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Zhao, Z, Chen SH, Kleeman MJ, Tyree M, Cayan D.  2011.  The impact of climate change on air quality-related meteorological conditions in california. Part I: Present time simulation analysis. Journal of Climate. 24:3344-3361.   10.1175/2011jcli3849.1   AbstractWebsite

This study investigates the impacts of climate change on meteorology and air quality conditions in California by dynamically downscaling Parallel Climate Model (PCM) data to high resolution (4 km) using the Weather Research and Forecast (WRF) model. This paper evaluates the present years' (2000-06) downscaling results driven by either PCM or National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) reanalysis data. The analyses focused on the air quality-related meteorological variables, such as planetary boundary layer height (PBLH), surface temperature, and wind. The differences of the climatology from the two sets of downscaling simulations and the driving global datasets were compared, which illustrated that most of the biases of the downscaling results were inherited from the driving global climate model (GCM). The downscaling process added mesoscale features but also introduced extra biases into the driving global data. The main source of bias in the PCM data is an imprecise prediction of the location and strength of the Pacific subtropical high (PSH). The analysis implied that using simulation results driven by PCM data as the input for air quality models will likely underestimate air pollution problems in California. Regional-averaged statistics of the downscaling results were estimated for two highly polluted areas, the South Coast Air Basin (SoCAB) and the San Joaquin Valley (SJV), by comparing to observations. The simulations driven by GFS data overestimated surface temperature and wind speed for most of the year, indicating that WRF has systematic errors in these two regions. The simulation matched the observations better during summer than winter in terms of bias. WRF has difficulty reproducing weak surface wind, which normally happens during stagnation events in these two regions. The shallow summer PBLH in the Central Valley is caused by the dominance of high pressure systems over the valley and the strong valley wind during summer. The change of meteorology and air quality in California due to climate change will be explored in Part II of this study, which compares the future (2047-53) and present (2000-06) simulation results driven by PCM data and is presented in a separate paper.

Reisen, WK, Cayan D, Tyree M, Barker CA, Eldridge B, Dettinger M.  2008.  Impact of climate variation on mosquito abundance in California. Journal of Vector Ecology. 33:89-98.   10.3376/1081-1710(2008)33[89:iocvom]2.0.co;2   AbstractWebsite

Temporal variation in the abundance of the encephalitis virus vector mosquito, Culex tarsalis Coquillet, was linked significantly with coincident and antecedent measures of regional climate, including temperature, precipitation, snow pack, and the El Nino/Southern Oscillation anomaly. Although variable among traps, historical records that spanned two to five decades revealed climate influences on spring and summer mosquito abundance as early as the previous fall through early summer. Correlations between winter and spring precipitation and snow pack and spring Cx. tarsalis abundance were stronger than correlations with summer abundance. Spring abundance was also correlated positively with winter and spring temperature, whereas summer abundance correlated negatively with spring temperature and not significantly with summer temperature. Correlations with antecedent climate provide the opportunity to forecast vector abundance and therefore encephalitis virus risk, a capability useful in intervention decision support systems at local and state levels.

Yang, Y, Russell LM, Xu L, Lou SJ, Lamjiri MA, Somerville RCJ, Miller AJ, Cayan DR, DeFlorio MJ, Ghan SJ, Liu Y, Singh B, Wang HL, Yoon JH, Rasch PJ.  2016.  Impacts of ENSO events on cloud radiative effects in preindustrial conditions: Changes in cloud fraction and their dependence on interactive aerosol emissions and concentrations. Journal of Geophysical Research-Atmospheres. 121:6321-6335.   10.1002/2015jd024503   AbstractWebsite

We use three 150 year preindustrial simulations of the Community Earth System Model to quantify the impacts of El Nino-Southern Oscillation (ENSO) events on shortwave and longwave cloud radiative effects (CRESW and CRELW). Compared to recent observations from the Clouds and the Earth's Radiant Energy System data set, the model simulation successfully reproduces larger variations of CRESW and CRELW over the tropics. The ENSO cycle is found to dominate interannual variations of cloud radiative effects. Simulated cooling (warming) effects from CRESW (CRELW) are strongest over the tropical western and central Pacific Ocean during warm ENSO events, with the largest difference between 20 and 60 W m(-2), with weaker effects of 10-40 W m(-2) over Indonesian regions and the subtropical Pacific Ocean. Sensitivity tests show that variations of cloud radiative effects are mainly driven by ENSO-related changes in cloud fraction. The variations in midlevel and high cloud fractions each account for approximately 20-50% of the interannual variations of CRESW over the tropics and almost all of the variations of CRELW between 60 degrees S and 60 degrees N. The variation of low cloud fraction contributes to most of the variations of CRESW over the midlatitude oceans. Variations in natural aerosol concentrations explained 10-30% of the variations of both CRESW and CRELW over the tropical Pacific, Indonesian regions, and the tropical Indian Ocean. Changes in natural aerosol emissions and concentrations enhance 3-5% and 1-3% of the variations of cloud radiative effects averaged over the tropics.

Das, T, Pierce DW, Cayan DR, Vano JA, Lettenmaier DP.  2011.  The importance of warm season warming to western US streamflow changes. Geophysical Research Letters. 38   10.1029/2011gl049660   AbstractWebsite

Warm season climate warming will be a key driver of annual streamflow changes in four major river basins of the western U.S., as shown by hydrological model simulations using fixed precipitation and idealized seasonal temperature changes based on climate projections with SRES A2 forcing. Warm season (April-September) warming reduces streamflow throughout the year; streamflow declines both immediately and in the subsequent cool season. Cool season (October-March) warming, by contrast, increases streamflow immediately, partially compensating for streamflow reductions during the subsequent warm season. A uniform warm season warming of 3 C drives a wide range of annual flow declines across the basins: 13.3%, 7.2%, 1.8%, and 3.6% in the Colorado, Columbia, Northern and Southern Sierra basins, respectively. The same warming applied during the cool season gives annual declines of only 3.5%, 1.7%, 2.1%, and 3.1%, respectively. Citation: Das, T., D. W. Pierce, D. R. Cayan, J. A. Vano, and D. P. Lettenmaier (2011), The importance of warm season warming to western U. S. streamflow changes, Geophys. Res. Lett., 38, L23403, doi: 10.1029/2011GL049660.

Pierce, DW, Cayan DR, Maurer EP, Abatzoglou JT, Hegewisch KC.  2015.  Improved bias correction techniques for hydrological simulations of climate change. Journal of Hydrometeorology. 16:2421-2442.   10.1175/jhm-d-14-0236.1   AbstractWebsite

Global climate model (GCM) output typically needs to be bias corrected before it can be used for climate change impact studies. Three existing bias correction methods, and a new one developed here, are applied to daily maximum temperature and precipitation from 21 GCMs to investigate how different methods alter the climate change signal of the GCM. The quantile mapping (QM) and cumulative distribution function transform (CDF-t) bias correction methods can significantly alter the GCM's mean climate change signal, with differences of up to 2 degrees C and 30% points for monthly mean temperature and precipitation, respectively. Equidistant quantile matching (EDCDFm) bias correction preserves GCM changes in mean daily maximum temperature but not precipitation. An extension to EDCDFm termed PresRat is introduced, which generally preserves the GCM changes in mean precipitation. Another problem is that GCMs can have difficulty simulating variance as a function of frequency. To address this, a frequency-dependent bias correction method is introduced that is twice as effective as standard bias correction in reducing errors in the models' simulation of variance as a function of frequency, and it does so without making any locations worse, unlike standard bias correction. Last, a preconditioning technique is introduced that improves the simulation of the annual cycle while still allowing the bias correction to take account of an entire season's values at once.

Das, T, Maurer EP, Pierce DW, Dettinger MD, Cayan DR.  2013.  Increases in flood magnitudes in California under warming climates. Journal of Hydrology. 501:101-110. AbstractWebsite

Downscaled and hydrologically modeled projections from an ensemble of 16 Global Climate Models suggest that flooding may become more intense on the western slopes of the Sierra Nevada mountains, the primary source for California's managed water system. By the end of the 21st century, all 16 climate projections for the high greenhouse-gas emission SRES A2 scenario yield larger floods with return periods ranging 2-50 years for both the Northern Sierra Nevada and Southern Sierra Nevada, regardless of the direction of change in mean precipitation. By end of century, discharges from the Northern Sierra Nevada with 50-year return periods increase by 30-90% depending on climate model, compared to historical values. Corresponding flood flows from the Southern Sierra increase by 50-100%. The increases in simulated 50 year flood flows are larger (at 95% confidence level) than would be expected due to natural variability by as early as 2035 for the SRES A2 scenario. (C) 2013 Elsevier B.V. All rights reserved.

Sumargo, E, Cayan DR.  2018.  The influence of cloudiness on hydrologic fluctuations in the mountains of the western United States. Water Resources Research. 54:8478-8499.   10.1029/2018wr022687   AbstractWebsite

This study investigates snowmelt and streamflow responses to cloudiness variability across the mountainous parts of the western United States. Twenty years (1996-2015) of Geostationary Operational Environmental Satellite-derived cloud cover indices (CC) with 4-km spatial and daily temporal resolutions are used as a proxy for cloudiness. The primary driver of nonseasonal fluctuations in daily mean solar insolation is the fluctuating cloudiness. We find that CC fluctuations are related to snowmelt and snow-fed streamflow fluctuations, to some extent (correlations of <0.5). Multivariate linear regression models of daily snowmelt (MELT) and streamflow (AQ) variations are constructed for each month from February to July, when snowmelt is most active. Predictors include CC from five antecedent days up to the current day. The CC-MELT and CC-AQ associations vary with time and location. The results show the dominance of negative correlations between CC and MELT, exemplifying the cloud-shading (or clear-sky) effect on snowmelt. The magnitude of the CC-MELT association (R-2) amounts to 5-61%, typically peaking in May. These associations fade earlier in summer during dry years than wet years, indicating the differing responses of thicker versus thinner snowpack. The CC-AQ association displays a less consistent pattern, with R-2 amounting to 2-47%. Nevertheless, MELT and AQ fluctuations exhibit spatially extensive patterns of correlations with daily cloudiness anomalies, indicating that the effects of cloudiness often operate over regional spatial scales. Plain Language Summary Much of the water supply in the western United States originates as mountain streams, which derive much of their water from snowmelt. The primary driver of mountain snowmelt is solar energy, and cloud cover regulates how much solar energy can reach the snow surface. Despite this fact, how snowmelt and streamflow respond to cloud cover (or its absence) has not been thoroughly studied. In our study, we describe snowmelt and streamflow responses to cloud cover using satellite images of cloud cover and surface records of snowmelt and streamflow. We find significant snowmelt and daily streamflow rate responses to cloud cover. Importantly, during the peak snowmelt season, snowmelt and streamflow decrease when cloud cover increases, and vice versa, confirming the cloud-shading effect on the snow surface. However, this cause-and-effect process is not so simple. We also find that cloud cover (or its absence) in the previous few days can affect how much snow melts and the streamflow rate is in a day. Snowmelt and streamflow responses to cloud cover are stronger, albeit shorter-lived, in dry years than in wet years, highlighting the relative importance of cloud cover in drier years.

Cayan, DR, Peterson DH.  1989.  The influence of North Pacific atmospheric circulation on streamflow in the West. Aspects of climate variability in the Pacific and the western Americas. ( Peterson DH, Ed.).:375-397., Washington, DC, U.S.A.: American Geophysical Union Abstract
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Cayan, DR, Riddle LG, Aguado E.  1993.  The influence of precipitation and temperature on seasonal streamflow in California. Water Resources Research. 29:1127-1140.   10.1029/92wr02802   AbstractWebsite

We examine the influence of climate parameters on seasonal streamflow in watersheds over a range of elevations in California and Oregon. Effects of precipitation, temperature, and snow water content (SWC) are diagnosed using linear regression models and categoric composites. Most of the models explain over 60-80% of the seasonal streamflow variability. The models and the composites provide insight into the climate influences which drive the individual watersheds. Low (warmer) basins have little snow and little memory of prior seasons' climate variability. High (cooler) basins, with more snow, have longer memories. Precipitation has the greatest influence on streamflow variations in spring. Temperature is important in spring in the mid and high elevations. By late spring, SWC accounts for nearly all of the summer streamflow variation at mid and high elevations, but earlier in the runoff season, precipitation and temperature add variance. The variations in surface climate parameters, including streamflow, are generally controlled by atmospheric circulation anomalies with a spatial scale much larger than those in watersheds. This explains why little skill was lost by broadening the scale of temperature and precipitation predictors to regional climate areas.

Pan, LL, Chen SH, Cayan D, Lin MY, Hart Q, Zhang MH, Liu YB, Wang JZ.  2011.  Influences of climate change on California and Nevada regions revealed by a high-resolution dynamical downscaling study. Climate Dynamics. 37:2005-2020.   10.1007/s00382-010-0961-5   AbstractWebsite

In this study, the influence of climate change to California and Nevada regions was investigated through high-resolution (4-km grid spacing) dynamical downscaling using the WRF (Weather Research & Forecasting) model. The dynamical downscaling was performed to both the GFS (Global forecast model) reanalysis (called GFS-WRF runs) from 2000-2006 and PCM (Parallel Climate Model) simulations (called PCM-WRF runs) from 1997-2006 and 2047-2056. The downscaling results were first validated by comparing current model outputs with the observational analysis PRISM (Parameter-elevation Regressions on Independent Slopes Model) dataset. In general, the dominant features from GFS-WRF runs and PCM-WRF runs were consistent with each other, as well as with PRISM results. The influences of climate change on the California and Nevada regions can be inferred from the model future runs. The averaged temperature showed a positive trend in the future, as in other studies. The temperature increases by around 1-2A degrees C under the assumption of business as usual over 50 years. This leads to an upward shifting of the freezing level (the contour line of 0A degrees C temperature) and more rain instead of snow in winter (December, January, and February). More hot days (> 32.2A degrees C or 90A degrees F) and extreme hot days (> 37.8A degrees C or 100A degrees F) are predicted in the Sacramento Valley and the southern parts of California and Nevada during summer (June, July, and August). More precipitation is predicted in northern California but not in southern California. Rainfall frequency slightly increases in the coast regions, but not in the inland area. No obvious trend of the surface wind was indicated. The probability distribution functions (PDF) of daily temperature, wind and precipitation for California and Nevada showed no significant change in shape in either winter or summer. The spatial distributions of precipitation frequency from GFS-WRF and PCM-WRF were highly correlated (r = 0.83). However, overall positive shifts were seen in the temperature field; increases of 2A degrees C for California and 3A degrees C for Nevada in summer and 2.5A degrees C for California and 1.5A degrees C for Nevada in winter. The PDFs predicted higher precipitation in winter and lower precipitation in the summer for both California and Nevada.

Cayan, DR.  1996.  Interannual climate variability and snowpack in the western United States. Journal of Climate. 9:928-948.   10.1175/1520-0442(1996)009<0928:icvasi>2.0.co;2   AbstractWebsite

An important part of the water supply in the western United States is derived from runoff fed by mountain snowmelt. Snow accumulation responds to both precipitation and temperature variations, and forms an interesting climatic index, since it integrates these influences over the entire late fall-spring period. Here, effects of cool season climate variability upon snow water equivalent (SWE) over the western part of the conterminous United States are examined. The focus is on measurements on/around 1 April, when snow accumulation is typically greatest. The primary data, from a network of mountainous snow courses, provides a good description of interannual fluctuations in snow accumulations, since many snow courses have records of five decades or more. For any given year, the spring SWE anomaly at a particular snow course is likely to be 25%-60% of its long-term average. Five separate regions of anomalous SWE variability are distinguished, using a rotated principal components analysis. Although effects vary with region and with elevation, in general, the anomalous winter precipitation has the strongest influence on spring SWE fluctuations. Anomalous temperature has a weaker effect overall, but it has great influence in lower elevations such as in the coastal Northwest, and during spring in higher elevations. The regional snow anomaly patterns are associated with precipitation and temperature anomalies in winter and early spring. Patterns of the precipitation, temperature, and snow anomalies extend over broad regional areas, much larger than individual watersheds. These surface anomalies are organized by the atmospheric circulation, with primary anomaly centers over the North Pacific Ocean as well as over western North America. For most of the regions, anomalously low SWE is associated with a winter circulation resembling the PNA pattern. With a strong low in the central North Pacific and high pressure over the Pacific Northwest, this pattern diverts North Pacific storms northward, away from the region. Both warm and cool phases of El Nino-Southern Oscillation tend to produce regional pattens with out-of-phase SWE anomalies in the Northwest and the Southwest.

DeFlorio, MJ, Goodwin ID, Cayan DR, Miller AJ, Ghan SJ, Pierce DW, Russell LM, Singh B.  2016.  Interannual modulation of subtropical Atlantic boreal summer dust variability by ENSO. Climate Dynamics. 46:585-599.   10.1007/s00382-015-2600-7   AbstractWebsite

Dust variability in the climate system has been studied for several decades, yet there remains an incomplete understanding of the dynamical mechanisms controlling interannual and decadal variations in dust transport. The sparseness of multi-year observational datasets has limited our understanding of the relationship between climate variations and atmospheric dust. We use available in situ and satellite observations of dust and a century-length fully coupled Community Earth System Model (CESM) simulation to show that the El Nino-Southern Oscillation (ENSO) exerts a control on North African dust transport during boreal summer. In CESM, this relationship is stronger over the dusty tropical North Atlantic than near Barbados, one of the few sites having a multi-decadal observed record. During strong La Nina summers in CESM, a statistically significant increase in lower tropospheric easterly wind is associated with an increase in North African dust transport over the Atlantic. Barbados dust and Pacific SST variability are only weakly correlated in both observations and CESM, suggesting that other processes are controlling the cross-basin variability of dust. We also use our CESM simulation to show that the relationship between downstream North African dust transport and ENSO fluctuates on multidecadal timescales and is associated with a phase shift in the North Atlantic Oscillation. Our findings indicate that existing observations of dust over the tropical North Atlantic are not extensive enough to completely describe the variability of dust and dust transport, and demonstrate the importance of global models to supplement and interpret observational records.

Guirguis, K, Gershunov A, Cayan DR.  2015.  Interannual variability in associations between seasonal climate, weather, and extremes: wintertime temperature over the Southwestern United States. Environmental Research Letters. 10   10.1088/1748-9326/10/12/124023   AbstractWebsite

Temperature variability in the Southwest US is investigated using skew-normal probability distribution functions (SN PDFs) fitted to observed wintertime daily maximum temperature records. These PDFs vary significantly between years, with important geographical differences in the relationship between the central tendency and tails, revealing differing linkages between weather and climate. The warmest and coldest extremes do not necessarily follow the distribution center. In some regions one tail of the distribution shows more variability than does the other. For example, in California the cold tail is more variable while the warm tail remains relatively stable, so warm years are associated with fewer cold extremes but not necessarily more warm extremes. The opposite relationship is seen in the Great Plains. Changes in temperature PDFs are conditioned by different phases of El Nino-La Nina (ENSO) and the Pacific decadal oscillation (PDO). In the Southern Great Plains, La Nina and/or negative PDO are associated with generally warmer conditions. However, in terms of extremes, while the warm tails become thicker and longer, the cool tails are not impacted-extremely warm days become more frequent but extremely cool days are not less frequent. In contrast, in coastal California, La Nina or negative PDO bring generally cooler conditions with more/stronger cold extremes but the warm extreme probability is not significantly affected. These results could have implications for global warming. If a rigid shift of the whole range occurs, then warm years are not necessarily a good analogue for a warmer climate. If global warming instead brings regional changes more aligned with a preferred state of dominant climate variability modes, then we may see asymmetric changes in the tails of local temperature PDFs.

Peterson, DH, Cayan DR, Festa JF.  1986.  Interannual variability in biogeochemistry of partially-mixed estuaries: dissolved silicate cycles in northern San Francisco Bay. Estuarine variability : Proceedings of the Eighth biennial international estuarine research conference, University of New Hampshire, Durham, July 28-August 2, 1985. ( Wolfe DA, Ed.).:123-128., Orlando, Fla.: Academic Press Abstract
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Miller, AJ, Cayan DR, Barnett TP, Graham NE, Oberhuber JM.  1994.  Interdecadal variability of the Pacific Ocean: model response to observed heat flux and wind stress anomalies. Climate Dynamics. 9:287-302.   10.1007/bf00204744   AbstractWebsite

Variability of the Pacific Ocean is examined in numerical simulations with an ocean general circulation model forced by observed anomalies of surface heat flux, wind stress and turbulent kinetic energy (TKE) over the period 1970-88. The model captures the 1976-77 winter time climate shift in sea surface temperature, as well as its monthly, seasonal and longer term variability as evidenced in regional time series and empirical orthogonal function analyses. Examination of the surface mixed-layer heat budget reveals that the 1976-77 shift was caused by a unique concurrance of sustained heat flux input anomalies and very strong horizontal advection anomalies during a multi-month period preceding the shift in both the central Pacific region (where cooling occurred) and the California coastal region (where warming occurred). In the central Pacific, the warm conditions preceding and the cold conditions following the shift tend to be maintained by anomalous vertical mixing due to increases in the atmospheric momentum flux (TKE input) into the mixed layer (which deepens in the model after the shift) from the early 1970s to the late 1970s and 1980s. Since the ocean model does not contain feedback to the atmosphere and it succeeds in capturing the major features of the 1976-77 shift, it appears that the midlatitude part of the shift was driven by the atmosphere, although effects of midlatitude ocean-atmosphere feedback are still possible. The surface mixed-layer heat budget also reveals that, in the central Pacific, the effects of heat flux input and vertical mixing anomalies are comparable in amplitude while horizontal advection anomalies are roughly half that size. In the California coastal region, in contrast, where wind variability is much weaker than in the central Pacific, horizontal advection and vertical mixing effects on the mixed-layer heat budget are only one-quarter the size of typical heat flux input anomalies.

Dettinger, MD, Cayan DR.  2003.  Interseasonal covariability of Sierra Nevada streamflow and San Francisco Bay salinity. Journal of Hydrology. 277:164-181.   10.1016/s0022-1694(03)00078-7   AbstractWebsite

The ecosystems of the San Francisco Bay estuary are influenced by the salinity of its waters, which in turn depends on flushing by freshwater inflows from the western slopes of the Sierra Nevada. Estimates of full-natural flows in eight major rivers that flush the Bay are analyzed here by extended empirical-orthogonal-function analyses to characterize distinct `modes' of seasonal flow and runoff variability. These modes provide a clear identification of the seasons in which the various rivers respond to hydroclimatic forcings and the seasons during which the rivers most strongly affect San Francisco Bay salinities. About 60 percent of the runoff variability is shared by the rivers over the course of a year but season-to-season differences among the rivers are more subtly distributed. Autumn and winter streamflows respond directly to concurrent (autumn and winter) precipitation and temperatures. Autumn and winter salinities are dominated by these flows, which in each season reflect mostly variations in flows from the central Sierra Nevada and the large Sacramento River. In contrast, spring runoff-rate and streamflow modes are functions of precipitation and temperature during the entire wet (winter and spring) season and are dominated by rivers of the central and southern Sierra Nevada. In turn, the critical spring salinities depend most on the streamflow fluctuations in those central and southern rivers. Published by Elsevier Science B.V.