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P. Das

Abstract

Neither the pseudo-adiabatic nor the saturation-adiabatic form of the thermodynamic equation used in meteorological practice is suitable for the study of cumulus dynamics inasmuch as this form ignores the microphysics of condensation and precipitation. A thermodynamic equation has been derived treating the cloud as a mixture of dry air, water vapor, and liquid water distributed into droplets, drops and/or other centers of condensation and evaporation. The equation implicitly includes the effect of fallout of the centers from their parent parcels of air and is explicitly supplemented by an equation of continuity for the centers. A simple way has been indicated for extending the basic equation which has been derived for condensation-evaporation centers of uniform mass (and fall velocity relative to air) to clouds having a population of centers of varying mass.

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Robert E. Eskridge and P. Das

Abstract

No abstract available.

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Viney P. Aneja and Mita Das

Abstract

Gas-phase hydrogen peroxide (H2O2) and ozone (O3) along With other trace gases and meteorology were monitored in two distinct regimes of high- and low-NOx (urban and rural) areas in North Carolina during the summer of 1991 as part of the Southern Oxidants Study (SOS). Gas-phase hydrogen peroxide concentrations ranged from less than 0.05 to about 1.0 ppbv and from less than 0.05 to 2.0 ppbv at the urban and rural sites, respectively. A clear diurnal trend was observed at both locations, though at the urban site the H2O2 profile lagged the ozone profile by 2–3 h. At the rural site, high H2O2 concentrations were observed on certain nights. The various physical, chemical, and meteorological parameters affecting H2O2 concentrations were examined using observational-based statistical analysis. It was found that in the urban air, H2O2 concentrations increased with increasing temperature, solar radiation, and ozone concentrations but decreased with increasing NOx, carbon monoxide, and relative humidity. In the rural air, hydrogen peroxide concentrations were also found to be affected in a similar way. The results of a multivariate statistical analysis indicates that the gas-phase H2O2 concentration observed at the sites is dependent on the atmospheric chemistry and the dynamical characteristics of the sites.

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Someshwar Das, U. C. Mohanty, and O. P. Sharma

Abstract

The performances of several versions of the Kuo-type cumulus parameterization schemes have been examined during different phases of the summer monsoon. These phases are the preonset, an onset and a period of break in the monsoon. Special sets of upper air observations that were collected from stationary ships forming polygons over the Arabian Sea and the Bay of Bengal during MONEX-79 were used for this purpose. Cumulus warming, drying and precipitation rates have been simulated in a semiprognostic way and compared with the observations.

The limitations of different schemes for numerical weather prediction are discussed. Among various Kuo-type cumulus parameterization schemes studied in this article, a modified Kuo-scheme is found to provide best results during the summer monsoon. In this scheme the moistening parameter is determined based upon the relative humidity and it is tuned for different phases of the monsoon.

A comparison of the performance of various schemes during different phases of the monsoon was made. The heating and drying rates were best simulated during a preonset phase, when compared with the other two periods. The largest deviations between observed and simulated values were obtained during a break in the monsoon.

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Julie A. Vano, Tapash Das, and Dennis P. Lettenmaier

Abstract

The Colorado River is the primary water source for much of the rapidly growing southwestern United States. Recent studies have projected reductions in Colorado River flows from less than 10% to almost 50% by midcentury because of climate change—a range that has clouded potential management responses. These differences in projections are attributable to variations in climate model projections but also to differing land surface model (LSM) sensitivities. This second contribution to uncertainty—specifically, variations in LSM runoff change with respect to precipitation (elasticities) and temperature (sensitivities)—are evaluated here through comparisons of multidecadal simulations from five commonly used LSMs (Catchment, Community Land Model, Noah, Sacramento Soil Moisture Accounting model, and Variable Infiltration Capacity model) all applied over the Colorado River basin at ⅛° latitude by longitude spatial resolution. The annual elasticity of modeled runoff (fractional change in annual runoff divided by fractional change in annual precipitation) at Lees Ferry ranges from two to six for the different LSMs. Elasticities generally are higher in lower precipitation and/or runoff regimes; hence, the highest values are for models biased low in runoff production, and the range of elasticities is reduced to two to three when adjusted to current runoff climatology. Annual temperature sensitivities (percent change in annual runoff per degree change in annual temperature) range from declines of 2% to as much as 9% per degree Celsius increase at Lees Ferry. For some LSMs, small areas, primarily at midelevation, have increasing runoff with increasing temperature; however, on a spatial basis, most sensitivities are negative.

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T. Das, H. G. Hidalgo, D. W. Pierce, T. P. Barnett, M. D. Dettinger, D. R. Cayan, C. Bonfils, G. Bala, and A. Mirin

Abstract

This study examines the geographic structure of observed trends in key hydrologically relevant variables across the western United States at ⅛° spatial resolution during the period 1950–99. Geographical regions, latitude bands, and elevation classes where these trends are statistically significantly different from trends associated with natural climate variations are identified. Variables analyzed include late-winter and spring temperature, winter-total snowy days as a fraction of winter-total wet days, 1 April snow water equivalent (SWE) as a fraction of October–March (ONDJFM) precipitation total [precip(ONDJFM)], and seasonal [JFM] accumulated runoff as a fraction of water-year accumulated runoff. Observed changes were compared to natural internal climate variability simulated by an 850-yr control run of the finite volume version of the Community Climate System Model, version 3 (CCSM3-FV), statistically downscaled to a ⅛° grid using the method of constructed analogs. Both observed and downscaled model temperature and precipitation data were then used to drive the Variable Infiltration Capacity (VIC) hydrological model to obtain the hydrological variables analyzed in this study. Large trends (magnitudes found less than 5% of the time in the long control run) are common in the observations and occupy a substantial part (37%–42%) of the mountainous western United States. These trends are strongly related to the large-scale warming that appears over 89% of the domain. The strongest changes in the hydrologic variables, unlikely to be associated with natural variability alone, have occurred at medium elevations [750–2500 m for JFM runoff fractions and 500–3000 m for SWE/Precip(ONDJFM)] where warming has pushed temperatures from slightly below to slightly above freezing. Further analysis using the data on selected catchments indicates that hydroclimatic variables must have changed significantly (at 95% confidence level) over at least 45% of the total catchment area to achieve a detectable trend in measures accumulated to the catchment scale.

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Someshwar Das, U. C. Mohanty, Ajit Tyagi, D. R. Sikka, P. V. Joseph, L. S. Rathore, Arjumand Habib, Saraju K. Baidya, Kinzang Sonam, and Abhijit Sarkar

This article describes a unique field experiment on Severe Thunderstorm Observations and Regional Modeling (STORM) jointly undertaken by eight South Asian countries. Several pilot field experiments have been conducted so far, and the results are analyzed. The field experiments will continue through 2016.

The STORM program was originally conceived for understanding the severe thunderstorms known as nor'westers that affect West Bengal and the northeastern parts of India during the pre-monsoon season. The nor'westers cause loss of human lives and damage to properties worth millions of dollars annually. Since the neighboring South Asian countries are also affected by thunderstorms, the STORM program is expanded to cover the South Asian countries under the South Asian Association for Regional Cooperation (SAARC). It covers all the SAARC countries (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) in three phases. Some of the science plans (monitoring the life cycle of nor'westers/severe thunderstorms and their three-dimensional structure) designed to understand the interrelationship among dynamics, cloud microphysics, and electrical properties in the thunderstorm environment are new to severe weather research. This paper describes the general setting of the field experiment and discusses preliminary results based on the pilot field data. Typical lengths and the intensity of squall lines, the speed of movements, and cloud-top temperatures and their heights are discussed based on the pilot field data. The SAARC STORM program will complement the Severe Weather Forecast Demonstration Project (SWFDP) of the WMO. It should also generate large-scale interest for fueling research among the scientific community and broaden the perspectives of operational meteorologists and researchers.

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Céline Bonfils, Benjamin D. Santer, David W. Pierce, Hugo G. Hidalgo, Govindasamy Bala, Tapash Das, Tim P. Barnett, Daniel R. Cayan, Charles Doutriaux, Andrew W. Wood, Art Mirin, and Toru Nozawa

Abstract

Large changes in the hydrology of the western United States have been observed since the mid-twentieth century. These include a reduction in the amount of precipitation arriving as snow, a decline in snowpack at low and midelevations, and a shift toward earlier arrival of both snowmelt and the centroid (center of mass) of streamflows. To project future water supply reliability, it is crucial to obtain a better understanding of the underlying cause or causes for these changes. A regional warming is often posited as the cause of these changes without formal testing of different competitive explanations for the warming. In this study, a rigorous detection and attribution analysis is performed to determine the causes of the late winter/early spring changes in hydrologically relevant temperature variables over mountain ranges of the western United States. Natural internal climate variability, as estimated from two long control climate model simulations, is insufficient to explain the rapid increase in daily minimum and maximum temperatures, the sharp decline in frost days, and the rise in degree-days above 0°C (a simple proxy for temperature-driven snowmelt). These observed changes are also inconsistent with the model-predicted responses to variability in solar irradiance and volcanic activity. The observations are consistent with climate simulations that include the combined effects of anthropogenic greenhouse gases and aerosols. It is found that, for each temperature variable considered, an anthropogenic signal is identifiable in observational fields. The results are robust to uncertainties in model-estimated fingerprints and natural variability noise, to the choice of statistical downscaling method, and to various processing options in the detection and attribution method.

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David W. Pierce, Daniel R. Cayan, Tapash Das, Edwin P. Maurer, Norman L. Miller, Yan Bao, M. Kanamitsu, Kei Yoshimura, Mark A. Snyder, Lisa C. Sloan, Guido Franco, and Mary Tyree

Abstract

Climate model simulations disagree on whether future precipitation will increase or decrease over California, which has impeded efforts to anticipate and adapt to human-induced climate change. This disagreement is explored in terms of daily precipitation frequency and intensity. It is found that divergent model projections of changes in the incidence of rare heavy (>60 mm day−1) daily precipitation events explain much of the model disagreement on annual time scales, yet represent only 0.3% of precipitating days and 9% of annual precipitation volume. Of the 25 downscaled model projections examined here, 21 agree that precipitation frequency will decrease by the 2060s, with a mean reduction of 6–14 days yr−1. This reduces California's mean annual precipitation by about 5.7%. Partly offsetting this, 16 of the 25 projections agree that daily precipitation intensity will increase, which accounts for a model average 5.3% increase in annual precipitation. Between these conflicting tendencies, 12 projections show drier annual conditions by the 2060s and 13 show wetter. These results are obtained from 16 global general circulation models downscaled with different combinations of dynamical methods [Weather Research and Forecasting (WRF), Regional Spectral Model (RSM), and version 3 of the Regional Climate Model (RegCM3)] and statistical methods [bias correction with spatial disaggregation (BCSD) and bias correction with constructed analogs (BCCA)], although not all downscaling methods were applied to each global model. Model disagreements in the projected change in occurrence of the heaviest precipitation days (>60 mm day−1) account for the majority of disagreement in the projected change in annual precipitation, and occur preferentially over the Sierra Nevada and Northern California. When such events are excluded, nearly twice as many projections show drier future conditions.

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Julie A. Vano, Bradley Udall, Daniel R. Cayan, Jonathan T. Overpeck, Levi D. Brekke, Tapash Das, Holly C. Hartmann, Hugo G. Hidalgo, Martin Hoerling, Gregory J. McCabe, Kiyomi Morino, Robert S. Webb, Kevin Werner, and Dennis P. Lettenmaier

The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamf lows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the ~100 years of instrumental record.

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