A53B-0873 1340h
The Warming of Lake Tahoe
We investigated the effects of climate variability on the thermal structure of Lake Tahoe, California-Nevada, 1970-2002, and with principal components analysis and step-wise multiple regression, related the volume-weighted average lake temperature to trends in climate. We then used a 1-dimensional hydrodynamic model to show that the observed trends in the climatic forcing variables can reasonably explain the observed changes in the lake. Trends in the climatic drivers include 1) upward trends in maximum and minimum daily air temperature at Tahoe City; and 2) a slight upward trend in downward long-wave radiation. Changes in the thermal structure of the lake include 1) a long-term warming trend, with the highest rates near the surface and at 400 m, and discernible in the average lake temperature and total heat content of the lake; 2) an increase in the resistance of the lake to mixing and stratification, as measured by the Schmidt Stability and Birge Work; 3) a trend toward decreasing depth of the October thermocline. We found that the upward trend in average lake temperature (0.016 $^{o}$C yr$^{-1}$) is caused by increasing daily air temperature and downward long-wave radiation. At daily to yearly time scales, lake temperature is also correlated with the indices of El Ni\~{n}o-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). The net average heat flux to the lake between 1970 and 2002 was 0.71 W m$^{-2}$, 10.4 times the reported geothermal flux. The long-term changes in the thermal structure of Lake Tahoe may interact with and exacerbate the well-documented trends in the lake's clarity and primary productivity.
A53B-0874 1340h
Bering Sea Observations Indicate Persistent Warming and Species Impacts
Observations over the previous four years show persistent warm and ice-free conditions from late winter through summer, despite large variability in climate indices such as the Arctic Oscillation(AO) and the Pacific Decadal Oscillation(PDO). If such conditions continue, it will have a major effect on the ecosystem, as Arctic species seek colder waters and sub-Arctic species become dominant. Such a change is ecologically and socially important as the Bering Sea provides 47 percent of the U.S. fishery production by weight and is home to major populations of sea birds and marine mammals. On the southeast Bering Sea shelf (57 deg N) the warmest vertically-averaged ocean temperatures of the decade occurred in 2001-2003(6 deg summer mean temperature relative to 4 deg summer mean temperature in 1995-1997), and sea ice is now nearly non-existent. These conditions follow a major transformation, or regime shift, of the Bering Sea around 1976/77, which changed from a predominantly cold Arctic climate to a warmer subarctic maritime climate as part of the PDO, accompanied by a major reorganization of the marine ecosystem. Over the last decade annual fisheries surveys indicate a continued decline in the addition of young fish and shellfish to cold water stocks, such as Greenland turbot and snow crab. However, Walleye Pollock, which prefers warmer waters, is characterized by a large, rather stable, population. Pacific Walrus is another species showing northward movement due to lack of sea ice and warmer temperatures. Weather data beginning in the 1910s and proxy data(e.g. tree rings) back to 1800 suggest that, except for a period in the 1930s, the Bering Sea was generally cool before 1977, with sufficient time for slow growing, long-lived, cold-adapted species to adjust. Thus the last decades, and particularly the previous few years, are a transition period for the Bering Sea ecosystem to warmer conditions. We hypothesize that the overall climate change occurring in the Arctic is making the Bering Sea less sensitive to the intrinsic climate variability of the North Pacific. Bering Sea indicators, such as sea ice cover and change in the types of fish, should be watched closely for the next five years to confirm or reject the hypothesis of the northward movement of a cold water curtain, replacing Arctic with sub-Arctic species.
A53B-0875 1340h
Summer High Temperature Trend in Taiwan
Taiwan was experiencing a rapid warming over the 20$^{th}$ century. In the last century climate record from the Central Weather Bureau, the averaged annual air temperatures have increased about 1.03$^{o}$C~ 1.45$^{o}$C, which is greater than twice of the global increase of 0.6$^{o}$C per century. In this study, the trend of the occurring frequency of summer daily-maximum temperature larger than 35$^{o}$C is analyzed for three different periods: 1900 \sim 1945, 1946\sim 1975 and 1976 \sim 2003. During the first forty\-six years, only six monitoring stations were set up. The highest occurring frequency of 10 days/summer was at Taipei, a basin in northern Taiwan, and the lowest of 0.1 days/summer was at Hengchun, the southern tip of Taiwan. During the second thirty years, a period of global cooling, twenty\-one observations sites were available. Among them, six are mountain stations with rare occurrence of temperature higher than 35$^{o}$C. Taipei had an averaged 16.7 days/summer frequency, which is apparently higher than that in the previous period, while Hengchun was with an averaged 0.2 days/summer. During the latest twenty\-eight years, the period of most significant global warming, the averaged occurring frequency at Taipei has increased to 23.7 days/summer, while Hengchun with 0.4 days/summer. In all, a spatial distribution pattern of high frequency over northern Taiwan then decreasing along western and eastern coasts toward southern region remains the same during all three periods. Since Taipei being the most urbanized and populated city in Taiwan, urbanization is intuitively blamed for resulting a local warming trend higher than the global one. However, through a regression analysis, we note that there exists a decreasing trend over the southwestern corner of Taiwan. For instance, at Kaohsiung, the second largest city with the highest industrial pollution emission, a trend of -1.5 days/decade can be identified during the latest twenty-eight years period, while Taipei with 5.4 days/decade increasing trend. Possibilities of regional cooling caused by aerosol loading and enhanced ventilation caused by summer monsoon are not to be neglected. Furthermore, based on the GCM projected trend provided by IPCC web site, we have estimated that an enlarged increasing trend of the occurring frequency of temperature larger than 35oC in Taiwan. Though uncertainties exist, the results have a significant policy implication.
A53B-0876 1340h
Synoptic Analysis of 2001-2004 "Long Rains" on Mt. Kilimanjaro, Tanzania
Recently, ice cores covering the last 10,000 years have been recovered from Mt. Kilimanjaro. Studies have suggested that East African precipitation is primarily driven by local-scale processes rather than large-scale atmospheric circulation. Interestingly, the changes seen in the Kilimanjaro ice cores closely resemble other climatic records from a large area in Africa as well as the Indian monsoon areas. So far, studies are further complicated by the lack of in situ data. To advance understanding of modern East African climate, this study focused on station data directly from Mt. Kilimanjaro's summit. First, these local measurements were compared to NCEP/NCAR reanalysis data to validate the global reanalysis in this particular region. Overall, the correspondence was reasonably good, opening the possibility for future studies, expanding the time frame over the past 50 years. Second, the use of both data sets allowed for an examination of commonalities of precipitation events during the "long rains" season (February - May) in 2001-2004 on Mt. Kilimanjaro and identified the key precipitation-causing processes. Results suggest that Kilimanjaro precipitation is related to strong convective activity over the Indian Ocean near Madagascar accompanied with anomalous airflow towards the continent where strong rising motion is responsible for the precipitation. In addition, the Indian Ocean appears to be the dominant source of moisture for Mt. Kilimanjaro snowfall. These findings provide a preliminary interpretation of the governing processes that control precipitation on Mt. Kilimanjaro, which contributes to a better understanding of current regional climate and aids in an improved interpretation of paleoclimatic records.
A53B-0877 1340h
Greenhouse Forcing Outweighs Decreasing Solar Radiation in Europe - Driving Rapid Temperature Rise Over Land
Since 1988, surface temperature over land in Europe increased three times faster than the northern hemisphere average. Here we contrast surface climatic and radiative parameters measured in central Europe over different time periods, including the extreme summer 2003, to pinpoint the role of individual radiative forcings in temperature increases. Interestingly, surface solar radiation rather decreases since 1981. Also, no net radiative cooling or warming is observed under changing cloud amounts. However, high correlation (r$_{T}$ = 0.86) to increasing temperature is found with total heating radiation at the surface, and very high correlation (r$_{T}$ = 0.98) with cloud-free longwave downward radiation. Preponderance of longwave downward radiative forcing suggests rapidly increasing greenhouse warming, which outweighs the decreasing solar radiation measured at the surface and drives rapid temperature increases over land.
A53B-0878 1340h
Regional Climate Response to Three Different Representations of Preindustrial Land Cover in the Western United States
The impacts on climate from anthropogenic changes in land use and, therefore, land cover characteristics have not been examined to the same level as the impacts of increasing atmospheric greenhouse gases. Global-scale climate studies indicate that changes in land surface character have had relatively large impacts on climate, with the most substantial responses occurring at the regional scale. It is important to understand the role of land cover in regional models, as anthropogenic land cover change continues to influence regional climates. In this study, we tested the sensitivity of a regional climate model, RegCM2.5, to three representations of potential preindustrial vegetation in the Western United States. We used the global National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) to drive the regional model. We performed one 17-year RegCM integration over the Western United States with each of the three land cover datasets. Each integration used the same driving conditions with 280 ppmv atmospheric CO$_{2}$. We used (1) the potential natural land cover dataset of BIOME4, which is an equilibrium vegetation model (Kaplan, 2001); (2) the satellite-based preindustrial dataset developed by Ramankutty and Foley (1999), and; (3) as a control, the RegCM2.5 default vegetation dataset. Results from the three runs were compared to reveal any statistically significant differences in values for climate characteristics such as surface temperature, evapotranspiration, and precipitation. The results allow us to examine the sensitivity of regional climate to specified land cover.
A53B-0879 1340h
Regional Climate and Hydrological Responses to El Nino in an Increased CO$_2$ Climate
Much of California typically experiences above-average precipitation amounts during El Nino (warm-phase ENSO) events. We would like to know if similar precipitation anomalies will occur in an increased greenhouse gas climate, and what corresponding river flow rates will be given that a smaller proportion of precipitation will be snow in the future than at present. The effects of increased atmospheric CO$_2$ on the frequency and amplitude of the ENSO phenomenon-as measured by anomalies in sea surface temperatures (SSTs)-are not known. However, we can use models to assess precipitation and other hydrological responses to ENSO under the assumption that the amplitude of ENSO will be unaffected by increased greenhouse gases. We performed an ensemble of simulations of global climate with a high-resolution model of the atmosphere forced with prescribed monthly-mean SSTs representing El Nino conditions in an increased CO$_2$ climate. These SSTs consist of observed climatological SSTs + a simulated SST response to doubled atmospheric CO$_2$ + observed SST anomalies for the winter 1997-1998 (the most recent strong El Nino). A 10-year control simulation of the present climate (forced by climatological observed SSTs) was also performed. After bias correction and statistical downscaling, results from the atmospheric model were used to drive a spatially resolved surface hydrology model configured for major watersheds in California. We assess precipitation rates and river flow rates in increased CO$_2$ El Nino conditions, and compare them to those in present-climate El Nino and increased CO$_2$ normal-year conditions.
A53B-0880 1340h
Stochastic modeling of daily summertime rainfall over the southwestern US and its relation to interannual variability
A large fraction of annual precipitation over the Southwestern US is concentrated in the summer season and attributable to the North American Monsoon System (NAMS). In addition, previous studies suggest strong relationships between the NAMS precipitation and rainfall over other regions, such as the Great Plains and the East Coast, suggesting regional rainfall over the southwest is also related to the larger-scale hydrologic cycle over North American continent. As such, the NAMS precipitation pattern has tremendous impact on the local hydrologic and ecological system in this region and may provide potential predictability for interannual variations in the seasonal rainfall during the summer. Here, the interannual variance in this summertime seasonal precipitation over 78 southwestern US stations is studied using Markov Chain models and empirical intensity distributions. Modeling results suggest that a 2-order Markov Chain can optimally portray the temporal structure of the summer daily precipitation process over the southwestern US. The 2-order Markov Chain model with stationary event frequency and intensity characteristics, in turn, can explain approximately 75 % of the interannual variance in the seasonal number of wet days and 85 % of the interannual variance in the total seasonal precipitation. In addition, only a small fraction of anomalous years at any given station (generally smaller than 20 %) show significant changes in either of these characteristics. However, relatively higher fractions of the anomalous years are observed in regions north of 37 N suggesting possible spatial heterogeneity in the frequency of non-stationary behavior of rainfall over the domain. In general, at a given station the anomalous years are related to both anomalous numbers of seasonal total wet days and anomalous light/heavy rain intensity distributions. Studies investigating variance explained by non-stationary variations in the occurrence and intensity characteristics indicate they display similar significance in capturing the remaining 15 % of interannual variance of seasonal total precipitation. However, numerical tests suggest that these two low frequency variations are not independent variables for the NAMS precipitation over the southwestern US. Complex covariance that cannot be described with stochastic statistical models may exist between those two variations. Further study with dynamic models and cluster analyses is needed to examine the low frequency variation processes and their influence on potentially predictable precipitation in this region.
A53B-0881 1340h
Large Shift in Endemic Oak Ranges due to Projected, Future Regional Climate Change in California
Native oaks are a prominent feature of California's landscape. For more than a century they have been under direct pressure from human land use including grazing, vineyard and orchard development, and urban expansion. In the coming century they face the additional threat of regional climate change. We used maps of potential and realized blue and valley oak ({\it Quercus douglasii} and {\it Q. lobata}) ranges with data on historical climate (1970-2000) and soil properties to build statistical models of potential habitat for these California endemic oaks. We then estimated the change in regional climate over the next 100 years due to increases of 1 % per year in global greenhouse gas concentrations, using output from the regional climate model RegCM2.5. The climate simulations lead to decreased precipitation and warmer summer temperatures throughout the current geographic range of these two oaks, resulting in the loss of most of their current habitat. Areas with potentially suitable climates are more restricted after climate change, occurring in the northern one-third of the state, a region currently occupied by conifer forest. Previous studies of acorn production, seedling establishment, and growth rates reinforce these findings, and support our conclusion that protected areas currently containing these oak species may be insufficient to preserve future populations.
http://www.es.ucsc.edu/~kueppers/home
A53B-0882 1340h
Regional Reconstruction of the Palmer Drought Series Indices and Precipitation in the North Aegean and Northwestern Turkey From an Oak Tree-Ring Chronology, AD 1169-1985
In the Mediterranean region of northeastern Greece and northwestern Turkey, securely-dated oak tree-ring chronologies of historic buildings extend modern oak forest chronologies back into the 11th century AD. The secure cross-dating of the building and forest chronologies indicates the presence of a common signal. The climate parameters of that signal are the precipitation of April-May-June from the year-of-growth and the previous year, and the Palmer Drought Series Indices (PDSI), a meteorological drought index, of the growing months in that region. The North Atlantic Oscillation (NAO) index of April also correlates significantly with the tree-ring chronology and with the April-May-June PDSI in this region. Using Principal Component Analysis, the precipitation and PDSI parameters are here reconstructed from AD 1169 to 1985, with comparisons to other precipitation reconstructions of tree-ring sequences from this region. The regional reconstruction indicates a drier period to the end of the Medieval Warm Period ca.AD 1350, and a fluctuating pattern during the Little Ice Age, ca.1350-1900. The early 20th century reconstruction shows a slightly drier period, then the tree-ring patterns of the last 40 years indicate a possible discontinuity of the normal precipitation-cambial growth relationship possibly due to the effect of the current global warming trend on tree-ring growth in this region.
A53B-0883 1340h
Future Changes in Extreme Events in the Western United States
Extreme temperatures and rainfall can have severe impacts on agriculture, human health and water availability. Projections of future extreme events are generally based on past climate records or modeling studies that are either too coarse or too short to be effective. Unfortunately temperature records indicate rapid changes in climate over the period for which global records have been kept. Furthermore precipitation is highly variable and difficult to predict and to model. Therefore projections based on these methods are less than ideal. Here we present results of long regional model simulations (50 years) to address potential future changes in extreme climate events. The advantage of this approach is that the events are explicitly modeled at high resolution allowing for significance testing of the results.
A53B-0884 1340h
Could Atmospheric Storage Play a Significant Role in Regional Precipitation Recycling?
Over the past decade, there has been a growing interest in the hydrologic community on the influence of land surface processes on regional precipitation patterns. Numerous studies have focused their attention on the contribution of local evapotranspiration to local precipitation, or precipitation recycling. The atmospheric moisture budget is generally expressed as the equation of continuity of water mass integrated over an atmospheric column of unit area. The general form of the equation is: $ \frac{\partial \cdot \{\overline{q}\}}{\partial t} + \nabla\cdot \{{\overline {q\textbf{v}}\}} + \nabla\cdot \{{\overline {q'\textbf{v}'}\}}= \overline{E}-\overline{P}$ where $\{{\cdot}\}$ indicates vertical integration with respect to pressure, q is the specific humidity, \textbf{v} is the horizontal wind vector, E is evapotranspiration rate, P is precipitation rate and the overbars indicate temporal averaging while the primes denote deviation from the temporal average. Existing theoretical models of precipitation recycling are based on the above equation of conservation of water vapor mass. However, in these models, the change in storage of atmospheric water vapor is usually neglected, on the assumption that the term is insignificant at monthly or longer timescales. But is this simplification really valid? In order to answer this question we need to quantify the relative magnitude of the neglected term. In this study we use six-hourly Reanalysis II data (from 1979-2003) over North America ($-170^\circ $ to $ -50^\circ$ lon and $20^\circ $ to $ 80^\circ$ lat) to numerically evaluate the relative magnitude of the terms in the moisture budget equation. When analyzing the ratio of the moisture tendency term ($ \frac{\partial \cdot \{\overline{q}\}}{\partial t}$) over the average horizontal transport term ($\frac{\partial \cdot \{\overline{qu}\}}{\partial x}$ , $\frac{\partial \cdot \{\overline{qv}\}}{\partial y}$), we have found that the average ratio over North America is around 0.03 at a seasonal scale, 0.07 at a monthly scale and 1.2 at a daily time scale. During some years, these ratios can be as large as 0.12, 0.5 and 60 for seasonal, monthly and daily timescales respectively. As expected, the term increases in importance at smaller time scales. The relative importance of the storage term is also dependent on the geographical location. Eastern Canada, northeastern US and the drier regions of southwestern US and western Mexico have important contributions of the storage term. In these regions the ratio is on average around 0.1 to 0.2 at a monthly time scale. Based on this simple scale analysis we can see that although the tendency term is smaller than the average transport term, a 10 to 20% contribution is non-negligible. The implication of including the storage term in moisture recycling effects will be explored.
A53B-0885 1340h
Regional Atmospheric Moisture Cycling over the Southwestern US
In this talk we use a suite of regional model simulations and surface and upper-air based observations to examine the summertime hydrologic cycle over the southwestern United States. At the climatological scale, it is found that seasonal precipitation is balanced predominantly by evaporation; in addition, this evaporation also supports a net vertically integrated moisture flux divergence from the region of the same magnitude as the precipitation itself. This vertically-integrated large-scale moisture flux divergence is the result of an offsetting balance between convergence of low-level moisture and divergence of moisture aloft (above 800mb). Based upon the balances found in this region, we develop a new "recycling" metric for precipitation (which is defined as the ratio of locally-derived precipitation to total precipitation) to better quantify the contributions of these various budget terms to the climatological rainfall as seen in both model simulations and observations. While traditional methods for estimating the recycling rate give a ratio of about 0.25, the new metric suggests a recycling rate of 0.80. This indicates that about 75-85 percent of the area-averaged precipitation is the result of evaporative processes, indicating a much greater importance of locally-derived rainfall in generating climatological precipitation than previously thought. As part of this talk we will discuss how the newly-developed regional moisture-cycling metric differs from traditional metrics and how estimates derived from both models and observations may provide greater insight into the regional feedback mechanisms that affect the response of seasonal rainfall variability to local and external forcing factors.
A53B-0886 1340h
Orographic and Large-scale Influence on Southern California Precipitation Patterns
Using the PSU/NCAR MM5 model initialized with ETA-model reanalysis data, the climate of Southern California was simulated from May 1995 to present at a 6-km grid space resolution. Because of the regions' intricate coastline and various mountain ranges, Southern California's climate patterns tend to be complex with numerous small-scale variations. We focus on how topography interacts with large-scale forcings to shape the climatological precipitation patterns in Southern California. Scatterplots of monthly-mean precipitation vs. elevation show that high altitudes generally receive more precipitation than low altitudes. This effect is especially pronounced on the coastal side of the major mountain ranges in Southern California, prompting us to divide our domain into a coastal zone and an inland zone. For an equal increase in elevation, the coastal zone experiences a precipitation enhancement that is one-third larger than that received at inland locations. In both zones, this orographic enhancement is only evident during the wet season (October through May), but is most significant in February. The coastal zone experiences enhanced precipitation during the wet season at all elevations, including the low-elevation coastline locations. Because orographic enhancement is minimal at the coastline, the presence of a wet season at such locales indicates that some portion of the coastal zone precipitation is produced by large-scale forcing. In contrast, a wet season only becomes apparent with increasing elevation at inland locations, as low-elevation locations receive little or no precipitation throughout the year. This finding suggests that inland precipitation is produced almost exclusively through orographic forcing; however, the extent to which this forcing occurs is still governed by synoptic-scale activity.
A53B-0887 1340h
The Origins of Southern California's Climate Diversity
The Penn State NCAR mesoscale model MM5, forced by the NCEP Eta model, was run at 6-kilometer resolution for nine years in the Southern California region. The simulation exhibits significant spatial structure in both forced and unforced surface air temperature (SAT) variability, and the goal of this study is to understand the reasons for this. The SAT seasonal cycle amplitude is primarily determined by distance from the coast, and exhibits no elevation dependence. In contrast, the diurnal cycle is strongly affected by elevation, with the highest elevations having a diurnal amplitude up to three times smaller than low-lying areas. This effect occurs year round, but the magnitude is largest during summer months, when the stability in this region is at its peak. The magnitude of unforced day-to-day variability is similarly structured, with reduced variability at high elevations in the summer months. The winter day-to-day variability exhibits no such dependence. We also discuss the physical mechanisms behind these spatial structures.
A53B-0888 1340h
Downscaling Spatial and Temporal Variation in Precipitation For Western North America under Forecast Climate Change
Potential changes in monthly precipitation for 372 climate stations in Western North America were derived using synoptic downscaling from the Canadian Centre for Climate Modelling and Analysis second generation coupled global circulation model (CGCM2). Daily 500 mb geopotential heights from the CGCM2 were used to represent future (2020-2050) synoptics while daily historical (1960-1990) 500 mb geopotential heights were obtained from the National Centers for Environmental Prediction / National Centre for Atmospheric Research (NCEP/NCAR) reanalysis project. Historical and future synoptic conditions were classified according to Changnon et al. (1993. Monthly Weather Review 121: 633-647). The historical pattern frequencies were linked to historical precipitation for selected weather stations across western North America to determine the relationship between synoptic patterns and spatial precipitation. Future synoptic patterns were used to forecast future precipitation; and GIS tools were applied to develop and display regional variations in future precipitation patterns for western North America.
A53B-0889 1340h
Wind Regimes in Southern California Winter
Two different and complementary classication methods are applied to the daily mean 10m wind simulated by MM5 in Southern California during the winter 1995-2003. The MM5 model is implemented on a triply nested grid of resolutions 54/18/6km covering the western U.S. with great details over the Southern California region. The wind variability during winter is dominated by three robust wind regimes. The first wind regime describes a strong north-easterly flow over the LA basin. This regime is commonly designated as "Santa Ana" conditions in Southern California. The second regime is a moderate north-westerly flow over the ocean with a maximum in the Southern California Bight. The third wind pattern shows a stronger north-westerly wind shifted toward the South and with a maximum near Point Conception. These last two patterns are slight variants of the climatological mean winds. The first two regimes are linearly associated with some particular synoptic conditions which doesn't seem to be favored by any of the large-scale weather regimes/teleconnections of the North Pacific/North America region.
A53B-0890 1340h
The Use of Bayesian Statistical Modeling to Aid in the Validation of Regional Climate Model Output
The application of regional climate modeling to assessments of future climate has grown dramatically in recent years. The need for high spatial resolution estimates of future climate has driven the use of these models. As a consequence, the need for validation, an assessment of how well the regional climate model represents a known climate, has also grown. Previous validation efforts have used gridded climate datasets such as those produced by the Climate Research Unit (CRU) of the University of East Anglia for comparison to regional model output. The disadvantages of this method are that the gridded climate datasets often exist at lower spatial resolution than the climate model output. In addition, some of these datasets only sample short time periods (i.e. 30 years or less) or don't include years of interest (i.e. 1990-2000). We have created a method of validation for regional climate model output using a Bayesian statistical model derived from observational data. We took temperature data from 115 observational stations in California, all with records of approximately 50 years in length, and created a statistical model based on this data. The statistical model takes into account the elevation of the station, distance from coastline, and the NOAA climate region in which the station resides. Initial results indicate that the statistical model provides reliable estimates of the mean monthly temperature at any given station. This statistical model is then used to estimate average temperatures corresponding to each of the climate model grid cells. These estimates are compared to the output of the regional climate model to assess how well the model matches the observed climate.
A53B-0891 1340h
Validation and Projection of North American Daily Screen-Level Temperature and Precipitation in the CCM
While coupled ocean-atmosphere general circulation models are generally validated on monthly to seasonal timescales, they are now widely used to predict potential climatic changes in extreme weather events under projected changes in radiative forcing due to human activities. In the present study, the daily minimum and maximum screen-level temperature and the daily precipitation simulated by the CNRM climate model (CCM) are validated over North America against in situ observations interpolated onto the CCM horizontal grid. The comparison between the simulated and observed distributions is made for both winter and summer seasons. It includes basic statistics such as moments and frequencies, but also more sophisticated diagnostics such as composites of daily temperatures for wet versus dry days, warm spells in summer, cold spells in winter, as well as wet spells for both seasons. Generally speaking, the CCM shows more realistic statistics for the winter than the summer season over North America. The main deficiency is an overestimation of summer precipitation, which is mainly due to large positive biases in the frequency of rainy days and particularly of low and medium precipitation rates. This drizzle problem is less pronounced in summer, but contributes significantly to the temperature biases found in both winter and summer. The daily temperature composites for wet versus dry days show realistic patterns for winter minima, but not for summer maxima. Cold spells and wet spells are well simulated in winter, which gives some confidence in the projected changes in frequency, date of occurence, duration, and intensity of these extreme events in the CCM. Conversely, the relatively poor simulation of warm spells and wet spells in summer emphasizes the need to improve the dynamical and physical processes that control these events in the CCM before providing credible scenarios on summer extremes with this model.
A53B-0892 1340h
Snow cover's influence on North American ground temperatures, 1950-2000
Borehole-based climate reconstructions suggest that the Northern Hemisphere warming has been about 1.2 K over the past 500 years while proxy methods indicate warming closer to 0.7 K. One suggested reconciliation of borehole and proxy reconstructions is that long-term variations in seasonal snow cover may influence the borehole record. We have developed a snow-ground thermal model that predicts transient warming or cooling of the annual mean surface ground temperature as a function of variations in surface air temperature and snow seasonality. The model is verified using meteorological and ground temperature observations from North America. Inter-annual correlation coefficients of observed and modeled ground temperatures from this dataset range from 0.81 to 0.99, demonstrating that the model is capable of detecting trends ground temperatures in the presence of snow. We compute the regional response of surface ground temperatures to changes in seasonal snow cover in North America from 1950-2000. Snow and air temperature data used in the modeling come from the United States Historical Climatology Network, the Canadian Daily Climatic Dataset, and a set of National Weather Service Co-Op stations in Alaska. Model results suggest snow cover has inhibited 0.2 K of the 0.5 K change in winter surface air temperature warming in the region over the past 50 years from entering the ground temperature record. Variations in snow event seasonality (onset and duration) have led to less than 0.05 K of net change in surface ground temperatures in North America during this period.
A53B-0893 1340h
Regional Climate Variability Studies with Coupled Climate-Air Quality Models
Three coupled climate-air quality models have been developed based on the PRCM (Purdue Regional Climate Model) with the aim to investigate climate-air quality interactions, and to account for air quality in regional climate variability study. Regional climatic responses due to air quality episodes have been numerically simulated with coupled climate-air quality models at the regional scale, including a tropospheric ozone episode over the Lake Michigan region and atmospheric aerosols from dust storms and biomass-burning activities in East Asia. The numerical models used in these studies have capability to simulate regional dynamical circulation and atmospheric conditions as well as to represent associated air quality episodes with coupling routines in order to investigate resulting climatic impacts in detail. From the weekly ozone episode simulation in July 1998, model results show the strong uneven regional warming/cooling effects and the modification of atmospheric stratification with the impacts on air temperature and atmospheric moisture. The April 1998 Asia dust storm modeling results show the regional warming caused by dust clouds and regional precipitation redistribution. A sensitivity study of smoke aerosols originated from southeast biomass-burning activities revealed the detrimental effects of precipitation near the source region and cause large precipitation to occur in cooler north-east Asia. These modeling studies demonstrated the strong climatic impacts due to regional air quality episodes and the necessity to include these impacts in future climate change study.
A53B-0894 1340h
Glacier Recession on Kilimanjaro and Associated Changes in Regional Climate and Tropical Atmospheric Circulation
The significance of tropical glaciers as climate proxy data has been steadily increasing in recent years, since they are essential for the detection of high-altitude, regional climate change. As with tropical glaciers worldwide, the famous glaciers on Kilimanjaro have been retreating continuously over the past century, with the onset of retreat around 1880. Due to peculiar features of this distinct volcano (physiogeographical setting, glacier shape and dynamics), our research concept for investigating glacier retreat proposes the definition of at least three different glacier regimes. Current investigations on these glacier regimes by energy and mass balance models, based on data from the University of Massachusetts automatic weather station on a plateau glacier, indicate that Kilimanjaro glaciers are most sensitive to changes in moisture-related climate variables like cloudiness, incoming shortwave radiation, precipitation and surface albedo, and that such changes due to a drier climate control the present glacier retreat. One essential question therefore arises. Under what climatic conditions has enough precipitation occurred on top of Kilimanjaro to enable the formation and maintenance of glaciers? Our results to date are in good accordance with other climate proxy data (e.g., lake levels, circulation indices), as these also indicate an abrupt drop in atmospheric moisture over East Africa in the late 19th century. Since East African precipitation amounts are strongly tied to sea surface temperature (SST) anomalies in the Indian Ocean, the key for understanding glacier retreat on Kilimanjaro might most probably be found in changes of the larger-scale (mesoscale) atmospheric circulation and related SST patterns, rather than in changes of local Kilimanjaro climate only. To meet the required research at different climatological scales, micrometeorological measurements over the glaciers and related modeling (see above) are complemented by studies with a numerical atmospheric model, to simulate changes in the mesoscale circulation over the Indian Ocean-East Africa region.
A53B-0895 1340h
Past, Present, and Future Climate Variability in the Pacific Northwest and its Influence on Carbon Exchange in an Old-growth Forest
Carbon uptake in evergreen conifer forests of the Pacific Northwest (PNW) has been shown in the past through micrometeorological and modeling methods to depend strongly on both total water-year precipitation amounts and the seasonality of precipitation, in addition to annual temperature variability. In this study, we examined the historical climatic variability at meteorological stations in close proximity to the Wind River Canopy Crane Research Facility (WRCCRF) to examine what influence such variability could have on old-growth forest ecosystem carbon exchange. The WRCCRF provides a unique opportunity to study carbon exchange between an old-growth temperate seasonal-rainforest and the atmosphere in a region which has experienced a significant amount of historical regional climate variability. Considering that temporal variability in climate can have a profound impact on forest carbon uptake and that the PNW climate variability is heavily influenced by ocean-atmosphere circulations, trends in the two dominant oscillations, the Pacific Decadal Oscillation (PDO) and the El Ni\~{n}o-Southern Oscillation (ENSO) were examined. Carbon fluxes measured with eddy-covariance techniques at WRCCRF since 1998 have shown significant interannual variability with the forest switching from a net carbon sink of 1.6 tC ha-1 yr-1 in 1999 to a net carbon source of 0.6 tC ha-1 yr-1 in 2003. Maximum net carbon uptake was measured during the 1998/1999 La Ni\~{n}a year. As anticipated, historical precipitation and temperature trends in this region were closely linked to PDO and ENSO phases. Precipitation was 10.2% above average during La Ni\~{n}a years and 9.5% above average during negative-phase PDO years, while 5% below normal during El Ni\~{n}o years and 9.5% below normal during the positive-phased PDO. Further analysis is needed to isolate the regional climatic differences from varying ENSO intensities and to study the coupled forcing mechanisms of in-phased ENSO and PDO events, though initially it appears that ENSO and PDO phase events have equal influence on regional precipitation (r-square = 0.2, water-year precipitation totals regressed separately against winter PDO and ENSO phase indices). Considering that global circulation models predict increased future climate variability in the PNW, increased interannual variability of carbon exchange is also expected. This impact of interannual and interdecadal climatic variability on old-growth forests is of particular interest considering that old-growth forest ecosystems in the Pacific Northwest represent an upper limit on carbon storage in this region and that old-growth forests are expected to be particularly sensitive to any regional climatic changes.
A53B-0896 1340h
Developing a Regional Climate Change Scenario for Air Quality Simulations in California
Changing climate has the ability to affect air quality by altering temperature and precipitation, as well as other meteorological variables. Here, we investigate possible climate change scenarios to evaluate the impacts on air quality in California. The regional air quality model (Community Multiscale Air Quality Model, CMAQ) requires a high-resolution model domain (4 km) in order to accurately assess changes in air quality over the complex topography of California. We evaluate existing regional and global climate change model simulations and methods to downscale these results to the air quality model grid by both statistical and dynamical techniques. Additionally, we investigate the impacts of these climatic changes on biogenic volatile organic compound (VOCs) and discuss their potential effect on air quality in the region.
A53B-0897 1340h
Emissions Pathways, Climate Change, and Future Wine Grape Quality in California
Grapes are the most valuable fruit crop in the nation, with wine grapes making up three-quarters of total grape value. California grows over 90% of wine grapes in the U.S., with an annual crop value of \$3.2 billion. Producing high-quality wine requires both human skill in vineyard management and winemaking, and environmental conditions suited to the optimal ripening of the grape on the vine. As wine grapes are long-lived perennial crops often in production for many decades, they are potentially sensitive to changes in climate. We used two state-of-the-art climate models (PCM and HadCM3), driven by scenarios of higher and lower greenhouse gas emissions (IPCC SRES scenarios A1fi and B1), to project climate in California over the coming century. Projected temperatures were used to estimate 1) wine grape ripening time based on accumulated growing degree days, and 2) average monthly temperature at ripening, a factor influencing potential quality. Ripening temperature ranges were designated as optimal, marginal, or impaired for producing high-quality wine grapes. For the top ten grape-growing counties in California, we compared modeled temperature averages for mid-century (2020-2049) and end-of-century (2070-2099) to a baseline of modeled growing degree day accumulation and observed average temperatures from weather stations. Across all models and scenarios, earlier ripening at higher temperatures produced shifts from optimal to marginal or impaired conditions across major grape-growing regions in the state by the end-of-century, with the notable exception of the cool coastal counties of Monterey and Mendocino. Some differences are apparent between higher and lower emissions scenarios between models. Significant adjustments may be required to adapt wine grape varieties, management, and growing regions to a changing climate over the coming century, and the magnitude of these adjustments could be affected by the emissions pathway followed during that time.
http://www.pnas.org/cgi/content/abstract/0404500101
A53B-0898 1340h
Complementary Dynamical and Statistical Downscaling from a GCM: Maha rainfall over Sri Lanka
There are two approaches to downscaling the results of the coarse scale of Global Climate Model (GCM) to fine-scales that are needed for applications. One may use a regional climate model that captures the fine scale details within a limited domain (dynamical downscaling) or use statistical relationships between GCM outputs and historical observations (statistical downscaling). Both approaches have relative strengths. Dynamical downscaling captures the physics explicitly and it provides complete solutions for the evolution of the atmosphere. It does not need extensive historical records. However, it is computationally expensive at fine scales. Statistical downscaling is simpler, inexpensive and can provide results that may be more skillful but it may be vulnerable to sampling error. We may also introduce details into the forecasts that have no physical basis. Sri Lanka is 224 km wide and 450 km long and has a mountain range with a narrow peak of over 2 km. The topography changes drastically over small distances and high-resolution downscaling is needed. Here, we attempt to downscale to a grid of 10-20 km. Sri Lanka receives 45-70% of its rainfall between October and December at the start of the main Maha cultivation season. The El Nino / Southern Oscillation and Indian Ocean Dipole phenomena modulate the Maha rainfall. These large-scale physical mechanisms are likely to be captured by GCM predictions leading to skillful predictions over Sri Lanka. The dynamical downscaling from the ECHAM4.5 GCM using the RegCM3 regional climate model was undertaken for Sri Lanka by Joshua Qian. The RegCM3 simulations yielded reasonable spatial distribution of precipitation at a resolution of 20-km. The GCM low-level wind fields from ECHAM5.4 GCM were used as a predictor to build statistical relations with observations. This downscaling work led to skillful predictions for Eastern Sri Lanka. These predictions are consistent with the reported mechanisms; the anomalous zonal wind brings preferential skill to the eastern windward side. The use of dynamical downscaling approach provided fine scale results that improve considerably upoun the GCM output. The use of a fine scale of 20 km was essential to obtain reasonable results. Statistical downscaling provided skillful predictions of seasonal rainfall for Eastern Sri Lanka. This skill was obtained at a finer scale than for the dynamical approach. The use of both techniques is complementary in that the dynamical downscaling provides physical insight that can be used to investigate statistical relationships between observations and GCM fields.
http://iri.columbia.edu/~mahaweli/
A53B-0899 1340h
Reliability of ECMWF reanalysis temperatures and climate change on the Tibetan Plateau
A significant limiting factor in assessing climate variability over the Tibetan Plateau (TP) is the sparse network of meteorological stations. A potentially valuable source of continuous long-term data for this region is provided by atmospheric reanalyses, such as the European Center for Medium Range Weather Forecasts ERA-40 effort. Here the quality of ERA-40 depictions of 2-m air temperature over the TP is examined. Evaluations rely on a data set of surface air temperatures for 161 stations obtained from the Institute of Plateau Meteorology at Chengdu, China Meteorological Administration. Our focus is on monthly temperature means and time series for ERA-40 grid cells within which there are at least four stations. This provides for reasonable grid cell estimates of temperature through averaging the station values. As assessed from means over the time series of common data coverage (September 1957-December 2000), ERA-40 temperatures are consistently low, by as much as $7\deg$C. Low biases are also present for individual months. However, correlations between monthly grid cell time series are quite high, indicating that ERA-40 captures interannual variability well. Furthermore, the temperature biases are almost entirely due to differences between the elevation of the ERA-40 grid cells and the average of the station elevations. The ERA-40 system does assimilate surface temperature observations from SYNOP reports. Efforts are underway to determine the extent to which these data are being used over the topographically complex TP, which bears on the applicability of our findings to the very data sparse western part of the plateau. Nonetheless, ERA-40 temperatures provide a surprisingly accurate depiction of temperature variability on the TP and can therefore be reliably used in climate studies, such as assessments of long-term variability in the Asian monsoon system. Interestingly, while the station data indicate a long-term upward trend in plateau temperatures, no trend is evident in the ERA-40 time series. This could reflect shortcomings in the ERA-40 reanalysis related to temporal changes in the amount and quality of assimilation data. However, since meteorological stations are located in low-lying populated areas whereas ERA-40 more reliably provides averaged plateau-wide temperatures, it could also suggest that reported climate change on the TP is due to urbanization and land use change in the vicinity of populated regions.
A53B-0900 1340h
An Underground Laboratory for the Study of Thermodynamical Processes Associated With Small Thermal Perturbations
The abandonned underground quarry of Vincennes is located near Paris (France) at about 18 m under the ground surface. The quarry is convenient for the study of the underground microclimate and of the reaction of a natural complex system to small perturbations. Temperature, Rn-222 and CO$_2$ levels, relative humidity, pressure, and water dripping fluxes have been measured since 1999 in various places of the cavity. The mean temperature is about $12.6\deg$C, with spatial variations of the order of $0.4\deg$C. In the absence of thermal perturbations, temporal variations does not exceed $0.2\deg$C per year. We study their relation with the outside temperature variations, measured in two meteorological stations located near Paris. A comparison is also made with temperature measured by Cassini IV at the end of the 18th century under the Observatory of Paris. We have recently performed temperature measurements in the same galery, located about 28 m under the city center. In the quarry of Vincennes, temperature is mainly controlled by diffusion from outside temperature through the rock covering the quarry, and by natural ventilation occuring in winter through the main access pit. This pit is also instrumented, and the ventilation is quantified by Rn-222 and CO$_2$ measurements. Understanding the role of water is also crucial, as water drips from the ceiling and the walls, and the atmosphere is saturated in almost all the quarry. Temperature variations induce evaporation/condensation processes, that have been clearly evidenced by heating experiments with low power sources, performed since 2001 in a dedicated room of the quarry. Their investigation also shows a strong non-linearity of the response of such a medium to thermal perturbations, with long-term, and possibly irreversible, effects.