University of Maryland, Baltimore County

About: University of Maryland, Baltimore County is a education organization based out in Baltimore, Maryland, United States. It is known for research contribution in the topics: Population & Aerosol. The organization has 8749 authors who have published 20843 publications receiving 795706 citations. The organization is also known as: UMBC.

Relationships between global precipitation and surface temperature on interannual and longer timescales (1979–2006)

Abstract: [1] Associations between global and regional precipitation and surface temperature anomalies on interannual and longer timescales are explored for the period of 1979–2006 using the GPCP precipitation product and the NASA-GISS surface temperature data set. Positive (negative) correlations are generally confirmed between these two variables over tropical oceans (lands). ENSO is the dominant factor in these interannual tropical relations. Away from the tropics, particularly in the Northern Hemisphere mid-high latitudes, this correlation relationship becomes much more complicated with positive and negative values of correlation tending to appear over both ocean and land, with a strong seasonal variation in the correlation patterns. Relationships between long-term linear changes in global precipitation and surface temperature are also assessed. Most intense long-term, linear changes in annual-mean rainfall during the data record tend to be within the tropics. For surface temperature however, the strongest linear changes are observed in the Northern Hemisphere mid-high latitudes, with much weaker temperature changes in the tropical region and Southern Hemisphere. Finally, the ratios between the linear changes in zonal-mean rainfall and temperature anomalies over the period are estimated. Globally, the calculation results in a +2.3%/°C precipitation change, although the magnitude is sensitive to small errors in the precipitation data set and to the length of record used for the calculation. The long-term temperature-precipitation relations are also compared to the interannual variations of the same ratio in a zonally averaged sense and are shown to have similar profiles, except for over tropical land areas.

Estimated impact of black carbon deposition during pre-monsoon season from Nepal Climate Observatory – Pyramid data and snow albedo changes over Himalayan glaciers

Abstract: . The possible minimal range of reduction in snow surface albedo due to dry deposition of black carbon (BC) in the pre-monsoon period (March–May) was estimated as a lower bound together with the estimation of its accuracy, based on atmospheric observations at the Nepal Climate Observatory – Pyramid (NCO-P) sited at 5079 m a.s.l. in the Himalayan region. A total BC deposition rate was estimated as 2.89 μg m−2 day−1 providing a total deposition of 266 μg m−2 for March–May at the site, based on a calculation with a minimal deposition velocity of 1.0×10−4 m s−1 with atmospheric data of equivalent BC concentration. Main BC size at NCO-P site was determined as 103.1–669.8 nm by correlation analyses between equivalent BC concentration and particulate size distributions in the atmosphere. The BC deposition from the size distribution data was also estimated. It was found that 8.7% of the estimated dry deposition corresponds to the estimated BC deposition from equivalent BC concentration data. If all the BC is deposited uniformly on the top 2-cm pure snow, the corresponding BC concentration is 26.0–68.2 μg kg−1, assuming snow density variations of 195–512 kg m−3 of Yala Glacier close to NCO-P site. Such a concentration of BC in snow could result in 2.0–5.2% albedo reductions. By assuming these albedo reductions continue throughout the year, and then applying simple numerical experiments with a glacier mass balance model, we estimated reductions would lead to runoff increases of 70–204 mm of water. This runoff is the equivalent of 11.6–33.9% of the annual discharge of a typical Tibetan glacier. Our estimates of BC concentration in snow surface for pre-monsoon season is comparable to those at similar altitudes in the Himalayan region, where glaciers and perpetual snow regions begin, in the vicinity of NCO-P. Our estimates from only BC are likely to represent a lower bound for snow albedo reductions, because we used a fixed slower deposition velocity. In addition, we excluded the effects of atmospheric wind and turbulence, snow aging, dust deposition, and snow albedo feedbacks. This preliminary study represents the first investigation of BC deposition and related albedo on snow, using atmospheric aerosol data observed at the southern slope in the Himalayas.

What would have happened to the ozone layer if chlorofluorocarbons (CFCs) had not been regulated

Abstract: . Ozone depletion by chlorofluorocarbons (CFCs) was first proposed by Molina and Rowland in their 1974 Nature paper. Since that time, the scientific connection between ozone losses and CFCs and other ozone depleting substances (ODSs) has been firmly established with laboratory measurements, atmospheric observations, and modeling studies. This science research led to the implementation of international agreements that largely stopped the production of ODSs. In this study we use a fully-coupled radiation-chemical-dynamical model to simulate a future world where ODSs were never regulated and ODS production grew at an annual rate of 3%. In this "world avoided" simulation, 17% of the globally-averaged column ozone is destroyed by 2020, and 67% is destroyed by 2065 in comparison to 1980. Large ozone depletions in the polar region become year-round rather than just seasonal as is currently observed in the Antarctic ozone hole. Very large temperature decreases are observed in response to circulation changes and decreased shortwave radiation absorption by ozone. Ozone levels in the tropical lower stratosphere remain constant until about 2053 and then collapse to near zero by 2058 as a result of heterogeneous chemical processes (as currently observed in the Antarctic ozone hole). The tropical cooling that triggers the ozone collapse is caused by an increase of the tropical upwelling. In response to ozone changes, ultraviolet radiation increases, more than doubling the erythemal radiation in the northern summer midlatitudes by 2060.

Correcting for forecast bias in soil moisture assimilation with the ensemble Kalman filter

Abstract: [1] Land surface models are usually biased in at least a subset of the simulated variables even after calibration. Bias estimation may therefore be needed for data assimilation. Here, in situ soil moisture profile observations in a small agricultural field were merged with Community Land Model (CLM2.0) simulations using different algorithms for state and forecast bias estimation with and without bias correction feedback. Simple state updating with the conventional ensemble Kalman filter (EnKF) allows for some implicit forecast bias correction. It is possible to estimate the soil moisture bias explicitly and derive superior soil moisture estimates with a generalized EnKF that uses a simple persistence model for the bias and assumes that the a priori bias error covariance is proportional to the a priori state error covariance. For the case of bi-weekly assimilation of the entire profile of soil moisture observations, bias estimation and correction typically reduces the RMSE in soil moisture (over the standard EnKF without bias correction) by around 60 percent. However, under the above assumptions, significant improvements are limited to state variables for which observations are available. Therefore, it is crucial to measure the state variables of interest. The best variant for state and bias estimation depends on the nature of the model bias and the output of interest to the user. In a model that is only biased for soil moisture, large and frequent increments for soil moisture updating may be required, which in turn may negatively impact the water balance and output fluxes. It is then better to post-process the soil moisture with the bias analysis without updating the model state.