitation. Spatially, overestimated precipitation magnitudes are evident for most regions of China, especially along the eastern margin of the Tibetan Plateau. Over southeastern China during summer, the precipitation amounts are underestimated. The multidecadal precipitation variability in CMIP5 is muted relative to observations, but improved when compared to CMIP3. We also assess precipitation trends and correlations relative to observations, and again find better agreement for CMIP5 than for CMIP3. Both observations and models indicated precipitation increases over parts of northwestern China, and decreases over the Tibetan Plateau throughout the 20th century. However, for the southeastern and northern regions of China there is poor agreement in precipitation trends. Precipitation is projected to increase across all of China under all the three emission scenarios during the 21st century. The largest significant trend is evident for RCP 8.5, which projects a precipitation increase of 1.5 mm/year, resulting in a 16% increase in precipitation by the end of the century. The smallest increases are projected to occur under the RCP 2.6 scenario, resulting in only a +6% change by 2100. The regions of greatest precipitation increases are the Tibetan Plateau and eastern China during summer, suggesting a potential change in the monsoonal circulation in the future.

[Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].

PubMed

Rúa-Uribe, Guillermo L; Suárez-Acosta, Carolina; Chauca, José; Ventosilla, Palmira; Almanza, Rita

2013-09-01

Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease. To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease. The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models. The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay. In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.

Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

NASA Astrophysics Data System (ADS)

Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

2017-08-01

Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

Climate controls on streamflow variability in the Missouri River Basin

NASA Astrophysics Data System (ADS)

Wise, E.; Woodhouse, C. A.; McCabe, G. J., Jr.; Pederson, G. T.; St-Jacques, J. M.

2017-12-01

The Missouri River's hydroclimatic variability presents a challenge for water managers, who must balance many competing demands on the system. Water resources in the Missouri River Basin (MRB) have increasingly been challenged by the droughts and floods that have occurred over the past several decades and the potential future exacerbation of these extremes by climate change. Here, we use observed and modeled hydroclimatic data and estimated natural flow records to describe the climatic controls on streamflow in the upper and lower portions of the MRB, examine atmospheric and oceanic patterns associated with high- and low-flow years, and investigate trends in climate and streamflow over the instrumental period. Results indicate that the two main source regions for total outflow, in the uppermost and lowermost parts of the basin, are under the influence of very different sets of climatic controls. Winter precipitation, impacted by changes in zonal versus meridional flow from the Pacific Ocean, as well as spring precipitation and temperature, play a key role in surface water supply variability in the upper basin. Lower basin flow is significantly correlated with precipitation in late spring and early summer, indicative of Atlantic-influenced circulation variability affecting the flow of moisture from the Gulf of Mexico. The upper basin, with decreasing snowpack and streamflow and warming spring temperatures, will be less likely to provide important flow supplements to the lower basin in the future.

Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections.

Sub-daily Statistical Downscaling of Meteorological Variables Using Neural Networks

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

Kumar, Jitendra; Brooks, Bjørn-Gustaf J.; Thornton, Peter E

2012-01-01

A new open source neural network temporal downscaling model is described and tested using CRU-NCEP reanal ysis and CCSM3 climate model output. We downscaled multiple meteorological variables in tandem from monthly to sub-daily time steps while also retaining consistent correlations between variables. We found that our feed forward, error backpropagation approach produced synthetic 6 hourly meteorology with biases no greater than 0.6% across all variables and variance that was accurate within 1% for all variables except atmospheric pressure, wind speed, and precipitation. Correlations between downscaled output and the expected (original) monthly means exceeded 0.99 for all variables, which indicates thatmore » this approach would work well for generating atmospheric forcing data consistent with mass and energy conserved GCM output. Our neural network approach performed well for variables that had correlations to other variables of about 0.3 and better and its skill was increased by downscaling multiple correlated variables together. Poor replication of precipitation intensity however required further post-processing in order to obtain the expected probability distribution. The concurrence of precipitation events with expected changes in sub ordinate variables (e.g., less incident shortwave radiation during precipitation events) were nearly as consistent in the downscaled data as in the training data with probabilities that differed by no more than 6%. Our downscaling approach requires training data at the target time step and relies on a weak assumption that climate variability in the extrapolated data is similar to variability in the training data.« less

Frequencies and Characteristics of Global Oceanic Precipitation from Shipboard Present-Weather Reports

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1995-01-01

Ship reports of present weather obtained from the Comprehensive Ocean-Atmosphere Data Set are analyzed for the period 1958-91 in order to elucidate regional and seasonal variations in the climatological frequency, phase, intensity, and character of oceanic precipitation. Specific findings of note include the following: 1) The frequency of thunderstorm reports, relative to all precipitation reports, is a strong function of location, with thunderstorm activity being favored within 1000-3000 km of major tropical and subtropical land masses, while being quite rare at other locations, even within the intertropical convergence zone. 2) The latitudinal frequency of precipitation over the southern oceans increases steadily toward the Antarctic continent and shows relatively little seasonal variation. The frequency of convective activity, however, shows considerable seasonal variability, with sharp winter maxima occurring near 38 deg. latitude in both hemispheres. 3) Drizzle is the preferred form of precipitation in a number of regions, most of which coincide with known regions of persistent marine stratus and stratocumulus in the subtropical highs. Less well documented is the high relative frequency of drizzle in the vicinity of the equatorial sea surface temperature front in the eastern Pacific. 4) Regional differences in the temporal scale of precipitation events (e.g., transient showers versus steady precipitation) are clearly depicted by way of the ratio of the frequency of precipitation at the observation time to the frequency of all precipitation reports, including precipitation during the previous hour. The results of this study suggest that many current satellite rainfall estimation techniques may substantially underestimate the fractional coverage or frequency of precipitation poleward of 50 deg. latitude and in the subtropical dry zones. They also draw attention to the need to carefully account for regional differences in the physical and spatial properties of rainfall when developing calibration relationships for satellite algorithms.

Variations in the Relationship Between Precipitation and Tree Growth in the North-Central Rocky Mountains Identified Using a Tree-Ring Network

NASA Astrophysics Data System (ADS)

Wise, E.

2007-12-01

Much of the western United States is in the midst of a multi-year drought that has placed a renewed sense of urgency on water availability issues. The characterization of variability over relevant space and time scales has emerged as one of the top needs concerning the hydrological cycle, but understanding hydroclimatic variability at decadal and longer time scales has been limited by instrumental data that are both spatially and temporally inadequate. The reconstruction of moisture variables from tree-rings has been recognized as an important source of information on long-term water supply variability. Moisture variables of interest may include annual precipitation, snowpack, summer precipitation, and streamflow. Trees in closely co-located sites can vary widely in the signal they reflect, particularly in a region with the complex topography and hydroclimatic variability that is seen in the north-central Rocky Mountains. In this study, climatic and geospatial information was combined with tree-ring chronologies in order to better-understand factors determining variations in the response of tree growth to a particular precipitation signal. Resulting spatial variability in moisture seasonality and growth response provide insight into the region's moisture patterns and better characterization of the region's hydroclimatic variability.

Spatial patterns of soil moisture connected to monthly-seasonal precipitation variability in a monsoon region

Treesearch

Yongqiang Liu

2003-01-01

The relations between monthly-seasonal soil moisture and precipitation variability are investigated by identifying the coupled patterns of the two hydrological fields using singular value decomposition (SVD). SVD is a technique of principal component analysis similar to empirical orthogonal knctions (EOF). However, it is applied to two variables simultaneously and is...

Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

NASA Astrophysics Data System (ADS)

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

2018-01-01

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

Effects of 4D-Var data assimilation using remote sensing precipitation products in a WRF over the complex Heihe River Basin

NASA Astrophysics Data System (ADS)

Pan, Xiaoduo; Li, Xin; Cheng, Guodong

2017-04-01

Traditionally, ground-based, in situ observations, remote sensing, and regional climate modeling, individually, cannot provide the high-quality precipitation data required for hydrological prediction, especially over complex terrain. Data assimilation techniques are often used to assimilate ground observations and remote sensing products into models for dynamic downscaling. In this study, the Weather Research and Forecasting (WRF) model was used to assimilate two satellite precipitation products (TRMM 3B42 and FY-2D) using the 4D-Var data assimilation method. The results show that the assimilation of remote sensing precipitation products can improve the initial WRF fields of humidity and temperature, thereby improving precipitation forecasting and decreasing the spin-up time. Hence, assimilating TRMM and FY-2D remote sensing precipitation products using WRF 4D-Var can be viewed as a positive step toward improving the accuracy and lead time of numerical weather prediction models, particularly for short-term weather forecasting. Future work is proposed to assimilate a suite of remote sensing data, e.g., the combination of precipitation and soil moisture data, into a WRF model to improve 7-8 day forecasts of precipitation and other atmospheric variables.

Variability and predictability of decadal mean temperature and precipitation over China in the CCSM4 last millennium simulation

NASA Astrophysics Data System (ADS)

Ying, Kairan; Frederiksen, Carsten S.; Zheng, Xiaogu; Lou, Jiale; Zhao, Tianbao

2018-02-01

The modes of variability that arise from the slow-decadal (potentially predictable) and intra-decadal (unpredictable) components of decadal mean temperature and precipitation over China are examined, in a 1000 year (850-1850 AD) experiment using the CCSM4 model. Solar variations, volcanic aerosols, orbital forcing, land use, and greenhouse gas concentrations provide the main forcing and boundary conditions. The analysis is done using a decadal variance decomposition method that identifies sources of potential decadal predictability and uncertainty. The average potential decadal predictabilities (ratio of slow-to-total decadal variance) are 0.62 and 0.37 for the temperature and rainfall over China, respectively, indicating that the (multi-)decadal variations of temperature are dominated by slow-decadal variability, while precipitation is dominated by unpredictable decadal noise. Possible sources of decadal predictability for the two leading predictable modes of temperature are the external radiative forcing, and the combined effects of slow-decadal variability of the Arctic oscillation (AO) and the Pacific decadal oscillation (PDO), respectively. Combined AO and PDO slow-decadal variability is associated also with the leading predictable mode of precipitation. External radiative forcing as well as the slow-decadal variability of PDO are associated with the second predictable rainfall mode; the slow-decadal variability of Atlantic multi-decadal oscillation (AMO) is associated with the third predictable precipitation mode. The dominant unpredictable decadal modes are associated with intra-decadal/inter-annual phenomena. In particular, the El Niño-Southern Oscillation and the intra-decadal variability of the AMO, PDO and AO are the most important sources of prediction uncertainty.

Intraseasonal SST-precipitation coupling during the Indian Summer Monsoon, and its modulation by the Indian Ocean Dipole

NASA Astrophysics Data System (ADS)

Jongaramrungruang, S.; Seo, H.; Ummenhofer, C.

2016-02-01

The Indian Summer Monsoon (ISM) plays a crucial role in shaping the large proportion of the total precipitation over the Indian subcontinent each year. The ISM rainfall exhibits a particularly strong intraseasonal variability, that has profound socioeconomic consequences, such as agricultural planning and flood preparation. However, our understanding of the variability on this time scale is still limited due to sparse data availability in the past. In this study, we used a combination of state-of-the-art high-resolution satellite estimate of rainfall, objectively analyzed surface flux, as well as atmospheric reanalysis product to investigate the nature of the ISM intraseasonal rainfall variability and how it varies year to year. The emphasis is placed on the Bay of Bengal (BoB) where the intraseasonal ocean-atmosphere coupling is most prominent. Results show that the maximum warming of SST leads the onset of heavy precipitation event by 3-5 days, and that surface heat flux and surface wind speed are weak prior to the rain but amplifies and peaks after the rain reaches its maximum. Furthermore, the Indian Ocean Dipole (IOD) significantly affects the observed intraseasonal SST-precipitation relationship. The pre-convection SST warming is stronger and more pronounced during the negative phase of the IOD, while the signal is weaker and less organized in the positive phase. This is explained by the column-integrated moisture budget analysis which reveals that, during the ISM heavy rainfall in the BoB, there is more moisture interchange in the form of enhanced vertical advection from the ocean to atmosphere in negative IOD years as compared to positive IOD years. Knowing the distinction of ISM variabilities during opposite phases of the IOD will help contribute to a more reliable prediction of ISM activities.

Contrasting precipitation seasonality influences evapotranspiration dynamics in water-limited shrublands

NASA Astrophysics Data System (ADS)

Villarreal, Samuel; Vargas, Rodrigo; Yepez, Enrico A.; Acosta, Jose S.; Castro, Angel; Escoto-Rodriguez, Martin; Lopez, Eulogio; Martínez-Osuna, Juan; Rodriguez, Julio C.; Smith, Stephen V.; Vivoni, Enrique R.; Watts, Christopher J.

2016-02-01

Water-limited ecosystems occupy nearly 30% of the Earth, but arguably, the controls on their ecosystem processes remain largely uncertain. We analyzed six site years of eddy covariance measurements of evapotranspiration (ET) from 2008 to 2010 at two water-limited shrublands: one dominated by winter precipitation (WP site) and another dominated by summer precipitation (SP site), but with similar solar radiation patterns in the Northern Hemisphere. We determined how physical forcing factors (i.e., net radiation (Rn), soil water content (SWC), air temperature (Ta), and vapor pressure deficit (VPD)) influence annual and seasonal variability of ET. Mean annual ET at SP site was 455 ± 91 mm yr-1, was mainly influenced by SWC during the dry season, by Rn during the wet season, and was highly sensitive to changes in annual precipitation (P). Mean annual ET at WP site was 363 ± 52 mm yr-1, had less interannual variability, but multiple variables (i.e., SWC, Ta, VPD, and Rn) were needed to explain ET among years and seasons. Wavelet coherence analysis showed that ET at SP site has a consistent temporal coherency with Ta and P, but this was not the case for ET at WP site. Our results support the paradigm that SWC is the main control of ET in water-limited ecosystems when radiation and temperature are not the limiting factors. In contrast, when P and SWC are decoupled from available energy (i.e., radiation and temperature), then ET is controlled by an interaction of multiple variables. Our results bring attention to the need for better understanding how climate and soil dynamics influence ET across these globally distributed ecosystems.

Climate and land use change in an Andean watershed: An NDVI analysis for the years 1985 to 2010

NASA Astrophysics Data System (ADS)

Mazzarino, M.; Finn, J.

2013-12-01

We perform a Landsat 5-TM derived Normalized Difference Vegetation Index (NDVI) analysis in a watershed (approximately 2700 km2) in southern Peru for the years 1985 through 2010. There in the Andes the livelihoods of the predominately Quechua speaking agro-pastoralists depend on access to natural resources. Vegetation within high-elevation wetlands, locally known as bofedales, is a critical resource that sustains herds of alpaca, sheep, and cattle especially during dry season months (June through August) and in drought. The watershed experiences high inter-annual variability in precipitation (attributed to the El Niño Southern Oscillation) and there are documented increases in air temperature and glacier retreat throughout the Andes. Using one dry-season scene per year for 20 of the 26 years from 1985 to 2010, we calculated NDVI for each pixel in the watershed and used these calculations to perform three objectives. First, we calculated mean NDVI for the Nuñoa watershed for each dry season scene. Using this annual watershed averaged NDVI as the response variable we performed a multiple linear regression with the covariates year, precipitation, and temperature in order to determine the relationship between the response and explanatory variables and if there is a trend in mean watershed dry-season NDVI from 1985 to 2010. Second, we delineated the wetlands (bofedales) based on a threshold value applied to the 26 year dry-season mean NDVI for each pixel in the watershed. Third, we performed a multiple linear regression for each pixel in the watershed (3,070,160) using cell specific annual dry-season NDVI as the response variable (n=20) and year, regional precipitation, and regional temperature indices as the predictor variables in order to review the spatial nature of NDVI changes in vegetation in the watershed throughout time (1985-2010), particularly with respect to bofedales. The results of these analyses indicate that there is reduced variability in dry season NDVI and a general increase in NDVI values in the watershed with time. Variability in mean dry season NDVI is highly correlated with wet season (DJFM) precipitation (R2 = 0.77, p-value < 0.05) and this relationship may explain much of the shift in NDVI values however; the increasing trend in NDVI in the watershed is not explained by a trend in precipitation. We were not able to determine a relationship between NDVI and temperature with our methods. And while an increase in dry-season NDVI is seen in the majority of the vegetated pixels (81%) throughout the watershed, approximately 30% of the wetland areas display a decrease in NDVI over the time period. Contemporary socio-political factors and resulting changes in land management and production systems in the region may be resulting in more intensive use of wetland areas, thereby causing the decreasing vegetation trends seen there. These factors, together with potential reductions in glacier melt from several small ice-capped mountains in the north of the study area may all be contributing to the spatial and temporal changes in NDVI seen in the watershed.

Large scale meteorological patterns and moisture sources during precipitation extremes over South Asia

NASA Astrophysics Data System (ADS)

Mehmood, S.; Ashfaq, M.; Evans, K. J.; Black, R. X.; Hsu, H. H.

2017-12-01

Extreme precipitation during summer season has shown an increasing trend across South Asia in recent decades, causing an exponential increase in weather related losses. Here we combine a cluster analyses technique (Agglomerative Hierarchical Clustering) with a Lagrangian based moisture analyses technique to investigate potential commonalities in the characteristics of the large scale meteorological patterns (LSMP) and moisture anomalies associated with the observed extreme precipitation events, and their representation in the Department of Energy model ACME. Using precipitation observations from the Indian Meteorological Department (IMD) and Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE), and atmospheric variables from Era-Interim Reanalysis, we first identify LSMP both in upper and lower troposphere that are responsible for wide spread precipitation extreme events during 1980-2015 period. For each of the selected extreme event, we perform moisture source analyses to identify major evaporative sources that sustain anomalous moisture supply during the course of the event, with a particular focus on local terrestrial moisture recycling. Further, we perform similar analyses on two sets of five-member ensemble of ACME model (1-degree and ¼ degree) to investigate the ability of ACME model in simulating precipitation extremes associated with each of the LSMP patterns and associated anomalous moisture sourcing from each of the terrestrial and oceanic evaporative region. Comparison of low and high-resolution model configurations provides insight about the influence of horizontal grid spacing in the simulation of extreme precipitation and the governing mechanisms.

Modeled intermittency risk for small streams in the Upper Colorado River Basin under climate change

USGS Publications Warehouse

Reynolds, Lindsay V.; Shafroth, Patrick B.; Poff, N. LeRoy

2015-01-01

Longer, drier summers projected for arid and semi-arid regions of western North America under climate change are likely to have enormous consequences for water resources and river-dependent ecosystems. Many climate change scenarios for this region involve decreases in mean annual streamflow, late summer precipitation and late-summer streamflow in the coming decades. Intermittent streams are already common in this region, and it is likely that minimum flows will decrease and some perennial streams will shift to intermittent flow under climate-driven changes in timing and magnitude of precipitation and runoff, combined with increases in temperature. To understand current intermittency among streams and analyze the potential for streams to shift from perennial to intermittent under a warmer climate, we analyzed historic flow records from streams in the Upper Colorado River Basin (UCRB). Approximately two-thirds of 115 gaged stream reaches included in our analysis are currently perennial and the rest have some degree of intermittency. Dry years with combinations of high temperatures and low precipitation were associated with more zero-flow days. Mean annual flow was positively related to minimum flows, suggesting that potential future declines in mean annual flows will correspond with declines in minimum flows. The most important landscape variables for predicting low flow metrics were precipitation, percent snow, potential evapotranspiration, soils, and drainage area. Perennial streams in the UCRB that have high minimum-flow variability and low mean flows are likely to be most susceptible to increasing streamflow intermittency in the future.

Precipitation Changes Throughout the South Pacific Convergence Zone During the Last 2000 Years

NASA Astrophysics Data System (ADS)

Maloney, A. E.; Nelson, D. B.; Sachs, J. P.

2016-12-01

The South Pacific Convergence Zone (SPCZ) is the southern hemisphere's most prominent precipitation feature extending 3000km southeastwards from Papua New Guinea to French Polynesia. Seasonal and interannual variability in SPCZ rainfall is well characterized by satellite data, however an understanding of this feature prior to the instrumental record is lacking. Rainfall in the western tropical Pacific is difficult to reconstruct due to a dearth of archives that are both high-resolution and continuous. Here we present molecular fossil hydroclimate reconstructions from the last 2000 years. The hydrogen isotopic composition of the algal lipid biomarker dinosterol was measured in 10 freshwater lake sediment cores from 7 lakes on 4 islands in Vanuatu, the Solomon Islands, and Wallis and Futuna. Coretop δ2Hdinosterol values were well correlated with satellite-derived rainfall rates, providing a transfer function for deriving precipitation rates from sedimentary δ2Hdinosterol values. The Vanuatu and Wallis records indicate that the south-western portion of the SPCZ was driest during the transition from the Medieval Warm Period (MWP) to the Little Ice Age (LIA) (1200-1400 CE) with rainfall rates as low as 2mm/day compare to more typical values of 4mm/day. Conversely, the central SPCZ (Solomon Islands) experienced the driest conditions ( 5mm/day) during the MWP (600-1200 CE) and has maintained high ( 9mm/day) rainfall rates since the LIA. The tropical water cycle influences global climate and these quantitative precipitation records are important for understanding SPCZ natural variability.

Investigating Runoff Efficiency in Upper Colorado River Streamflow Over Past Centuries

NASA Astrophysics Data System (ADS)

Woodhouse, Connie A.; Pederson, Gregory T.

2018-01-01

With increasing concerns about the impact of warming temperatures on water resources, more attention is being paid to the relationship between runoff and precipitation, or runoff efficiency. Temperature is a key influence on Colorado River runoff efficiency, and warming temperatures are projected to reduce runoff efficiency. Here, we investigate the nature of runoff efficiency in the upper Colorado River (UCRB) basin over the past 400 years, with a specific focus on major droughts and pluvials, and to contextualize the instrumental period. We first verify the feasibility of reconstructing runoff efficiency from tree-ring data. The reconstruction is then used to evaluate variability in runoff efficiency over periods of high and low flow, and its correspondence to a reconstruction of late runoff season UCRB temperature variability. Results indicate that runoff efficiency has played a consistent role in modulating the relationship between precipitation and streamflow over past centuries, and that temperature has likely been the key control. While negative runoff efficiency is most common during dry periods, and positive runoff efficiency during wet years, there are some instances of positive runoff efficiency moderating the impact of precipitation deficits on streamflow. Compared to past centuries, the 20th century has experienced twice as many high flow years with negative runoff efficiency, likely due to warm temperatures. These results suggest warming temperatures will continue to reduce runoff efficiency in wet or dry years, and that future flows will be less than anticipated from precipitation due to warming temperatures.

Investigating runoff efficiency in upper Colorado River streamflow over past centuries

USGS Publications Warehouse

Woodhouse, Connie A.; Pederson, Gregory T.

2018-01-01

With increasing concerns about the impact of warming temperatures on water resources, more attention is being paid to the relationship between runoff and precipitation, or runoff efficiency. Temperature is a key influence on Colorado River runoff efficiency, and warming temperatures are projected to reduce runoff efficiency. Here, we investigate the nature of runoff efficiency in the upper Colorado River (UCRB) basin over the past 400 years, with a specific focus on major droughts and pluvials, and to contextualize the instrumental period. We first verify the feasibility of reconstructing runoff efficiency from tree-ring data. The reconstruction is then used to evaluate variability in runoff efficiency over periods of high and low flow, and its correspondence to a reconstruction of late runoff season UCRB temperature variability. Results indicate that runoff efficiency has played a consistent role in modulating the relationship between precipitation and streamflow over past centuries, and that temperature has likely been the key control. While negative runoff efficiency is most common during dry periods, and positive runoff efficiency during wet years, there are some instances of positive runoff efficiency moderating the impact of precipitation deficits on streamflow. Compared to past centuries, the 20th century has experienced twice as many high flow years with negative runoff efficiency, likely due to warm temperatures. These results suggest warming temperatures will continue to reduce runoff efficiency in wet or dry years, and that future flows will be less than anticipated from precipitation due to warming temperatures.

Statistical-Dynamical Seasonal Forecasts of Central-Southwest Asian Winter Precipitation.

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Goddard, Lisa; Barnston, Anthony G.

2005-06-01

Interannual precipitation variability in central-southwest (CSW) Asia has been associated with East Asian jet stream variability and western Pacific tropical convection. However, atmospheric general circulation models (AGCMs) forced by observed sea surface temperature (SST) poorly simulate the region's interannual precipitation variability. The statistical-dynamical approach uses statistical methods to correct systematic deficiencies in the response of AGCMs to SST forcing. Statistical correction methods linking model-simulated Indo-west Pacific precipitation and observed CSW Asia precipitation result in modest, but statistically significant, cross-validated simulation skill in the northeast part of the domain for the period from 1951 to 1998. The statistical-dynamical method is also applied to recent (winter 1998/99 to 2002/03) multimodel, two-tier December-March precipitation forecasts initiated in October. This period includes 4 yr (winter of 1998/99 to 2001/02) of severe drought. Tercile probability forecasts are produced using ensemble-mean forecasts and forecast error estimates. The statistical-dynamical forecasts show enhanced probability of below-normal precipitation for the four drought years and capture the return to normal conditions in part of the region during the winter of 2002/03.May Kabul be without gold, but not without snow.—Traditional Afghan proverb

Downscaling future climate projections to the watershed scale: A north San Francisco Bay estuary case study

USGS Publications Warehouse

Micheli, Elisabeth; Flint, Lorraine; Flint, Alan; Weiss, Stuart; Kennedy, Morgan

2012-01-01

We modeled the hydrology of basins draining into the northern portion of the San Francisco Bay Estuary (North San Pablo Bay) using a regional water balance model (Basin Characterization Model; BCM) to estimate potential effects of climate change at the watershed scale. The BCM calculates water balance components, including runoff, recharge, evapotranspiration, soil moisture, and stream flow, based on climate, topography, soils and underlying geology, and the solar-driven energy balance. We downscaled historical and projected precipitation and air temperature values derived from weather stations and global General Circulation Models (GCMs) to a spatial scale of 270 m. We then used the BCM to estimate hydrologic response to climate change for four scenarios spanning this century (2000–2100). Historical climate patterns show that Marin’s coastal regions are typically on the order of 2 °C cooler and receive five percent more precipitation compared to the inland valleys of Sonoma and Napa because of marine influences and local topography. By the last 30 years of this century, North Bay scenarios project average minimum temperatures to increase by 1.0 °C to 3.1 °C and average maximum temperatures to increase by 2.1 °C to 3.4 °C (in comparison to conditions experienced over the last 30 years, 1981–2010). Precipitation projections for the 21st century vary between GCMs (ranging from 2 to 15% wetter than the 20th-century average). Temperature forcing increases the variability of modeled runoff, recharge, and stream discharge, and shifts hydrologic cycle timing. For both high- and low-rainfall scenarios, by the close of this century warming is projected to amplify late-season climatic water deficit (a measure of drought stress on soils) by 8% to 21%. Hydrologic variability within a single river basin demonstrated at the scale of subwatersheds may prove an important consideration for water managers in the face of climate change. Our results suggest that in arid environments characterized by high topo-climatic variability, land and water managers need indicators of local watershed hydrology response to complement regional temperature and precipitation estimates. Our results also suggest that temperature forcing may generate greater drought stress affecting soils and stream flows than can be estimated by variability in precipitation alone.

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

PubMed

Prein, Andreas F; Gobiet, Andreas

2017-01-01

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

Temporal analyses of Salmonellae in a headwater spring ecosystem reveals the effects of precipitation and runoff events.

PubMed

Gaertner, James P; Garres, Tiffany; Becker, Jesse C; Jimenez, Maria L; Forstner, Michael R J; Hahn, Dittmar

2009-03-01

Sediments and water from the spring and slough arm of Spring Lake, the pristine headwaters of the San Marcos River, Texas, were analyzed for Salmonellae by culture and molecular techniques before and after three major precipitation events, each with intermediate dry periods. Polymerase chain reaction (PCR)-assisted analyses of enrichment cultures detected Salmonellae in samples after all three precipitation events, but failed to detect them immediately prior to the rainfall events. Detection among individual locations differed with respect to the precipitation event analyzed, and strains isolated were highly variable with respect to serovars. These results demonstrate that rainwater associated effects, most likely surface runoff, provide an avenue for short-term pollution of aquatic systems with Salmonellae that do not, however, appear to establish for the long-term in water nor sediments.

A Precipitation Climatology of the Snowy Mountains, Australia

NASA Astrophysics Data System (ADS)

Theobald, Alison; McGowan, Hamish; Speirs, Johanna

2014-05-01

The precipitation that falls in the Snowy Mountains region of southeastern Australia provides critical water resources for hydroelectric power generation. Water storages in this region are also a major source of agricultural irrigation, environmental flows, and offer a degree of flood protection for some of the major river systems in Australia. Despite this importance, there remains a knowledge gap regarding the long-term, historic variability of the synoptic weather systems that deliver precipitation to the region. This research aims to increase the understanding of long-term variations in precipitation-bearing weather systems resulting in runoff into the Snowy Mountains catchments and reservoirs, and the way in which these are influenced by large-scale climate drivers. Here we present initial results on the development of a climatology of precipitation-bearing synoptic weather systems (synoptic typology), spanning a period of over 100 years. The synoptic typology is developed from the numerical weather model re-analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), in conjunction with regional precipitation and temperature data from a network of private gauges. Given the importance of surface, mid- and upper-air patterns on seasonal precipitation, the synoptic typing will be based on a range of meteorological variables throughout the depth of the troposphere, highlighting the importance of different atmospheric levels on the development and steering of synoptic precipitation bearing systems. The temporal and spatial variability of these synoptic systems, their response to teleconnection forcings and their contribution to inflow generation in the headwater catchments of the Snowy Mountains will be investigated. The resulting climatology will provide new understanding of the drivers of regional-scale precipitation variability at inter- and intra-annual timescales. It will enable greater understanding of how variability in synoptic scale atmospheric circulation affects the hydroclimate of alpine environments in southeast Australia - allowing recently observed precipitation declines to be placed in the context of a long-term record spanning at least 100 years. This information will provide further insight into the impacts of predicted anthropogenic climate change and will ultimately lead to more informed water resource management in the Snowy Mountains.

Long-term variability and changes in thunderstorm induced extreme precipitation in Slovakia over 1951-2010

NASA Astrophysics Data System (ADS)

Pecho, J.; Faško, P.; Bližák, V.; Kajaba, P.; Košálová, J.; Bochníček, O.; Lešková, L.

2012-04-01

It is well known that extreme precipitation associated with intensive rains, in summer induced mostly by local thunderstorm activity, could cause very significant problems in economical and social spheres of the countries. Heavy precipitation and consecutive flash-floods are the most serious weather-related hazards over the territory of Slovakia. The extreme precipitation analyses play a strategic role in many climatological and hydrological evaluations designed for the wide range of technical and engineering applications as well as climate change impact assessments. A thunderstorm, as a violent local storm produced by a cumulonimbus cloud and accompanied by thunder and lightning, represents extreme convective activity in the atmosphere depending upon the release of latent heat, by the condensation of water vapor, for most of its energy. Under the natural conditions of Slovakia the incidence of thunderstorms has been traditionally concentrated in the summer or warm half-year (Apr.-Sept.), but increasing air temperature resulting in higher water vapor content and more intense short-term precipitation is associated with more frequent thunderstorm occurrence in early spring as well as autumn. It is the main reason why the studies of thunderstorm phenomena have increased in Slovakia in recent years. It was found that thunderstorm occurrence, in terms of incidence of storm days, has profoundly changed particularly in spring season (~ 30 % in April and May). The present contribution is devoted to verifying the hypothesis that recently the precipitation has been more intense and significant shifts in seasonal incidence have occurred in particular regions in Slovakia. On the basis of the 60-year (1951-2010) meteorological observation series obtained from more than 20 synoptic stations, the analysis of trends and long-term variability of the days with thunderstorms and the accompanying precipitation for seasons was undertaken. Contribution also attempts to explain the main causes of the thunderstorm as well as extreme precipitation variability. Furthermore, differentiation of daily sums of precipitation for the days with thunderstorms, their long-term variability and probability of occurrence is also presented. Key words: thunderstorm occurrence, trend analysis, extreme precipitation, day with thunderstorm, climate change, climate variability, Slovakia

Scale dependency of regional climate modeling of current and future climate extremes in Germany

NASA Astrophysics Data System (ADS)

Tölle, Merja H.; Schefczyk, Lukas; Gutjahr, Oliver

2017-11-01

A warmer climate is projected for mid-Europe, with less precipitation in summer, but with intensified extremes of precipitation and near-surface temperature. However, the extent and magnitude of such changes are associated with creditable uncertainty because of the limitations of model resolution and parameterizations. Here, we present the results of convection-permitting regional climate model simulations for Germany integrated with the COSMO-CLM using a horizontal grid spacing of 1.3 km, and additional 4.5- and 7-km simulations with convection parameterized. Of particular interest is how the temperature and precipitation fields and their extremes depend on the horizontal resolution for current and future climate conditions. The spatial variability of precipitation increases with resolution because of more realistic orography and physical parameterizations, but values are overestimated in summer and over mountain ridges in all simulations compared to observations. The spatial variability of temperature is improved at a resolution of 1.3 km, but the results are cold-biased, especially in summer. The increase in resolution from 7/4.5 km to 1.3 km is accompanied by less future warming in summer by 1 ∘C. Modeled future precipitation extremes will be more severe, and temperature extremes will not exclusively increase with higher resolution. Although the differences between the resolutions considered (7/4.5 km and 1.3 km) are small, we find that the differences in the changes in extremes are large. High-resolution simulations require further studies, with effective parameterizations and tunings for different topographic regions. Impact models and assessment studies may benefit from such high-resolution model results, but should account for the impact of model resolution on model processes and climate change.

Variability and Change in Seasonal Water Storage in the Major Arctic Draining Eurasian River Systems

NASA Astrophysics Data System (ADS)

Serreze, M. C.; Barrett, A. P.

2015-12-01

Variability and change in seasonal water storage in the major Arctic-draining watersheds of Eurasia (Ob. Yenisei and Lena) are assessed in several ways using a combination of storage estimates from the NASA GRACE satellite system, gauged runoff and output from the NASA MERRA atmospheric reanalysis. The study is motivated by the pronounced environmental changes observed in the northern high latitudes and recognition of the climatic importance of changes in hydrology both within and beyond the region. Monthly storage changes based on GRACE gravimetric measurements (2002-2015) and from a water balance approach for the same period calculating storage changes as a residual using gauged runoff along with aerologically-determined net precipitation (atmospheric vapor flux convergence minus the time change in atmospheric precipitable water) from MERRA are generally in good agreement. Agreement is also good for calculations in which aerologically-determined net precipitation is replaced with the MERRA forecasts of precipitation and evapotranspiration. On average, the storage in each of the three watersheds examined (the Ob, Yenisei and Lena) peaks in March and is at a minimum in September. However, this seasonal cycle, primarily driven by snowpack storage through autumn and winter, and snowmelt through spring and summer, varies considerably from year to year in amplitude, phase and between the three watersheds in response to variability in precipitation, evapotranspiration, and near surface air temperature. As assessed over the longer period 1979-2015 covered by MERRA, there is evidence that in response to rising air temperatures influencing precipitation phase and snow storage, peak storage has shifted to earlier in the winter. While recent work provides evidence for a link between increased autumn snowfall over Eurasia and reduced autumn sea ice extent that provides for a moisture source, the effect of increased snowfall is not clearly apparent in water storage.

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.

Analysis of climate and anthropogenic impacts on runoff in the Lower Pra River Basin of Ghana.

PubMed

Awotwi, Alfred; Anornu, Geophrey Kwame; Quaye-Ballard, Jonathan; Annor, Thompson; Forkuo, Eric Kwabena

2017-12-01

The Lower Pra River Basin (LPRB), located in the forest zone of southern Ghana has experienced changes due to variability in precipitation and diverse anthropogenic activities. Therefore, to maintain the functions of the ecosystem for water resources management, planning and sustainable development, it is important to differentiate the impacts of precipitation variability and anthropogenic activities on stream flow changes. We investigated the variability in runoff and quantified the contributions of precipitation and anthropogenic activities on runoff at the LPRB. Analysis of the precipitation-runoff for the period 1970-2010 revealed breakpoints in 1986, 2000, 2004 and 2010 in the LPRB. The periods influenced by anthropogenic activities were categorized into three periods 1987-2000, 2001-2004 and 2005-2010, revealing a decrease in runoff during 1987-2000 and an increase in runoff during 2001-2004 and 2005-2010. Assessment of monthly, seasonal and annual runoff depicted a significant increasing trend in the runoff time series during the dry season. Generally, runoff increased at a rate of 9.98 × 10 7 m 3 yr -1 , with precipitation variability and human activities contributing 17.4% and 82.3% respectively. The dominant small scale alluvial gold mining activity significantly contributes to the net runoff variability in LPRB.

Models are likely to underestimate increase in heavy rainfall in regions with high rainfall intensity

NASA Astrophysics Data System (ADS)

Borodina, Aleksandra; Fischer, Erich M.; Knutti, Reto

2017-04-01

Model projections of heavy rainfall are uncertain. On timescales of few decades, internal variability plays an important role and therefore poses a challenge to detect robust model responses. We show that spatial aggregation across regions with intense heavy rainfall events, - defined as grid cells with high annual precipitation maxima (Rx1day), - allows to reduce the role of internal variability and thus to detect a robust signal during the historical period. This enables us to evaluate models with observational datasets and to constrain long-term projections of the intensification of heavy rainfall, i.e., to recalibrate full model ensemble consistent with observations resulting in narrower range of projections. In the regions of intense heavy rainfall, we found two present-day metrics that are related to a model's projection. The first metric is the observed relationship between the area-weighted mean of the annual precipitation maxima (Rx1day) and the global land temperatures. The second is the fraction of land exhibiting statistically significant relationships between local annual precipitation maxima (Rx1day) and global land temperatures over the historical period. The models that simulate high values in both metrics are those that are in better agreement with observations and show strong future intensification of heavy rainfall. This implies that changes in heavy rainfall are likely to be more intense than anticipated from the multi-model mean.

Precipitation and ice core isotopes from the Asian Summer Monsoon region reflect coherent ENSO variability

NASA Astrophysics Data System (ADS)

Cai, Z.; Tian, L.; Bowen, G. J.

2017-12-01

Oxygen isotope signals (δ18O) from paleo-archives are important proxies for past Asian Summer Monsoon (ASM) climate reconstruction. However, causes of interannual variation in the δ18O values of modern precipitation across the ASM region remain in argument. We report interannual δ18O variation in southern Tibetan Plateau precipitation based on long-term observations at Lhasa. These data, together with precipitation δ18O records from five Global Network of Isotopes in Precipitation (GNIP) stations and two ice core δ18O records, were used to define a regional metric of ASM precipitation δ18O (ASMOI). Back-trajectory analyses for rainy season precipitation events indicate that moisture sources vary little between years with relatively high and low δ18O values, a result that is consistent for the south (Lhasa), southeast (Bangkok), and east ASM regions (Hong Kong). In contrast, δ18O values at these three locations are significantly correlated with convection in the estimated source regions and along transport paths. These results suggest that upstream convection, rather than moisture source change, causes interannual variation in ASM precipitation δ18O values. Contrasting values of the ASMOI in El Niño and La Niña years reveal a positive isotope-El Niño Southern Oscillation (ENSO) response (e.g., high values corresponding to warm phases), which we interpret as a response to changes in regional convection. We show that the isotope-ENSO response is amplified at high elevation sites and during La Niña years. These findings should improve interpretations of paleo-δ18O data as a proxy for past ASM variation and provide new opportunities to use data from this region to study paleo-ENSO activity.

ENSO variability reflected in precipitation oxygen isotopes across the Asian Summer Monsoon region

NASA Astrophysics Data System (ADS)

Cai, Zhongyin; Tian, Lide; Bowen, Gabriel J.

2017-10-01

Oxygen isotope signals (δ18O) from paleo-archives are important proxies for past Asian Summer Monsoon (ASM) climate reconstruction. However, causes of interannual variation in the δ18O values of modern precipitation across the ASM region remain in argument. We report interannual δ18O variation in southern Tibetan Plateau precipitation based on long-term observations at Lhasa. These data, together with precipitation δ18O records from five Global Network of Isotopes in Precipitation (GNIP) stations and two ice core δ18O records, were used to define a regional metric of ASM precipitation δ18O (ASMOI). Back-trajectory analyses for rainy season precipitation events indicate that moisture sources vary little between years with relatively high and low δ18O values, a result that is consistent for the south (Lhasa), southeast (Bangkok), and east ASM regions (Hong Kong). In contrast, δ18O values at these three locations are significantly correlated with convection in the estimated source regions and along transport paths. These results suggest that upstream convection, rather than moisture source change, causes interannual variation in ASM precipitation δ18O values. Contrasting values of the ASMOI in El Niño and La Niña years reveal a positive isotope-El Niño Southern Oscillation (ENSO) response (e.g., high values corresponding to warm phases), which we interpret as a response to changes in regional convection. We show that the isotope-ENSO response is amplified at high elevation sites and during La Niña years. These findings should improve interpretations of paleo-δ18O data as a proxy for past ASM variation and provide new opportunities to use data from this region to study paleo-ENSO activity.

Large-scale connection between aerosol optical depth and summer monsoon circulation, and precipitation over northeast Asia

NASA Astrophysics Data System (ADS)

Kim, Sang-Woo; Yoon, Soon-Chang; Choi, Suk-Jin; Choi, In-Jin

2010-05-01

We investigated the large-scale connection between columnar aerosol loads and summer monsoon circulation, and also the precipitation over northeast Asia using aerosol optical depth (AOD) data obtained from the 8-year MODIS, AERONET Sun/sky radiometer, and precipitation data acquired under the Global Precipitation Climatology Project (GPCP). These high-quality data revealed the large-scale link between AOD and summer monsoon circulation, precipitation in July over northeast Asian countries, and their distinct spatial and annual variabilities. Compared to the mean AOD for the entire period of 2001-2008, the increase of almost 40-50% in the AOD value in July 2005 and July 2007 was found over the downwind regions of China (Yellow Sea, Korean peninsula, and East Sea), with negative precipitation anomalies. This can be attributable to the strong westerly confluent flows, between cyclone flows by continental thermal low centered over the northern China and anti-cyclonic flows by the western North Pacific High, which transport anthropogenic pollution aerosols emitted from east China to aforementioned downwind high AOD regions along the rim of the Pacific marine airmass. In July 2002, however, the easterly flows transported anthropogenic aerosols from east China to the southwestern part of China in July 2002. As a result, the AOD off the coast of China was dramatically reduced in spite of decreasing rainfall. From the calculation of the cross-correlation coefficient between MODIS-derived AOD anomalies and GPCP precipitation anomalies over the period 2001-2008, we found negative correlations over the areas encompassed by 105-115E and 30-35N and by 120-140E and 35-40N (Yellow Sea, Korean peninsula, and East Sea). This suggests that aerosol loads over these regions are easily influenced by the Asian monsoon flow system and associated precipitation.

Variability of precipitation in Poland under climate change

NASA Astrophysics Data System (ADS)

Szwed, Małgorzata

2018-02-01

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

Quantifying how the full local distribution of daily precipitation is changing and its uncertainties

NASA Astrophysics Data System (ADS)

Stainforth, David; Chapman, Sandra; Watkins, Nicholas

2016-04-01

The study of the consequences of global warming would benefit from quantification of geographical patterns of change at specific thresholds or quantiles, and better understandings of the intrinsic uncertainties in such quantities. For precipitation a range of indices have been developed which focus on high percentiles (e.g. rainfall falling on days above the 99th percentile) and on absolute extremes (e.g. maximum annual one day precipitation) but scientific assessments are best undertaken in the context of changes in the whole climatic distribution. Furthermore, the relevant thresholds for climate-vulnerable policy decisions, adaptation planning and impact assessments, vary according to the specific sector and location of interest. We present a methodology which maintains the flexibility to provide information at different thresholds for different downstream users, both scientists and decision makers. We develop a method[1,2] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes in daily precipitation data. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the amount of precipitation on those days. Our method is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of precipitation distributions are changing. This involves not only determining which quantiles and geographical locations show the greatest and smallest changes, but also those at which uncertainty undermines the ability to make confident statements about any change there may be. We demonstrate this approach using E-OBS gridded data[3] which are timeseries of local daily precipitation across Europe over the last 60+ years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the geographical pattern of change at given thresholds of precipitation. This information is model- independent, thus providing data of direct value in model calibration and assessment. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, 2013 [2] S C Chapman, D A Stainforth, N W Watkins, 2015 Limits to the quantification of local climate change, ERL,10, 094018 (2015), ERL,10, 094018 [3] M R Haylock et al . 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119

Should Variations of d2H, d18O and d17O in Precipitation be Considered 'Settled Science' or a 'New Frontier' For Understanding Cloud Dynamics and Microphysics?

NASA Astrophysics Data System (ADS)

Aggarwal, P. K.; araguas Araguas, L.; Belachew, D.; Terzer, S.; Wassenaar, L. I.; Longstaffe, F. J.; Schumacher, C.; Funk, A. B.; Steinacker, R.; Kaltenboeck, R.

2017-12-01

After more than 60 years of isotope measurements in precipitation, there are relatively well established patterns of variation, but their origin and controlling parameters remain a matter of debate, preventing a fuller integration of isotope-based information in meteorology. The prevailing hypothesis based on temperature and Rayleigh distillation has been successful in explaining many of the patterns, particularly at a seasonal or annual scale, and attempts to explain variances by 'tweaking' the prevailing hypothesis suggest that the underlying science may be considered to be 'settled'. A rigorous evaluation at the storm event scale, where precipitation acquires its isotope composition, however, does not provide a satisfactory explanation in most cases. We have conducted an year-long study with high-frequency sampling (5-15 min) of mid-latitude precipitation at Vienna and more than 1000 samples have been analyzed for d2H, d18O and d17O. We have also collected profiles of reflectivity and doppler velocity using a vertically pointed micro-rain radar, particle size distribution in precipitation using a disdrometer, and conducted aerological analysis of air and moisture circulation using sounding data. A combined evaluation of isotope and meteorological data provides a detailed understanding of isotope variability. We will discuss these results and the light they shed on boundary layer and tropospheric moisture circulation in frontal or convective precipitation, the relative roles of vapor deposition and riming growth of precipitation, and the origin of d-excess. The agreement between meteorological observations and isotopic variability is extremely promising and may help open a new frontier in the use of isotopes for weather and climate studies.

Objective classification of atmospheric circulation over southern Scandinavia

NASA Astrophysics Data System (ADS)

Linderson, Maj-Lena

2001-02-01

A method for calculating circulation indices and weather types following the Lamb classification is applied to southern Scandinavia. The main objective is to test the ability of the method to describe the atmospheric circulation over the area, and to evaluate the extent to which the pressure patterns determine local precipitation and temperature in Scania, southernmost Sweden. The weather type classification method works well and produces distinct groups. However, the variability within the group is large with regard to the location of the low pressure centres, which may have implications for the precipitation over the area. The anticyclonic weather type dominates, together with the cyclonic and westerly types. This deviates partly from the general picture for Sweden and may be explained by the southerly location of the study area. The cyclonic type is most frequent in spring, although cloudiness and amount of rain are lowest during this season. This could be explained by the occurrence of weaker cyclones or low air humidity during this time of year. Local temperature and precipitation were modelled by stepwise regression for each season, designating weather types as independent variables. Only the winter season-modelled temperature and precipitation show a high and robust correspondence to the observed temperature and precipitation, even though <60% of the precipitation variance is explained. In the other seasons, the connection between atmospheric circulation and the local temperature and precipitation is low. Other meteorological parameters may need to be taken into account. The time and space resolution of the mean sea level pressure (MSLP) grid may affect the results, as many important features might not be covered by the classification. Local physiography may also influence the local climate in a way that cannot be described by the atmospheric circulation pattern alone, stressing the importance of using more than one observation series.

Inhibition of microbial biofuel production in drought-stressed switchgrass hydrolysate

DOE PAGES

Ong, Rebecca Garlock; Higbee, Alan; Bottoms, Scott; ...

2016-11-08

Here, interannual variability in precipitation, particularly drought, can affect lignocellulosic crop biomass yields and composition, and is expected to increase biofuel yield variability. However, the effect of precipitation on downstream fermentation processes has never been directly characterized. In order to investigate the impact of interannual climate variability on biofuel production, corn stover and switchgrass were collected during 3 years with significantly different precipitation profiles, representing a major drought year (2012) and 2 years with average precipitation for the entire season (2010 and 2013). All feedstocks were AFEX (ammonia fiber expansion)-pretreated, enzymatically hydrolyzed, and the hydrolysates separately fermented using xylose-utilizing strainsmore » of Saccharomyces cerevisiae and Zymomonas mobilis. As a result, a chemical genomics approach was also used to evaluate the growth of yeast mutants in the hydrolysates.« less

Quantitative assessment of the impacts of climate change and human activities on runoff change in a typical karst watershed, SW China.

PubMed

Wu, Luhua; Wang, Shijie; Bai, Xiaoyong; Luo, Weijun; Tian, Yichao; Zeng, Cheng; Luo, Guangjie; He, Shiyan

2017-12-01

The Yinjiang River watershed is a typical karst watershed in Southwest China. The present study explored runoff change and its responses to different driving factors in the Yinjiang River watershed over the period of 1984 to 2015. The methods of cumulative anomaly, continuous wavelet analysis, Mann-Kendall rank correlation trend test, and Hurst exponent were applied to analyze the impacts of climate change and human activities on runoff change. The contributions of climate change and human activities to runoff change were quantitatively assessed using the comparative method of the slope changing ratio of cumulative quantity (SCRCQ). The following results were obtained: (1) From 1984 to 2015, runoff and precipitation exhibited no-significant increasing trend, whereas evaporation exhibited significant decreasing trend. (2) In the future, runoff, precipitation, and evaporation will exhibit weak anti-persistent feature with different persistent times. This feature indicated that in their persistent times, runoff and precipitation will continuously decline, whereas evaporation will continuously increase. (3) Runoff and precipitation were well-synchronized with abrupt change features and stage characteristics, and exhibited consistent multi-timescale characteristics that were different from that of evaporation. (4) The contribution of precipitation to runoff change was 50%-60% and was considered high and stable. The contribution of evaporation to runoff change was 10%-90% and was variable with a positive or negative effects. The contribution of human activities to runoff change was 20%-60% and exerted a low positive or negative effect. (5) Climatic factors highly contributed to runoff change. By contrast, the contribution of human activities to runoff change was low. The contribution of climatic factors to runoff change was highly variable because of differences among base periods. In conclusion, this paper provides a basic theoretical understanding of the main factors that contribute to runoff change in a karst watershed. Copyright © 2017 Elsevier B.V. All rights reserved.

Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

Contrasts Between Precipitation over Mediterranean Sea and Adjacent Continental Areas Based on Decadal Scale Satellite Estimates

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2007-01-01

Most knowledge concerning the last century's climatology and climate dynamics of precipitation over the Mediterranean Sea basin is based on observations taken from rain gauges surrounding the sea itself. In turn, most of the observations come from Southern Europe, with many fewer measurements taken from widely scattered sites situated over North Africa, the Middle East, and the Balkans. This aspect of research on the Mediterranean Sea basin is apparent in a recent compilation of studies presented in book form concerning climate variability of the Mediterranean region [Lionello, P., P. Malanotte-Rizzoli, and R. Boscolo (eds.), 2006: Mediterranean Climate Variability. Elsevier, Amsterdam, 9 chapters.] In light of this missing link to over-water observations, this study (in conjunction with four companion studies by Z. Haddad, A. Mugnai, T. Nakazawa, and G. Stephens) will contrast the nature of precipitation variability directly over the Mediterranean Sea to precipitation variability over the surrounding land areas based on three decades of satellite-based precipitation estimates which have stood up well to validation scrutiny. The satellite observations are drawn from the Global Precipitation Climatology Project (GPCP) dataset extending back to 1979 and the TRMM Merged Algorithm 3b42 dataset extending back to 1998. Both datasets are mostly produced from microwave measurements, excepting the period from 1979 to mid-1987 when only infrared satellite measurements were available for the GPCP estimates. The purpose of this study is to emphasize how the salient properties of precipitation variability over land and sea across a hierarchy of space and time scales, and the salient differences in these properties, might be used in guiding short-term climate models to better predictions of future climate states under different regional temperature-change scenarios.

Phenotypic plasticity facilitates resistance to climate change in a highly variable environment.

PubMed

Richter, Sarah; Kipfer, Tabea; Wohlgemuth, Thomas; Calderón Guerrero, Carlos; Ghazoul, Jaboury; Moser, Barbara

2012-05-01

Increased summer drought will exacerbate the regeneration of many tree species at their lower latitudinal and altitudinal distribution limits. In vulnerable habitats, introduction of more drought-tolerant provenances or species is currently considered to accelerate tree species migration and facilitate forest persistence. Trade-offs between drought adaptation and growth plasticity might, however, limit the effectiveness of assisted migration, especially if introductions focus on provenances or species from different climatic regions. We tested in a common garden experiment the performance of Pinus sylvestris seedlings from the continental Central Alps under increased temperatures and extended spring and/or summer drought, and compared seedling emergence, survival and biomass allocation to that of P. sylvestris and closely related Pinus nigra from a Mediterranean seed source. Soil heating had only minor effects on seedling performance but high spring precipitation doubled the number of continental P. sylvestris seedlings present after the summer drought. At the same time, twice as many seedlings of the Mediterranean than the continental P. sylvestris provenance were present, which was due to both higher emergence and lower mortality under dry conditions. Both P. sylvestris provenances allocated similar amounts of biomass to roots when grown under low summer precipitation. Mediterranean seedlings, however, revealed lower phenotypic plasticity than continental seedlings under high precipitation, which might limit their competitive ability in continental Alpine forests in non-drought years. By contrast, high variability in the response of individual seedlings to summer drought indicates the potential of continental P. sylvestris provenances to adapt to changing environmental conditions.

A global satellite assisted precipitation climatology

USGS Publications Warehouse

Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

2015-01-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0,http://dx.doi.org/10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

A global satellite-assisted precipitation climatology

NASA Astrophysics Data System (ADS)

Funk, C.; Verdin, A.; Michaelsen, J.; Peterson, P.; Pedreros, D.; Husak, G.

2015-10-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high-resolution (0.05°) global precipitation climatologies that perform reasonably well in data-sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, doi:10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

Variability of temperature sensitivity of extreme precipitation from a regional-to-local impact scale perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2016-12-01

Relating precipitation intensity to temperature is a popular approach to assess potential changes of extreme events in a warming climate. Potential increases in extreme rainfall induced hazards, such as flash flooding, serve as motivation. It has not been addressed whether the temperature-precipitation scaling approach is meaningful on a regional to local level, where the risk of climate and weather impact is dealt with. Substantial variability of temperature sensitivity of extreme precipitation has been found that results from differing methodological assumptions as well as from varying climatological settings of the study domains. Two aspects are consistently found: First, temperature sensitivities beyond the expected consistency with the Clausius-Clapeyron (CC) equation are a feature of short-duration, convective, sub-daily to sub-hourly high-percentile rainfall intensities at mid-latitudes. Second, exponential growth ceases or reverts at threshold temperatures that vary from region to region, as moisture supply becomes limited. Analyses of pooled data, or of single or dispersed stations over large areas make it difficult to estimate the consequences in terms of local climate risk. In this study we test the meaningfulness of the scaling approach from an impact scale perspective. Temperature sensitivities are assessed using quantile regression on hourly and sub-hourly precipitation data from 189 stations in the Austrian south-eastern Alpine region. The observed scaling rates vary substantially, but distinct regional and seasonal patterns emerge. High sensitivity exceeding CC-scaling is seen on the 10-minute scale more than on the hourly scale, in storms shorter than 2 hours duration, and in shoulder seasons, but it is not necessarily a significant feature of the extremes. To be impact relevant, change rates need to be linked to absolute rainfall amounts. We show that high scaling rates occur in lower temperature conditions and thus have smaller effect on absolute precipitation intensities. While reporting of mere percentage numbers can be misleading, scaling studies can add value to process understanding on the local scale, if the factors that influence scaling rates are considered from both a methodological and a physical perspective.

Regional Community Climate Simulations with variable resolution meshes in the Community Earth System Model

NASA Astrophysics Data System (ADS)

Zarzycki, C. M.; Gettelman, A.; Callaghan, P.

2017-12-01

Accurately predicting weather extremes such as precipitation (floods and droughts) and temperature (heat waves) requires high resolution to resolve mesoscale dynamics and topography at horizontal scales of 10-30km. Simulating such resolutions globally for climate scales (years to decades) remains computationally impractical. Simulating only a small region of the planet is more tractable at these scales for climate applications. This work describes global simulations using variable-resolution static meshes with multiple dynamical cores that target the continental United States using developmental versions of the Community Earth System Model version 2 (CESM2). CESM2 is tested in idealized, aquaplanet and full physics configurations to evaluate variable mesh simulations against uniform high and uniform low resolution simulations at resolutions down to 15km. Different physical parameterization suites are also evaluated to gauge their sensitivity to resolution. Idealized variable-resolution mesh cases compare well to high resolution tests. More recent versions of the atmospheric physics, including cloud schemes for CESM2, are more stable with respect to changes in horizontal resolution. Most of the sensitivity is due to sensitivity to timestep and interactions between deep convection and large scale condensation, expected from the closure methods. The resulting full physics model produces a comparable climate to the global low resolution mesh and similar high frequency statistics in the high resolution region. Some biases are reduced (orographic precipitation in the western United States), but biases do not necessarily go away at high resolution (e.g. summertime JJA surface Temp). The simulations are able to reproduce uniform high resolution results, making them an effective tool for regional climate studies and are available in CESM2.

High-resolution speleothem record of precipitation from the Yucatan Peninsula spanning the Maya Preclassic Period

NASA Astrophysics Data System (ADS)

Medina-Elizalde, Martín; Burns, Stephen J.; Polanco-Martínez, Josué M.; Beach, Timothy; Lases-Hernández, Fernanda; Shen, Chuan-Chou; Wang, Hao-Cheng

2016-03-01

We produced a new high-resolution absolute U-Th dated stalagmite oxygen isotope record (δ18O) from Río Secreto, Playa del Carmen, Yucatan Peninsula (YP). This new 1434-year stalagmite record (named Itzamna after the Maya god of creation) spans the time interval between BCE 1037 and CE 397 with an average resolution of 8 ± 2 years. It provides a novel view of climate evolution over the Preclassic and early Classic periods in Maya history. To understand the controls of regional precipitation δ18O on seasonal time scales, we characterized the amount effect between precipitation amount (P) and precipitation δ18O (δP). We found that precipitation δ18O in the Yucatan Peninsula is controlled by the amount effect on seasonal scales (δP/ΔP = - 0.0137 ± 0.0031‰ per mm, r = 0.9), as suspected but never before demonstrated. Cave drip δ18O is consistent with the annual amount-weighted δ18O composition of precipitation. Multiple lines of evidence suggest that stalagmite δ18O reflects isotopic equilibrium conditions and thus stalagmite δ18O changes are interpreted to reflect precipitation amount. We determined quantitative precipitation changes from the stalagmite δ18O record following previous methods (Medina-Elizalde and Rohling, 2012). The stalagmite precipitation record suggests twelve periods of anomalous precipitation reductions ranging between about 30 and 70% below mean conditions at the time and with durations from 6 years to 31 years. Between BCE 520 and 166, the speleothem precipitation record suggests that the YP experienced an interval of high precipitation labeled the Late Preclassic Humid Period (LPHP) with precipitation maxima of up to + 86 ± 20%. Preclassic Maya cultural expansion in El Mirador Basin, located in northern Guatemala, took place while the peninsula transitioned from the LPHP to an interval with below average precipitation. We find that the Preclassic abandonment of major centers in the Mirador Basin and others around the Maya Lowlands was synchronous with two unprecedented multi-decadal events of severe precipitation reduction with magnitudes of - 55 ± 13% and - 49 ± 12 and centered at CE 186 and 234, respectively. We also find evidence that centennial scale precipitation variability in the YP during the Preclassic Period may have been associated with shifts in rainfall fluxes from Atlantic tropical cyclones.

Malaria incidence trends and their association with climatic variables in rural Gwanda, Zimbabwe, 2005-2015.

PubMed

Gunda, Resign; Chimbari, Moses John; Shamu, Shepherd; Sartorius, Benn; Mukaratirwa, Samson

2017-09-30

Malaria is a public health problem in Zimbabwe. Although many studies have indicated that climate change may influence the distribution of malaria, there is paucity of information on its trends and association with climatic variables in Zimbabwe. To address this shortfall, the trends of malaria incidence and its interaction with climatic variables in rural Gwanda, Zimbabwe for the period January 2005 to April 2015 was assessed. Retrospective data analysis of reported cases of malaria in three selected Gwanda district rural wards (Buvuma, Ntalale and Selonga) was carried out. Data on malaria cases was collected from the district health information system and ward clinics while data on precipitation and temperature were obtained from the climate hazards group infrared precipitation with station data (CHIRPS) database and the moderate resolution imaging spectro-radiometer (MODIS) satellite data, respectively. Distributed lag non-linear models (DLNLM) were used to determine the temporal lagged association between monthly malaria incidence and monthly climatic variables. There were 246 confirmed malaria cases in the three wards with a mean incidence of 0.16/1000 population/month. The majority of malaria cases (95%) occurred in the > 5 years age category. The results showed no correlation between trends of clinical malaria (unconfirmed) and confirmed malaria cases in all the three study wards. There was a significant association between malaria incidence and the climatic variables in Buvuma and Selonga wards at specific lag periods. In Ntalale ward, only precipitation (1- and 3-month lag) and mean temperature (1- and 2-month lag) were significantly associated with incidence at specific lag periods (p < 0.05). DLNM results suggest a key risk period in current month, based on key climatic conditions in the 1-4 month period prior. As the period of high malaria risk is associated with precipitation and temperature at 1-4 month prior in a seasonal cycle, intensifying malaria control activities over this period will likely contribute to lowering the seasonal malaria incidence.

The impact of Southern Atlantic moisture source in the precipitation regime of Sahel and Brazilian Nordeste using lagrangian models

NASA Astrophysics Data System (ADS)

Drumond, A.; Nieto, R.; Gimeno, L.; Ambrizzi, T.; Trigo, R.

2009-04-01

The socio-economical problems related to the severe droughts observed over Brazilian "Nordeste" and Sahel are well known nowadays. Several studies have showed that the precipitation regimes over these regions are influenced by the Inter Tropical Convergence Zone (ITCZ) variability, which can be related with the climatic variations observed in the South and North Tropical Atlantic basins. However, a climatological detailed assessment of the annual cycle of the oceanic moisture contribution to both these regions is still needed in order to get a better understanding of their precipitation regimes and variability. To answer this question, a climatological seasonal analysis of the moisture supply from the South Atlantic to the precipitation in the "Nordeste" and Sahel was performed using a new Lagrangian method of diagnosis which identifies the humidity contributions to the moisture budget over a region. The applied methodology computes budgets of evaporation minus precipitation by calculating changes in the specific humidity along forward-trajectories for the following 10 days. In order to take into account distinct regional contributions we have divided the South Atlantic basin in several latitudinal bands (with a 5° width), and all air-masses residing over each region were tracked forward using the available 5-year dataset (2000-2004). For the Sahel, the preliminary results suggest that the oceanic band northwards 10 degrees south acts as a moisture source for the precipitation along the year and its contribution reaches the maximum during the austral winter, probably related to the ITCZ annual migration over the region. On the other hand, the precipitation over "Nordeste" can be better related to air masses emanating from the oceanic bands between 10 and 20 degrees south. However the response over the region is very heterogeneous spatially and temporally probably due to the high variability of the local climate characteristics. In order to clarify dynamically the origin of the moisture that reaches the semi-arid "Nordeste", a backward-trajectories analysis is being conducted and the results will be presented elsewhere.

Variability of Radiosonde-Observed Precipitable Water in the Baltic Region

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

Jakobson, Erko; Ohvril, H.; Okulov, O.

The total mass of columnar water vapor (precipitable water, W) is an important parameter of atmospheric thermodynamic and radiative models. In this work radiosonde observations from 17 aerological stations in the Baltic region during 14 years, 1989?2002, were used to examine the variability of precipitable water. A table of monthly and annual means of W for the stations is given. Seasonal and annual means of W are expressed as linear functions of geographical latitude. Linear formulas are also derived for parameterization of precipitable water as function of surface water vapor pressure at each station.

Towards water vapor assimilation into mesoscale models for improved precipitation forecast

NASA Astrophysics Data System (ADS)

Demoz, B.; Whiteman, D.; Venable, D.; Joseph, E.

2006-05-01

Atmospheric water vapor plays a primary role in the life cycle of clouds, precipitation and is crucial in understanding many aspects of the water cycle. It is very important to short-range mesoscale and storm-scale weather prediction. Specifically, accurate characterization of water vapor at low levels is a necessary condition for quantitative precipitation forecast (QPF), the initiation of convection and various thermodynamic and microphysical processes in mesoscale severe weather systems. However, quantification of its variability (both temporal and spatial) and integration of high quality and high frequency water vapor profiles into mesoscale models have been challenging. We report on a conceptual proposal that attempts to 1) define approporiate lidar-based data and instrumentation required for mesoscale data assimilation and 2) a possible federated network of ground-based lidars that may be capable of acquiring such high resolution water vapor data sets and 3) a possible frame work of assimilation of the data into a mesoscale model.

Online dynamical downscaling of temperature and precipitation within the iLOVECLIM model (version 1.1)

NASA Astrophysics Data System (ADS)

Quiquet, Aurélien; Roche, Didier M.; Dumas, Christophe; Paillard, Didier

2018-02-01

This paper presents the inclusion of an online dynamical downscaling of temperature and precipitation within the model of intermediate complexity iLOVECLIM v1.1. We describe the following methodology to generate temperature and precipitation fields on a 40 km × 40 km Cartesian grid of the Northern Hemisphere from the T21 native atmospheric model grid. Our scheme is not grid specific and conserves energy and moisture in the same way as the original climate model. We show that we are able to generate a high-resolution field which presents a spatial variability in better agreement with the observations compared to the standard model. Although the large-scale model biases are not corrected, for selected model parameters, the downscaling can induce a better overall performance compared to the standard version on both the high-resolution grid and on the native grid. Foreseen applications of this new model feature include the improvement of ice sheet model coupling and high-resolution land surface models.

Modeling Responses of Dryland Spring Triticale, Proso Millet and Foxtail Millet to Initial Soil Water in the High Plains

USDA-ARS?s Scientific Manuscript database

Dryland farming strategies in the High Plains must make efficient use of limited and variable precipitation and stored water in the soil profile for stable and sustainable farm productivity. Current research efforts focus on replacing summer fallow in the region with more profitable and environmenta...

Evaluating optimum limited irrigation management strategies for corn production in the ogallala aquifer region

USDA-ARS?s Scientific Manuscript database

Water is the major factor limiting crop production in the Ogallala Aquifer Region of the U.S. Central High Plains. Seasonal precipitation is highly variable, low in amount, and not enough to meet full corn water needs. The Ogallala Aquifer is the major source of irrigation water for commercial agric...

Climate Change Impact Assessment in Pacific North West Using Copula based Coupling of Temperature and Precipitation variables

NASA Astrophysics Data System (ADS)

Qin, Y.; Rana, A.; Moradkhani, H.

2014-12-01

The multi downscaled-scenario products allow us to better assess the uncertainty of the changes/variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. Using the joint distribution of temperature and precipitation is also of significant importance in hydrological applications and climate change studies. In the present study, we have used multi-modelled statistically downscaled-scenario ensemble of precipitation and temperature variables using 2 different statistically downscaled climate dataset. The datasets used are, 10 Global Climate Models (GCMs) downscaled products from CMIP5 daily dataset, namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, leading to 2 ensemble time series from 20 GCM products. Thereafter the ensemble PDFs of both precipitation and temperature is evaluated for summer, winter, and yearly periods for all the 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables enabling users to model the joint behavior of the variables with any level of correlation and dependency. Moreover, the probabilistic distribution helps remove the limitations on marginal distributions of variables in question. The joint distribution is then used to estimate the change trends of the joint precipitation and temperature in the current and future, along with estimation of the probabilities of the given change. Results have indicated towards varied change trends of the joint distribution of, summer, winter, and yearly time scale, respectively in all 10 sub-basins. Probabilities of changes, as estimated by the joint precipitation and temperature, will provide useful information/insights for hydrological and climate change predictions.

Climatological Downscaling and Evaluation of AGRMET Precipitation Analyses Over the Continental U.S.

NASA Astrophysics Data System (ADS)

Garcia, M.; Peters-Lidard, C. D.; Eylander, J. B.; Daly, C.; Tian, Y.; Zeng, J.

2007-05-01

The spatially distributed application of a land surface model (LSM) over a region of interest requires the application of similarly distributed precipitation fields that can be derived from various sources, including surface gauge networks, surface-based radar, and orbital platforms. The spatial variability of precipitation influences the spatial organization of soil temperature and moisture states and, consequently, the spatial variability of land- atmosphere fluxes. The accuracy of spatially-distributed precipitation fields can contribute significantly to the uncertainty of model-based hydrological states and fluxes at the land surface. Collaborations between the Air Force Weather Agency (AFWA), NASA, and Oregon State University have led to improvements in the processing of meteorological forcing inputs for the NASA-GSFC Land Information System (LIS; Kumar et al. 2006), a sophisticated framework for LSM operation and model coupling experiments. Efforts at AFWA toward the production of surface hydrometeorological products are currently in transition from the legacy Agricultural Meteorology modeling system (AGRMET) to use of the LIS framework and procedures. Recent enhancements to meteorological input processing for application to land surface models in LIS include the assimilation of climate-based information for the spatial interpolation and downscaling of precipitation fields. Climatological information included in the LIS-based downscaling procedure for North America is provided by a monthly high-resolution PRISM (Daly et al. 1994, 2002; Daly 2006) dataset based on a 30-year analysis period. The combination of these sources and methods attempts to address the strengths and weaknesses of available legacy products, objective interpolation methods, and the PRISM knowledge-based methodology. All of these efforts are oriented on an operational need for timely estimation of spatial precipitation fields at adequate spatial resolution for customer dissemination and near-real-time simulations in regions of interest. This work focuses on value added to the AGRMET precipitation product by the inclusion of high-quality climatological information on a monthly time scale. The AGRMET method uses microwave-based satellite precipitation estimates from various polar-orbiting platforms (NOAA POES and DMSP), infrared-based estimates from geostationary platforms (GOES, METEOSAT, etc.), related cloud analysis products, and surface gauge observations in a complex and hierarchical blending process. Results from processing of the legacy AGRMET precipitation products over the U.S. using LIS-based methods for downscaling, both with and without climatological factors, are evaluated against high-resolution monthly analyses using the PRISM knowledge- based method (Daly et al. 2002). It is demonstrated that the incorporation of climatological information in a downscaling procedure can significantly enhance the accuracy, and potential utility, of AFWA precipitation products for military and civilian customer applications.

A comparison of extreme rainfall characteristics in the Brazilian Amazon derived from two gridded data sets and a national rain gauge network

NASA Astrophysics Data System (ADS)

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

2010-07-01

Two issues of particular importance for the Amazon watershed are: whether annual maxima obtained from reanalysis and raingauge records agree well enough for the former to be useful in extending records of the latter; and whether reported trends in Amazon annual rainfall are reflected in the behavior of annual extremes in precipitation estimated from reanalyses and raingauge records. To explore these issues, three sets of daily precipitation data (1979-2001) from the Brazilian Amazon were analyzed (NCEP/NCAR and ERA-40 reanalyses, and records from the raingauge network of the Brazilian water resources agency - ANA), using the following variables: (1) mean annual maximum precipitation totals, accumulated over one, two, three and five days; (2) linear trends in these variables; (3) mean length of longest within-year "dry" spell; (4) linear trends in these variables. Comparisons between variables obtained from all three data sources showed that reanalyses underestimated time-trends and mean annual maximum precipitation (over durations of one to five days), and the correlations between reanalysis and spatially-interpolated raingauge estimates were small for these two variables. Both reanalyses over-estimated mean lengths of dry period relative to the mean length recorded by the raingauge network. Correlations between the trends calculated from all three data sources were small. Time-trends averaged over the reanalysis grid-squares, and spatially-interpolated time trends from raingauge data, were all clustered around zero. In conclusion, although the NCEP/NCAR and ERA-40 gridded data-sets may be valuable for studies of inter-annual variability in precipitation totals, they were found to be inappropriate for analysis of precipitation extremes.

Sensitivity of U.S. summer precipitation to model resolution and convective parameterizations across gray zone resolutions

NASA Astrophysics Data System (ADS)

Gao, Yang; Leung, L. Ruby; Zhao, Chun; Hagos, Samson

2017-03-01

Simulating summer precipitation is a significant challenge for climate models that rely on cumulus parameterizations to represent moist convection processes. Motivated by recent advances in computing that support very high-resolution modeling, this study aims to systematically evaluate the effects of model resolution and convective parameterizations across the gray zone resolutions. Simulations using the Weather Research and Forecasting model were conducted at grid spacings of 36 km, 12 km, and 4 km for two summers over the conterminous U.S. The convection-permitting simulations at 4 km grid spacing are most skillful in reproducing the observed precipitation spatial distributions and diurnal variability. Notable differences are found between simulations with the traditional Kain-Fritsch (KF) and the scale-aware Grell-Freitas (GF) convection schemes, with the latter more skillful in capturing the nocturnal timing in the Great Plains and North American monsoon regions. The GF scheme also simulates a smoother transition from convective to large-scale precipitation as resolution increases, resulting in reduced sensitivity to model resolution compared to the KF scheme. Nonhydrostatic dynamics has a positive impact on precipitation over complex terrain even at 12 km and 36 km grid spacings. With nudging of the winds toward observations, we show that the conspicuous warm biases in the Southern Great Plains are related to precipitation biases induced by large-scale circulation biases, which are insensitive to model resolution. Overall, notable improvements in simulating summer rainfall and its diurnal variability through convection-permitting modeling and scale-aware parameterizations suggest promising venues for improving climate simulations of water cycle processes.

Regional model simulations of New Zealand climate

NASA Astrophysics Data System (ADS)

Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

1998-03-01

Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

A five-year study of the impact of nitrogen addition on methane uptake in alpine grassland.

PubMed

Yue, Ping; Li, Kaihui; Gong, Yanming; Hu, Yukun; Mohammat, Anwar; Christie, Peter; Liu, Xuejun

2016-08-30

It remains unclear how nitrogen (N) deposition affects soil methane (CH4) uptake in semiarid and arid zones. An in situ field experiment was conducted from 2010 to 2014 to systematically study the effect of various N application rates (0, 10, 30, and 90 kg N ha(-1) yr(-1)) on CH4 flux in alpine grassland in the Tianshan Mountains. No significant influence of N addition on CH4 uptake was found. Initially the CH4 uptake rate increased with increasing N application rate by up to 11.5% in 2011 and then there was gradual inhibition by 2014. However, the between-year variability in CH4 uptake was very highly significant with average uptake ranging from 52.9 to 106.6 μg C m(-2) h(-1) and the rate depended largely on seasonal variability in precipitation and temperature. CH4 uptake was positively correlated with soil temperature, air temperature and to a lesser extent with precipitation, and was negatively correlated with soil moisture and NO3(-)-N content. The results indicate that between-year variability in CH4 uptake was impacted by precipitation and temperature and was not sensitive to elevated N deposition in alpine grassland.

A five-year study of the impact of nitrogen addition on methane uptake in alpine grassland

PubMed Central

Yue, Ping; Li, Kaihui; Gong, Yanming; Hu, Yukun; Mohammat, Anwar; Christie, Peter; Liu, Xuejun

2016-01-01

It remains unclear how nitrogen (N) deposition affects soil methane (CH4) uptake in semiarid and arid zones. An in situ field experiment was conducted from 2010 to 2014 to systematically study the effect of various N application rates (0, 10, 30, and 90 kg N ha−1 yr−1) on CH4 flux in alpine grassland in the Tianshan Mountains. No significant influence of N addition on CH4 uptake was found. Initially the CH4 uptake rate increased with increasing N application rate by up to 11.5% in 2011 and then there was gradual inhibition by 2014. However, the between-year variability in CH4 uptake was very highly significant with average uptake ranging from 52.9 to 106.6 μg C m−2 h−1 and the rate depended largely on seasonal variability in precipitation and temperature. CH4 uptake was positively correlated with soil temperature, air temperature and to a lesser extent with precipitation, and was negatively correlated with soil moisture and NO3−-N content. The results indicate that between-year variability in CH4 uptake was impacted by precipitation and temperature and was not sensitive to elevated N deposition in alpine grassland. PMID:27571892

Relating annual increments of the endangered Blanding's turtle plastron growth to climate

PubMed Central

Richard, Monik G; Laroque, Colin P; Herman, Thomas B

2014-01-01

This research is the first published study to report a relationship between climate variables and plastron growth increments of turtles, in this case the endangered Nova Scotia Blanding's turtle (Emydoidea blandingii). We used techniques and software common to the discipline of dendrochronology to successfully cross-date our growth increment data series, to detrend and average our series of 80 immature Blanding's turtles into one common chronology, and to seek correlations between the chronology and environmental temperature and precipitation variables. Our cross-dated chronology had a series intercorrelation of 0.441 (above 99% confidence interval), an average mean sensitivity of 0.293, and an average unfiltered autocorrelation of 0.377. Our master chronology represented increments from 1975 to 2007 (33 years), with index values ranging from a low of 0.688 in 2006 to a high of 1.303 in 1977. Univariate climate response function analysis on mean monthly air temperature and precipitation values revealed a positive correlation with the previous year's May temperature and current year's August temperature; a negative correlation with the previous year's October temperature; and no significant correlation with precipitation. These techniques for determining growth increment response to environmental variables should be applicable to other turtle species and merit further exploration. PMID:24963390

Relating annual increments of the endangered Blanding's turtle plastron growth to climate.

PubMed

Richard, Monik G; Laroque, Colin P; Herman, Thomas B

2014-05-01

This research is the first published study to report a relationship between climate variables and plastron growth increments of turtles, in this case the endangered Nova Scotia Blanding's turtle (Emydoidea blandingii). We used techniques and software common to the discipline of dendrochronology to successfully cross-date our growth increment data series, to detrend and average our series of 80 immature Blanding's turtles into one common chronology, and to seek correlations between the chronology and environmental temperature and precipitation variables. Our cross-dated chronology had a series intercorrelation of 0.441 (above 99% confidence interval), an average mean sensitivity of 0.293, and an average unfiltered autocorrelation of 0.377. Our master chronology represented increments from 1975 to 2007 (33 years), with index values ranging from a low of 0.688 in 2006 to a high of 1.303 in 1977. Univariate climate response function analysis on mean monthly air temperature and precipitation values revealed a positive correlation with the previous year's May temperature and current year's August temperature; a negative correlation with the previous year's October temperature; and no significant correlation with precipitation. These techniques for determining growth increment response to environmental variables should be applicable to other turtle species and merit further exploration.

Reconstruction of the South Atlantic Subtropical Dipole index for the past 12,000 years from surface temperature proxy

PubMed Central

Wainer, Ilana; Prado, Luciana Figueiredo; Khodri, Myriam; Otto-Bliesner, Bette

2014-01-01

Climate indices based on sea surface temperature (SST) can synthesize information related to physical processes that describe change and variability in continental precipitation from floods to droughts. The South Atlantic Subtropical Dipole index (SASD) is based on the distribution of SST in the South Atlantic and fits these criteria. It represents the dominant mode of variability of SST in the South Atlantic, which is modulated by changes in the position and intensity of the South Atlantic Subtropical High. Here we reconstructed an index of the South Atlantic Ocean SST (SASD-like) for the past twelve thousand years (the Holocene period) based on proxy-data. This has great scientific implications and important socio-economic ramifications because of its ability to infer variability of precipitation and moisture over South America where past climate data is limited. For the first time a reconstructed index based on proxy data on opposite sides of the SASD-like mode is able to capture, in the South Atlantic, the significant cold events in the Northern Hemisphere at 12.9−11.6 kyr BP and 8.6−8.0 ky BP. These events are related, using a transient model simulation, to precipitation changes over South America. PMID:24924600

Reconstruction of the South Atlantic Subtropical Dipole index for the past 12,000 years from surface temperature proxy.

PubMed

Wainer, Ilana; Prado, Luciana Figueiredo; Khodri, Myriam; Otto-Bliesner, Bette

2014-06-13

Climate indices based on sea surface temperature (SST) can synthesize information related to physical processes that describe change and variability in continental precipitation from floods to droughts. The South Atlantic Subtropical Dipole index (SASD) is based on the distribution of SST in the South Atlantic and fits these criteria. It represents the dominant mode of variability of SST in the South Atlantic, which is modulated by changes in the position and intensity of the South Atlantic Subtropical High. Here we reconstructed an index of the South Atlantic Ocean SST (SASD-like) for the past twelve thousand years (the Holocene period) based on proxy-data. This has great scientific implications and important socio-economic ramifications because of its ability to infer variability of precipitation and moisture over South America where past climate data is limited. For the first time a reconstructed index based on proxy data on opposite sides of the SASD-like mode is able to capture, in the South Atlantic, the significant cold events in the Northern Hemisphere at 12.9-11.6 kyr BP and 8.6-8.0 ky BP. These events are related, using a transient model simulation, to precipitation changes over South America.

High sensitivity of gross primary production in the Rocky Mountains to summer rain

USGS Publications Warehouse

Berkelhammer, M.; Stefanescu, I.C.; Joiner, J.; Anderson, Lesleigh

2017-01-01

In the catchments of the Rocky Mountains, peak snowpack is declining in response to warmer spring temperatures. To understand how this will influence terrestrial gross primary production (GPP), we compared precipitation data across the intermountain west with satellite retrievals of solar-induced fluorescence (SIF), a proxy for GPP. Annual precipitation patterns explained most of the spatial and temporal variability of SIF, but the slope of the response was dependent on site to site differences in the proportion of snowpack to summer rain. We separated the response of SIF to different seasonal precipitation amounts and found that SIF was approximately twice as sensitive to variations in summer rain than snowpack. The response of peak GPP to a secular decline in snowpack will likely be subtle, whereas a change in summer rain amount will have precipitous effects on GPP. The study suggests that the rain use efficiency of Rocky Mountain ecosystems is strongly dependent on precipitation form and timing.

Numerical modeling of an intense precipitation event and its associated lightning activity over northern Greece

NASA Astrophysics Data System (ADS)

Pytharoulis, I.; Kotsopoulos, S.; Tegoulias, I.; Kartsios, S.; Bampzelis, D.; Karacostas, T.

2016-03-01

This study investigates an intense precipitation event and its lightning activity that affected northern Greece and primarily Thessaloniki on 15 July 2014. The precipitation measurement of 98.5 mm in 15 h at the Aristotle University of Thessaloniki set a new absolute record maximum. The thermodynamic analysis indicated that the event took place in an environment that could support deep thunderstorm activity. The development of this intense event was associated with significant low-level convergence and upper-level divergence even before its triggering and a positive vertical gradient of relative vorticity advection. The high resolution (1.667 km × 1.667 km) non-hydrostatic WRF-ARW numerical weather prediction model was used to simulate this intense precipitation event, while the Lightning Potential Index was utilized to calculate the potential for lightning activity. Sensitivity experiments suggested that although the strong synoptic forcing assumed primary role in the occurrence of intense precipitation and lightning activity, their spatiotemporal variability was affected by topography. The application of the very fine resolution topography of NASA Shuttle Radar Topographic Mission improved the simulated precipitation and the calculated lightning potential.

The poleward shift of South Atlantic Convergence Zone in recent decades

NASA Astrophysics Data System (ADS)

Zilli, Marcia T.; Carvalho, Leila M. V.; Lintner, Benjamin R.

2018-05-01

During austral summer (December-January-February or DJF), intense precipitation over central-eastern Brazil is modulated by the South American Monsoon System and the South Atlantic Convergence Zone (SACZ). Previous studies identified spatial variability in precipitation trends over this region, suggestive of a poleward shift of the SACZ in recent years. To identify underlying mechanisms associated with changes in the precipitation intensity and position of the SACZ, decadal averages of observed precipitation and the mean state of the atmosphere and ocean during three different periods from 1979 to 2014 are compared. Results show evidence of decreasing (increasing) average daily precipitation along the equatorward (poleward) margin of the climatological SACZ, likely related to a poleward shift of the convergence zone. Precipitation reduction along the equatorward margin of the SACZ is associated with weakening of the poleward winds along the eastern Brazilian coast and drying of low-to-mid troposphere (700 hPa) over the tropical Atlantic. These changes in circulation and moisture are likely related to the poleward expansion of the South Atlantic Subtropical High.

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.

Intraseasonal variability of organized convective systems in the Central Andes: Relationship to Regional Dynamical Features

NASA Astrophysics Data System (ADS)

Mohr, K. I.; Slayback, D. A.; Nicholls, S.; Yager, K.

2013-12-01

The Andes extend from the west coast of Colombia (10N) to the southern tip of Chile (53S). In southern Peru and Bolivia, the Central Andes is split into separate eastern and western cordilleras, with a high plateau (≥ 3000 m), the Altiplano, between them. Because 90% of the Earth's tropical mountain glaciers are located in the Central Andes, our study focuses on this region, defining its zonal extent as 7S-21S and the meridional extent as the terrain 1000 m and greater. Although intense convection occurs during the wet season in the Altiplano, it is not included in the lists of regions with frequent or the most intense convection. The scarcity of in-situ observations with sufficient density and temporal resolution to resolve individual storms or even mesoscale-organized cloud systems and documented biases in microwave-based rainfall products in poorly gauged mountainous regions have impeded the development of an extensive literature on convection and convective systems in this region. With the tropical glaciers receding at unprecedented rates, leaving seasonal precipitation as an increasingly important input to the water balance in alpine valley ecosystems and streams, understanding the nature and characteristics of the seasonal precipitation becomes increasingly important for the rural economies in this region. Previous work in analyzing precipitation in the Central Andes has emphasized interannual variability with respect to ENSO, this is the first study to focus on shorter scale variability with respect to organized convection. The present study took advantage of the University of Utah's Precipitation Features database compiled from 14 years of TRMM observations (1998-2012), supplemented by field observations of rainfall and streamflow, historical gauge data, and long-term WRF-simulations, to analyze the intraseasonal variability of precipitating systems and their relationship regional dynamical features such as the Bolivian High. Through time series and wavelet analysis, we found an important 8-10 day cycle related to but lagging convective surges in the Amazon basin and enhanced upper-level cyclonic flow around the Bolivian High. The majority of the organized convection in the region tended to be weak (< 5 mm/hr rain rates) and shallow (< 12 km). The timing of response (i.e., formation and distribution of organized convection) due to changes in moisture transport around the Bolivian High was similar in the wetter eastern and drier western cordilleras of the Central Andes. The response to upper level moisture transport was modulated by local soil moisture and elevation slope and aspect, with higher elevation, eastern facing peaks having a stronger response than western-facing and lower elevation areas. Streamflow data support the hypothesis that the majority of the light rainfall infiltrates the shallow sub-surface, rather than contributing to surface channel runoff, helping to sustain the high altitude peatlands in the Andean valleys.

Taking the pulse of mountains: Ecosystem responses to climatic variability

USGS Publications Warehouse

Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

2003-01-01

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change across a broad range of climates and mountain ecosystems in the northwestern U.S.A.

Ranch profitability given increased precipitation variability and flexible stocking

USDA-ARS?s Scientific Manuscript database

Forage and cattle performance relationships with spring precipitation, combined with cattle market price variability, were incorporated into a ranch level model to determine if addition of a yearling enterprise to the base cow-calf herd would improve profitability with increasing (25% and 50% greate...

The sensitivity of the atmospheric branch of the global water cycle to temperature fluctuations at synoptic to decadal time-scales in different satellite- and model-based products

NASA Astrophysics Data System (ADS)

Nogueira, Miguel

2018-02-01

Spectral analysis of global-mean precipitation, P, evaporation, E, precipitable water, W, and surface temperature, Ts, revealed significant variability from sub-daily to multi-decadal time-scales, superposed on high-amplitude diurnal and yearly peaks. Two distinct regimes emerged from a transition in the spectral exponents, β. The weather regime covering time-scales < 10 days with β ≥ 1; and the macroweather regime extending from a few months to a few decades with 0 <β <1. Additionally, the spectra showed a generally good statistical agreement amongst several different model- and satellite-based datasets. Detrended cross-correlation analysis (DCCA) revealed three important results which are robust across all datasets: (1) Clausius-Clapeyron (C-C) relationship is the dominant mechanism of W non-periodic variability at multi-year time-scales; (2) C-C is not the dominant control of W, P or E non-periodic variability at time-scales below about 6 months, where the weather regime is approached and other mechanisms become important; (3) C-C is not a dominant control for P or E over land throughout the entire time-scale range considered. Furthermore, it is suggested that the atmosphere and oceans start to act as a single coupled system at time-scales > 1-2 years, while at time-scales < 6 months they are not the dominant drivers of each other. For global-ocean and full-globe averages, ρDCCA showed large spread of the C-C importance for P and E variability amongst different datasets at multi-year time-scales, ranging from negligible (< 0.3) to high ( 0.6-0.8) values. Hence, state-of-the-art climate datasets have significant uncertainties in the representation of macroweather precipitation and evaporation variability and its governing mechanisms.

Impact of Resolution on the Representation of Precipitation Variability Associated With the ITCZ

NASA Astrophysics Data System (ADS)

De Benedetti, Marc; Moore, G. W. K.

2017-12-01

The Intertropical Convergence Zone (ITCZ) is responsible for most of the weather and climate in equatorial regions along with many tropical-midlatitude interactions. It is therefore important to understand how models represent its structure and variability. Most ITCZ-associated precipitation is convective, making it unclear how horizontal resolution impacts its representation. To assess this, we introduce a novel technique that involves calculation of the precipitation field's decorrelation length scale (DCLS) using model data sets that share a common lineage with horizontal resolutions from 16 to 160 km. All resolutions captured the ITCZ's mean structure; however, imprints of topography, such as Hawaii and sea surface temperature, including the variability associated with upwelling cold water off the coast of South America, are more clearly represented at higher resolutions. The DCLS analysis indicates that there are changes in the spatial variability of the ITCZ's precipitation that are not reflected in its mean structure, thus confirming its utility as a diagnostic.

How important is interannual variability in the climatic interpretation of moraine sequences?

NASA Astrophysics Data System (ADS)

Leonard, E. M.; Laabs, B. J. C.; Plummer, M. A.

2017-12-01

Mountain glaciers respond to both long-term climate and interannual forcing. Anderson et al. (2014) pointed out that kilometer-scale fluctuations in glacier length may result from interannual variability in temperature and precipitation given a "steady" climate with no long-term trends in mean or variability of temperature and precipitation. They cautioned that use of outermost moraines from the Last Glacial Maximum (LGM) as indicators of LGM climate will, because of the role of interannual forcing, result in overestimation of the magnitude of long-term temperature depression and/or precipitation enhancement. Here we assess the implications of these ideas, by examining the effect of interannual variability on glacier length and inferred magnitude of LGM climate change from present under both an assumed steady LGM climate and an LGM climate with low-magnitude, long-period variation in summer temperature and annual precipitation. We employ both the original 1-stage linear glacier model (Roe and O'Neal, 2009) used by Anderson et al. (2014) and a newer 3-stage linear model (Roe and Baker, 2014). We apply the models to two reconstructed LGM glaciers in the Colorado Sangre de Cristo Mountains. Three-stage-model results indicate that, absent long-term variations through a 7500-year-long LGM, interannual variability would result in overestimation of mean LGM temperature depression from the outermost moraine of 0.2-0.6°C. If small long-term cyclic variations of temperature (±0.5°C) and precipitation (±5%) are introduced, the overestimation of LGM temperature depression reduces to less than 0.4°C, and if slightly greater long-term variation (±1.0°C and ±10% precipitation) is introduced, the magnitude of overestimation is 0.3°C or less. Interannual variability may produce a moraine sequence that differs from the sequence that would be expected were glacier length forced only by long-term climate. With small amplitude (±0.5°C and ±5% precipitation) long-term variation, the moraine sequence expected if forced by a combination of interannual variability and long-term climate differs from that expected based on long-term climate forcing alone in 38% of model runs. With the larger amplitude long-term forcing (±1.0°C and ±10% precipitation) this difference occurs in 20% of model runs.

Evaluating Precipitation Elevation Gradients in the Alaska Range using Ice Core and Alpine Weather Station Records

NASA Astrophysics Data System (ADS)

McConnell, E.; Osterberg, E. C.; Winski, D.; Kreutz, K. J.; Wake, C. P.; Campbell, S. W.; Ferris, D. G.; Birkel, S. D.

2016-12-01

Precipitation in Alaska is sensitive to the Aleutian Low (ALow) pressure system and North Pacific sea-surface temperatures, as shown by the increase in Alaskan sub-Arctic precipitation associated with the 1976 shift to the positive phase of the Pacific Decadal Oscillation (PDO). Precipitation in the high-elevation accumulation zones of Alaskan alpine glaciers provides critical mass input for glacial mass balance, which has been declining in recent decades from warmer summer temperatures despite the winter precipitation increase. Twin >1500-year ice cores collected from the summit plateau of Mount Hunter in Denali National Park, Alaska show a remarkable doubling of annual snow accumulation over the past 150 years, with most of the change observed in the winter. Other alpine ice cores collected from the Alaska and Saint Elias ranges show similar snowfall increases over recent decades. However, although Alaskan weather stations at low elevation recorded a 7-38% increase in winter precipitation across the 1976 PDO transition, this increase is not as substantial as that recorded in the Mt. Hunter ice core. Weather stations at high-elevation alpine sites are comparatively rare, and reasons for the enhanced precipitation trends at high elevation in Alaska remain unclear. Here we use Automatic Weather Station data from the Mt. Hunter drill site (3,900 m a.s.l) and from nearby Denali climber's Base Camp (2,195 m a.s.l.) to evaluate the relationships between alpine and lowland Alaskan precipitation on annual, seasonal, and storm-event temporal scales from 2008-2016. Both stations are located on snow and have sonic snow depth sounders to record daily precipitation. We focus on the role of variable ALow and North Pacific High strength in influencing Alaskan precipitation elevational gradients, particularly in association with the extreme 2015-2016 El Niño event, the 2009-2010 moderate El Niño event, and the 2010-2011 moderate La Niña event. Our analysis will improve our paleoclimate interpretations of the 1200-year Mt. Hunter accumulation record, and improve our ability to integrate low-elevation hydroclimate proxies from lake sediment cores.

Linking precipitation, evapotranspiration and soil moisture content for the improvement of predictability over land

NASA Astrophysics Data System (ADS)

Catalano, Franco; Alessandri, Andrea; De Felice, Matteo

2013-04-01

Climate change scenarios are expected to show an intensification of the hydrological cycle together with modifications of evapotranspiration and soil moisture content. Evapotranspiration changes have been already evidenced for the end of the 20th century. The variance of evapotranspiration has been shown to be strongly related to the variance of precipitation over land. Nevertheless, the feedbacks between evapotranspiration, soil moisture and precipitation have not yet been completely understood at present-day. Furthermore, soil moisture reservoirs are associated to a memory and thus their proper initialization may have a strong influence on predictability. In particular, the linkage between precipitation and soil moisture is modulated by the effects on evapotranspiration. Therefore, the investigation of the coupling between these variables appear to be of primary importance for the improvement of predictability over the continents. The coupled manifold (CM) technique (Navarra and Tribbia 2005) is a method designed to separate the effects of the variability of two variables which are connected. This method has proved to be successful for the analysis of different climate fields, like precipitation, vegetation and sea surface temperature. In particular, the coupled variables reveal patterns that may be connected with specific phenomena, thus providing hints regarding potential predictability. In this study we applied the CM to recent observational datasets of precipitation (from CRU), evapotranspiration (from GIMMS and MODIS satellite-based estimates) and soil moisture content (from ESA) spanning a time period of 23 years (1984-2006) with a monthly frequency. Different data stratification (monthly, seasonal, summer JJA) have been employed to analyze the persistence of the patterns and their characteristical time scales and seasonality. The three variables considered show a significant coupling among each other. Interestingly, most of the signal of the evapotranspiration-precipitation coupled terms comes from the summer (JJA), when convective motions increase sensitivity to surface conditions over land. The CM analysis of the response of evapotranspiration to soil moisture allowed a characterization of the robustness of the coupling between these two variables which has been identified as a key requirement for precipitation predictability (Koster et al. 2000). References Navarra, A., and J. Tribbia (2005), The coupled manifold, J. Atmos. Sci., 62, 310-330. Koster, R. D., M. J. Suarez, and M. Heiser (2000), Variance and predictability of precipitation at seasonal-to-interannual timescales, J. Hydrometeor., 1, 26-46.

Agronomic responses to late-seeded cover crops in a semiarid region

USDA-ARS?s Scientific Manuscript database

Intensification of cropping systems in the Great Plains beyond annual cropping practices may be limited by inadequate precipitation, short growing seasons, and highly variable climatic conditions. Inclusion of cover crops in dryland cropping systems may serve as an effective intensification strateg...

Patterns of change in high frequency precipitation variability over North America.

PubMed

Roque-Malo, Susana; Kumar, Praveen

2017-09-18

Precipitation variability encompasses attributes associated with the sequencing and duration of events of the full range of magnitudes. However, climate change studies have largely focused on extreme events. Using analyses of long-term weather station data, we show that high frequency events, such as fraction of wet days in a year and average duration of wet and dry periods, are undergoing significant changes across North America. Further, these changes are more prevalent and larger than those associated with extremes. Such trends also exist for events of a range of magnitudes. Existence of localized clusters with opposing trend to that of broader geographic variation illustrates the role of microclimate and other drivers of trends. Such hitherto unknown patterns over the entire North American continent have the potential to significantly inform our characterization of the resilience and vulnerability of a broad range of ecosystems and agricultural and socio-economic systems. They can also set new benchmarks for climate model assessments.

Reconstructions of Columbia River streamflow from tree-ring chronologies in the Pacific Northwest, USA

USGS Publications Warehouse

Littell, Jeremy; Pederson, Gregory T.; Gray, Stephen T.; Tjoelker, Michael; Hamlet, Alan F.; Woodhouse, Connie A.

2016-01-01

We developed Columbia River streamflow reconstructions using a network of existing, new, and updated tree-ring records sensitive to the main climatic factors governing discharge. Reconstruction quality is enhanced by incorporating tree-ring chronologies where high snowpack limits growth, which better represent the contribution of cool-season precipitation to flow than chronologies from trees positively sensitive to hydroclimate alone. The best performing reconstruction (back to 1609 CE) explains 59% of the historical variability and the longest reconstruction (back to 1502 CE) explains 52% of the variability. Droughts similar to the high-intensity, long-duration low flows observed during the 1920s and 1940s are rare, but occurred in the early 1500s and 1630s-1640s. The lowest Columbia flow events appear to be reflected in chronologies both positively and negatively related to streamflow, implying low snowpack and possibly low warm-season precipitation. High flows of magnitudes observed in the instrumental record appear to have been relatively common, and high flows from the 1680s to 1740s exceeded the magnitude and duration of observed wet periods in the late-19th and 20th Century. Comparisons between the Columbia River reconstructions and future projections of streamflow derived from global climate and hydrologic models show the potential for increased hydrologic variability, which could present challenges for managing water in the face of competing demands

Assessing Changes in Precipitation and Impacts on Groundwater in Southeastern Brazil using Regional Hydroclimate Reconstruction

NASA Astrophysics Data System (ADS)

Nunes, A.; Fernandes, M.; Silva, G. C., Jr.

2017-12-01

Aquifers can be key players in regional water resources. Precipitation infiltration is the most relevant process in recharging the aquifers. In that regard, understanding precipitation changes and impacts on the hydrological cycle helps in the assessment of groundwater availability from the aquifers. Regional modeling systems can provide precipitation, near-surface air temperature, together with soil moisture at different ground levels from coupled land-surface schemes. More accurate those variables are better the evaluation of the precipitation impact on the groundwater. Downscaling of global reanalysis very often employs regional modeling systems, in order to give more detailed information for impact assessment studies at regional scales. In particular, the regional modeling system, Satellite-enhanced Regional Downscaling for Applied Studies (SRDAS), might improve the accuracy of hydrometeorological variables in regions with spatial and temporal scarcity of in-situ observations. SRDAS combines assimilation of precipitation estimates from gauge-corrected satellite-based products with spectral nudging technique. The SRDAS hourly outputs provide monthly means of atmospheric and land-surface variables, including precipitation, used in the calculations of the hydrological budget terms. Results show the impact of changes in precipitation on groundwater in the aquifer located near the southeastern coastline of Brazil, through the assessment of the water-cycle terms, using a hydrological model during dry and rainy periods found in the 15-year numerical integration of SRDAS.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Climate variability controls on unsaturated water and chemical movement, High Plains aquifer, USA

USGS Publications Warehouse

Gurdak, J.J.; Hanson, R.T.; McMahon, P.B.; Bruce, B.W.; McCray, J.E.; Thyne, G.D.; Reedy, R.C.

2007-01-01

Responses in the vadose zone and groundwater to interannual, interdecadal, and multidecadal climate variability have important implications for groundwater resource sustainability, yet they are poorly documented and not well understood in most aquifers of the USA. This investigation systematically examines the role of interannual to multidecadal climate variability on groundwater levels, deep infiltration (3-23 m) events, and downward displacement (>1 m) of chloride and nitrate reservoirs in thick (15-50 m) vadose zones across the regionally extensive High Plains aquifer. Such vadose zone responses are unexpected across much of the aquifer given a priori that unsaturated total-potential profiles indicate upward water movement from the water table toward the root zone, mean annual potential evapotranspiration exceeds mean annual precipitation, and millennia-scale evapoconcentration results in substantial vadose zone chloride and nitrate reservoirs. Using singular spectrum analysis (SSA) to reconstruct precipitation and groundwater level time-series components, variability was identified in all time series as partially coincident with known climate cycles, such as the Pacific Decadal Oscillation (PDO) (10-25 yr) and the El Nin??o/Southern Oscillation (ENSO) (2-6 yr). Using these lag-correlated hydrologic time series, a new method is demonstrated to estimate climate-varying unsaturated water flux. The results suggest the importance of interannual to interdecadal climate variability on water-flux estimation in thick vadose zones and provide better understanding of the climate-induced transients responsible for the observed deep infiltration and chemical-mobilization events. Based on these results, we discuss implications for climate-related sustainability of the High Plains aquifer. ?? Soil Science Society of America.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

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.

Probabilistic discrimination between liquid rainfall events, hailstorms, biomass burning and industrial fires from C-Band Radar Polarimetric Variables

NASA Astrophysics Data System (ADS)

Valencia, J. M.; Sepúlveda, J.; Hoyos, C.; Herrera, L.

2017-12-01

Characterization and identification of fire and hailstorm events using weather radar data in a tropical complex topography region is an important task in risk management and agriculture. Polarimetric variables from a C-Band Dual polarization weather radar have potential uses in particle classification, due to the relationship their sensitivity to shape, spatial orientation, size and fall behavior of particles. In this sense, three forest fires and two chemical fires were identified for the Áburra Valley regions. Measurements were compared between each fire event type and with typical data radar retrievals for liquid precipitation events. Results of this analysis show different probability density functions for each type of event according to the particles present in them. This is very important and useful result for early warning systems to avoid precipitation false alarms during fire events within the study region, as well as for the early detection of fires using radar retrievals in remote cases. The comparative methodology is extended to hailstorm cases. Complementary sensors like laser precipitation sensors (LPM) disdrometers and meteorological stations were used to select dates of solid precipitation occurrence. Then, in this dates weather radar data variables were taken in pixels surrounding the stations and solid precipitation polar values were statistically compared with liquid precipitation values. Spectrum precipitation measured by LPM disdrometer helps to define typical features like particles number, fall velocities and diameters for both precipitation types. In addition, to achieve a complete hailstorm characterization, other meteorological variables were analyzed: wind field from meteorological stations and radar wind profiler, profiling data from Micro Rain Radar (MRR), and thermodynamic data from a microwave radiometer.

Spatio-temporal patterns of the effects of precipitation variability and land use/cover changes on long-term changes in sediment yield in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Gao, Guangyao; Zhang, Jianjun; Liu, Yu; Ning, Zheng; Fu, Bojie; Sivapalan, Murugesu

2017-09-01

Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC) was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961-2011), showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space-time variability of sediment yield was expressed notionally as a product of two factors representing (i) the effect of precipitation and (ii) the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation-sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events) also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.

Global salinity predictors of western United States precipitation

NASA Astrophysics Data System (ADS)

Liu, T.; Schmitt, R. W.; Li, L.

2016-12-01

Moisture transport from the excess of evaporation over precipitation in the global ocean drives terrestrial precipitation patterns. Sea surface salinity (SSS) is sensitive to changes in ocean evaporation and precipitation, and therefore, to changes in the global water cycle. We use the Met Office Hadley Centre EN4.2.0 SSS dataset to search for teleconnections between autumn-lead seasonal salinity signals and winter precipitation over the western United States. NOAA CPC Unified observational US precipitation in winter months is extracted from bounding boxes over the northwest and southwest and averaged. Lead autumn SON SSS in ocean areas that are relatively highly correlated with winter DJF terrestrial precipitation are filtered by a size threshold and treated as individual predictors. After removing linear trends from the response and explanatory variables and accounting for multiple collinearity, we use best subsets regression and the Bayesian information criterion (BIC) to objectively select the best model to predict terrestrial precipitation using SSS and SST predictors. The combination of autumn SSS and SST predictors can skillfully predict western US winter terrestrial precipitation (R2 = 0.51 for the US Northwest and R2 = 0.7 for the US Southwest). In both cases, SSS is a better predictor than SST. Thus, incorporating SSS can greatly enhance the accuracy of existing precipitation prediction frameworks that use SST-based climate indices and by extension improve watershed management.

The Potential for Predicting Precipitation on Seasonal-to-Interannual Timescales

NASA Technical Reports Server (NTRS)

Koster, R. D.

1999-01-01

The ability to predict precipitation several months in advance would have a significant impact on water resource management. This talk provides an overview of a project aimed at developing this prediction capability. NASA's Seasonal-to-Interannual Prediction Project (NSIPP) will generate seasonal-to-interannual sea surface temperature predictions through detailed ocean circulation modeling and will then translate these SST forecasts into forecasts of continental precipitation through the application of an atmospheric general circulation model and a "SVAT"-type land surface model. As part of the process, ocean variables (e.g., height) and land variables (e.g., soil moisture) will be updated regularly via data assimilation. The overview will include a discussion of the variability inherent in such a modeling system and will provide some quantitative estimates of the absolute upper limits of seasonal-to-interannual precipitation predictability.

Potential impacts of climate variability on respiratory morbidity in children, infants, and adults.

PubMed

Souza, Amaury de; Fernandes, Widinei Alves; Pavão, Hamilton Germano; Lastoria, Giancarlo; Albrez, Edilce do Amaral

2012-01-01

To determine whether climate variability influences the number of hospitalizations for respiratory diseases in infants, children, and adults in the city of Campo Grande, Brazil. We used daily data on admissions for respiratory diseases, precipitation, air temperature, humidity, and wind speed for the 2004-2008 period. We calculated the thermal comfort index, effective temperature, and effective temperature with wind speed (wind-chill or heat index) using the meteorological data obtained. Generalized linear models, with Poisson multiple regression, were used in order to predict hospitalizations for respiratory disease. The variables studied were (collectively) found to show relatively high correlation coefficients in relation to hospital admission for pneumonia in children (R² = 68.4%), infants (R² = 71.8%), and adults (R² = 81.8%). Our results indicate a quantitative risk for an increase in the number of hospitalizations of children, infants, and adults, according to the increase or decrease in temperature, humidity, precipitation, wind speed, and thermal comfort index in the city under study.

Using Multiple Metrics to Analyze Trends and Sensitivity of Climate Variability in New York City

NASA Astrophysics Data System (ADS)

Huang, J.; Towey, K.; Booth, J. F.; Baez, S. D.

2017-12-01

As the overall temperature of Earth continues to warm, changes in the Earth's climate are being observed through extreme weather events, such as heavy precipitation events and heat waves. This study examines the daily precipitation and temperature record of the greater New York City region during the 1979-2014 period. Daily station observations from three greater New York City airports: John F. Kennedy (JFK), LaGuardia (LGA) and Newark (EWR), are used in this study. Multiple statistical metrics are used in this study to analyze trends and variability in temperature and precipitation in the greater New York City region. The temperature climatology reveals a distinct seasonal cycle, while the precipitation climatology exhibits greater annual variability. Two types of thresholds are used to examine the variability of extreme events: extreme threshold and daily anomaly threshold. The extreme threshold indicates how the strength of the overall maximum is changing whereas the daily anomaly threshold indicates if the strength of the daily maximum is changing over time. We observed an increase in the frequency of anomalous daily precipitation events over the last 36 years, with the greatest frequency occurring in 2011. The most extreme precipitation events occur during the months of late summer through early fall, with approximately four expected extreme events occurring per year during the summer and fall. For temperature, the greatest frequency and variation in temperature anomalies occur during winter and spring. In addition, temperature variance is also analyzed to determine if there is greater day-to-day temperature variability today than in the past.

Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050.

PubMed

Song, Yongze; Ge, Yong; Wang, Jinfeng; Ren, Zhoupeng; Liao, Yilan; Peng, Junhuan

2016-07-07

Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well constructed in previous research. This study aims to estimate these nonlinear relationships and predict future malaria scenarios in northern China. Nonlinear relationships between malaria incidence and predictor variables were constructed using a genetic programming (GP) method, to predict the spatial distributions of malaria under climate change scenarios. For this, the examples of monthly average malaria incidence were used in each county of northern China from 2004 to 2010. Among the five variables at county level, precipitation rate and temperature are used for projections, while elevation, water density index, and gross domestic product are held at their present-day values. Average malaria incidence was 0.107 ‰ per annum in northern China, with incidence characteristics in significant spatial clustering. A GP-based model fit the relationships with average relative error (ARE) = 8.127 % for training data (R(2) = 0.825) and 17.102 % for test data (R(2) = 0.532). The fitness of GP results are significantly improved compared with those by generalized additive models (GAM) and linear regressions. With the future precipitation rate and temperature conditions in Special Report on Emission Scenarios (SRES) family B1, A1B and A2 scenarios, spatial distributions and changes in malaria incidences in 2020, 2030, 2040 and 2050 were predicted and mapped. The GP method increases the precision of predicting the spatial distribution of malaria incidence. With the assumption of varied precipitation rate and temperature, and other variables controlled, the relationships between incidence and the varied variables appear sophisticated nonlinearity and spatially differentiation. Using the future fluctuated precipitation and the increased temperature, median malaria incidence in 2020, 2030, 2040 and 2050 would significantly increase that it might increase 19 to 29 % in 2020, but currently China is in the malaria elimination phase, indicating that the effective strategies and actions had been taken. While the mean incidences will not increase even reduce due to the incidence reduction in high-risk regions but the simultaneous expansion of the high-risk areas.

Winter precipitation effect in a mid-latitude temperature-limited environment: the case of common juniper at high elevation in the Alps

NASA Astrophysics Data System (ADS)

Pellizzari, Elena; Pividori, Mario; Carrer, Marco

2014-10-01

Common juniper (Juniperus communis L.) is by far the most widespread conifer in the world. However, tree-ring research dealing with this species is still scarce, mainly due to the difficulty in crossdating associated with the irregular stem shape with strip-bark growth form in older individuals and the high number of missing and wedging rings. Given that many different species of the same genus have been successfully used in tree-ring investigations and proved to be reliable climate proxies, this study aims to (i) test the possibility to successfully apply dendrochronological techniques on common juniper growing above the treeline and (ii) verify the climate sensitivity of the species with special regard to winter precipitation, a climatic factor that generally does not affect tree-ring growth in all Alpine high-elevation tree species. Almost 90 samples have been collected in three sites in the central and eastern Alps, all between 2100 and 2400 m in elevation. Despite cross-dating difficulties, we were able to build a reliable chronology for each site, each spanning over 200 years. Climate-growth relationships computed over the last century highlight that juniper growth is mainly controlled by the amount of winter precipitation. The high variability of the climate-growth associations among sites, corresponds well to the low spatial dependence of this meteorological factor. Fairly long chronologies and the presence of a significant precipitation signal open up the possibility to reconstruct past winter precipitation.

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.

Comparing maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada produced by two different methods

USGS Publications Warehouse

Simpson, James J.; Hufford, Gary L.; Daly, Christopher; Berg, Jared S.; Fleming, Michael D.

2005-01-01

Maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada, produced by Oregon State University's Spatial Climate Analysis Service (SCAS) and the Alaska Geospatial Data Clearinghouse (AGDC), were analyzed. Because both sets of maps are generally available and in use by the community, there is a need to document differences between the processes and input data sets used by the two groups to produce their respective set of maps and to identify similarities and differences between the two sets of maps and possible reasons for the differences. These differences do not affect the observed large-scale patterns of seasonal and annual variability. Alaska is divided into interior and coastal zones, with consistent but different variability, separated by a transition region. The transition region has high interannual variability but low long-term mean variability. Both data sets support the four major ecosystems and ecosystem transition zone identified in our earlier work. Differences between the two sets of maps do occur, however, on the regional scale; they reflect differences in physiographic domains and in the treatment of these domains by the two groups (AGDC, SCAS). These differences also provide guidance for an improved observational network for Alaska. On the basis of validation with independent in situ data, we conclude that the data set produced by SCAS provides the best spatial coverage of Alaskan long-term mean monthly surface temperature and precipitation currently available. ?? The Arctic Institute of North America.

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.

Multiple causes of nonstationarity in the Weihe annual low-flow series

NASA Astrophysics Data System (ADS)

Xiong, Bin; Xiong, Lihua; Chen, Jie; Xu, Chong-Yu; Li, Lingqi

2018-02-01

Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to analyze future occurrences of low-flow extremes in similar areas.

Role of moisture transport for Central American precipitation

NASA Astrophysics Data System (ADS)

María Durán-Quesada, Ana; Gimeno, Luis; Amador, Jorge

2017-02-01

A climatology of moisture sources linked with Central American precipitation was computed based upon Lagrangian trajectories for the analysis period 1980-2013. The response of the annual cycle of precipitation in terms of moisture supply from the sources was analysed. Regional precipitation patterns are mostly driven by moisture transport from the Caribbean Sea (CS). Moisture supply from the eastern tropical Pacific (ETPac) and northern South America (NSA) exhibits a strong seasonal pattern but weaker compared to CS. The regional distribution of rainfall is largely influenced by a local signal associated with surface fluxes during the first part of the rainy season, whereas large-scale dynamics forces rainfall during the second part of the rainy season. The Caribbean Low Level Jet (CLLJ) and the Chocó Jet (CJ) are the main conveyors of regional moisture, being key to define the seasonality of large-scale forced rainfall. Therefore, interannual variability of rainfall is highly dependent of the regional LLJs to the atmospheric variability modes. The El Niño-Southern Oscillation (ENSO) was found to be the dominant mode affecting moisture supply for Central American precipitation via the modulation of regional phenomena. Evaporative sources show opposite anomaly patterns during warm and cold ENSO phases, as a result of the strengthening and weakening, respectively, of the CLLJ during the summer months. Trends in both moisture supply and precipitation over the last three decades were computed, results suggest that precipitation trends are not homogeneous for Central America. Trends in moisture supply from the sources identified show a marked north-south seesaw, with an increasing supply from the CS Sea to northern Central America. Long-term trends in moisture supply are larger for the transition months (March and October). This might have important implications given that any changes in the conditions seen during the transition to the rainy season may induce stronger precipitation trends.

Simulation of seasonal US precipitation and temperature by the nested CWRF-ECHAM system

NASA Astrophysics Data System (ADS)

Chen, Ligang; Liang, Xin-Zhong; DeWitt, David; Samel, Arthur N.; Wang, Julian X. L.

2016-02-01

This study investigates the refined simulation skill that results when the regional Climate extension of the Weather Research and Forecasting (CWRF) model is nested in the ECMWF Hamburg version 4.5 (ECHAM) atmospheric general circulation model over the United States during 1980-2009, where observed sea surface temperatures are used in both models. Over the contiguous US, for each of the four seasons from winter to fall, CWRF reduces the root mean square error of the ECHAM seasonal mean surface air temperature simulation by 0.19, 0.82, 2.02 and 1.85 °C, and increases the equitable threat score of seasonal mean precipitation by 0.18, 0.11, 0.09 and 0.12. CWRF also simulates much more realistically daily precipitation frequency and heavy precipitation events, typically over the Central Great Plains, Cascade Mountains and Gulf Coast States. These CWRF skill enhancements are attributed to the increased spatial resolution and physics refinements in representing orographic, terrestrial hydrology, convection, and cloud-aerosol-radiation effects and their interactions. Empirical orthogonal function analysis of seasonal mean precipitation and surface air temperature interannual variability shows that, in general, CWRF substantially improves the spatial distribution of both quantities, while temporal evolution (i.e. interannual variability) of the first 3 primary patterns is highly correlated with that of the driving ECHAM (except for summer precipitation), and they both have low temporal correlations against observations. During winter, when large-scale forcing dominates, both models also have similar responses to strong ENSO signals where they successfully capture observed precipitation composite anomalies but substantially fail to reproduce surface air temperature anomalies. When driven by the ECMWF Reanalysis Interim, CWRF produces a very realistic interannual evolution of large-scale precipitation and surface air temperature patterns where the temporal correlations with observations are significant. These results indicate that CWRF can greatly improve mesoscale regional climate structures but it cannot change interannual variations of the large-scale patterns, which are determined by the driving lateral boundary conditions.

Statistical downscaling of summer precipitation over northwestern South America

NASA Astrophysics Data System (ADS)

Palomino Lemus, Reiner; Córdoba Machado, Samir; Raquel Gámiz Fortis, Sonia; Castro Díez, Yolanda; Jesús Esteban Parra, María

2015-04-01

In this study a statistical downscaling (SD) model using Principal Component Regression (PCR) for simulating summer precipitation in Colombia during the period 1950-2005, has been developed, and climate projections during the 2071-2100 period by applying the obtained SD model have been obtained. For these ends the Principal Components (PCs) of the SLP reanalysis data from NCEP were used as predictor variables, while the observed gridded summer precipitation was the predictand variable. Period 1950-1993 was utilized for calibration and 1994-2010 for validation. The Bootstrap with replacement was applied to provide estimations of the statistical errors. All models perform reasonably well at regional scales, and the spatial distribution of the correlation coefficients between predicted and observed gridded precipitation values show high values (between 0.5 and 0.93) along Andes range, north and north Pacific of Colombia. Additionally, the ability of the MIROC5 GCM to simulate the summer precipitation in Colombia, for present climate (1971-2005), has been analyzed by calculating the differences between the simulated and observed precipitation values. The simulation obtained by this GCM strongly overestimates the precipitation along a horizontal sector through the center of Colombia, especially important at the east and west of this country. However, the SD model applied to the SLP of the GCM shows its ability to faithfully reproduce the rainfall field. Finally, in order to get summer precipitation projections in Colombia for the period 1971-2100, the downscaled model, recalibrated for the total period 1950-2010, has been applied to the SLP output from MIROC5 model under the RCP2.6, RCP4.5 and RCP8.5 scenarios. The changes estimated by the SD models are not significant under the RCP2.6 scenario, while for the RCP4.5 and RCP8.5 scenarios a significant increase of precipitation appears regard to the present values in all the regions, reaching around the 27% in northern Colombia region under the RCP8.5 scenario. Keywords: Statistical downscaling, precipitation, Principal Component Regression, climate change, Colombia. ACKNOWLEDGEMENTS This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

The transfer of seasonal isotopic variability between precipitation and drip water at eight caves in the monsoon regions of China

NASA Astrophysics Data System (ADS)

Duan, Wuhui; Ruan, Jiaoyang; Luo, Weijun; Li, Tingyong; Tian, Lijun; Zeng, Guangneng; Zhang, Dezhong; Bai, Yijun; Li, Jilong; Tao, Tao; Zhang, Pingzhong; Baker, Andy; Tan, Ming

2016-06-01

This study presents new stable isotope data for precipitation (δ18Op) and drip water (δ18Od) from eight cave sites in the monsoon regions of China (MRC), with monthly to bi-monthly sampling intervals from May-2011 to April-2014, to investigate the regional-scale climate forcing on δ18Op and how the isotopic signals are transmitted to various drip sites. The monthly δ18Op values show negative correlation with surface air temperature at all the cave sites except Shihua Cave, which is opposite to that expected from the temperature effect. In addition, although the monthly δ18Op values are negatively correlated with precipitation at all the cave sites, only three sites are significant at the 95% level. These indicate that, due to the various vapor sources, a large portion of variability in δ18Op in the MRC cannot be explained simply by either temperature or precipitation alone. All the thirty-four drip sites are classified into three types based on the δ18Od variability. About 82% of them are static drips with little discernable variation in δ18Od through the whole study period, but the drip rates of these drips are not necessary constant. Their discharge modes are site-specific and the oxygen isotopic composition of the stalagmites growing from them may record the average of multi-year climatic signals, which are modulated by the seasonality of recharge and potential effects of evaporation, and in some cases infiltration from large rainfall events. About 12% of the thirty-four drip sites are seasonal drips, although the amplitude of δ18Od is narrower than that of δ18Op, the monthly response of δ18Od to coeval precipitation is not completely damped, and some of them follow the seasonal trend of δ18Op very well. These drips may be mainly recharged by present-day precipitation, mixing with some stored water. Thus, the stalagmites growing under them may record portions of the seasonal climatic signals embedded in δ18Op. About 6% of the thirty-four drip sites are medium-variability drips, with constant and relatively low δ18Od values in the wet season, but with variable and relatively high δ18Od values in the dry season, reflecting flow switching in the karst or evaporation inside the cave.

Exploring the impact of climate variability during the Last Glacial Maximum on the pattern of human occupation of Iberia.

PubMed

Burke, Ariane; Levavasseur, Guillaume; James, Patrick M A; Guiducci, Dario; Izquierdo, Manuel Arturo; Bourgeon, Lauriane; Kageyama, Masa; Ramstein, Gilles; Vrac, Mathieu

2014-08-01

The Last Glacial Maximum (LGM) was a global climate event, which had significant repercussions for the spatial distribution and demographic history of prehistoric populations. In Eurasia, the LGM coincides with a potential bottleneck for modern humans and may mark the divergence date for Asian and European populations (Keinan et al., 2007). In this research, the impact of climate variability on human populations in the Iberian Peninsula during the Last Glacial Maximum (LGM) is examined with the aid of downscaled high-resolution (16 × 16 km) numerical climate experiments. Human sensitivity to short time-scale (inter-annual) climate variability during this key time period, which follows the initial modern human colonisation of Eurasia and the extinction of the Neanderthals, is tested using the spatial distribution of archaeological sites. Results indicate that anatomically modern human populations responded to small-scale spatial patterning in climate variability, specifically inter-annual variability in precipitation levels as measured by the standard precipitation index. Climate variability at less than millennial scale, therefore, is shown to be an important component of ecological risk, one that played a role in regulating the spatial behaviour of prehistoric human populations and consequently affected their social networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mapping the Spatial and Temporal Distribution of N and O Isotopes in Precipitation Nitrate Across the Northeastern and Mid-Atlantic United States

NASA Astrophysics Data System (ADS)

Elliott, E. M.; Kendall, C.; Harlin, K.; Butler, T.; Carlton, R.; Wankel, S.

2004-12-01

Atmospheric deposition of N is a universally important pathway by which ecosystems receive fixed, bioavailable N. Since the 1880s, atmospheric deposition of N has become increasingly important, as NOx emissions from fossil fuel combustion have steadily increased. In particular, the Northeastern and Mid-Atlantic U.S. receive some of the highest rates of nitrate wet deposition in the country, causing a cascade of detrimental effects. In order to effectively mediate the impacts of nitrate deposition, it is critical to understand the dynamics among NOx sources, atmospheric chemical transformations and transport, and the characteristics of the nitrate that is ultimately deposited. To address this need, this research takes advantage of recent methodological improvements, coupled with national networks (NADP, AIRMoN) of archived precipitation, to characterize N and O isotopic composition of nitrate in precipitation across the Northeastern and Mid-Atlantic U.S. We investigate the critical question of whether variations in \\delta15N and \\delta18O of nitrate wet deposition are mainly a function of atmospheric processes (e.g., seasonal variations in reaction pathways) or variable NOx source contributions (e.g., power plant emissions, vehicle exhaust). Spatial and seasonal variability of \\delta15N and \\delta18O is investigated using bimonthly archived samples from 2000. Furthermore, a high resolution record of daily precipitation from a single site is used to highlight within-season isotopic variability. Potential correlations between isotopic values and major NOx sources are explored using EPA datasets for monthly county-level emissions from two major NOx sources, electric generating units and on-road vehicles. Analysis of samples for \\Delta17O is in progress. A key concern regarding analysis of archived samples is nitrate preservation. We tested the stability of nitrate concentrations, and hence potential isotopic fractionations, by reanalyzing filtered, refrigerated, archived NADP samples with a range of nitrate and ammonium concentrations. We found highly significant correlations (R2=0.9995, p<0.001, n=28) between nitrate concentrations measured in 2000 and 2003, indicating that no major alterations had occurred. With regard to spatial patterns, preliminary isotopic analyses indicate that \\delta15N of precipitation nitrate varies considerably among states. Moreover, initial data corroborate previously reported seasonal trends in both \\delta15N and \\delta18O, with higher values in the colder months. Seasonal trends in \\delta15N are remarkably consistent, with up to an 8 \\permil difference between winter and summer months. \\delta18O values of nitrate are generally higher and have a smaller range than previously reported for precipitation, with values ranging from +60 to +90 \\permil. In addition, archived daily precipitation collected during 2000 from a single AIRMoN site give insight into the seasonal and within-season variability of \\delta15N and \\delta18O of precipitation nitrate. Back-trajectory analyses are used to examine the geographic source of air masses for individual events, and seasonal frontal patterns are discussed.

West African warming: Investigating Temperature Trends and their relation between Precipitation Trends over West African Sahel.

NASA Astrophysics Data System (ADS)

LY, M., Jr.

2014-12-01

It is now admitted that the West African region faces a lot of constraints due to the comprehensiveness of the high climate variability and potential climate change. This is mainly due to the lack of a large number of datasets and long-term records as summarized in the in the IPCC reports. This paper aims to provide improved knowledge and evidence on current and future climate conditions, for better manage climate variability over seasons and from year to year and strengthen the capacity to adapt to future climate change. In this regards, we analyse the evolution of some extreme temperature and precipitation indices over a large area of West Africa. Prior results show a general warming trend at individual stations throughout the region during the period from 1960 to 2010, namely negative trends in the number of cool nights, and positive trends in the number of warm days and length of warm spells. Trends in rainfall-related indices are not as uniform as the ones in temperatures, rather they display marked multi-decadal variability, as expected. To refine analyses of temperature variations and their relation to precipitation we investigated on cluster analysis aimed at distinguishing different sub-regions, such as continental and coastal, and relevant seasons, such as wet, dry/cold and dry warm. This will contribute to significantly lower uncertainties by developing better and more tailored temperature and precipitation trends to inform the user communities on climate related risks, as well as enhance their resilience to food insecurity and other climate related disasters.

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

NASA Astrophysics Data System (ADS)

Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

2001-08-01

An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

Multi-scale streamflow variability responses to precipitation over the headwater catchments in southern China

NASA Astrophysics Data System (ADS)

Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie

2017-08-01

This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.

Drought change in the middle reach of the Yellow River since the late Ming Dynasty and their correlation with runoff

NASA Astrophysics Data System (ADS)

Chen, F.

2017-12-01

Because of the reported decreasing trends in precipitation and streamflow in north-central China (Starting point of Ancient Silk Road), it is essential to understand long-term in water resource availability in this area. Thus, this research presents a new February-August PDSI reconstruction spanning CE 1615-2013 for the southern edge of the Gobi Desert under a highly variable arid and semi-arid climate in northern China. In addition to this new PDSI reconstruction, some previously published annual precipitation/PDSI reconstructions from the neighbouring regions were also used to infer the large-scale hydro-climatic signal of the middle reach of the Yellow River. Spatial correlation analyses with gridded precipitation data showed that the tree-ring records were indeed able to capture much of the regional interannual hydro-climatic signal variability. Using principal component analyses on the reconstructions and documentary records, many large-scale dry and flood events were found during the period AD 1615-2006. Many of these dry events have had profound impacts on the people of the study area over the past several centuries. Temporal correlations among the reconstruction and climatic indices, such as the El Niño-Southern Oscillation, demonstrate that water availability is influenced by tropical and high-latitude forcings in the Pacific rim. Continued work in this direction should enable us to understand better the hydrological change under global warming and the past climate variability of the silk road over long temporal and large spatial scales.

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.

Improving snow water equivalent simulations in an alpine basin using blended gage precipitation and snow pillow measurements

NASA Astrophysics Data System (ADS)

Sohrabi, M.; Safeeq, M.; Conklin, M. H.

2017-12-01

Snowpack is a critical freshwater reservoir that sustains ecosystem, natural habitat, hydropower, agriculture, and urban water supply in many areas around the world. Accurate estimation of basin scale snow water equivalent (SWE), through both measurement and modeling, has been significantly recognized to improve regional water resource management. Recent advances in remote data acquisition techniques have improved snow measurements but our ability to model snowpack evolution is largely hampered by poor knowledge of inherently variable high-elevation precipitation patterns. For a variety of reasons, majority of the precipitation gages are located in low and mid-elevation range and function as drivers for basin scale hydrologic modeling. Here, we blend observed gage precipitation from low and mid-elevation with point observations of SWE from high-elevation snow pillow into a physically based snow evolution model (SnowModel) to better represent the basin-scale precipitation field and improve snow simulations. To do this, we constructed two scenarios that differed in only precipitation. In WTH scenario, we forced the SnowModel using spatially distributed gage precipitation data. In WTH+SP scenario, the model was forced with spatially distributed precipitation data derived from gage precipitation along with observed precipitation from snow pillows. Since snow pillows do not directly measure precipitation, we uses positive change in SWE as a proxy for precipitation. The SnowModel was implemented at daily time step and 100 m resolution for the Kings River Basin, USA over 2000-2014. Our results show an improvement in snow simulation under WTH+SP as compared to WTH scenario, which can be attributed to better representation in high-elevation precipitation patterns under WTH+SP. The average Nash Sutcliffe efficiency over all snow pillow and course sites was substantially higher for WTH+SP (0.77) than for WTH scenario (0.47). The maximum difference in observed and simulated peak SWE was 810 mm for WTH and 380 mm for WTH+SP, which led to underestimation of snow season length and melt rate by up to 30 days and 12 mm/day, respectively, in WTH scenario. These results indicate that point scale snow observations at higher elevation can be used to improve precipitation input to hydrologic modeling in mountainous basins.

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

PubMed Central

Gobiet, Andreas

2016-01-01

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

A Satellite Infrared Technique for Diurnal Rainfall Variability Studies

NASA Technical Reports Server (NTRS)

Anagnostou, Emmanouil

1998-01-01

Reliable information on the distribution of precipitation at high temporal resolution (

Climate signals in a multispecies tree-ring network from central and southern Italy and reconstruction of the late summer temperatures since the early 1700s

NASA Astrophysics Data System (ADS)

Leonelli, Giovanni; Coppola, Anna; Salvatore, Maria Cristina; Baroni, Carlo; Battipaglia, Giovanna; Gentilesca, Tiziana; Ripullone, Francesco; Borghetti, Marco; Conte, Emanuele; Tognetti, Roberto; Marchetti, Marco; Lombardi, Fabio; Brunetti, Michele; Maugeri, Maurizio; Pelfini, Manuela; Cherubini, Paolo; Provenzale, Antonello; Maggi, Valter

2017-11-01

A first assessment of the main climatic drivers that modulate the tree-ring width (RW) and maximum latewood density (MXD) along the Italian Peninsula and northeastern Sicily was performed using 27 forest sites, which include conifers (RW and MXD) and broadleaves (only RW). Tree-ring data were compared using the correlation analysis of the monthly and seasonal variables of temperature, precipitation and standardized precipitation index (SPI, used to characterize meteorological droughts) against each species-specific site chronology and against the highly sensitive to climate (HSTC) chronologies (based on selected indexed individual series). We find that climate signals in conifer MXD are stronger and more stable over time than those in conifer and broadleaf RW. In particular, conifer MXD variability is directly influenced by the late summer (August, September) temperature and is inversely influenced by the summer precipitation and droughts (SPI at a timescale of 3 months). The MXD sensitivity to August-September (AS) temperature and to summer drought is mainly driven by the latitudinal gradient of summer precipitation amounts, with sites in the northern Apennines showing stronger climate signals than sites in the south. Conifer RW is influenced by the temperature and drought of the previous summer, whereas broadleaf RW is more influenced by summer precipitation and drought of the current growing season. The reconstruction of the late summer temperatures for the Italian Peninsula for the past 300 years, based on the HSTC chronology of conifer MXD, shows a stable model performance that underlines periods of climatic cooling (and likely also wetter conditions) in 1699, 1740, 1814, 1914 and 1938, and follows well the variability of the instrumental record and of other tree-ring-based reconstructions in the region. Considering a 20-year low-pass-filtered series, the reconstructed temperature record consistently deviates < 1 °C from the instrumental record. This divergence may also be due to the precipitation patterns and drought stresses that influence the tree-ring MXD at our study sites. The reconstructed late summer temperature variability is also linked to summer drought conditions and it is valid for the west-east oriented region including Sardinia, Sicily, the Italian Peninsula and the western Balkan area along the Adriatic coast.

A Theoretical Framework for Examining Geographical Variability in the Microphysical Mechanisms of Precipitation Development.

DTIC Science & Technology

1986-06-01

Energy and Natural Resources SWS Contract Report 391 FINAL REPORT A THEORETICAL FRAMEWORK FOR EXAMINING GEOGRAPHICAL VARIABILITY IN THE MICROPHYSICAL...U) A Theoretical Framework for Examining Geographical Variability in the Microphysical Mechanisms of Precipitation Development 12. PERSONAL AUTHOR(S...concentration. Oter key parameters include the degree of entrainment and stability of the environment. I 5 - T17 Unclassified ,.-. . A THEORETICAL FRAMEWORK FOR

A critical assessment of the Burning Index in Los Angeles County, California

USGS Publications Warehouse

Schoenberg, F.P.; Chang, H.-C.; Keeley, J.E.; Pompa, J.; Woods, J.; Xu, H.

2007-01-01

The Burning Index (BI) is commonly used as a predictor of wildfire activity. An examination of data on the BI and wildfires in Los Angeles County, California, from January 1976 to December 2000 reveals that although the BI is positively associated with wildfire occurrence, its predictive value is quite limited. Wind speed alone has a higher correlation with burn area than BI, for instance, and a simple alternative point process model using wind speed, relative humidity, precipitation and temperature well outperforms the BI in terms of predictive power. The BI is generally far too high in winter and too low in fall, and may exaggerate the impact of individual variables such as wind speed or temperature during times when other variables, such as precipitation or relative humidity, render the environment ill suited for wildfires. ?? IAWF 2007.

Predictability of Seasonal Precipitation Intensities Associated with Tropical Cyclones and Disturbances in Indo-China Region

NASA Astrophysics Data System (ADS)

Revel, M.; Utsumi, N.; Yoshikawa, S.; Kanae, S.

2016-12-01

Summer Monsoon precipitation provide support for the livelihood of the people of Southeast Asia where the population density is very high. Monsoon precipitation shows high variation in seasonal and yearly time scales affecting daily life of the people in the regions such Indo-China peninsula where most of the countries depend on agricultural economy. Predictability of seasonal extreme events such as flooding and droughts by different climatic conditions will enhance the ability to mitigate the risk of natural disasters in Indo-China peninsula. In addition lower tropospheric (850hPa) wind flow pattern is very useful in understanding the seasonal variability of Southeastern Asian Summer Monsoon. Furthermore summer monsoon in the Indo-China peninsula is strongly influenced by the local wind-terrain-precipitation interaction. Recently a set of Monsoon Indices has been developed by several researches, Indo China Monsoon Indices (ICMIs) as a representation of lower tropospheric wind flow patterns around Southeast Asian. On the other hand different precipitation providing weather systems vary according to the global position and local weather system. Responses of ICMIs to different precipitation providing weather systems may vary in temporal and spatial scales. Hence the seasonal responses of differentiated precipitation with ICMIs in Indo-China peninsula are being investigated. Objective detection methods are been adopted in order to identify the locations of tropical cyclones (TCs), and westward propagating disturbances (WDs) using a Japanese 25-year ReAnalysis data and the Global Precipitation Climatology Project One-Degree Daily data is differentiated into TCs, and WDs related precipitation. TCs contribute highly over the east coast of Indo China peninsula where WDs contributed all over land area of Indo-China peninsula but more towards Bay of Bengal. Correlations and regressions suggest that the indices which is calculated using the wind patterns, situated west of Indo-China peninsula tend to increase the moisture production to precipitation which is produced by seasonal winds and local convections. The increment of indices in the east of the peninsula tends withdraw the moisture of TCs and WDs related precipitation in Indo-China peninsula, as those originate from east of the peninsula.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Precipitation Anomalies in the Tropical Indian Ocean and Possible Links to the Initiation of El Nino

NASA Technical Reports Server (NTRS)

Curtis, Scott; Adler, Robert F.; Huffman, George J.; Starr, David OC. (Technical Monitor)

2001-01-01

A pattern of variability in precipitation and 1000mb zonal winds for the tropical Indian Ocean during, 1979 to 1999 (AtmIO mode) is described using EOFs. The AtmIO mode consists of a cross-equatorial gradient of precipitation anomalies and equatorial wind anomalies of alternating signs on the Equator. The positive phase is defined as enhanced precipitation to the In "n south of the equator, suppressed precipitation to the north, and anomalous westerlies centered on the island of Sumatra. In September-October 1981, February-March 1990, and October-December 1996 the AtmIO mod-, was positive and there was a significant 30-60 day variability in the gradient of precipitation anomalies. These cases coincided with moderate to heavy ,activity in the Madden-Jullan Oscillation (MJO). Links between the AtmIO, MJO, and El Nino are discussed.

Synoptic moisture pathways associated with mean and extreme precipitation over Canada for winter and spring

NASA Astrophysics Data System (ADS)

Tan, X.; Gan, T. Y. Y.; Chen, Y. D.

2017-12-01

Dominant synoptic moisture pathway patterns of vertically integrated water vapor transport (IVT) in winter and spring over Canada West and East were identified using the self-organizing map method. Large-scale meteorological patterns (LSMPs) were related to the variability in seasonal precipitation totals and occurrences of precipitation extremes. Changes in both occurrences of LSMPs and seasonal precipitation occurred under those LSMPs were evaluated to attribute observed changes in seasonal precipitation totals and occurrences of precipitation extremes. Effects of large-scale climate anomalies on occurrences of LSMPs were also examined. Results show that synoptic moisture pathways and LSMPs exhibit the propagation of jet streams as the location and direction of ridges and troughs, and the strength and center of pressure lows and highs varied considerably between LSMPs. Significant decreases in occurrences of synoptic moisture pathway patterns that are favorable with positive precipitation anomalies and more precipitation extremes in winter over Canada West resulted in decreases in seasonal precipitation and occurrences of precipitation extremes. LSMPs resulting in a hot and dry climate and less (more) frequent precipitation extremes over the Canadian Prairies in winter and northwestern Canada in spring are more likely to occur in years with a negative phase of PNA. Occurrences of LSMPs for a wet climate and frequent occurrences of extreme precipitation events over southeastern Canada are associated with a positive phase of NAO. In El Niño years or negative PDO years, LSMPs associated with a dry climate and less frequent precipitation extremes over western Canada tend to occur.

High-Resolution Experimental Investigation of mass transfer enhancement by chemical oxidation from DNAPL entrapped in variable-aperture fractures

NASA Astrophysics Data System (ADS)

Arshadi, M.; Rajaram, H.; Detwiler, R. L.; Jones, T.

2012-12-01

Permanganate oxidation of DNAPL- contaminated fractured rock is an effective remediation technology. Permanganate ion reacts with dissolved DNAPL in a bi-molecular oxidation-reduction reaction. The consumption of dissolved DNAPL in this reaction results in increased concentration gradients away from the free-phase DNAPL, resulting in reaction-enhanced mass transfer, which accelerates contaminant removal. The specific objective of our research was to perform high-resolution non-intrusive experimental studies of permanganate oxidation in a 15.24 × 15.24 cm, transparent, analog, variable-aperture fracture with complex initial TCE entrapped phase geometry. Our experimental system uses light-transmission techniques to accurately measure both fracture aperture and the evolution of individual entrapped DNAPL blobs during the remediation experiments at high resolution (pixel size : 6.2×10-3 cm). Three experiments were performed with different flow rates and permanganate inflow concentrations to observe DNAPL-permanganate interactions across a broader range of conditions. Prior to initiating each experiment, the aperture field within the fracture was measured. The oxidation experiment was initiated by TCE injection into the water saturated fracture till the TCE reached the outflow end, followed by water re-injection through the fracture. The flowing water mobilized some TCE. We continued injection of water till TCE mobilization ceased, leaving behind the residual TCE entrapped within the variable-aperture fracture. Subsequently, permanganate injection through the fracture resulted in propagation of a fingered reaction front into the fracture. We developed image processing algorithms to analyze the evolution of DNAPL phase geometry over the duration of the experiment. The permanganate consumption rate varied significantly within the fracture due to the complex flow and DNAPL concentration fields. Precipitated MnO2 was clearly evident on the downstream side of DNAPL blobs near the inflow boundary indicating high reaction rates in these regions. This behavior is explained by the diversion of permanganate around entrapped DNAPL blobs and downstream advection of dissolved DNAPL. Our results indicate that the total rate of mass transfer from the DNAPL blobs is higher at early times, when not much MnO2 has formed and precipitated. With time, MnO2 precipitation in the fracture leads to changes the aperture field and flow field. Precipitated MnO2 around TCE blobs also decreases the DNAPL accessible surface area. By comparing the results of three experiments, we conclude that low permanganate concentrations and high flow rates lead to more efficient DNAPL remediation, resulting from the fact that under these conditions there would be slower MnO2 formation and less precipitation within the fracture. We also present results on the time-evolution of fracture-scale permanganate consumption and DNAPL removal rates. The experimental observations are being used to develop improved high-resolution numerical models of reactive transport in variable-aperture fractures. The overall goal is to relate the coupled processes of DNAPL removal, permanganate consumption, MnO2 formation and associated changes in aperture and interface area; to derive fracture-scale effective representations of these processes.

Modelling the regional variability of the probability of high trihalomethane occurrence in municipal drinking water.

PubMed

Cool, Geneviève; Lebel, Alexandre; Sadiq, Rehan; Rodriguez, Manuel J

2015-12-01

The regional variability of the probability of occurrence of high total trihalomethane (TTHM) levels was assessed using multilevel logistic regression models that incorporate environmental and infrastructure characteristics. The models were structured in a three-level hierarchical configuration: samples (first level), drinking water utilities (DWUs, second level) and natural regions, an ecological hierarchical division from the Quebec ecological framework of reference (third level). They considered six independent variables: precipitation, temperature, source type, seasons, treatment type and pH. The average probability of TTHM concentrations exceeding the targeted threshold was 18.1%. The probability was influenced by seasons, treatment type, precipitations and temperature. The variance at all levels was significant, showing that the probability of TTHM concentrations exceeding the threshold is most likely to be similar if located within the same DWU and within the same natural region. However, most of the variance initially attributed to natural regions was explained by treatment types and clarified by spatial aggregation on treatment types. Nevertheless, even after controlling for treatment type, there was still significant regional variability of the probability of TTHM concentrations exceeding the threshold. Regional variability was particularly important for DWUs using chlorination alone since they lack the appropriate treatment required to reduce the amount of natural organic matter (NOM) in source water prior to disinfection. Results presented herein could be of interest to authorities in identifying regions with specific needs regarding drinking water quality and for epidemiological studies identifying geographical variations in population exposure to disinfection by-products (DBPs).

Historical Changes in Precipitation and Streamflow in the U.S. Great Lakes Basin, 1915-2004

USGS Publications Warehouse

Hodgkins, Glenn A.; Dudley, Robert W.; Aichele, Stephen S.

2007-01-01

The total amount of water in the Great Lakes Basin is important in the long-term allocation of water to human use and to riparian and aquatic ecosystems. The water available during low-flow periods is particularly important because the short-term demands for the water can exceed the supply. Precipitation increased over the last 90 years in the U.S. Great Lakes Basin. Total annual precipitation increased by 4.5 inches from 1915 to 2004 (based on the average of 34 U.S. Historical Climatology Network stations), 3.5 inches from 1935 to 2004 (average of 34 stations), and 4.2 inches from 1955 to 2004 (average of 37 stations). Variability in precipitation from year to year was large, but there were numerous years with relatively low precipitation in the 1930s and 1960s and many years with relatively high precipitation after about 1970. Annual runoff increased over the last 50 years in the U.S. Great Lakes Basin. Mean annual runoff increased by 2.6 inches, based on the average of 43 U.S. Geological Survey streamflow-gaging stations from 1955 to 2004 on streams that were relatively free of human influences. Variability in runoff from year to year was large, but on average runoff was relatively low from 1955 to about 1970 and relatively high from about 1970 to 1995. Runoff increased at all stations in the basin except in and near the Upper Peninsula of Michigan, where relatively small runoff decreases occurred. Changes in annual runoff for the 16 stations with data from 1935 to 2004 were similar to the changes from 1955 to 2004. The mean annual 7-day low runoff (the lowest annual average of 7 consecutive days of runoff) increased from 1955 to 2004 by 0.048 cubic feet per second per square mile based on the average of 27 stations. Runoff in the U.S. Great Lakes Basin from 1955 to 2004 increased for all months except April. November through January and July precipitation and runoff increased by similar amounts. There were differences between precipitation and runoff changes for February, March, and April, which were likely due to lower ratios of snowfall to rain and earlier snowmelt runoff in recent years. Increases in precipitation were larger than increases in runoff for May, June, August, September, and October. Some of this difference could be due to the different locations of the precipitation and streamflow stations in the basin. Part of the difference may be explained by changes in evapotranspiration. Some of the few highly urbanized and highly regulated stations analyzed in this report had larger increases in annual 7-day low-runoff from 1955 to 2004 than any of the stations in the U.S. Great Lakes Basin that are on streams relatively free of human influences. This demonstrates the human influence over time on very low streamflows. Changes-even over periods as long as 90 years-can be part of longer cycles. Previous studies of Great Lakes Basin precipitation and St. Lawrence River streamflow, using data from the mid-1800s to the late-1900s, showed low precipitation and streamflow in the late 1800s and early 1900s relative to earlier and later periods.

Assessment of the Suitability of High Resolution Numerical Weather Model Outputs for Hydrological Modelling in Mountainous Cold Regions

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Hayashi, M.; Fang, X.; Gutmann, E. D.; Li, Y.

2017-12-01

The hydrology of mountainous cold regions has a large spatial variability that is driven both by climate variability and near-surface process variability associated with complex terrain and patterns of vegetation, soils, and hydrogeology. There is a need to downscale large-scale atmospheric circulations towards the fine scales that cold regions hydrological processes operate at to assess their spatial variability in complex terrain and quantify uncertainties by comparison to field observations. In this research, three high resolution numerical weather prediction models, namely, the Intermediate Complexity Atmosphere Research (ICAR), Weather Research and Forecasting (WRF), and Global Environmental Multiscale (GEM) models are used to represent spatial and temporal patterns of atmospheric conditions appropriate for hydrological modelling. An area covering high mountains and foothills of the Canadian Rockies was selected to assess and compare high resolution ICAR (1 km × 1 km), WRF (4 km × 4 km), and GEM (2.5 km × 2.5 km) model outputs with station-based meteorological measurements. ICAR with very low computational cost was run with different initial and boundary conditions and with finer spatial resolution, which allowed an assessment of modelling uncertainty and scaling that was difficult with WRF. Results show that ICAR, when compared with WRF and GEM, performs very well in precipitation and air temperature modelling in the Canadian Rockies, while all three models show a fair performance in simulating wind and humidity fields. Representation of local-scale atmospheric dynamics leading to realistic fields of temperature and precipitation by ICAR, WRF, and GEM makes these models suitable for high resolution cold regions hydrological predictions in complex terrain, which is a key factor in estimating water security in western Canada.

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.

Influence of formulation and processing variables on properties of itraconazole nanoparticles made by advanced evaporative precipitation into aqueous solution.

PubMed

Bosselmann, Stephanie; Nagao, Masao; Chow, Keat T; Williams, Robert O

2012-09-01

Nanoparticles, of the poorly water-soluble drug, itraconazole (ITZ), were produced by the Advanced Evaporative Precipitation into Aqueous Solution process (Advanced EPAS). This process combines emulsion templating and EPAS processing to provide improved control over the size distribution of precipitated particles. Specifically, oil-in-water emulsions containing the drug and suitable stabilizers are sprayed into a heated aqueous solution to induce precipitation of the drug in form of nanoparticles. The influence of processing parameters (temperature and volume of the heated aqueous solution; type of nozzle) and formulation aspects (stabilizer concentrations; total solid concentrations) on the size of suspended ITZ particles, as determined by laser diffraction, was investigated. Furthermore, freeze-dried ITZ nanoparticles were evaluated regarding their morphology, crystallinity, redispersibility, and dissolution behavior. Results indicate that a robust precipitation process was developed such that size distribution of dispersed nanoparticles was shown to be largely independent across the different processing and formulation parameters. Freeze-drying of colloidal dispersions resulted in micron-sized agglomerates composed of spherical, sub-300-nm particles characterized by reduced crystallinity and high ITZ potencies of up to 94% (w/w). The use of sucrose prevented particle agglomeration and resulted in powders that were readily reconstituted and reached high and sustained supersaturation levels upon dissolution in aqueous media.

Surface-Atmosphere Moisture Interactions in the Frozen Ground Regions of Eurasia.

PubMed

Ford, Trent W; Frauenfeld, Oliver W

2016-01-18

Climate models simulate an intensifying Arctic hydrologic cycle in response to climatic warming, however the role of surface-atmosphere interactions from degrading frozen ground is unclear in these projections. Using Modern-Era Retrospective Analysis for Research and Applications (MERRA) data in high-latitude Eurasia, we examine long-term variability in surface-atmosphere coupling as represented by the statistical relationship between surface evaporative fraction (EF) and afternoon precipitation. Changes in EF, precipitation, and their statistical association are then related to underlying permafrost type and snow cover. Results indicate significant positive trends in July EF in the Central Siberian Plateau, corresponding to significant increases in afternoon precipitation. The positive trends are only significant over continuous permafrost, with non-significant or negative EF and precipitation trends over isolated, sporadic, and discontinuous permafrost areas. Concurrently, increasing EF and subsequent precipitation are found to coincide with significant trends in May and June snowmelt, which potentially provides the moisture source for the observed enhanced latent heating and moisture recycling in the region. As climate change causes continuous permafrost to transition to discontinuous, discontinuous to sporadic, sporadic to isolated, and isolated permafrost disappears, this will also alter patterns of atmospheric convection, moisture recycling, and hence the hydrologic cycle in high-latitude land areas.

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.

Seasonal-to-Interannual Precipitation Variability and Predictability in a Coupled Land-Atmosphere System

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, M. J.; Heiser, M.

1998-01-01

In an earlier GCM study, we showed that interactive land surface processes generally contribute more to continental precipitation variance than do variable sea surface temperatures (SSTs). A new study extends this result through an analysis of 16-member ensembles of multi-decade GCM simulations. We can now show that in many regions, although land processes determine the amplitude of the interannual precipitation anomalies, variable SSTs nevertheless control their timing. The GCM data can be processed into indices that describe geographical variations in (1) the potential for seasonal-to-interannual prediction, and (2) the extent to which the predictability relies on the proper representation of land-atmosphere feedback.

Tree-ring-based estimates of long-term seasonal precipitation in the Souris River Region of Saskatchewan, North Dakota and Manitoba

USGS Publications Warehouse

Ryberg, Karen R.; Vecchia, Aldo V.; Akyüz, F. Adnan; Lin, Wei

2016-01-01

Historically unprecedented flooding occurred in the Souris River Basin of Saskatchewan, North Dakota and Manitoba in 2011, during a longer term period of wet conditions in the basin. In order to develop a model of future flows, there is a need to evaluate effects of past multidecadal climate variability and/or possible climate change on precipitation. In this study, tree-ring chronologies and historical precipitation data in a four-degree buffer around the Souris River Basin were analyzed to develop regression models that can be used for predicting long-term variations of precipitation. To focus on longer term variability, 12-year moving average precipitation was modeled in five subregions (determined through cluster analysis of measures of precipitation) of the study area over three seasons (November–February, March–June and July–October). The models used multiresolution decomposition (an additive decomposition based on powers of two using a discrete wavelet transform) of tree-ring chronologies from Canada and the US and seasonal 12-year moving average precipitation based on Adjusted and Homogenized Canadian Climate Data and US Historical Climatology Network data. Results show that precipitation varies on long-term (multidecadal) time scales of 16, 32 and 64 years. Past extended pluvial and drought events, which can vary greatly with season and subregion, were highlighted by the models. Results suggest that the recent wet period may be a part of natural variability on a very long time scale.

Distinguishing Southern Africa precipitation response by strength of El Niño events

NASA Astrophysics Data System (ADS)

Pomposi, C.; Funk, C. C.; Shukla, S.; Magadzire, T.

2017-12-01

The El Niño Southern Oscillation (ENSO) is a leading mode of interannual precipitation variability and the main source of skill for seasonal climate predictions. Interannual precipitation variability linked to ENSO can have drastic impacts on agricultural systems and food resources in the semi-arid tropics, highlighting the need for increased information regarding ENSO's links to sub-seasonal to seasonal precipitation variations. The present work describes a case study on recent precipitation variability during warm ENSO events (i.e. El Niño) for the austral summer rainy season (December-February) in Southern Africa. Using a blending of observational and model data, it is found that the probability distribution of precipitation varies according to the strength of El Niño events. Strong El Niño events show a much clearer tendency for drying than moderate or weak events, which have smaller absolute magnitude anomalies and larger spatial heterogeneity in the precipitation response. A dynamical exploration of the various precipitation responses is also completed. The techniques utilized can be easily expanded to study likelihood of drought during El Niño for a variety of other regions and also provides information about El Niño strength and its influence on regional teleconnections. Finally, this presentation will describe the channels by which seasonal forecasting information is disseminated in the region and utilized by the Famine Early Warning Systems Network to help mitigate the impacts of potential food insecurity crises.

Climatically driven yield variability of major crops in Khakassia (South Siberia)

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

2018-06-01

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States

USGS Publications Warehouse

Bucklin, David N.; Watling, James I.; Speroterra, Carolina; Brandt, Laura A.; Mazzotti, Frank J.; Romañach, Stephanie S.

2013-01-01

High-resolution (downscaled) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different downscaling approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between downscaling approaches and that the variation attributable to downscaling technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between downscaling techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of downscaling applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative downscaling methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.

Climatically driven yield variability of major crops in Khakassia (South Siberia)

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

2017-12-01

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

Exploring a Variable-Resolution Approach for Simulating Regional Climate in the Rocky Mountain Region Using the VR-CESM

NASA Astrophysics Data System (ADS)

Wu, Chenglai; Liu, Xiaohong; Lin, Zhaohui; Rhoades, Alan M.; Ullrich, Paul A.; Zarzycki, Colin M.; Lu, Zheng; Rahimi-Esfarjani, Stefan R.

2017-10-01

The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. In this study we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10-40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. These results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.

Rising synchrony controls western North American ecosystems

Treesearch

Bryan A. Black; Peter van der Sleen; Emanuele Di Lorenzo; Daniel Griffin; William J. Sydeman; Jason B. Dunham; Ryan R. Rykaczewski; Marisol García-Reyes; Mohammad Safeeq; Ivan Arismendi; Steven J. Bograd

2018-01-01

Along the western margin of North America, the winter expression of the North Pacific High (NPH) strongly influences interannual variability in coastal upwelling, storm track position, precipitation, and river discharge. Coherence among these factors induces covariance among physical and biological processes across adjacent marine and terrestrial ecosystems. Here, we...

North-South precipitation patterns in western North America on interannual-to-decadal timescales

USGS Publications Warehouse

Dettinger, M.D.; Cayan, D.R.; Diaz, Henry F.; Meko, D.M.

1998-01-01

The overall amount of precipitation deposited along the West Coast and western cordillera of North America from 25??to 55??N varies from year to year, and superimposed on this domain-average variability are varying north-south contrasts on timescales from at least interannual to interdecadal. In order to better understand the north-south precipitation contrasts, their interannual and decadal variations are studied in terms of how much they affect overall precipitation amounts and how they are related to large-scale climatic patterns. Spatial empirical orthogonal functions (EOFs) and spatial moments (domain average, central latitude, and latitudinal spread) of zonally averaged precipitation anomalies along the westernmost parts of North America are analyzed, and each is correlated with global sea level pressure (SLP) and sea surface temperature series, on interannual (defined here as 3-7 yr) and decadal (>7 yr) timescales. The interannual band considered here corresponds to timescales that are particularly strong in tropical climate variations and thus is expected to contain much precipitation variability that is related to El Nino-Southern Oscillation; the decadal scale is defined so as to capture the whole range of long-term climatic variations affecting western North America. Zonal EOFs of the interannual and decadal filtered versions of the zonal-precipitation series are remarkably similar. At both timescales, two leading EOFs describe 1) a north-south seesaw of precipitation pivoting near 40??N and 2) variations in precipitation near 40??N, respectively. The amount of overall precipitation variability is only about 10% of the mean and is largely determined by precipitation variations around 40??-45??N and most consistently influenced by nearby circulation patterns; in this sense, domain-average precipitation is closely related to the second EOF. The central latitude and latitudinal spread of precipitation distributions are strongly influenced by precipitation variations in the southern parts of western North America and are closely related to the first EOF. Central latitude of precipitation moves south (north) with tropical warming (cooling) in association with midlatitude western Pacific SLP variations, on both interannual and decadal timescales. Regional patterns and zonal averages of precipitation-sensitive tree-ring series are used to corroborate these patterns and to extend them into the past and appear to share much long- and short-term information with the instrumentally based zonal precipitation EOFs and moments.The overall amount of precipitation deposited along the West Coast and western cordillera of North America from 25?? to 55 ??N varies from year to year, and superimposed on this domain-average variability are varying north-south contrasts on timescales from at least interannual to interdecadal. In order to better understand the north-south precipitation contrasts, their interannual and decadal variations are studied in terms of how much they affect overall precipitation amounts and how they are related to large-scale climatic patterns. Spatial empirical orthogonal functions (EOFs) and spatial moments (domain average, central latitude, and latitudinal spread) of zonally averaged precipitation anomalies along the westernmost parts of North America are analyzed, and each is correlated with global sea level pressure (SLP) and sea surface temperature series, on interannual (defined here as 3-7 yr) and decadal (>7 yr) timescales. The interannual band considered here corresponds to timescales that are particularly strong in tropical climate variations and thus is expected to contain much precipitation variability that is related to El Nino-Southern Oscillation; the decadal scale is defined so as to capture the whole range of long-term climatic variations affecting western North America. Zonal EOFs of the interannual and decadal filtered versions of the zonal-precipitation series are remarkably similar. At both tim

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

NASA Astrophysics Data System (ADS)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

NASA Astrophysics Data System (ADS)

Santos, Monica; Fragoso, Marcelo

2010-05-01

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude, latitude, distance from sea and distance to the highest orographic barrier) on the rainfall behaviours described by the studied variables. The techniques of spatial interpolation evaluated include univariate and multivariate methods: cokriging, kriging, IDW (inverse distance weighted) and multiple linear regression. Validation procedures were used, assessing the estimated errors in the analysis of descriptive statistics of the models. Multiple linear regression models produced satisfactory results in relation to 70% of the rainfall parameters, suggested by lower average percentage of error. However, the results also demonstrates that there is no an unique and ideal model, depending on the rainfall parameter in consideration. Probably, the unsatisfactory results obtained in relation to some rainfall parameters was motivated by constraints as the spatial complexity of the precipitation patterns, as well as to the deficient spatial coverage of the territory by the rain-gauges network. References Diodato, N. (2005). The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. Internacional Journal of Climatology, 25(3), 351-363. Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228, 113 - 129.

Changes in the type of precipitation and associated cloud types in Eastern Romania (1961-2008)

NASA Astrophysics Data System (ADS)

Manea, Ancuta; Birsan, Marius-Victor; Tudorache, George; Cărbunaru, Felicia

2016-03-01

Recent climate change is characterized (among other things) by changes in the frequency of some meteorological phenomena. This paper deals with the long-term changes in various precipitation types, and the connection between their variability and cloud type frequencies, at 11 meteorological stations from Eastern Romania over 1961-2008. These stations were selected with respect to data record completeness for all considered variables (weather phenomena and cloud type). The meteorological variables involved in the present study are: monthly number of days with rain, snowfall, snow showers, rain and snow (sleet), sleet showers and monthly frequency of the Cumulonimbus, Nimbostratus and Stratus clouds. Our results show that all stations present statistically significant decreasing trends in the number of days with rain in the warm period of the year. Changes in the frequency of days for each precipitation type show statistically significant decreasing trends for non-convective (stratiform) precipitation - rain, drizzle, sleet and snowfall -, while the frequencies of rain shower and snow shower (convective precipitation) are increasing. Cloud types show decreasing trends for Nimbostratus and Stratus, and increasing trends for Cumulonimbus.

Characterizing Climate Controls on Vegetation Seasonality in the North American Southwest

NASA Astrophysics Data System (ADS)

Fish, M. A.; Cook, B.; Smerdon, J. E.; Seager, R.; Williams, P.

2014-12-01

The North American Southwest, which extends from Colorado to southern Mexico and California to eastern Texas, encompasses a diversity of climates, elevations, and ecosystems. This region is expected to experience significant climatic change, and associated impacts, in the coming decades. To better understand the spatiotemporal variability of vegetation in the Southwest and the expected climatic controls on timing and spatial extend of vegetation growth, we compared GIMMS normalized difference vegetation index (NDVI, 1981-2011) against temperature and precipitation data. Spatial variations in vegetation seasonality and the timing of peak NDVI are linked to spatial variability in the precipitation regimes across the Southwest. Regions with spring NDVI peaks are dominated by winter precipitation, while late summer and fall peaks are in regions with significant summer precipitation driven by the North American Monsoon. Inter-annual variability in peak NDVI is positively correlated with precipitation and negatively correlated with temperature, with the largest correlation coefficients at one-month lags. The only significant long-term trends in NDVI are for northern Mexico, where agricultural productivity has been increasing over the last 30 years.

Using TRMM Data To Understand Interannual Variations In the Tropical Water Balance

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Fitzjarrald, Dan; Arnold, James E. (Technical Monitor)

2002-01-01

A significant element of the science rationale for TRMM centered on assembling rainfall data needed to validate climate models-- climatological estimates of precipitation, its spatial and temporal variability, and vertical modes of latent heat release. Since the launch of TRMM, a great interest in the science community has emerged for quantifying interannual variability (IAV) of precipitation and its relationship to sea-surface temperature (SST) changes. The fact that TRMM has sampled one strong warm/ cold ENSO couplet, together with the prospect for a mission lifetime approaching ten years, has bolstered this interest in these longer time scales. Variability on a regional basis as well as for the tropics as a whole is of concern. Our analysis of TRMM results so far has shown surprising lack of concordance between various algorithms in quantifying IAV of precipitation. The first objective of this talk is to quantify the sensitivity of tropical precipitation to changes in SSTs. We analyze performance of the 3A11, 3A25, and 3B31 algorithms and investigate their relationship to scattering-- based algorithms constructed from SSM/I and TRMM 85 kHz data. The physical basis for the differences (and similarities) in depicting tropical oceanic and land rainfall will be discussed. We argue that scattering-based estimates of variability constitute a useful upper bound for precipitation variations. These results lead to the second question addressed in this talk-- How do TRMM precipitation / SST sensitivities compare to estimates of oceanic evaporation and what are the implications of these uncertainties in determining interannual changes in large-scale moisture transport? We summarize results of an analysis performed using COADS data supplemented by SSM/I estimates of near-surface variables to assess evaporation sensitivity to SST. The response of near 5 W sq m/K is compared to various TRMM precipitation sensitivities. Implied moisture convergence over the tropics and its sensitivity to errors of these algorithms is discussed.

Characterizing hydroclimatic variability in tributaries of the Upper Colorado River Basin—WY1911-2001

NASA Astrophysics Data System (ADS)

Matter, Margaret A.; Garcia, Luis A.; Fontane, Darrell G.; Bledsoe, Brian

2010-01-01

SummaryMountain snowpack is the main source of water in the semi-arid Colorado River Basin (CRB), and while the demands for water are increasing, competing and often conflicting, the supply is limited and has become increasingly variable over the 20th Century. Greater variability is believed to contribute to lower accuracy in water supply forecasts, plus greater variability violates the assumption of stationarity, a fundamental assumption of many methods used in water resources engineering planning, design and management. Thus, it is essential to understand the underpinnings of hydroclimatic variability in order to accurately predict effects of climate changes and effectively meet future water supply challenges. A new methodology was applied to characterized time series of temperature, precipitation, and streamflow (i.e., historic and reconstructed undepleted flows) according to the three climate regimes that occurred in CRB during the 20th Century. Results for two tributaries in the Upper CRB show that hydroclimatic variability is more deterministic than previously thought because it entails complementary temperature and precipitation patterns associated with wetter or drier conditions on climate regime and annual scales. Complementary temperature and precipitation patterns characterize climate regime type (e.g., cool/wet and warm/dry), and the patterns entail increasing or decreasing temperatures and changes in magnitude and timing of precipitation according to the climate regime type. Accompanying each climate regime on annual scales are complementary temperature ( T) and precipitation ( P) patterns that are associated with upcoming precipitation and annual basin yield (i.e., total annual flow volume at a streamflow gauge). Annual complementary T and P patterns establish by fall, are detectable as early as September, persist to early spring, are related to the relative magnitude of upcoming precipitation and annual basin yield, are unique to climate regime type, and are specific to each river basin. Thus, while most of the water supply in the Upper CRB originates from winter snowpack, statistically significant indictors of relative magnitude of upcoming precipitation and runoff are evident in the fall, well before appreciable snow accumulation. Results of this study suggest strategies that may integrated into existing forecast methods to potentially improve forecast accuracy and advance lead time by as much as six months (i.e., from April 1 to October 1 of the previous year). These techniques also have applications in downscaling climate models and in river restoration and management.

The impact of boreal autumn SST anomalies over the South Pacific on boreal winter precipitation over East Asia

NASA Astrophysics Data System (ADS)

Ao, Juan; Sun, Jianqi

2016-05-01

The possible mechanism behind the variability in the dipole pattern of boreal winter precipitation over East Asia is analyzed in this study. The results show that the SST anomalies (SSTAs) over the South Pacific Ocean (SPO) in boreal autumn are closely related to the variability in the dipole pattern of boreal winter precipitation over East Asia. The physical link between the boreal autumn SPO SSTAs and the boreal winter East Asian precipitation dipole pattern is shown to mainly be the seasonal persistence of the SPO SSTAs themselves. The seasonal persistence of the SPO SSTAs can memorize and transport the signal of the boreal autumn SSTAs to the following winter, and then stimulates a meridional teleconnection pattern from the SH to the NH, resulting in a meridional dipole pattern of atmospheric circulation over East Asia in boreal winter. As a major influencing factor, this dipole pattern of the atmospheric circulation can finally lead to the anomalous precipitation dipole pattern over East Asia in boreal winter. These observed physical processes are further confirmed in this study through numerical simulation. The evidence from this study, showing the impact of the SPO SSTAs in boreal autumn, not only deepens our understanding of the variability in East Asian boreal winter precipitation, but also provides a potentially useful predictor for precipitation in the region.

Precipitation response to the current ENSO variability in a warming world

NASA Astrophysics Data System (ADS)

Bonfils, C.; Santer, B. D.; Phillips, T. J.; Marvel, K.; Leung, L.

2013-12-01

The major triggers of past and recent droughts include large modes of variability, such as ENSO, as well as specific and persistent patterns of sea surface temperature anomalies (SSTAs; Hoerling and Kumar, 2003, Shin et al. 2010, Schubert et al. 2009). However, alternative drought initiators are also anticipated in response to increasing greenhouse gases, potentially changing the relative contribution of ocean variability as drought initiator. They include the intensification of the current zonal wet-dry patterns (the thermodynamic mechanism, Held and Soden, 2006), a latitudinal redistribution of global precipitation (the dynamical mechanism, Seager et al. 2007, Seidel et al. 2008, Scheff and Frierson 2008) and a reduction of local soil moisture and precipitation recycling (the land-atmosphere argument). Our ultimate goal is to investigate whether the relative contribution of those mechanisms change over time in response to global warming. In this study, we first perform an EOF analysis of the 1900-1999 time series of observed global SST field and identify a simple ENSO-like (ENSOL) mode of SST variability. We show that this mode is well spatially and temporally correlated with observed worldwide regional precipitation and drought variability. We then develop concise metrics to examine the fidelity with which the CMIP5 coupled global climate models (CGCMs) capture this particular ENSO-like mode in the current climate, and their ability to replicate the observed teleconnections with precipitation. Based on the CMIP5 model projections of future climate change, we finally analyze the potential temporal variations in ENSOL to be anticipated under further global warming, as well as their associated teleconnections with precipitation (pattern, amplitude, and total response). Overall, our approach allows us to determine what will be the effect of the current ENSO-like variability (i.e., as measured with instrumental observations) on precipitation in a warming world. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, and is supported, among others, by C.B. Early Career Research Program award.

Climate change impacts on faecal indicator and waterborne pathogen concentrations and disease

NASA Astrophysics Data System (ADS)

Hofstra, Nynke; Vermeulen, Lucie C.; Wondmagegn, Berhanu Y.

2013-04-01

Changes in temperature and precipitation patterns may impact on the concentrations of the faecal indicator E. coli and waterborne pathogens, such as Cryptosporidium, in the surface water, and consequently - through drinking water, recreational water or consumption of irrigated vegetables - on the risk of waterborne disease. Although an increased temperature would generally increase the decline of pathogens and therefore decrease the surface water concentrations, increased precipitation and an increased incidence of extreme precipitation may increase surface water concentrations through increased (sub-)surface runoff and an increased risk of sewer overflows. And while the diluting effect of increased precipitation decreases the surface water concentration, decreased precipitation increases the percentage of sewage in the surface water and therefore increases the concentration. Moreover, (extreme) precipitation after drought may also increase the concentration. Changes in behaviour, such as increased recreation and irrigation with higher temperatures may impact on the disease risk. What the balance is between these positive and negative impacts of climate change on faecal indicator and waterborne pathogen concentrations and disease is not well known yet. A lack of available statistical or process-based models and suitable scenarios prevents quantitative analyses. We will present two examples of recent studies that aim to assess the impact of climate change on faecal indicator concentrations and waterborne disease. The first is a study on the relationship between climate variables and E. coli concentrations in the water of river systems in the Netherlands for the period 1985 - 2010. This study shows that each of the variables water temperature (negatively), precipitation and discharge (both positively) are significantly correlated with E. coli concentrations for most measurement locations. We will also present a linear regression model, including all of these variables. In the second example we assess the relationship between the weather variables precipitation and minimum and maximum temperature and the number of diarrhoeal cases in Ethiopia. We have digitised data from the Ethiopian health service and hospitals on the number of diarrhoeal cases for the period 2005 - 2010 and used meteorological data from their weather service. Very strong correlations can be found between the monthly weather variables and the number of diarrhoeal cases and a linear regression model including all variables explains a large part of the variability of the data. The studies indicate that climate change may increase the waterborne pathogen concentration in surface water and disease risk and should therefore not be ignored as a threat to microbial water quality.

How Does Snow Persistence Relate to Annual Streamflow in Mountain Watersheds of the Western U.S. With Wet Maritime and Dry Continental Climates?

NASA Astrophysics Data System (ADS)

Hammond, John C.; Saavedra, Freddy A.; Kampf, Stephanie K.

2018-04-01

With climate warming, many regions are experiencing changes in snow accumulation and persistence. These changes are known to affect streamflow volume, but the magnitude of the effect varies between regions. This research evaluates whether variables derived from remotely sensed snow cover can be used to estimate annual streamflow at the small watershed scale across the western U.S., a region with a wide range of climate types. We compared snow cover variables derived from MODIS, snow persistence (SP), and snow season (SS), to more commonly utilized metrics, snow fraction (fraction of precipitation falling as snow, SF), and peak snow water equivalent (SWE). Each variable represents different information about snow, and this comparison assesses similarities and differences between the snow metrics. Next, we evaluated how two snow variables, SP and SWE, related to annual streamflow (Q) for 119 USGS reference watersheds and examined whether these relationships varied for wet/warm (precipitation surplus) and dry/cold (precipitation deficit) watersheds. Results showed high correlations between all snow variables, but the slopes of these relationships differed between climates, with wet/warm watersheds displaying lower SF and higher SWE for the same SP. In dry/cold watersheds, both SP and SNODAS SWE correlated with Q spatially across all watersheds and over time within individual watersheds. We conclude that SP can be used to map spatial patterns of annual streamflow generation in dry/cold parts of the region. Applying this approach to the Upper Colorado River Basin demonstrates that 50% of streamflow comes from areas >3,000 masl. If the relationship between SP and Q is similar in other dry/cold regions, this approach could be used to estimate annual streamflow in ungauged basins.

Groundwater Variability in a Sandstone Catchment and Linkages with Large-scale Climatic Circulatio

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Lavers, D. A.; Bradley, C.

2015-12-01

Groundwater is a crucial water resource that sustains river ecosystems and provides public water supply. Furthermore, during periods of prolonged high rainfall, groundwater-dominated catchments can be subject to protracted flooding. Climate change and associated projected increases in the frequency and intensity of hydrological extremes have implications for groundwater levels. This study builds on previous research undertaken on a Chalk catchment by investigating groundwater variability in a UK sandstone catchment: the Tern in Shropshire. In contrast to the Chalk, sandstone is characterised by a more lagged response to precipitation inputs; and, as such, it is important to determine the groundwater behaviour and its links with the large-scale climatic circulation to improve process understanding of recharge, groundwater level and river flow responses to hydroclimatological drivers. Precipitation, river discharge and groundwater levels for borehole sites in the Tern basin over 1974-2010 are analysed as the target variables; and we use monthly gridded reanalysis data from the Twentieth Century Reanalysis Project (20CR). First, groundwater variability is evaluated and associations with precipitation / discharge are explored using monthly concurrent and lagged correlation analyses. Second, gridded 20CR reanalysis data are used in composite and correlation analyses to identify the regions of strongest climate-groundwater association. Results show that reasonably strong climate-groundwater connections exist in the Tern basin, with a several months lag. These lags are associated primarily with the time taken for recharge waters to percolate through to the groundwater table. The uncovered patterns improve knowledge of large-scale climate forcing of groundwater variability and may provide a basis to inform seasonal prediction of groundwater levels, which would be useful for strategic water resource planning.

Strategies for Near Real Time Estimation of Precipitable Water Vapor

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz E.

1996-01-01

Traditionally used for high precision geodesy, the GPS system has recently emerged as an equally powerful tool in atmospheric studies, in particular, climatology and meteorology. There are several products of GPS-based systems that are of interest to climatologists and meteorologists. One of the most useful is the GPS-based estimate of the amount of Precipitable Water Vapor (PWV) in the troposphere. Water vapor is an important variable in the study of climate changes and atmospheric convection (Yuan et al., 1993), and is of crucial importance for severe weather forecasting and operational numerical weather prediction (Kuo et al., 1993).

Continuous Real-time Measurements of δ-values of Precipitation during Rain Events: Insights into Tropical Convection

NASA Astrophysics Data System (ADS)

He, S.; Goodkin, N.; Jackisch, D.; Ong, M. R.

2017-12-01

Studying how the tropical convection affects stable isotopes in precipitation can help us understand the evolution of the precipitation isotopes over time and improve the interpretation of paleoclimate records in the tropical region. We have been continuously monitoring δ-values of precipitation during rain events in Singapore for the past three years (2014-2017) using a diffusion sampler-cavity ring-down spectrometer (DS-CRDS) system. This period of time spans the most recent El Niño and La Niña, and thus affords us the opportunity to use our ultra-high temporal resolutsion data to examine the El Niño-Southern Oscillation (ENSO) impact on the precipitation isotopes during convection and the intra-annual variability in the region. δ-values of precipitation could change significantly during a single event, and mainly exhibits "V" (or "U" ) shape or "W" shape patterns. The mesoscale subsidence and rain re-evaporation are two processes that largely shape the isotopes of precipitation during events. Time series of the initial, highest and lowest δ-values of individual events, and absolute change in δ-values during these events show clear evolution over time. Events with low δ-values occurred less frequently in 2015 than the other years. Likewise, the frequency of events with larger magnitude change in δ-values and low initial values are also lower in 2015. The events with low averaged δ-values usually have very low initial δ-values, and are closely associated with organized regional convection, indicating that the convective activities in the upwind area can significantly influence the δ-values of precipitation. All these observations suggest lower intensity and frequency of regional organized convection in 2015. The ENSO event in 2015 was likely responsible for these changes. During an ENSO event, convection over the central and eastern Pacific is strengthened while that of the western Pacific and Southeast Asia is supressed, resulting in a weakened monsoon in the region. Therefore, we believe that ENSO can not only impact the regional convection, but also drive the intra-annual variability in δ-values of precipitation in the area.

Short-term variability of gamma radiation at the ARM Eastern North Atlantic facility (Azores).

PubMed

Barbosa, S M; Miranda, P; Azevedo, E B

2017-06-01

This work addresses the short-term variability of gamma radiation measured continuously at the Eastern North Atlantic (ENA) facility located in the Graciosa island (Azores, 39N; 28W), a fixed site of the Atmospheric Radiation Measurement programme (ARM). The temporal variability of gamma radiation is characterized by occasional anomalies over a slowly-varying signal. Sharp peaks lasting typically 2-4 h are coincident with heavy precipitation and result from the scavenging effect of precipitation bringing radon progeny from the upper levels to the ground surface. However the connection between gamma variability and precipitation is not straightforward as a result of the complex interplay of factors such as the precipitation intensity, the PBL height, the cloud's base height and thickness, or the air mass origin and atmospheric concentration of sub-micron aerosols, which influence the scavenging processes and therefore the concentration of radon progeny. Convective precipitation associated with cumuliform clouds forming under conditions of warming of the ground relative to the air does not produce enhancements in gamma radiation, since the drop growing process is dominated by the fast accretion of liquid water, resulting in the reduction of the concentration of radionuclides by dilution. Events of convective precipitation further contribute to a reduction in gamma counts by inhibiting radon release from the soil surface and by attenuating gamma rays from all gamma-emitting elements on the ground. Anomalies occurring in the absence of precipitation are found to be associated with a diurnal cycle of maximum gamma counts before sunrise decreasing to a minimum in the evening, which are observed in conditions of thermal stability and very weak winds enabling the build-up of near surface radon progeny during the night. Copyright © 2017 Elsevier Ltd. All rights reserved.

Holocene Multi-Decadal to Millennial-Scale Hydrologic Variability on the South American Altiplano

NASA Astrophysics Data System (ADS)

Fritz, S. C.; Baker, P. A.; Ekdahl, E.; Burns, S.

2006-12-01

On orbital timescales, lacustrine sediment records in the tropical central Andes show massive changes in lake level due to mechanisms related to global-scale drivers, varying at precessional timescales. Here we use stable isotopic and diatom records from two lakes in the Lake Titicaca drainage basin to reconstruct multi- decadal to millennial scale precipitation variability during the last 7000 to 8000 years. The records are tightly coupled at multi-decadal to millennial scales with each other and with lake-level fluctuations in Lake Titicaca, indicating that the lakes are recording a regional climate signal. A quantitative reconstruction of precipitation from stable isotopic data indicates that the central Andes underwent significant wet to dry alternations at multi- centennial frequencies with an amplitude of 30 to 40% of total precipitation. A strong millennial-scale component, similar in duration to periods of increased ice rafted debris flux in the North Atlantic, is observed in both lake records, suggesting that tropical North Atlantic sea-surface temperature (SST) variability may partly control regional precipitation. No clear relationship is evident between these records and the inferred ENSO history from Lago Pallcacocha in the northern tropical Andes. In the instrumental period, regional precipitation variability on inter-annual timescales is clearly influenced by Pacific modes; for example, most El Ninos produce dry and warm conditions in this part of the central Andes. However, on longer timescales, the control of tropical Pacific modes is less clear. Our reconstructions suggest that the cold intervals of the Holocene Bond events are periods of increased precipitation in the central Andes, thus indicating an anti-phasing of precipitation variation in the southern tropics of South America relative to the Northern Hemisphere monsoon region.

Climate change and water availability for vulnerable agriculture

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas; Tarquis, Ana Maria

2017-04-01

Climatic projections for the Mediterranean basin indicate that the area will suffer a decrease in water resources due to climate change. The key climatic trends identified for the Mediterranean region are continuous temperature increase, further drying with precipitation decrease and the accentuation of climate extremes, such as droughts, heat waves and/or forest fires, which are expected to have a profound effect on agriculture. Indeed, the impact of climate variability on agricultural production is important at local, regional, national, as well as global scales. Agriculture of any kind is strongly influenced by the availability of water. Climate change will modify rainfall, evaporation, runoff, and soil moisture storage patterns. Changes in total seasonal precipitation or in its pattern of variability are both important. Similarly, with higher temperatures, the water-holding capacity of the atmosphere and evaporation into the atmosphere increase, and this favors increased climate variability, with more intense precipitation and more droughts. As a result, crop yields are affected by variations in climatic factors, such as air temperature and precipitation, and the frequency and severity of the above mentioned extreme events. The aim of this work is to briefly present the main effects of climate change and variability on water resources with respect to water availability for vulnerable agriculture, namely in the Mediterranean region. Results of undertaken studies in Greece on precipitation patterns and drought assessment using historical data records are presented. Based on precipitation frequency analysis, evidence of precipitation reductions is shown. Drought is assessed through an agricultural drought index, namely the Vegetation Health Index (VHI), in Thessaly, a drought-prone region in central Greece. The results justify the importance of water availability for vulnerable agriculture and the need for drought monitoring in the Mediterranean basin as part of an integrated climate adaptation strategy.

Growth responses of Scots pine to climatic factors on reclaimed oil shale mined land.

PubMed

Metslaid, Sandra; Stanturf, John A; Hordo, Maris; Korjus, Henn; Laarmann, Diana; Kiviste, Andres

2016-07-01

Afforestation on reclaimed mining areas has high ecological and economic importance. However, ecosystems established on post-mining substrate can become vulnerable due to climate variability. We used tree-ring data and dendrochronological techniques to study the relationship between climate variables and annual growth of Scots pine (Pinus sylvestris L.) growing on reclaimed open cast oil shale mining areas in Northeast Estonia. Chronologies for trees of different age classes (50, 40, 30) were developed. Pearson's correlation analysis between radial growth indices and monthly climate variables revealed that precipitation in June-July and higher mean temperatures in spring season enhanced radial growth of pine plantations, while higher than average temperatures in summer months inhibited wood production. Sensitivity of radial increment to climatic factors on post-mining soils was not homogenous among the studied populations. Older trees growing on more developed soils were more sensitive to precipitation deficit in summer, while growth indices of two other stand groups (young and middle-aged) were highly correlated to temperature. High mean temperatures in August were negatively related to annual wood production in all trees, while trees in the youngest stands benefited from warmer temperatures in January. As a response to thinning, mean annual basal area increment increased up to 50 %. By managing tree competition in the closed-canopy stands, through the thinning activities, tree sensitivity and response to climate could be manipulated.

Influence of sub-kilometer precipitation datasets on simulated snowpack and glacier winter balance in alpine terrain.

NASA Astrophysics Data System (ADS)

Vionnet, Vincent; Six, Delphine; Auger, Ludovic; Lafaysse, Matthieu; Quéno, Louis; Réveillet, Marion; Dombrowski-Etchevers, Ingrid; Thibert, Emmanuel; Dumont, Marie

2017-04-01

Capturing spatial and temporal variabilities of meteorological conditions at fine scale is necessary for modelling snowpack and glacier winter mass balance in alpine terrain. In particular, precipitation amount and phase are strongly influenced by the complex topography. In this study, we assess the impact of three sub-kilometer precipitation datasets (rainfall and snowfall) on distributed simulations of snowpack and glacier winter mass balance with the detailed snowpack model Crocus for winter 2011-2012. The different precipitation datasets at 500-m grid spacing over part of the French Alps (200*200 km2 area) are coming either from (i) the SAFRAN precipitation analysis specially developed for alpine terrain, or from (ii) operational outputs of the atmospheric model AROME at 2.5-km grid spacing downscaled to 500 m with fixed lapse rate or from (iii) a version of the atmospheric model AROME at 500-m grid spacing. Others atmospherics forcings (air temperature and humidity, incoming longwave and shortwave radiation, wind speed) are taken from the AROME simulations at 500-m grid spacing. These atmospheric forcings are firstly compared against a network of automatic weather stations. Results are analysed with respect to station location (valley, mid- and high-altitude). The spatial pattern of seasonal snowfall and its dependency with elevation is then analysed for the different precipitation datasets. Large differences between SAFRAN and the two versions of AROME are found at high-altitude. Finally, results of Crocus snowpack simulations are evaluated against (i) punctual in-situ measurements of snow depth and snow water equivalent, and (ii) maps of snow covered areas retrieved from optical satellite data (MODIS). Measurements of winter accumulation of six glaciers of the French Alps are also used and provide very valuable information on precipitation at high-altitude where the conventional observation network is scarce. This study illustrates the potential and limitations of high-resolution atmospheric models to drive simulations of snowpack and glacier winter mass balance in alpine terrain.

Tree-ring δ18O in African mahogany (Entandrophragma utile) records regional precipitation and can be used for climate reconstructions

NASA Astrophysics Data System (ADS)

van der Sleen, Peter; Groenendijk, Peter; Zuidema, Pieter A.

2015-04-01

The availability of instrumental climate data in West and Central Africa is very restricted, both in space and time. This limits the understanding of the regional climate system and the monitoring of climate change and causes a need for proxies that allow the reconstruction of paleoclimatic variability. Here we show that oxygen isotope values (δ18O) in tree rings of Entandrophragma utile from North-western Cameroon correlate to precipitation on a regional to sub-continental scale (1930-2009). All found correlations were negative, following the proposed recording of the 'amount effect' by trees in the tropics. The capacity of E. utile to record the variability of regional precipitation is also confirmed by the significant correlation of tree-ring δ18O with river discharge data (1944-1983), outgoing longwave radiation (a proxy for cloud cover; 1974-2011) and sea surface salinity in the Gulf of Guinea (1950-2011). Furthermore, the high values in the δ18O chronology from 1970 onwards coincide with the Sahel drought period. Given that E. utile presents clear annual growth rings, has a wide-spread distribution in tropical Africa and is long lived (> 250 years), we argue that the analysis of oxygen isotopes in growth rings of this species is a promising tool for the study of paleoclimatic variability during the last centuries in West and Central Africa.

Norwegian fjord sediments reveal NAO related winter temperature and precipitation changes of the past 2800 years

NASA Astrophysics Data System (ADS)

Faust, Johan C.; Fabian, Karl; Milzer, Gesa; Giraudeau, Jacques; Knies, Jochen

2016-02-01

The North Atlantic Oscillation (NAO) is the leading mode of atmospheric circulation variability in the North Atlantic region. Associated shifts of storm tracks, precipitation and temperature patterns affect energy supply and demand, fisheries and agricultural, as well as marine and terrestrial ecological dynamics. Long-term NAO records are crucial to better understand its response to climate forcing factors, and assess predictability and shifts associated with ongoing climate change. A recent study of instrumental time series revealed NAO as main factor for a strong relation between winter temperature, precipitation and river discharge in central Norway over the past 50 years. Here we compare geochemical measurements with instrumental data and show that primary productivity recorded in central Norwegian fjord sediments is sensitive to NAO variability. This observation is used to calibrate paleoproductivity changes to a 500-year reconstruction of winter NAO (Luterbacher et al., 2001). Conditioned on a stationary relation between our climate proxy and the NAO we establish a first high resolution NAO proxy record (NAOTFJ) from marine sediments covering the past 2800 years. The NAOTFJ shows distinct co-variability with climate changes over Greenland, solar activity and Northern Hemisphere glacier dynamics as well as climatically associated paleo-demographic trends. The here presented climate record shows that fjord sediments provide crucial information for an improved understanding of the linkages between atmospheric circulation, solar and oceanic forcing factors.

Dynamic Downscaling of Seasonal Simulations over South America.

NASA Astrophysics Data System (ADS)

Misra, Vasubandhu; Dirmeyer, Paul A.; Kirtman, Ben P.

2003-01-01

In this paper multiple atmospheric global circulation model (AGCM) integrations at T42 spectral truncation and prescribed sea surface temperature were used to drive regional spectral model (RSM) simulations at 80-km resolution for the austral summer season (January-February-March). Relative to the AGCM, the RSM improves the ensemble mean simulation of precipitation and the lower- and upper-level tropospheric circulation over both tropical and subtropical South America and the neighboring ocean basins. It is also seen that the RSM exacerbates the dry bias over the northern tip of South America and the Nordeste region, and perpetuates the erroneous split intertropical convergence zone (ITCZ) over both the Pacific and Atlantic Ocean basins from the AGCM. The RSM at 80-km horizontal resolution is able to reasonably resolve the Altiplano plateau. This led to an improvement in the mean precipitation over the plateau. The improved resolution orography in the RSM did not substantially change the predictability of the precipitation, surface fluxes, or upper- and lower-level winds in the vicinity of the Andes Mountains from the AGCM. In spite of identical convective and land surface parameterization schemes, the diagnostic quantities, such as precipitation and surface fluxes, show significant differences in the intramodel variability over oceans and certain parts of the Amazon River basin (ARB). However, the prognostic variables of the models exhibit relatively similar model noise structures and magnitude. This suggests that the model physics are in large part responsible for the divergence of the solutions in the two models. However, the surface temperature and fluxes from the land surface scheme of the model [Simplified Simple Biosphere scheme (SSiB)] display comparable intramodel variability, except over certain parts of ARB in the two models. This suggests a certain resilience of predictability in SSiB (over the chosen domain of study) to variations in horizontal resolution. It is seen in this study that the summer precipitation over tropical and subtropical South America is highly unpredictable in both models.

Centennial and Extreme Climate Variability in the Last 1500 Year from the Belize Central Shelf Lagoon (Central America): Successive Droughts and Floods Linked to the Demise of the Mayan Civilization

NASA Astrophysics Data System (ADS)

Droxler, A. W.; Agar Cetin, A.; Bentley, S. J.

2014-12-01

This study focuses on the last 1500 yr precipitation record archived in the mixed carbonate/siliciclastic sediments accumulated in the Belize Central Shelf Lagoon, part of the Yucatan Peninsula eastern continental margin, proximal to the land areas where the Mayan Civilization thrived and then abruptly collapsed. This study is mainly based upon the detailed analyses of cores, BZE-RH-SVC-58 and 68, retrieved in 30 and 19 m of water depth from Elbow Caye Lagoon and English Caye Channel, respectively. The core timeframe is well-constrained by AMS radiocarbon dating of benthic foraminifera, Quinqueloculina. Carbonate content was determined by carbonate bomb, particle size fractions with a Malvern Master Sizer 2000 particle size analyzer, and element (Ti, Si, K, Fe, Al, Ca, and Sr) counts via X-Ray Fluorescence (XRF). The variations of elements such as Ti and K counts, and Ti/Al in these two cores have recorded, in the past past 1500 years, the weathering rate variations of the adjacent Maya Mountain, defining alternating periods of high precipitation and droughts, linked to large climate fluctuations and extreme events, highly influenced by the ITCZ latitudinal migration. The CE 800-900 century just preceding the Medieval Climate Anomaly (MCA), characterized by unusually low Ti counts and Ti/Al, is interpreted to represent a time of low precipitation and resulting severe droughts in the Yucatan Peninsula, contemporaneous with the Mayan Terminal Classic Collapse. High Ti counts and Ti/Al, although highly variable, during the MCA (CE 900-1350) are interpreted as an unusually warm period characterized by two 100-to-250 years-long intervals of higher precipitation when the number of tropical cyclones peaked. These two intervals of high precipitation during the MCA are separated by a century (CE 1000 -1100) of severe droughts and low tropical storm frequency coinciding with the collapse of Chichen Itza (CE 1040-1100). The Little Ice Age (CE 1350-1850), several centuries during which Ti counts and Ti/Al reach minimum values, is characterized by systematic drier and colder climate conditions with low frequency of tropical cyclones. Two extreme Ti and K count minima might coincide with historical drought times and related Caribbean-wide famines in the year CE 1535 and the last third of the 18th century (CE 1765-1800).

A high-resolution, regional analysis of stormwater runoff for managed aquifer recharge site assessment

NASA Astrophysics Data System (ADS)

Young, K. S.; Fisher, A. T.; Beganskas, S.; Harmon, R. E.; Teo, E. K.; Weir, W. B.; Lozano, S.

2016-12-01

Distributed Stormwater Collection-Managed Aquifer Recharge (DSC-MAR) presents a cost-effective method of aquifer replenishment by collecting runoff and infiltrating it into underlying aquifers, but its successful implementation demands thorough knowledge of the distribution and availability of hillslope runoff. We applied a surface hydrology model to analyze the dynamics of hillslope runoff at high resolution (0.1 to 1.0 km2) across the 350 km2 San Lorenzo River Basin (SLRB) watershed, northern Santa Cruz County, CA. We used a 3 m digital elevation model to create a detailed model grid, which we parameterized with high-resolution geologic, hydrologic, and land use data. To analyze hillslope runoff under a range of precipitation regimes, we developed dry, normal, and wet climate scenarios from historic daily precipitation records (1981-2014). Simulation results show high spatial variability of hillslope runoff generation as a function of differences in precipitation and soil and land use conditions, and reveal a consistent increase in the spatial and temporal variability of runoff under wetter climate scenarios. Our results suggest that there may be opportunities to develop successful DSC-MAR projects that provide benefits during all climate scenarios. In the SLRB, our results indicate that annual hillslope runoff generation achieves a target minimum of 100 acre-ft, per 100 acres of drainage area, in approximately 15% of the region during dry climate scenarios and 60% of the region during wet climate scenarios. The high spatial and temporal resolution of our simulation output enables quantification of hillslope runoff at sub-watershed scales, commensurate with the spacing and operation of DSC-MAR. This study demonstrates a viable tool for screening of potential DSC-MAR project sites and assessing project performance under a range of climate and land use scenarios.

Compound Specific δD Values Across a Tropical Precipitation Gradient: Implications for Low-latitude Paleoclimate Reconstructions

NASA Astrophysics Data System (ADS)

Douglas, P. M.; Pagani, M.; Brenner, M.; Curtis, J. H.; Hodell, D. A.

2009-12-01

Hydrogen isotopes (δD) of terrestrial and aquatic plant lipids have been used to reconstruct past continental hydrological change in low-latitude settings. Generally, lipid δD values correlate strongly with the isotopic composition of precipitation, although evapotranspiration and biosynthetic fractionation are important influences on the δD of leaf waxes. Few studies have focused on constraining the controls on δD values of lipids in the tropics, where high evaporation rates impact both leaf and lake water isotopic composition. We measured δD values in surface waters and lipids extracted from leaves, lake sediments and soils along a latitudinal transect across Mexico, Guatemala and Honduras, a region with distinct dry and wet seasons. The δD values of leaf waxes extracted from lake sediments are positively correlated with surface water δD values (r = 0.73). The apparent fractionation between stream waters (inferred to represent plant source water) and leaf waxes (ɛlw) is negatively correlated with mean annual precipitation (r = -0.89), likely due to greater evapotranspiration and D-enriched leaf water in drier climates. δD values of leaf waxes extracted directly from leaves collected during the rainy season (August 2008) are similarly correlated with surface water δD values (r = 0.85). Leaf ɛlw values, however, are not significantly correlated with mean annual precipitation. It is possible that the correlation between ɛlw and mean annual precipitation in lake sediment leaf waxes is related to seasonal variability in evapotranspiration. Specifically, lake sediment leaf waxes could predominantly represent production during the dry season when evapotranspiration effects are strongest and when many tropical tree species shed their leaves. Possible seasonal variability in fractionation between source water and leaf wax lipids should be taken into account when interpreting leaf wax δD records from tropical locations, both in terms of controlling for long-term variability in seasonality and when comparing records from different sites. Overall, the results of this research indicate that both the isotopic composition of precipitation and the intensity of evapotranspiration control the δD of terrestrial plant leaf waxes in the tropics.

Regional variation in canopy transpiration of Central European beech forests.

PubMed

Schipka, Florian; Heimann, Jutta; Leuschner, Christoph

2005-03-01

Forest hydrologists have hypothesised that canopy transpiration (E(c)) of European temperate forests occurs at rather similar rates in stands with different tree species and hydrologic regimes. We tested this hypothesis by synchronously measuring xylem sap flow in four mature stands of Fagus sylvatica along a precipitation gradient with the aim (1) of exploring the regional variability of annual canopy transpiration (E(c(t))) in this species, and (2) of analysing the relationship between precipitation (P) and E(c(t)). E(c(t)) rates of 216, 225, 272 and 303 mm year(-1) corresponded to precipitation averages of 520, 710, 801 and 1,040 mm year(-1) in the four stands. We explored the regional variability of E(c(t)) in Central European colline to sub-montane beech stands in two meta-analyses based on (1) existing sap flow data on beech (n=5 observations), or (2) all canopy transpiration data on beech obtained by different techniques (sap flow, micrometeorological or soil water budget approaches, n=25). With a coefficient of variation (CV) of 20%, the regional variability of E(c(t)) (213-421 mm year(-1)) was smaller than the variation in corresponding precipitation (550-1,480 mm year(-1)). The mean E(c(t)) for beech was 289 (+/-58) mm year(-1) (n=25). A humped-shaped relationship between E(c(t)) and P, with a broad transpiration maximum in the precipitation range from ca. 700 to 1,000 mm year(-1), was found which may indicate soil moisture limitation of transpiration for P 1,000 mm year(-1). Thus, the precipitation level significantly influences canopy transpiration of humid temperate forests; however, the size of the P influence on E(c(t)) and, in part, the direction of its effect differ from forests in semi-arid or arid climates. European beech has the capacity to maintain high E(c) rates in both humid and partly dry summer climates (P<550 mm year(-1)).

Simulation of daily pesticide concentrations from watershed characteristics and monthly climatic data

USGS Publications Warehouse

Vecchia, Aldo V.; Crawford, Charles G.

2006-01-01

A time-series model was developed to simulate daily pesticide concentrations for streams in the coterminous United States. The model was based on readily available information on pesticide use, climatic variability, and watershed charac-teristics and was used to simulate concentrations for four herbicides [atrazine, ethyldipropylthiocarbamate (EPTC), metolachlor, and trifluralin] and three insecticides (carbofuran, ethoprop, and fonofos) that represent a range of physical and chemical properties, application methods, national application amounts, and areas of use in the United States. The time-series model approximates the probability distributions, seasonal variability, and serial correlation characteristics in daily pesticide concentration data from a national network of monitoring stations. The probability distribution of concentrations for a particular pesticide and station was estimated using the Watershed Regressions for Pesticides (WARP) model. The WARP model, which was developed in previous studies to estimate the probability distribution, was based on selected nationally available watershed-characteristics data, such as pesticide use and soil characteristics. Normality transformations were used to ensure that the annual percentiles for the simulated concentrations agree closely with the percentiles estimated from the WARP model. Seasonal variability in the transformed concentrations was maintained by relating the transformed concentration to precipitation and temperature data from the United States Historical Climatology Network. The monthly precipitation and temperature values were estimated for the centroids of each watershed. Highly significant relations existed between the transformed concentrations, concurrent monthly precipitation, and concurrent and lagged monthly temperature. The relations were consistent among the different pesticides and indicated the transformed concentrations generally increased as precipitation increased but the rate of increase depended on a temperature-dependent growing-season effect. Residual variability of the transformed concentrations, after removal of the effects of precipitation and temperature, was partitioned into a signal (systematic variability that is related from one day to the next) and noise (random variability that is not related from one day to the next). Variograms were used to evaluate measurement error, seasonal variability, and serial correlation of the historical data. The variogram analysis indicated substantial noise resulted, at least in part, from measurement errors (the differences between the actual concen-trations and the laboratory concentrations). The variogram analysis also indicated the presence of a strongly correlated signal, with an exponentially decaying serial correlation function and a correlation time scale (the time required for the correlation to decay to e-1 equals 0.37) that ranged from about 18 to 66 days, depending on the pesticide type. Simulated daily pesticide concentrations from the time-series model indicated the simulated concentrations for the stations located in the northeastern quadrant of the United States where most of the monitoring stations are located generally were in good agreement with the data. The model neither consistently overestimated or underestimated concentrations for streams that are located in this quadrant and the magnitude and timing of high or low concentrations generally coincided reasonably well with the data. However, further data collection and model development may be necessary to determine whether the model should be used for areas for which few historical data are available.