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Articles 1 - 7 of 7

Full-Text Articles in Physical Sciences and Mathematics

Ocean–Atmosphere Interactions Modulate Irrigation’S Climate Impacts, Nir Y. Krakauer, Michael J. Puma, Benjamin I. Cook, Pierre Gentine, Larisa Nazarenko Nov 2016

Ocean–Atmosphere Interactions Modulate Irrigation’S Climate Impacts, Nir Y. Krakauer, Michael J. Puma, Benjamin I. Cook, Pierre Gentine, Larisa Nazarenko

Publications and Research

Numerous studies have focused on the local and regional climate effects of irrigated agriculture and other land cover and land use change (LCLUC) phenomena, but there are few studies on the role of ocean– atmosphere interaction in modulating irrigation climate impacts. Here, we compare simulations with and without interactive sea surface temperatures of the equilibrium effect on climate of contemporary (year 2000) irrigation geographic extent and intensity.We find that ocean–atmosphere interaction does impact the magnitude of globalmean and spatially varying climate impacts, greatly increasing their global reach. Local climate effects in the irrigated regions remain broadly similar, while non-local effects, …


Bathymetric Survey For Lakes Azuei And Enriquillo, Hispaniola, Michael Piasecki, Mahrokh Moknatian, Fred Moshary, Joseph Cleto, Yolanda Leon, Jorge Gonzalez, Daniel Comarazamy Jun 2016

Bathymetric Survey For Lakes Azuei And Enriquillo, Hispaniola, Michael Piasecki, Mahrokh Moknatian, Fred Moshary, Joseph Cleto, Yolanda Leon, Jorge Gonzalez, Daniel Comarazamy

Publications and Research

The two largest lakes on the Caribbean Island of Hispaniola, Lake Azuei in Haiti and Lake Enriquillo in the Dominican Republic, have experienced dramatic growth and surface area expansion over the past few years leading to severe flooding and loss of arable land around the lake perimeters. In order to better understand the reasons for this unprecedented rate of expansion and the resulting consequences a multi-disciplinary team comprised of researchers from Haiti, the DR, and the US have embarked on an extensive data collecting and hydrologic and climatological modeling campaign. While the sensor deployment entails stations that measure climatological data …


Historical Trends In Mean And Extreme Runoff And Streamflow Based On Observations And Climate Models, Behzad Asadieh, Nir Y. Krakauer, Balázs M. Fekete May 2016

Historical Trends In Mean And Extreme Runoff And Streamflow Based On Observations And Climate Models, Behzad Asadieh, Nir Y. Krakauer, Balázs M. Fekete

Publications and Research

To understand changes in global mean and extreme streamflow volumes over recent decades, we statistically analyzed runoff and streamflow simulated by the WBM-plus hydrological model using either observational-based meteorological inputs from WATCH Forcing Data (WFD), or bias-corrected inputs from five global climate models (GCMs) provided by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Results show that the bias-corrected GCM inputs yield very good agreement with the observation-based inputs in average magnitude of runoff and streamflow. On global average, the observation-based simulated mean runoff and streamflow both decreased about 1.3% from 1971 to 2001. However, GCM-based simulations yield increasing trends over …


Estimating The Probability Of Vegetation To Be Groundwater Dependent Based On The Evaluation Of Tree Models, Isabel C. Pérez Hoyos, Nir Y. Krakauer, Reza Khanbilvardi Apr 2016

Estimating The Probability Of Vegetation To Be Groundwater Dependent Based On The Evaluation Of Tree Models, Isabel C. Pérez Hoyos, Nir Y. Krakauer, Reza Khanbilvardi

Publications and Research

Groundwater Dependent Ecosystems (GDEs) are increasingly threatened by humans’ rising demand for water resources. Consequently, it is imperative to identify the location of GDEs to protect them. This paper develops a methodology to identify the probability of an ecosystem to be groundwater dependent. Probabilities are obtained by modeling the relationship between the known locations of GDEs and factors influencing groundwater dependence, namely water table depth and climatic aridity index. Probabilities are derived for the state of Nevada, USA, using modeled water table depth and aridity index values obtained from the Global Aridity database. The model selected results from the performance …


Ensemble Forecasts: Probabilistic Seasonal Forecasts Based On A Model Ensemble, Hannah Aizenman, Michael D. Grossberg, Nir Y. Krakauer, Irina Gladkova Mar 2016

Ensemble Forecasts: Probabilistic Seasonal Forecasts Based On A Model Ensemble, Hannah Aizenman, Michael D. Grossberg, Nir Y. Krakauer, Irina Gladkova

Publications and Research

Ensembles of general circulation model (GCM) integrations yield predictions for meteorological conditions in future months. Such predictions have implicit uncertainty resulting from model structure, parameter uncertainty, and fundamental randomness in the physical system. In this work, we build probabilistic models for long-term forecasts that include the GCM ensemble values as inputs but incorporate statistical correction of GCM biases and different treatments of uncertainty. Specifically, we present, and evaluate against observations, several versions of a probabilistic forecast for gridded air temperature 1 month ahead based on ensemble members of the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 …


A Review Of Advances In The Identification And Characterization Of Groundwater Dependent Ecosystems Using Geospatial Technologies, Isabel C. Pérez Hoyos, Nir Y. Krakauer, Reza Khanbilvardi, Roy A. Armstrong Mar 2016

A Review Of Advances In The Identification And Characterization Of Groundwater Dependent Ecosystems Using Geospatial Technologies, Isabel C. Pérez Hoyos, Nir Y. Krakauer, Reza Khanbilvardi, Roy A. Armstrong

Publications and Research

Groundwater Dependent Ecosystem (GDE) protection is increasingly being recognized as essential for the sustainable management and allocation of water resources. GDE services are crucial for human well-being and for a variety of flora and fauna. However, the conservation of GDEs is only possible if knowledge about their location and extent is available. Several studies have focused on the identification of GDEs at specific locations using ground-based measurements. However, recent progress in remote sensing technologies and their integration with Geographic Information Systems (GIS) has provided alternative ways to map GDEs at a much larger spatial extent. This paper presents a review …


Sefo: A Package For Generating Probabilistic Forecasts From Nmme Predictive Ensembles, Nir Krakauer Mar 2016

Sefo: A Package For Generating Probabilistic Forecasts From Nmme Predictive Ensembles, Nir Krakauer

Publications and Research

Long-range weather forecasts based on output from ensembles of computer simulations are attracting increasing interest. A variety of methods have been proposed to convert the ensemble outputs to calibrated probabilistic forecasts. The package presented here (SeFo, for Seasonal Forecasting) implements a number of methods for producing forecasts of monthly surface air temperature anomalies up to 9 months in advance using output from the North American Multi-Model Ensemble (NMME). The package contains modules for downloading and reading past observations and ensemble output; producing forecast probability distributions; and verifying and calibrating a user-determined subset of methods using arbitrary past periods. By changing …