Norman Miller - Profile on Academia.edu (original) (raw)

Papers by Norman Miller

Climate, Extreme Heat and Energy Demand in California

Journal of Applied Meteorology and Climatology, 2008

ABSTRACT Over the twenty-first century, the frequency of extreme-heat events for major cities in ... more ABSTRACT Over the twenty-first century, the frequency of extreme-heat events for major cities in heavily air conditioned California is projected to increase rapidly. Extreme heat is defined here as the temperature threshold for the 90th-percentile excedence probability (T90) of the local warmest summer days under the current climate. Climate projections from three atmosphere-ocean general circulation models, with a range of low to midhigh temperature sensitivity forced by the Special Report on Emission Scenarios higher, middle, and lower emission scenarios, indicate that these increases in temperature extremes and variance are projected to exceed the rate of increase in mean temperature. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-99 tend to be 20%-30% higher than those projected under the lower B1 emission scenario. Increases range from approximately 2 times the present-day number of days for inland California cities (e.g., Sacramento and Fresno), up to 4 times for previously temperate coastal cities (e.g., Los Angeles and San Diego), implying that present-day "heat wave" conditions may dominate summer months--and patterns of electricity demand--in the future. When the projected extreme heat and observed relationships between high temperature and electricity demand for California are mapped onto current availability, maintaining technology and population constant for demand-side calculations, a potential for electricity deficits as high as 17% during T90 peak electricity demand periods is found. Similar increases in extreme-heat days are likely for other southwestern U.S. urban locations, as well as for large cities in developing nations with rapidly increasing electricity demands. In light of the electricity response to recent extreme-heat events, such as the July 2006 heat waves in California, Missouri, and New York, these results suggest that future increases in peak electricity demand will challenge current transmission and supply methods as well as future planned supply capacities when population and income growth are taken into account.

Relationship between atmospheric circulation and snowpack in the western USA

Hydrological Processes, 2006

Snow anomalies in the western USA have a significant impact on water availability, and hence have... more Snow anomalies in the western USA have a significant impact on water availability, and hence have been widely investigated by many researchers. This study focuses on how anomalous atmospheric circulation affects snowpack accumulation in the western USA. Our results indicate that the mid-latitude atmospheric circulation anomalies induced by the El Niño-Southern Oscillation (ENSO) tend to drive winter precipitation shifts, leading

Analysis of the Sensitivity of Sea Surface Temperature Boundary Conditions on Sierra Nevada Snowpack Using the Weather Research and Forecasting Model

AGU Spring Meeting Abstracts, May 1, 2008

Calibration and Validation of WRF 3.0-CLM3.5 in Snowpack Simulations

AGU Fall Meeting Abstracts, Dec 1, 2009

The Community Land Model version 3.5 (CLM3.5) developed by the National Center for Atmospheric Re... more The Community Land Model version 3.5 (CLM3.5) developed by the National Center for Atmospheric Research (NCAR) was coupled into the Weather Research and Forecasting (WRF) Model version 3.0. The performance of WRF3.0-CLM3.5 in simulating snowpack was extensively evaluated with in-situ observations from a mountainous site called Col de Porte, located in northern Alps region of France, and the Columbia River Basin, located in the northwestern United States. CLM3.5 was configured with a five-layer snow scheme, and includes snow compaction and liquid water transfer processes, and a sophisticated snow albedo scheme. WRF3.0-CLM3.5 was forced with the National Center for Atmospheric Research/National Centers for Environmental Prediction Reanalysis data to simulate for the 1988-1989 snow season for the Col de Porte site and the 2001-2002 season for the Columbia River Basin, with 60km-20km two-way nested domains. The initial simulations show that WRF3.0-CLM3.5 significantly improves snow simulations when compared to those produced with the WRF3.0 coupled to the Noah land surface scheme at the both study sites. However, WRF3.0-CLM3.5 still tends to underestimate the observed snowpack. Calibration with the observed data from the Col de Porte site indicates that the snow water content bias mainly results from stronger, high elevation incoming solar radiation. An adjustment for the radiation scheme in WRF3.0 was made to reduce the incoming radiation to better fit with the observations. This adjustment improves snow simulations at both Col de Porte site and the Columbia River Basin. Additional offline snow simulations with CLM3.5 driven with observed forcing data were performed at the Col de Porte site. These offline simulations are compared to the results produced with the coupled WRF3.0-CLM3.5. Through this comparison, snow-atmosphere interactions are quantitatively indentified. The improved snow simulations in WRF3.0-CLM3.5 will benefit regional hydro-climate research and forecasts.

An Analysis of Snow Processes Within a Regional Climate Model

AGUFM, Dec 1, 2003

Journal of Hydrometeorology, Apr 1, 2007

The impacts of snow on daily weather variability, as well as the mechanisms of snowmelt over the ... more The impacts of snow on daily weather variability, as well as the mechanisms of snowmelt over the Sierra Nevada, California-Nevada, mountainous region, were studied using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) forced by 6-h reanalysis data from the National Centers for Environmental Prediction. The analysis of two-way nested 36-12-km MM5 simulations during the 1998 snowmelt season (April-June) shows that the snow water equivalent (SWE) is underestimated when there are conditions with higher temperature and greater precipitation than observations. An observed daily SWE dataset derived from the snow telemetry network was assimilated into the Noah land surface model within MM5. This SWE assimilation reduces the warm bias. The reduction of the warm bias results from suppressed upward sensible heat flux caused by the decreased skin temperature. This skin temperature reduction is the result of the longer assimilated snow duration than in the model run without SWE assimilation. Meanwhile, the cooled surface leads to a more stable atmosphere, resulting in a decrease in the exaggerated precipitation. Additionally, the detailed analysis of the snowmelt indicates that the absence of vegetation fraction in the most sophisticated land surface model (Noah) in the MM5 package results in an overestimation of solar radiation reaching the snow surface, giving rise to heavier snowmelt. An underestimated surface albedo also weakly contributes to the stronger snowmelt. The roles of the vegetation fraction and albedo in snowmelt are further verified by an additional offline simulation from a more realistic land surface model with advanced snow and vegetation schemes forced by the MM5 output. An improvement in SWE description is clearly seen in this offline simulation over the Sierra Nevada region.

Modeling Air–Land–Sea Interactions Using the Integrated Regional Model System in Monterey Bay, California

Monthly Weather Review, Apr 1, 2012

Theoretical and Applied Climatology, Oct 20, 2010

In this study, the influence of land use change and irrigation in the California Central Valley i... more In this study, the influence of land use change and irrigation in the California Central Valley is quantified using the Pennsylvania State University/National Center for Atmospheric Research fifth generation Mesoscale Model (MM5) coupled with the Community Land Model version 3 (CLM3). The simulations were forced with modern-day and presettlement land use types at 30-km spatial resolution for the period 1 October 1995 to 30 September 1996. This study shows that land use change has significantly altered the structure of the planetary boundary layer (PBL) that affects near-surface temperature. In contrast, many land-use change studies indicate that albedo and evapotranspiration variations are the key processes influencing climate at local-to-regional scales. Our modeling results show that modern-day daily maximum near-surface air temperature (Tmax) has decreased due to agricultural expansion since presettlement. This decrease is caused by weaker sensible heat flux resulting from the lower surface roughness lengths associated with modern-day crops. The lower roughness lengths in the Central Valley also result in stronger winds that lead to a higher PBL. The higher PBL produces stronger sensible heat flux, causing nighttime warming. In addition to land use change, cropland irrigation has also affected hydroclimate processes within the California Central Valley. We generated a 10-member MM5-CLM3 ensemble simulation, where each ensemble member was forced by a fixed volumetric soil water content (SWC) between 3% and 30%, at 3% intervals, over the irrigated areas during a spring-summer growing season, 1 March to 31 August 1996. The results show that irrigation lowers the modern-day cropland surface temperature. Daytime cooling is produced by irrigation-related evaporation enhancement. This increased evaporation also dominates the nighttime surface cooling process. Surface cooling and the resulting weaker sensible heat flux further lower the near-surface air temperature. Thus, irrigation strengthens the daytime near-surface air temperature reduction that is caused by land use change, and a similar temperature change is seen for observations over irrigated cropland. Based on our modeling results, the nighttime near-surface warming induced by land use change is alleviated by low-intensity irrigation (17%<SWC<19%), but such warming completely reverses to a cooling effect under high-intensity irrigation (SWC>19%). The land use changes discussed in this study are commonly observed in many regions of the world, and the physical processes identified here can be used to better understand temperature variations over other areas with similar land cover changes.

Global and Planetary Change, Feb 1, 2008

In the western United States, more than 79 000 km 2 has been converted to irrigated agriculture a... more In the western United States, more than 79 000 km 2 has been converted to irrigated agriculture and urban areas. These changes have the potential to alter surface temperature by modifying the energy budget at the land-atmosphere interface. This study reports the seasonally varying temperature responses of four regional climate models (RCMs)-RSM, RegCM3, MM5-CLM3, and DRCMto conversion of potential natural vegetation to modern land-cover and land-use over a 1-year period. Three of the RCMs supplemented soil moisture, producing large decreases in the August mean (−1.4 to − 3.1°C) and maximum (− 2.9 to −6.1°C) 2-m air temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9% to 36% absolute change). Modeled changes in the August minimum 2-m air temperature were not as pronounced or consistent across the models. Converting natural vegetation to urban land-cover produced less pronounced temperature effects in all models, with the magnitude of the effect dependent upon the preexisting vegetation type and urban parameterizations. Overall, the RCM results indicate that the temperature impacts of land-use change are most pronounced during the summer months, when surface heating is strongest and differences in surface soil moisture between irrigated land and natural vegetation are largest.

Hydrological Processes, Jun 2, 2004

Snow anomalies in the western United States (U.S.) have been widely investigated by many research... more Snow anomalies in the western United States (U.S.) have been widely investigated by many researchers due to its impact on water availability. This study focuses on how anomalous atmospheric circulation affects snowpack accumulation in the western U.S. using observations and output from the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). Our results indicate that the mid-latitude atmospheric circulation anomalies induced by the El Nino-Southern Oscillation (ENSO) tend to drive winter precipitation shifts, leading to an anomalous snowpack distribution in the western U.S. The warm phase of ENSO produces increased snowpack in the Southwest, while the cold phase of ENSO generates increased snowpack in the Northwest. Temperature has a secondary impact on the anomalous snowpack distribution during ENSO episodes. Additionally, the non-linear atmospheric dynamics-related Pacific-North American (PNA) pattern is found to strongly affect snow anomalies in the western U.S. independent from ENSO. The positive phase of the PNA pattern produces colder temperature and stronger precipitation due to the lower pressure in the region, leading to an above normal snowpack. Conversely, the negative phase of the PNA pattern generates warmer temperature and weaker precipitation resulting from the higher pressure, producing a below than normal snowpack in the western U.S. In general, the NCAR-CCM3 reproduces the observed processes. However, model biases are identified and reported. The information provided in this study strengthens our understanding of climate and water supply variability in the western U.S.

Hydrological Processes, Feb 1, 2011

To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the... more To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth-generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5-CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5-CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land-surface model. One important cause for the underestimated SWE in Noah is its unrealistic land-surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow-season surface albedo overestimated by MM5-Noah is now more accurately predicted by MM5-CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near-surface cold bias in MM5-Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5-CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5-Noah. In addition, the over-predicted precipitation in the Pacific Northwest as shown in MM5-Noah is significantly decreased in MM5 CLM3 due to the lower evaporation resulting from the longer snow duration.

Runoff Simulation over the Sierra Nevada Region Using a Coupled Regional Climate Model

The land surface scheme (NOAH) in the current version of the Penn State-National Center for Atmos... more The land surface scheme (NOAH) in the current version of the Penn State-National Center for Atmospheric Research (NCAR) fifth generation Mesoscale Model (MM5) insufficiently treats snowmelt runoff over the Sierra Nevada region due to an insufficient treatment of the snow processes. To improve snowmelt runoff simulation, we have coupled the newly released NCAR Community Land Model version 3 (CLM3) to MM5. CLM3 physically describes the mass and heat transfer within the snowpack using 5 snow layers that include liquid water and solid ice. Interactions among the snow, soil, and vegetation are a function of the CLM3 mass and energy equations. Additionally, a river routing scheme has been adopted in CLM3 to better describe the runoff hydrograph. Several observed datasets from different sources were used to evaluate the model output, including snow depth, temperature, and precipitation from the automated Snowpack Telemetry system, snow cover and vegetation indices from the MODIS satellite data, and streamflow data from the U.S. Geological Survey. In this presentation, we describe the results from an MM5-CLM3 integration from April 1 to June 30, 1998 with 60 km and 20 km nested domains. The results indicate that the coupled model significantly improves the simulation of the snow mass, resulting in a better description of the runoff in the Sierra Nevada region. The application of the river routing scheme further improves the runoff hydrograph simulation. Meanwhile, MM5-CLM3 produces better simulations for the surface air temperature and precipitation as it has more realistic descriptions of the surface energy balance and hydrological cycle when compared to the original version of MM5 with the NOAH land surface model. The coupling of the advanced CLM3 with MM5 significantly improves the regional hydroclimate and water resources predictability.

Analysis of the Sensitivity of Sea Surface Temperature Boundary Conditions on Sierra Nevada Snowpack Using the Weather Research and Forecasting Model

Climate Dynamics, 2012

Sixteen global general circulation models were used to develop probabilistic projections of tempe... more Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling. Keywords Climate change Á Regional climate modeling Á Dynamical downscaling Á Statistical downscaling Electronic supplementary material The online version of this article (

Geophysical Research Letters, 2005

Two simulations, control and land use change, were performed for an eight week period (2 April-16... more Two simulations, control and land use change, were performed for an eight week period (2 April-16 May 1990) to determine the net sensitivity of the local climate around the Three Gorges Dam. The analysis indicates that the large reservoir acts as a potential evaporating surface that decreases the surface temperature, cools the lower atmosphere, decreasing upward motion, and increasing sinking air mass. Such sinking results in low level moisture divergence, decreasing cloudiness, and increasing net downward radiation, which increases the surface temperature. However, results indicate that evaporative cooling dominates radiative warming in this initial study. The strong evaporation also supplies moisture to the atmosphere, suggesting an increase in precipitation, but the sinking moist air diverges away from the TGD region with no net change in precipitation. This numerical study represents an initial methodology for quantification of the impact of the Three Gorges Dam on the local climate and a more comprehensive, fine-scale set of multi-season simulations with additional observational data is needed for a more complete analysis.

Geophysical Research Letters, Dec 1, 2004

An Analysis Of Simulated California Climate Using Multiple Dynamical And Statistical techniques

This paper was prepared as the result of work sponsored by the California Energy Commission (Ener... more This paper was prepared as the result of work sponsored by the California Energy Commission (Energy Commission) and the California Environmental Protection Agency (Cal/EPA). It does not necessarily represent the views of the Energy Commission, Cal/EPA, their employees, or the State of California. The Energy Commission, Cal/EPA, the State of California, their employees, contractors, and subcontractors make no warrant, express or implied, and assume no legal liability for the information in this paper; nor does any party represent that the uses of this information will not infringe upon privately owned rights. This paper has not been approved or disapproved by the California Energy Commission or Cal/EPA, nor has the California Energy Commission or Cal/EPA passed upon the accuracy or adequacy of the information in this paper. F IN A L P A P E R

Ecological Modelling, Aug 1, 2010

Extrapolating simulations of bioenergy crop agro-ecosystems beyond data-rich sites requires bioph... more Extrapolating simulations of bioenergy crop agro-ecosystems beyond data-rich sites requires biophysically accurate ecosystem models and careful estimation of model parameters not available in the literature. To increase biophysical accuracy we added C 4 perennial grass functionality and agricultural practices to the Biome-BGC (BioGeochemical Cycles) ecosystem model. This new model, Agro-BGC, includes enzyme-driven C 4 photosynthesis, individual live and dead leaf, stem, and root carbon and nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that simulates nitrogen fertilization, harvest, fire, and incremental irrigation. To obtain spatially generalizable vegetation parameters we used a numerical method to optimize five unavailable parameters for Panicum virgatum (switchgrass) using biomass yield data from three sites: Mead, Nebraska, Rockspring, Pennsylvania, and Mandan, North Dakota. We then verified simulated switchgrass yields at three independent sites in Illinois (IL). Agro-BGC is more accurate than Biome-BGC in representing the physiology and dynamics of C 4 grass and management practices associated with agro-ecosystems. The simulated two-year average mature yields with single-site Rockspring optimization have Root Mean Square Errors (RMSE) of 70, 152, and 162 and biases of 43, −87, 156 g carbon m −2 for Shabbona, Urbana, and Simpson IL, respectively. The simulated annual yields in June, August, October, December, and February have RMSEs of 114, 390, and 185 and biases of −19, −258, and 147 g carbon m −2 for Shabbona, Urbana, and Simpson IL, respectively. These RMSE and bias values are all within the largest 90% confidence interval around respective IL site measurements. Twenty-four of twenty-six simulated annual yields with Rockspring optimization are within 95% confidence intervals of Illinois site measurements during the mature fourth and fifth years of growth. Ten of eleven simulated two-year average mature yields with Rockspring optimization are within 65% confidence intervals of Illinois site measurements and the eleventh is within the 95% confidence interval. Rockspring optimized Agro-BGC achieves accuracies comparable to those of two previously published models: Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) and Integrated Farm System Model (IFSM). Agro-BGC suffers from static vegetation parameters that can change seasonally and as plants age. Using mature plant data for optimization mitigates this deficiency. Our results suggest that a multi-site optimization scheme using mature plant data from more sites would be adequate for generating spatially generalizable vegetation parameters for simulating mature bioenergy crop agro-ecosystems with Agro-BGC.

Energy, Aug 1, 2012

Global climate change is making California's mild Mediterranean climate significantly warmer, and... more Global climate change is making California's mild Mediterranean climate significantly warmer, and a substantial impact on building energy usage is anticipated. Studies on building cooling and energy demand have been inaccurate and insufficient regarding the impacts of climate change on the peak load pattern shifts of different kinds of buildings. This study utilized archived General Circulation Model (GCM) projections and statistically downscaled these data to the site scale for use in building cooling and heating simulations. Building energy usage was projected out to the years of 2040, 2070, and 2100. This study found that under the condition that the cooling technology stays at the same level in the future, electricity use for cooling will increase by 50% over the next 100 years in certain areas of California under the IPCC (Intergovernmental Panel on Climate Change)'s worst-case carbon emission scenario, A1F1. Under the IPCC's most likely carbon emission scenario (A2), cooling electricity usage will increase by about 25%. Certain types of buildings will be more sensitive to climate change than others. The aggregated energy consumption of all buildings including both heating and cooling will only increase slightly.

Climate, Extreme Heat and Energy Demand in California

Journal of Applied Meteorology and Climatology, 2008

ABSTRACT Over the twenty-first century, the frequency of extreme-heat events for major cities in ... more ABSTRACT Over the twenty-first century, the frequency of extreme-heat events for major cities in heavily air conditioned California is projected to increase rapidly. Extreme heat is defined here as the temperature threshold for the 90th-percentile excedence probability (T90) of the local warmest summer days under the current climate. Climate projections from three atmosphere-ocean general circulation models, with a range of low to midhigh temperature sensitivity forced by the Special Report on Emission Scenarios higher, middle, and lower emission scenarios, indicate that these increases in temperature extremes and variance are projected to exceed the rate of increase in mean temperature. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-99 tend to be 20%-30% higher than those projected under the lower B1 emission scenario. Increases range from approximately 2 times the present-day number of days for inland California cities (e.g., Sacramento and Fresno), up to 4 times for previously temperate coastal cities (e.g., Los Angeles and San Diego), implying that present-day &quot;heat wave&quot; conditions may dominate summer months--and patterns of electricity demand--in the future. When the projected extreme heat and observed relationships between high temperature and electricity demand for California are mapped onto current availability, maintaining technology and population constant for demand-side calculations, a potential for electricity deficits as high as 17% during T90 peak electricity demand periods is found. Similar increases in extreme-heat days are likely for other southwestern U.S. urban locations, as well as for large cities in developing nations with rapidly increasing electricity demands. In light of the electricity response to recent extreme-heat events, such as the July 2006 heat waves in California, Missouri, and New York, these results suggest that future increases in peak electricity demand will challenge current transmission and supply methods as well as future planned supply capacities when population and income growth are taken into account.

Relationship between atmospheric circulation and snowpack in the western USA

Hydrological Processes, 2006

Snow anomalies in the western USA have a significant impact on water availability, and hence have... more Snow anomalies in the western USA have a significant impact on water availability, and hence have been widely investigated by many researchers. This study focuses on how anomalous atmospheric circulation affects snowpack accumulation in the western USA. Our results indicate that the mid-latitude atmospheric circulation anomalies induced by the El Niño-Southern Oscillation (ENSO) tend to drive winter precipitation shifts, leading

Analysis of the Sensitivity of Sea Surface Temperature Boundary Conditions on Sierra Nevada Snowpack Using the Weather Research and Forecasting Model

AGU Spring Meeting Abstracts, May 1, 2008

Calibration and Validation of WRF 3.0-CLM3.5 in Snowpack Simulations

AGU Fall Meeting Abstracts, Dec 1, 2009

The Community Land Model version 3.5 (CLM3.5) developed by the National Center for Atmospheric Re... more The Community Land Model version 3.5 (CLM3.5) developed by the National Center for Atmospheric Research (NCAR) was coupled into the Weather Research and Forecasting (WRF) Model version 3.0. The performance of WRF3.0-CLM3.5 in simulating snowpack was extensively evaluated with in-situ observations from a mountainous site called Col de Porte, located in northern Alps region of France, and the Columbia River Basin, located in the northwestern United States. CLM3.5 was configured with a five-layer snow scheme, and includes snow compaction and liquid water transfer processes, and a sophisticated snow albedo scheme. WRF3.0-CLM3.5 was forced with the National Center for Atmospheric Research/National Centers for Environmental Prediction Reanalysis data to simulate for the 1988-1989 snow season for the Col de Porte site and the 2001-2002 season for the Columbia River Basin, with 60km-20km two-way nested domains. The initial simulations show that WRF3.0-CLM3.5 significantly improves snow simulations when compared to those produced with the WRF3.0 coupled to the Noah land surface scheme at the both study sites. However, WRF3.0-CLM3.5 still tends to underestimate the observed snowpack. Calibration with the observed data from the Col de Porte site indicates that the snow water content bias mainly results from stronger, high elevation incoming solar radiation. An adjustment for the radiation scheme in WRF3.0 was made to reduce the incoming radiation to better fit with the observations. This adjustment improves snow simulations at both Col de Porte site and the Columbia River Basin. Additional offline snow simulations with CLM3.5 driven with observed forcing data were performed at the Col de Porte site. These offline simulations are compared to the results produced with the coupled WRF3.0-CLM3.5. Through this comparison, snow-atmosphere interactions are quantitatively indentified. The improved snow simulations in WRF3.0-CLM3.5 will benefit regional hydro-climate research and forecasts.

An Analysis of Snow Processes Within a Regional Climate Model

AGUFM, Dec 1, 2003

Journal of Hydrometeorology, Apr 1, 2007

The impacts of snow on daily weather variability, as well as the mechanisms of snowmelt over the ... more The impacts of snow on daily weather variability, as well as the mechanisms of snowmelt over the Sierra Nevada, California-Nevada, mountainous region, were studied using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5) forced by 6-h reanalysis data from the National Centers for Environmental Prediction. The analysis of two-way nested 36-12-km MM5 simulations during the 1998 snowmelt season (April-June) shows that the snow water equivalent (SWE) is underestimated when there are conditions with higher temperature and greater precipitation than observations. An observed daily SWE dataset derived from the snow telemetry network was assimilated into the Noah land surface model within MM5. This SWE assimilation reduces the warm bias. The reduction of the warm bias results from suppressed upward sensible heat flux caused by the decreased skin temperature. This skin temperature reduction is the result of the longer assimilated snow duration than in the model run without SWE assimilation. Meanwhile, the cooled surface leads to a more stable atmosphere, resulting in a decrease in the exaggerated precipitation. Additionally, the detailed analysis of the snowmelt indicates that the absence of vegetation fraction in the most sophisticated land surface model (Noah) in the MM5 package results in an overestimation of solar radiation reaching the snow surface, giving rise to heavier snowmelt. An underestimated surface albedo also weakly contributes to the stronger snowmelt. The roles of the vegetation fraction and albedo in snowmelt are further verified by an additional offline simulation from a more realistic land surface model with advanced snow and vegetation schemes forced by the MM5 output. An improvement in SWE description is clearly seen in this offline simulation over the Sierra Nevada region.

Modeling Air–Land–Sea Interactions Using the Integrated Regional Model System in Monterey Bay, California

Monthly Weather Review, Apr 1, 2012

Theoretical and Applied Climatology, Oct 20, 2010

In this study, the influence of land use change and irrigation in the California Central Valley i... more In this study, the influence of land use change and irrigation in the California Central Valley is quantified using the Pennsylvania State University/National Center for Atmospheric Research fifth generation Mesoscale Model (MM5) coupled with the Community Land Model version 3 (CLM3). The simulations were forced with modern-day and presettlement land use types at 30-km spatial resolution for the period 1 October 1995 to 30 September 1996. This study shows that land use change has significantly altered the structure of the planetary boundary layer (PBL) that affects near-surface temperature. In contrast, many land-use change studies indicate that albedo and evapotranspiration variations are the key processes influencing climate at local-to-regional scales. Our modeling results show that modern-day daily maximum near-surface air temperature (Tmax) has decreased due to agricultural expansion since presettlement. This decrease is caused by weaker sensible heat flux resulting from the lower surface roughness lengths associated with modern-day crops. The lower roughness lengths in the Central Valley also result in stronger winds that lead to a higher PBL. The higher PBL produces stronger sensible heat flux, causing nighttime warming. In addition to land use change, cropland irrigation has also affected hydroclimate processes within the California Central Valley. We generated a 10-member MM5-CLM3 ensemble simulation, where each ensemble member was forced by a fixed volumetric soil water content (SWC) between 3% and 30%, at 3% intervals, over the irrigated areas during a spring-summer growing season, 1 March to 31 August 1996. The results show that irrigation lowers the modern-day cropland surface temperature. Daytime cooling is produced by irrigation-related evaporation enhancement. This increased evaporation also dominates the nighttime surface cooling process. Surface cooling and the resulting weaker sensible heat flux further lower the near-surface air temperature. Thus, irrigation strengthens the daytime near-surface air temperature reduction that is caused by land use change, and a similar temperature change is seen for observations over irrigated cropland. Based on our modeling results, the nighttime near-surface warming induced by land use change is alleviated by low-intensity irrigation (17%<SWC<19%), but such warming completely reverses to a cooling effect under high-intensity irrigation (SWC>19%). The land use changes discussed in this study are commonly observed in many regions of the world, and the physical processes identified here can be used to better understand temperature variations over other areas with similar land cover changes.

Global and Planetary Change, Feb 1, 2008

In the western United States, more than 79 000 km 2 has been converted to irrigated agriculture a... more In the western United States, more than 79 000 km 2 has been converted to irrigated agriculture and urban areas. These changes have the potential to alter surface temperature by modifying the energy budget at the land-atmosphere interface. This study reports the seasonally varying temperature responses of four regional climate models (RCMs)-RSM, RegCM3, MM5-CLM3, and DRCMto conversion of potential natural vegetation to modern land-cover and land-use over a 1-year period. Three of the RCMs supplemented soil moisture, producing large decreases in the August mean (−1.4 to − 3.1°C) and maximum (− 2.9 to −6.1°C) 2-m air temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9% to 36% absolute change). Modeled changes in the August minimum 2-m air temperature were not as pronounced or consistent across the models. Converting natural vegetation to urban land-cover produced less pronounced temperature effects in all models, with the magnitude of the effect dependent upon the preexisting vegetation type and urban parameterizations. Overall, the RCM results indicate that the temperature impacts of land-use change are most pronounced during the summer months, when surface heating is strongest and differences in surface soil moisture between irrigated land and natural vegetation are largest.

Hydrological Processes, Jun 2, 2004

Snow anomalies in the western United States (U.S.) have been widely investigated by many research... more Snow anomalies in the western United States (U.S.) have been widely investigated by many researchers due to its impact on water availability. This study focuses on how anomalous atmospheric circulation affects snowpack accumulation in the western U.S. using observations and output from the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3). Our results indicate that the mid-latitude atmospheric circulation anomalies induced by the El Nino-Southern Oscillation (ENSO) tend to drive winter precipitation shifts, leading to an anomalous snowpack distribution in the western U.S. The warm phase of ENSO produces increased snowpack in the Southwest, while the cold phase of ENSO generates increased snowpack in the Northwest. Temperature has a secondary impact on the anomalous snowpack distribution during ENSO episodes. Additionally, the non-linear atmospheric dynamics-related Pacific-North American (PNA) pattern is found to strongly affect snow anomalies in the western U.S. independent from ENSO. The positive phase of the PNA pattern produces colder temperature and stronger precipitation due to the lower pressure in the region, leading to an above normal snowpack. Conversely, the negative phase of the PNA pattern generates warmer temperature and weaker precipitation resulting from the higher pressure, producing a below than normal snowpack in the western U.S. In general, the NCAR-CCM3 reproduces the observed processes. However, model biases are identified and reported. The information provided in this study strengthens our understanding of climate and water supply variability in the western U.S.

Hydrological Processes, Feb 1, 2011

To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the... more To improve simulations of regional-scale snow processes and related cold-season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth-generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5-CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5-CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land-surface model. One important cause for the underestimated SWE in Noah is its unrealistic land-surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow-season surface albedo overestimated by MM5-Noah is now more accurately predicted by MM5-CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near-surface cold bias in MM5-Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5-CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5-Noah. In addition, the over-predicted precipitation in the Pacific Northwest as shown in MM5-Noah is significantly decreased in MM5 CLM3 due to the lower evaporation resulting from the longer snow duration.

Runoff Simulation over the Sierra Nevada Region Using a Coupled Regional Climate Model

The land surface scheme (NOAH) in the current version of the Penn State-National Center for Atmos... more The land surface scheme (NOAH) in the current version of the Penn State-National Center for Atmospheric Research (NCAR) fifth generation Mesoscale Model (MM5) insufficiently treats snowmelt runoff over the Sierra Nevada region due to an insufficient treatment of the snow processes. To improve snowmelt runoff simulation, we have coupled the newly released NCAR Community Land Model version 3 (CLM3) to MM5. CLM3 physically describes the mass and heat transfer within the snowpack using 5 snow layers that include liquid water and solid ice. Interactions among the snow, soil, and vegetation are a function of the CLM3 mass and energy equations. Additionally, a river routing scheme has been adopted in CLM3 to better describe the runoff hydrograph. Several observed datasets from different sources were used to evaluate the model output, including snow depth, temperature, and precipitation from the automated Snowpack Telemetry system, snow cover and vegetation indices from the MODIS satellite data, and streamflow data from the U.S. Geological Survey. In this presentation, we describe the results from an MM5-CLM3 integration from April 1 to June 30, 1998 with 60 km and 20 km nested domains. The results indicate that the coupled model significantly improves the simulation of the snow mass, resulting in a better description of the runoff in the Sierra Nevada region. The application of the river routing scheme further improves the runoff hydrograph simulation. Meanwhile, MM5-CLM3 produces better simulations for the surface air temperature and precipitation as it has more realistic descriptions of the surface energy balance and hydrological cycle when compared to the original version of MM5 with the NOAH land surface model. The coupling of the advanced CLM3 with MM5 significantly improves the regional hydroclimate and water resources predictability.

Analysis of the Sensitivity of Sea Surface Temperature Boundary Conditions on Sierra Nevada Snowpack Using the Weather Research and Forecasting Model

Climate Dynamics, 2012

Sixteen global general circulation models were used to develop probabilistic projections of tempe... more Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling. Keywords Climate change Á Regional climate modeling Á Dynamical downscaling Á Statistical downscaling Electronic supplementary material The online version of this article (

Geophysical Research Letters, 2005

Two simulations, control and land use change, were performed for an eight week period (2 April-16... more Two simulations, control and land use change, were performed for an eight week period (2 April-16 May 1990) to determine the net sensitivity of the local climate around the Three Gorges Dam. The analysis indicates that the large reservoir acts as a potential evaporating surface that decreases the surface temperature, cools the lower atmosphere, decreasing upward motion, and increasing sinking air mass. Such sinking results in low level moisture divergence, decreasing cloudiness, and increasing net downward radiation, which increases the surface temperature. However, results indicate that evaporative cooling dominates radiative warming in this initial study. The strong evaporation also supplies moisture to the atmosphere, suggesting an increase in precipitation, but the sinking moist air diverges away from the TGD region with no net change in precipitation. This numerical study represents an initial methodology for quantification of the impact of the Three Gorges Dam on the local climate and a more comprehensive, fine-scale set of multi-season simulations with additional observational data is needed for a more complete analysis.

Geophysical Research Letters, Dec 1, 2004

An Analysis Of Simulated California Climate Using Multiple Dynamical And Statistical techniques

This paper was prepared as the result of work sponsored by the California Energy Commission (Ener... more This paper was prepared as the result of work sponsored by the California Energy Commission (Energy Commission) and the California Environmental Protection Agency (Cal/EPA). It does not necessarily represent the views of the Energy Commission, Cal/EPA, their employees, or the State of California. The Energy Commission, Cal/EPA, the State of California, their employees, contractors, and subcontractors make no warrant, express or implied, and assume no legal liability for the information in this paper; nor does any party represent that the uses of this information will not infringe upon privately owned rights. This paper has not been approved or disapproved by the California Energy Commission or Cal/EPA, nor has the California Energy Commission or Cal/EPA passed upon the accuracy or adequacy of the information in this paper. F IN A L P A P E R

Ecological Modelling, Aug 1, 2010

Extrapolating simulations of bioenergy crop agro-ecosystems beyond data-rich sites requires bioph... more Extrapolating simulations of bioenergy crop agro-ecosystems beyond data-rich sites requires biophysically accurate ecosystem models and careful estimation of model parameters not available in the literature. To increase biophysical accuracy we added C 4 perennial grass functionality and agricultural practices to the Biome-BGC (BioGeochemical Cycles) ecosystem model. This new model, Agro-BGC, includes enzyme-driven C 4 photosynthesis, individual live and dead leaf, stem, and root carbon and nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that simulates nitrogen fertilization, harvest, fire, and incremental irrigation. To obtain spatially generalizable vegetation parameters we used a numerical method to optimize five unavailable parameters for Panicum virgatum (switchgrass) using biomass yield data from three sites: Mead, Nebraska, Rockspring, Pennsylvania, and Mandan, North Dakota. We then verified simulated switchgrass yields at three independent sites in Illinois (IL). Agro-BGC is more accurate than Biome-BGC in representing the physiology and dynamics of C 4 grass and management practices associated with agro-ecosystems. The simulated two-year average mature yields with single-site Rockspring optimization have Root Mean Square Errors (RMSE) of 70, 152, and 162 and biases of 43, −87, 156 g carbon m −2 for Shabbona, Urbana, and Simpson IL, respectively. The simulated annual yields in June, August, October, December, and February have RMSEs of 114, 390, and 185 and biases of −19, −258, and 147 g carbon m −2 for Shabbona, Urbana, and Simpson IL, respectively. These RMSE and bias values are all within the largest 90% confidence interval around respective IL site measurements. Twenty-four of twenty-six simulated annual yields with Rockspring optimization are within 95% confidence intervals of Illinois site measurements during the mature fourth and fifth years of growth. Ten of eleven simulated two-year average mature yields with Rockspring optimization are within 65% confidence intervals of Illinois site measurements and the eleventh is within the 95% confidence interval. Rockspring optimized Agro-BGC achieves accuracies comparable to those of two previously published models: Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) and Integrated Farm System Model (IFSM). Agro-BGC suffers from static vegetation parameters that can change seasonally and as plants age. Using mature plant data for optimization mitigates this deficiency. Our results suggest that a multi-site optimization scheme using mature plant data from more sites would be adequate for generating spatially generalizable vegetation parameters for simulating mature bioenergy crop agro-ecosystems with Agro-BGC.

Energy, Aug 1, 2012

Global climate change is making California's mild Mediterranean climate significantly warmer, and... more Global climate change is making California's mild Mediterranean climate significantly warmer, and a substantial impact on building energy usage is anticipated. Studies on building cooling and energy demand have been inaccurate and insufficient regarding the impacts of climate change on the peak load pattern shifts of different kinds of buildings. This study utilized archived General Circulation Model (GCM) projections and statistically downscaled these data to the site scale for use in building cooling and heating simulations. Building energy usage was projected out to the years of 2040, 2070, and 2100. This study found that under the condition that the cooling technology stays at the same level in the future, electricity use for cooling will increase by 50% over the next 100 years in certain areas of California under the IPCC (Intergovernmental Panel on Climate Change)'s worst-case carbon emission scenario, A1F1. Under the IPCC's most likely carbon emission scenario (A2), cooling electricity usage will increase by about 25%. Certain types of buildings will be more sensitive to climate change than others. The aggregated energy consumption of all buildings including both heating and cooling will only increase slightly.