Soroosh Sorooshian - Profile on Academia.edu (original) (raw)

Papers by Soroosh Sorooshian

Research paper thumbnail of Achieving a Sustainable California Water Future through Innovations in Science and Technology

Cover Image: 12-hr satellite precipitation accumulation estimate (mm) on March 28, 2014 (20:00 UT... more Cover Image: 12-hr satellite precipitation accumulation estimate (mm) on March 28, 2014 (20:00 UTC) over California, produced by the G-WADI PERSIANN-CCS System of the UC Irvine Center for Hydrometeorology and Remote-sensing (CHRS)

Research paper thumbnail of Simulating California reservoir operation using the classification and regression‐tree algorithm combined with a shuffled cross‐validation scheme

Water Resources Research, Mar 1, 2016

Research paper thumbnail of Identification and Application of Physical and Chemical Parameters to Predict Indicator Bacterial Concentration in a Small Californian Creek

Water Environment Research, Jun 1, 2009

This study of Aliso Creek in California aimed to identify physical and chemical parameters that c... more This study of Aliso Creek in California aimed to identify physical and chemical parameters that could be measured instantly to be used in a model to serve as surrogates for indicator bacterial concentrations during dry season flow. In this study, a new data smoothing technique and ranking/categorizing analysis was used to reduce variation to allow better delineation of the relationships between adopted variables and concentrations of indicator bacteria. The ranking/categorizing approach clarified overall trends between physico-chemical data and the indicators and suggested sources of the bacteria. This study also applied a principle component regression model to the data. Although the model was promising for predicting concentrations of total and fecal coliforms, it was somewhat weaker in predicting enteroccocci. Water Environ. Res., 81, 633 (2009).

Research paper thumbnail of NOTES AND CORRESPONDENCE Radar Z-R Relationship for Summer Monsoon Storms in Arizona

Radar-based estimates of rainfall rates and accumulations are one of the principal tools used by ... more Radar-based estimates of rainfall rates and accumulations are one of the principal tools used by the National Weather Service (NWS) to identify areas of extreme precipitation that could lead to flooding. Radar-based rainfall estimates have been compared to gauge observations for 13 convective storm events over a densely instrumented, experimental watershed to derive an accurate reflectivity-rainfall rate (i.e., Z-R) relationship for these events. The resultant Z-R relationship, which is much different than the NWS operational Z-R, has been examined for a separate, independent event that occurred over a different location. For all events studied, the NWS operational Z-R significantly overestimates rainfall compared to gauge measurements. The gauge data from the experimental network, the NWS operational rain estimates, and the improved estimates resulting from this study have been input into a hydrologic model to "predict" watershed runoff for an intense event. Rainfall data from the gauges and from the derived Z-R relation produce predictions in relatively good agreement with observed streamflows. The NWS Z-R estimates lead to predicted peak discharge rates that are more than twice as large as the observed discharges. These results were consistent over a relatively wide range of subwatershed areas (4-148 km 2 ). The experimentally derived Z-R relationship may provide more accurate radar estimates for convective storms over the southwest United States than does the operational convective Z-R used by the NWS. These initial results suggest that the generic NWS Z-R relation, used nationally for convective storms, might be substantially improved for regional application.

Research paper thumbnail of Innovate 2 Innovation - An Assessment of California's Innovation Ecosystem (Phase II) California's Water Future

Research paper thumbnail of Model study of soil-moisture influence on precipitation seesaw in the southern United States

Tellus A, 2004

A coupled atmosphere-land-surface mesoscale model is used to assess the responses of precipitatio... more A coupled atmosphere-land-surface mesoscale model is used to assess the responses of precipitation to soil-moisture anomalies in two regions: (1) the core region of the North American Monsoon (NAM; 105 Results from a series of numerical experiments integrated from July to September 2000 show that precipitation increases in the NAM region in July with a prescribed wet soil-moisture anomaly; meanwhile, precipitation decreases in the CS-US region. In the following months, when the prescribed wet soil-moisture anomaly in the NAM region was removed, the increase in precipitation in the NAM region becomes weaker and shifts eastward to the CS-US region. By September, an inverse precipitation seesaw in these two regions is built up. Except for local evaporation, the transportation of atmospheric moisture affects the interaction between soil moisture and precipitation, especially in the regions and periods without the prescribed soil-moisture anomaly. The soil-moisture anomaly in the NAM region is only partially responsible for the precipitation seesaw in the southern United States.

Research paper thumbnail of A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

Scientific Data, 2019

This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° ... more This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydro...

Research paper thumbnail of Climate forecasts: A new tool for hazard management in the southwestern US

New tools available to resource and flood managers include climate forecasts that predict above o... more New tools available to resource and flood managers include climate forecasts that predict above or below normal precipitation and temperature up to a year in advance. Predictions of the 1997-98 El Niño event and its potentially damaging impacts greatly increased the visibility of these forecasts and have left many wondering how best to take advantage of this new technology. To find out which forecasts agencies access, how they are interpreted, and how they are used, we conducted in-depth interviews with water suppliers, flood control districts, and emergency managers in Arizona. We asked agencies to discuss their experiences with the forecasts, suggest improvements to them, and discuss some of the barriers that prevent agencies from responding to forecasts effectively. The intent of this article is to provide practical advice to emergency managers who are considering incorporating climate forecasts into their operations.

Research paper thumbnail of Identification and Application of Physical and Chemical Parameters to Predict Indicator Bacterial Concentration in a Small Californian Creek

Water Environment Research, 2009

This study of Aliso Creek in California aimed to identify physical and chemical parameters that c... more This study of Aliso Creek in California aimed to identify physical and chemical parameters that could be measured instantly to be used in a model to serve as surrogates for indicator bacterial concentrations during dry season flow. In this study, a new data smoothing technique and ranking/categorizing analysis was used to reduce variation to allow better delineation of the relationships between adopted variables and concentrations of indicator bacteria. The ranking/categorizing approach clarified overall trends between physico-chemical data and the indicators and suggested sources of the bacteria. This study also applied a principle component regression model to the data. Although the model was promising for predicting concentrations of total and fecal coliforms, it was somewhat weaker in predicting enteroccocci. Water Environ. Res., 81, 633 (2009).

Research paper thumbnail of Model study of soil-moisture influence on precipitation seesaw in the southern United States

Tellus A: Dynamic Meteorology and Oceanography, 2004

A coupled atmosphere-land-surface mesoscale model is used to assess the responses of precipitatio... more A coupled atmosphere-land-surface mesoscale model is used to assess the responses of precipitation to soil-moisture anomalies in two regions: (1) the core region of the North American Monsoon (NAM; 105 Results from a series of numerical experiments integrated from July to September 2000 show that precipitation increases in the NAM region in July with a prescribed wet soil-moisture anomaly; meanwhile, precipitation decreases in the CS-US region. In the following months, when the prescribed wet soil-moisture anomaly in the NAM region was removed, the increase in precipitation in the NAM region becomes weaker and shifts eastward to the CS-US region. By September, an inverse precipitation seesaw in these two regions is built up. Except for local evaporation, the transportation of atmospheric moisture affects the interaction between soil moisture and precipitation, especially in the regions and periods without the prescribed soil-moisture anomaly. The soil-moisture anomaly in the NAM region is only partially responsible for the precipitation seesaw in the southern United States.

Research paper thumbnail of Soil moisture–precipitation feedback on the North American monsoon system in the MM5-OSU model

Quarterly Journal of the Royal Meteorological Society, 2004

Model (MM5) linked to the Oregon State University (OSU) land-surface scheme, is used to assess th... more Model (MM5) linked to the Oregon State University (OSU) land-surface scheme, is used to assess the strength of soil moisture-precipitation feedback in the region of influence of the North American monsoon (NAM). Two control simulations are made with external forcing taken from the National Centers for Environmental Prediction re-analysis, and with a nested horizontal resolution of 30 km, for the period 1 June to 30 September in wetter than average (1999) and drier than average (2000) monsoon seasons. These two model runs are then repeated with a prescribed precipitation rate anomaly in July over the entire NAM region, and comparisons made between atmospheric and land-surface states in the two control runs and the two runs with anomalous precipitation. The results show that size and importance of soil moisture-precipitation feedbacks in the NAM region have substantial interannual variability, and that the resulting behaviour has a strong dependency on the intensity of the prescribed precipitation anomaly. It is also shown that a marked precipitation anomaly in the NAM region results in modified soil moisture, rainfall, and surface temperature, which persist for about one month, and that a precipitation anomaly within the NAM region not only has an impact on soil moisture locally, but also causes a remote, downwind soil moisture anomaly one month later. Analysis of the modelled response to the soil moisture anomaly indicates that not only land-atmosphere interactions, but also the large-scale atmospheric circulation act together to determine the modified precipitation and soil moisture fields in the NAM system.

Research paper thumbnail of How significant is the impact of irrigation on the local hydroclimate in California’s Central Valley? Comparison of model results with ground and remote-sensing data

Journal of Geophysical Research, 2011

The effect of irrigation on regional climate has been studied over the years. However, in most st... more The effect of irrigation on regional climate has been studied over the years. However, in most studies, the model was usually set at coarse resolution, and the soil moisture was set to field capacity at each time step. We reinvestigated this issue over the Central Valley of California's agricultural area by: (1) using the regional climate model at different resolutions down to the finest resolution of 4 km for the most inner domain, covering California's Central Valley, the central coast, the Sierra Nevada Mountains, and water; (2) using a more realistic irrigation scheme in the model through the use of different allowable soil water depletion configurations; and (3) evaluating the simulated results against satellite and in situ observations available through the California Irrigation Management Information System (CIMIS). The simulation results with fine model resolution and with the more realistic irrigation scheme indicate that the surface meteorological fields are noticeably improved when compared with observations from the CIMIS network and Moderate Resolution Imaging Spectroradiometer data. Our results also indicate that irrigation has significant impacts on local meteorological fields by decreasing temperature by 3°-7°C and increasing relative humidity by 9-20%, depending on model resolutions and allowable soil water depletion configurations. More significantly, our results using the improved model show that the effects of irrigation on weather and climate do not extend very far into nonirrigated regions.

Research paper thumbnail of Influence of irrigation schemes used in regional climate models on evapotranspiration estimation: Results and comparative studies from California's Central Valley agricultural regions

Journal of Geophysical Research: Atmospheres, 2012

The agricultural sector is the largest consumer of water in California. The impacts of irrigation... more The agricultural sector is the largest consumer of water in California. The impacts of irrigation on local and/or regional weather and climate have been studied and reported in recent literature. However, because of the lack of observations and realistic irrigation schemes employed in the numerical models, most previous studies fall in the category of sensitivity tests, focusing on temperature variations. The results being reported in this paper are obtained by incorporating into the MM5/Noah land surface model an irrigation method practiced in California's farming sector. The proposed irrigation scheme is based on the principle that irrigation occurs when available soil-water content is less than the maximum allowable water depletion (SW m ), which depends on both soil type and crop type. The study's focus was to evaluate the impact of a more realistic irrigation scheme on surface fluxes, especially evapotranspiration (ET). It is demonstrated that more accurate amounts and patterns of ET in the Central Valley are realized, as compared to ET estimates (in terms of amounts and spatial distribution) obtained from remotely sensed observation as well as in situ ground data. It is demonstrated that significant discrepancies of ET estimates between different irrigation schemes used in regional hydroclimate modeling exist, which may result in erroneous conclusions about the impact of irrigation on regional water balance, especially over and near agricultural areas.

Research paper thumbnail of Model Climatology of the North American Monsoon Onset Period during 1980–2001

Journal of Climate, 2004

In this study, the seasonal development of the North American monsoon system (NAMS), as simulated... more In this study, the seasonal development of the North American monsoon system (NAMS), as simulated by a mesoscale model during a 22-yr simulation from 1980 through 2001, is assessed. Comparison between model simulations and observations shows that the model simulation reproduces the precipitation, skin temperature, and wind field patterns in the seasonal development (May-July) of the NAMS reasonably well and that the mesoscale features and spatial heterogeneity of the NAMS are described correctly. The onset of the monsoon in the central and southern Sierra Madre Occidental (SMO) in Mexico occurs on 20 June, about 2 weeks earlier than the onset in Sonora, Mexico (6 July), the Sonoran Desert, and central Arizona and New Mexico (8 July). The temperature in Mexico is highest after the onset of the monsoon and then decreases with the increasing monsoon rainfall. However, the temperature in the Sonoran Desert and central Arizona and New Mexico is highest just prior to the onset of the monsoon, and high temperatures may then persist throughout July. The lower-level (700 hPa) zonal wind field reverses from westerly to easterly over the central and southern SMO just before the onset of rain in these regions; this is associated with the abrupt northward movement of the subtropical high over this region. The progression of the subtropical high into central Arizona and New Mexico results in a local reduction in the westerly flow, and although the southwesterly flow weakens, atmospheric moisture is still mainly from the Gulf of California and the eastern Pacific Ocean.

Research paper thumbnail of Influence of Spatial Resolution on Diurnal Variability during the North American Monsoon

Journal of Climate, 2008

Diurnal variability is an important yet poorly understood aspect of the warm-season precipitation... more Diurnal variability is an important yet poorly understood aspect of the warm-season precipitation regime over southwestern North America. In an effort to improve its understanding, diurnal variability is investigated numerically using the fifth-generation Pennsylvania State University (PSU)–NCAR Mesoscale Model (MM5). The goal herein is to determine the possible influence of spatial resolution on the diurnal cycle. The model is initialized every 48 h using the operational NCEP Eta Model 212 grid (40 km) model analysis. Model simulations are carried out at horizontal resolutions of both 9 and 3 km. Overall, the model reproduces the basic features of the diurnal cycle of rainfall over the core monsoon region of northwestern Mexico and the southwestern United States. In particular, the model captures the diurnal amplitude and phase, with heavier rainfall at high elevations along the Sierra Madre Occidental in the early afternoon that shifts to lower elevations along the west slopes in ...

Research paper thumbnail of One-dimensional snow water and energy balance model for vegetated surfaces

Hydrological Processes, 1999

We developed and evaluated a three-layer snow model for application in general circulation models... more We developed and evaluated a three-layer snow model for application in general circulation models. This onedimensional snow model has many features of the detailed physically based model SNTHERM, yet is computationally much simpler. We have also extended the point model to vegetated areas using the parameterization concepts of the Biosphere-Atmosphere Transfer Scheme (BATS). Results of model applications for two types of vegetated ®elds Ð a short grassland in the French Alps and an old aspen forest in the southern study area of BOREAS Ð were presented. The results, on one hand, indicate the suitability of the model structure and parameter setting; on the other hand, the results explore the limitation of using `point' ®eld observations to evaluate an area model.

Research paper thumbnail of Simulation of snow mass and extent in general circulation models

Hydrological Processes, 1999

An evaluation of the Biosphere±Atmosphere Transfer Scheme (BATS) snow submodel was conducted, bot... more An evaluation of the Biosphere±Atmosphere Transfer Scheme (BATS) snow submodel was conducted, both in a stand-alone mode and within the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). We evaluated, in the stand-alone mode, the performance of BATS parameterizations at local scales using ground-based observations from the former Soviet Union and from Mammoth Mountain, California. The BATS snow scheme reproduces well the seasonal evolution of snow water equivalent in both sites, and the results for the Mammoth Mountain site compare well with those from a more complex, physically based model (SNTHERM). In the coupled mode, we evaluated the modelled snow cover extent, snow mass, precipitation and temperature from BATS as linked to the NCAR CCM3 using available observations. The coupled models capture the broad pattern of seasonal and geographical distribution of snow cover, with better overall performance than the passive microwave snow data derived from the Nimbus-7 Scanning Multi-channel Microwave Radiometer (SMMR) which generally underestimates snow depth. In terms of continents, the snow mass is better simulated during the accumulation period than during the melt period, which is the case for both North America and Eurasia. The simulation of snow mass, precipitation and air temperature for North America is slightly better than that for Eurasia. A rigorous evaluation of snow simulations in coupled land±atmosphere models requires high quality global datasets of snow cover extent, snow depth and snow water equivalent. The available datasets and model outputs are not yet ready to ful®l this objective.

Research paper thumbnail of Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue

Agricultural and Forest Meteorology, 2000

The Semi-Arid Land-Surface-Atmosphere Program ("SALSA") is a multi-agency, multi-national researc... more The Semi-Arid Land-Surface-Atmosphere Program ("SALSA") is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and humaninduced environmental change in semi-arid regions. The ultimate goal of SALSA is to adva nce scientific understanding of the semi-arid portion of the hydrosphere-biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special i ssue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigations during 1997-1999 are then presented. Scientists from about 20 US, 5 European (4 French and 1 Dutch), and 3 Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large-scale interdisciplinary science with relatively limited resources.

Research paper thumbnail of Satellite Rainfall Applications for Surface Hydrology

Background image is a satellite photo of the Ganges River Delta.

Research paper thumbnail of Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops

Journal of Hydrology, Mar 1, 2006

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing... more The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrologic models and in land surface parameterization schemes of atmospheric models. The MOPEX science strategy involves three major steps: data preparation, a priori parameter estimation methodology development, and demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrologic basins in the United States (US) and in other countries. This database is being continuously expanded to include more basins in all parts of the world. A number of international MOPEX workshops have been convened to bring together interested hydrologists and land surface modelers from all over world to exchange knowledge and experience in developing a priori parameter estimation techniques.

Research paper thumbnail of Achieving a Sustainable California Water Future through Innovations in Science and Technology

Cover Image: 12-hr satellite precipitation accumulation estimate (mm) on March 28, 2014 (20:00 UT... more Cover Image: 12-hr satellite precipitation accumulation estimate (mm) on March 28, 2014 (20:00 UTC) over California, produced by the G-WADI PERSIANN-CCS System of the UC Irvine Center for Hydrometeorology and Remote-sensing (CHRS)

Research paper thumbnail of Simulating California reservoir operation using the classification and regression‐tree algorithm combined with a shuffled cross‐validation scheme

Water Resources Research, Mar 1, 2016

Research paper thumbnail of Identification and Application of Physical and Chemical Parameters to Predict Indicator Bacterial Concentration in a Small Californian Creek

Water Environment Research, Jun 1, 2009

This study of Aliso Creek in California aimed to identify physical and chemical parameters that c... more This study of Aliso Creek in California aimed to identify physical and chemical parameters that could be measured instantly to be used in a model to serve as surrogates for indicator bacterial concentrations during dry season flow. In this study, a new data smoothing technique and ranking/categorizing analysis was used to reduce variation to allow better delineation of the relationships between adopted variables and concentrations of indicator bacteria. The ranking/categorizing approach clarified overall trends between physico-chemical data and the indicators and suggested sources of the bacteria. This study also applied a principle component regression model to the data. Although the model was promising for predicting concentrations of total and fecal coliforms, it was somewhat weaker in predicting enteroccocci. Water Environ. Res., 81, 633 (2009).

Research paper thumbnail of NOTES AND CORRESPONDENCE Radar Z-R Relationship for Summer Monsoon Storms in Arizona

Radar-based estimates of rainfall rates and accumulations are one of the principal tools used by ... more Radar-based estimates of rainfall rates and accumulations are one of the principal tools used by the National Weather Service (NWS) to identify areas of extreme precipitation that could lead to flooding. Radar-based rainfall estimates have been compared to gauge observations for 13 convective storm events over a densely instrumented, experimental watershed to derive an accurate reflectivity-rainfall rate (i.e., Z-R) relationship for these events. The resultant Z-R relationship, which is much different than the NWS operational Z-R, has been examined for a separate, independent event that occurred over a different location. For all events studied, the NWS operational Z-R significantly overestimates rainfall compared to gauge measurements. The gauge data from the experimental network, the NWS operational rain estimates, and the improved estimates resulting from this study have been input into a hydrologic model to "predict" watershed runoff for an intense event. Rainfall data from the gauges and from the derived Z-R relation produce predictions in relatively good agreement with observed streamflows. The NWS Z-R estimates lead to predicted peak discharge rates that are more than twice as large as the observed discharges. These results were consistent over a relatively wide range of subwatershed areas (4-148 km 2 ). The experimentally derived Z-R relationship may provide more accurate radar estimates for convective storms over the southwest United States than does the operational convective Z-R used by the NWS. These initial results suggest that the generic NWS Z-R relation, used nationally for convective storms, might be substantially improved for regional application.

Research paper thumbnail of Innovate 2 Innovation - An Assessment of California's Innovation Ecosystem (Phase II) California's Water Future

Research paper thumbnail of Model study of soil-moisture influence on precipitation seesaw in the southern United States

Tellus A, 2004

A coupled atmosphere-land-surface mesoscale model is used to assess the responses of precipitatio... more A coupled atmosphere-land-surface mesoscale model is used to assess the responses of precipitation to soil-moisture anomalies in two regions: (1) the core region of the North American Monsoon (NAM; 105 Results from a series of numerical experiments integrated from July to September 2000 show that precipitation increases in the NAM region in July with a prescribed wet soil-moisture anomaly; meanwhile, precipitation decreases in the CS-US region. In the following months, when the prescribed wet soil-moisture anomaly in the NAM region was removed, the increase in precipitation in the NAM region becomes weaker and shifts eastward to the CS-US region. By September, an inverse precipitation seesaw in these two regions is built up. Except for local evaporation, the transportation of atmospheric moisture affects the interaction between soil moisture and precipitation, especially in the regions and periods without the prescribed soil-moisture anomaly. The soil-moisture anomaly in the NAM region is only partially responsible for the precipitation seesaw in the southern United States.

Research paper thumbnail of A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

Scientific Data, 2019

This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° ... more This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydro...

Research paper thumbnail of Climate forecasts: A new tool for hazard management in the southwestern US

New tools available to resource and flood managers include climate forecasts that predict above o... more New tools available to resource and flood managers include climate forecasts that predict above or below normal precipitation and temperature up to a year in advance. Predictions of the 1997-98 El Niño event and its potentially damaging impacts greatly increased the visibility of these forecasts and have left many wondering how best to take advantage of this new technology. To find out which forecasts agencies access, how they are interpreted, and how they are used, we conducted in-depth interviews with water suppliers, flood control districts, and emergency managers in Arizona. We asked agencies to discuss their experiences with the forecasts, suggest improvements to them, and discuss some of the barriers that prevent agencies from responding to forecasts effectively. The intent of this article is to provide practical advice to emergency managers who are considering incorporating climate forecasts into their operations.

Research paper thumbnail of Identification and Application of Physical and Chemical Parameters to Predict Indicator Bacterial Concentration in a Small Californian Creek

Water Environment Research, 2009

This study of Aliso Creek in California aimed to identify physical and chemical parameters that c... more This study of Aliso Creek in California aimed to identify physical and chemical parameters that could be measured instantly to be used in a model to serve as surrogates for indicator bacterial concentrations during dry season flow. In this study, a new data smoothing technique and ranking/categorizing analysis was used to reduce variation to allow better delineation of the relationships between adopted variables and concentrations of indicator bacteria. The ranking/categorizing approach clarified overall trends between physico-chemical data and the indicators and suggested sources of the bacteria. This study also applied a principle component regression model to the data. Although the model was promising for predicting concentrations of total and fecal coliforms, it was somewhat weaker in predicting enteroccocci. Water Environ. Res., 81, 633 (2009).

Research paper thumbnail of Model study of soil-moisture influence on precipitation seesaw in the southern United States

Tellus A: Dynamic Meteorology and Oceanography, 2004

A coupled atmosphere-land-surface mesoscale model is used to assess the responses of precipitatio... more A coupled atmosphere-land-surface mesoscale model is used to assess the responses of precipitation to soil-moisture anomalies in two regions: (1) the core region of the North American Monsoon (NAM; 105 Results from a series of numerical experiments integrated from July to September 2000 show that precipitation increases in the NAM region in July with a prescribed wet soil-moisture anomaly; meanwhile, precipitation decreases in the CS-US region. In the following months, when the prescribed wet soil-moisture anomaly in the NAM region was removed, the increase in precipitation in the NAM region becomes weaker and shifts eastward to the CS-US region. By September, an inverse precipitation seesaw in these two regions is built up. Except for local evaporation, the transportation of atmospheric moisture affects the interaction between soil moisture and precipitation, especially in the regions and periods without the prescribed soil-moisture anomaly. The soil-moisture anomaly in the NAM region is only partially responsible for the precipitation seesaw in the southern United States.

Research paper thumbnail of Soil moisture–precipitation feedback on the North American monsoon system in the MM5-OSU model

Quarterly Journal of the Royal Meteorological Society, 2004

Model (MM5) linked to the Oregon State University (OSU) land-surface scheme, is used to assess th... more Model (MM5) linked to the Oregon State University (OSU) land-surface scheme, is used to assess the strength of soil moisture-precipitation feedback in the region of influence of the North American monsoon (NAM). Two control simulations are made with external forcing taken from the National Centers for Environmental Prediction re-analysis, and with a nested horizontal resolution of 30 km, for the period 1 June to 30 September in wetter than average (1999) and drier than average (2000) monsoon seasons. These two model runs are then repeated with a prescribed precipitation rate anomaly in July over the entire NAM region, and comparisons made between atmospheric and land-surface states in the two control runs and the two runs with anomalous precipitation. The results show that size and importance of soil moisture-precipitation feedbacks in the NAM region have substantial interannual variability, and that the resulting behaviour has a strong dependency on the intensity of the prescribed precipitation anomaly. It is also shown that a marked precipitation anomaly in the NAM region results in modified soil moisture, rainfall, and surface temperature, which persist for about one month, and that a precipitation anomaly within the NAM region not only has an impact on soil moisture locally, but also causes a remote, downwind soil moisture anomaly one month later. Analysis of the modelled response to the soil moisture anomaly indicates that not only land-atmosphere interactions, but also the large-scale atmospheric circulation act together to determine the modified precipitation and soil moisture fields in the NAM system.

Research paper thumbnail of How significant is the impact of irrigation on the local hydroclimate in California’s Central Valley? Comparison of model results with ground and remote-sensing data

Journal of Geophysical Research, 2011

The effect of irrigation on regional climate has been studied over the years. However, in most st... more The effect of irrigation on regional climate has been studied over the years. However, in most studies, the model was usually set at coarse resolution, and the soil moisture was set to field capacity at each time step. We reinvestigated this issue over the Central Valley of California's agricultural area by: (1) using the regional climate model at different resolutions down to the finest resolution of 4 km for the most inner domain, covering California's Central Valley, the central coast, the Sierra Nevada Mountains, and water; (2) using a more realistic irrigation scheme in the model through the use of different allowable soil water depletion configurations; and (3) evaluating the simulated results against satellite and in situ observations available through the California Irrigation Management Information System (CIMIS). The simulation results with fine model resolution and with the more realistic irrigation scheme indicate that the surface meteorological fields are noticeably improved when compared with observations from the CIMIS network and Moderate Resolution Imaging Spectroradiometer data. Our results also indicate that irrigation has significant impacts on local meteorological fields by decreasing temperature by 3°-7°C and increasing relative humidity by 9-20%, depending on model resolutions and allowable soil water depletion configurations. More significantly, our results using the improved model show that the effects of irrigation on weather and climate do not extend very far into nonirrigated regions.

Research paper thumbnail of Influence of irrigation schemes used in regional climate models on evapotranspiration estimation: Results and comparative studies from California's Central Valley agricultural regions

Journal of Geophysical Research: Atmospheres, 2012

The agricultural sector is the largest consumer of water in California. The impacts of irrigation... more The agricultural sector is the largest consumer of water in California. The impacts of irrigation on local and/or regional weather and climate have been studied and reported in recent literature. However, because of the lack of observations and realistic irrigation schemes employed in the numerical models, most previous studies fall in the category of sensitivity tests, focusing on temperature variations. The results being reported in this paper are obtained by incorporating into the MM5/Noah land surface model an irrigation method practiced in California's farming sector. The proposed irrigation scheme is based on the principle that irrigation occurs when available soil-water content is less than the maximum allowable water depletion (SW m ), which depends on both soil type and crop type. The study's focus was to evaluate the impact of a more realistic irrigation scheme on surface fluxes, especially evapotranspiration (ET). It is demonstrated that more accurate amounts and patterns of ET in the Central Valley are realized, as compared to ET estimates (in terms of amounts and spatial distribution) obtained from remotely sensed observation as well as in situ ground data. It is demonstrated that significant discrepancies of ET estimates between different irrigation schemes used in regional hydroclimate modeling exist, which may result in erroneous conclusions about the impact of irrigation on regional water balance, especially over and near agricultural areas.

Research paper thumbnail of Model Climatology of the North American Monsoon Onset Period during 1980–2001

Journal of Climate, 2004

In this study, the seasonal development of the North American monsoon system (NAMS), as simulated... more In this study, the seasonal development of the North American monsoon system (NAMS), as simulated by a mesoscale model during a 22-yr simulation from 1980 through 2001, is assessed. Comparison between model simulations and observations shows that the model simulation reproduces the precipitation, skin temperature, and wind field patterns in the seasonal development (May-July) of the NAMS reasonably well and that the mesoscale features and spatial heterogeneity of the NAMS are described correctly. The onset of the monsoon in the central and southern Sierra Madre Occidental (SMO) in Mexico occurs on 20 June, about 2 weeks earlier than the onset in Sonora, Mexico (6 July), the Sonoran Desert, and central Arizona and New Mexico (8 July). The temperature in Mexico is highest after the onset of the monsoon and then decreases with the increasing monsoon rainfall. However, the temperature in the Sonoran Desert and central Arizona and New Mexico is highest just prior to the onset of the monsoon, and high temperatures may then persist throughout July. The lower-level (700 hPa) zonal wind field reverses from westerly to easterly over the central and southern SMO just before the onset of rain in these regions; this is associated with the abrupt northward movement of the subtropical high over this region. The progression of the subtropical high into central Arizona and New Mexico results in a local reduction in the westerly flow, and although the southwesterly flow weakens, atmospheric moisture is still mainly from the Gulf of California and the eastern Pacific Ocean.

Research paper thumbnail of Influence of Spatial Resolution on Diurnal Variability during the North American Monsoon

Journal of Climate, 2008

Diurnal variability is an important yet poorly understood aspect of the warm-season precipitation... more Diurnal variability is an important yet poorly understood aspect of the warm-season precipitation regime over southwestern North America. In an effort to improve its understanding, diurnal variability is investigated numerically using the fifth-generation Pennsylvania State University (PSU)–NCAR Mesoscale Model (MM5). The goal herein is to determine the possible influence of spatial resolution on the diurnal cycle. The model is initialized every 48 h using the operational NCEP Eta Model 212 grid (40 km) model analysis. Model simulations are carried out at horizontal resolutions of both 9 and 3 km. Overall, the model reproduces the basic features of the diurnal cycle of rainfall over the core monsoon region of northwestern Mexico and the southwestern United States. In particular, the model captures the diurnal amplitude and phase, with heavier rainfall at high elevations along the Sierra Madre Occidental in the early afternoon that shifts to lower elevations along the west slopes in ...

Research paper thumbnail of One-dimensional snow water and energy balance model for vegetated surfaces

Hydrological Processes, 1999

We developed and evaluated a three-layer snow model for application in general circulation models... more We developed and evaluated a three-layer snow model for application in general circulation models. This onedimensional snow model has many features of the detailed physically based model SNTHERM, yet is computationally much simpler. We have also extended the point model to vegetated areas using the parameterization concepts of the Biosphere-Atmosphere Transfer Scheme (BATS). Results of model applications for two types of vegetated ®elds Ð a short grassland in the French Alps and an old aspen forest in the southern study area of BOREAS Ð were presented. The results, on one hand, indicate the suitability of the model structure and parameter setting; on the other hand, the results explore the limitation of using `point' ®eld observations to evaluate an area model.

Research paper thumbnail of Simulation of snow mass and extent in general circulation models

Hydrological Processes, 1999

An evaluation of the Biosphere±Atmosphere Transfer Scheme (BATS) snow submodel was conducted, bot... more An evaluation of the Biosphere±Atmosphere Transfer Scheme (BATS) snow submodel was conducted, both in a stand-alone mode and within the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). We evaluated, in the stand-alone mode, the performance of BATS parameterizations at local scales using ground-based observations from the former Soviet Union and from Mammoth Mountain, California. The BATS snow scheme reproduces well the seasonal evolution of snow water equivalent in both sites, and the results for the Mammoth Mountain site compare well with those from a more complex, physically based model (SNTHERM). In the coupled mode, we evaluated the modelled snow cover extent, snow mass, precipitation and temperature from BATS as linked to the NCAR CCM3 using available observations. The coupled models capture the broad pattern of seasonal and geographical distribution of snow cover, with better overall performance than the passive microwave snow data derived from the Nimbus-7 Scanning Multi-channel Microwave Radiometer (SMMR) which generally underestimates snow depth. In terms of continents, the snow mass is better simulated during the accumulation period than during the melt period, which is the case for both North America and Eurasia. The simulation of snow mass, precipitation and air temperature for North America is slightly better than that for Eurasia. A rigorous evaluation of snow simulations in coupled land±atmosphere models requires high quality global datasets of snow cover extent, snow depth and snow water equivalent. The available datasets and model outputs are not yet ready to ful®l this objective.

Research paper thumbnail of Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue

Agricultural and Forest Meteorology, 2000

The Semi-Arid Land-Surface-Atmosphere Program ("SALSA") is a multi-agency, multi-national researc... more The Semi-Arid Land-Surface-Atmosphere Program ("SALSA") is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and humaninduced environmental change in semi-arid regions. The ultimate goal of SALSA is to adva nce scientific understanding of the semi-arid portion of the hydrosphere-biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special i ssue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigations during 1997-1999 are then presented. Scientists from about 20 US, 5 European (4 French and 1 Dutch), and 3 Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large-scale interdisciplinary science with relatively limited resources.

Research paper thumbnail of Satellite Rainfall Applications for Surface Hydrology

Background image is a satellite photo of the Ganges River Delta.

Research paper thumbnail of Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops

Journal of Hydrology, Mar 1, 2006

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing... more The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrologic models and in land surface parameterization schemes of atmospheric models. The MOPEX science strategy involves three major steps: data preparation, a priori parameter estimation methodology development, and demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrologic basins in the United States (US) and in other countries. This database is being continuously expanded to include more basins in all parts of the world. A number of international MOPEX workshops have been convened to bring together interested hydrologists and land surface modelers from all over world to exchange knowledge and experience in developing a priori parameter estimation techniques.