The Use of Weather Forecasts to Characterise Near-Surface Optical Turbulence

2010 ◽  
Vol 138 (3) ◽  
pp. 453-473 ◽  
Author(s):  
S. Cheinet ◽  
A. Beljaars ◽  
K. Weiss-Wrana ◽  
Y. Hurtaud
2002 ◽  
Author(s):  
Omar S. Khalil ◽  
Johannes S. Kanger ◽  
Xiaomao Wu ◽  
Rene A. Bolt ◽  
Shu-Jen Yeh ◽  
...  

2016 ◽  
Vol 16 (10) ◽  
pp. 6475-6494 ◽  
Author(s):  
Jianglong Zhang ◽  
Jeffrey S. Reid ◽  
Matthew Christensen ◽  
Angela Benedetti

Abstract. A major continental-scale biomass burning smoke event from 28–30 June 2015, spanning central Canada through the eastern seaboard of the United States, resulted in unforecasted drops in daytime high surface temperatures on the order of 2–5  °C in the upper Midwest. This event, with strong smoke gradients and largely cloud-free conditions, provides a natural laboratory to study how aerosol radiative effects may influence numerical weather prediction (NWP) forecast outcomes. Here, we describe the nature of this smoke event and evaluate the differences in observed near-surface air temperatures between Bismarck (clear) and Grand Forks (overcast smoke), to evaluate to what degree solar radiation forcing from a smoke plume introduces daytime surface cooling, and how this affects model bias in forecasts and analyses. For this event, mid-visible (550 nm) smoke aerosol optical thickness (AOT, τ) reached values above 5. A direct surface cooling efficiency of −1.5 °C per unit AOT (at 550 nm, τ550) was found. A further analysis of European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), United Kingdom Meteorological Office (UKMO) near-surface air temperature forecasts for up to 54 h as a function of Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOT data across more than 400 surface stations, also indicated the presence of the daytime aerosol direct cooling effect, but suggested a smaller aerosol direct surface cooling efficiency with magnitude on the order of −0.25 to −1.0 °C per unit τ550. In addition, using observations from the surface stations, uncertainties in near-surface air temperatures from ECMWF, NCEP, and UKMO model runs are estimated. This study further suggests that significant daily changes in τ550 above 1, at which the smoke-aerosol-induced direct surface cooling effect could be comparable in magnitude with model uncertainties, are rare events on a global scale. Thus, incorporating a more realistic smoke aerosol field into numerical models is currently less likely to significantly improve the accuracy of near-surface air temperature forecasts. However, regions such as eastern China, eastern Russia, India, and portions of the Saharan and Taklamakan deserts, where significant daily changes in AOTs are more frequent, are likely to benefit from including an accurate aerosol analysis into numerical weather forecasts.


2020 ◽  
Vol 148 (10) ◽  
pp. 3995-4008
Author(s):  
Andrea Manrique-Suñén ◽  
Nube Gonzalez-Reviriego ◽  
Verónica Torralba ◽  
Nicola Cortesi ◽  
Francisco J. Doblas-Reyes

AbstractSubseasonal predictions bridge the gap between medium-range weather forecasts and seasonal climate predictions. This time scale is crucial for operations and planning in many sectors such as energy and agriculture. For users to trust these predictions and efficiently make use of them in decision-making, the quality of predicted near-surface parameters needs to be systematically assessed. However, the method to follow in a probabilistic evaluation of subseasonal predictions is not trivial. This study aims to offer an illustration of the impact that the verification setup might have on the calculation of the skill scores, thus providing some guidelines for subseasonal forecast evaluation. For this, several forecast verification setups to calculate the fair ranked probability skill score for tercile categories have been designed. These setups use different number of samples to compute the fair RPSS as well as different ways to define the climatology, characterized by different time periods to average (week or month). These setups have been tested by evaluating 2-m temperature in ECMWF-Ext-ENS 20-yr hindcasts for all of the initializations in 2016 against the ERA-Interim reanalysis. Then, the implications on skill score values of each of the setups are analyzed. Results show that to obtain a robust skill score several start dates need to be employed. It is also shown that a constant monthly climatology over each calendar month may introduce spurious skill score associated with the seasonal cycle. A weekly climatology bears similar results to a monthly running-window climatology; however, the latter provides a better reference climatology when bias adjustment is applied.


2005 ◽  
Vol 32 (2) ◽  
pp. 334-345
Author(s):  
John Turner

Great advances have been made in recent years in our understanding of the weather of the Antarctic and how the climate of the continent varies on a range of time-scales. The observations from the stations are still the most accurate meteorological measurements that we have, but satellites have been important in providing data for remote parts of the continent and the Southern Ocean. With the large amount of data that is available today weather forecasts are much more accurate than just a few years ago and can provide valuable guidance up to several days ahead over the Southern Ocean and Antarctic coastal region. However, predicting the weather for the interior of the Antarctic is still very difficult. Recent research has shown that the climate of the Antarctic is affected by tropical atmospheric and oceanic climate cycles, such as the El Niño-Southern Oscillation, but the links are complex. The picture of climate change across the Antarctic during the last 50 years is complex, with only the Antarctic Peninsula showing a significant warming. By the end of the twenty-first century near-surface air temperatures across much of the Antarctic continent are expected to increase by several degrees. A small increase in precipitation is also expected.


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