scholarly journals Seasonal and diurnal performance of daily forecasts with WRF-NOAHMP V3.8.1 over the United Arab Emirates

2020 ◽  
Author(s):  
Oliver Branch ◽  
Thomas Schwitalla ◽  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
...  
Keyword(s):  
United Arab Emirates ◽  
Weather Forecasting ◽  
Heat Waves ◽  
Sea Breeze ◽  
Dust Storms ◽  
Dew Point ◽  
Cold Bias ◽  
Mountain Regions ◽  
Numerical Weather Forecasting ◽  
Daily Forecast

Abstract. Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates (UAE) where extreme events like heat waves, flash floods and dust storms are severe. Hence, accurate forecasting of quantities like surface temperatures and humidity is very important. To date, there have been few seasonal-to-annual scale verification studies with WRF at high spatial and temporal resolution. This study employs a convection-permitting scale (2.7 km grid scale) simulation with WRF-NOAHMP, in daily forecast mode, from January 01 to November 30 2015. WRF was verified using measurements of 2 m air temperature (T-2m), dew point (TD-2m), and 10 m windspeed (UV-10m) from 48 UAE surface stations. Analysis was made of seasonal and diurnal performance within the desert, marine and mountain regions of the UAE. Results show that WRF represents temperature (T-2m) quite adequately during the daytime with biases ≤ +1 ˚C. There is however a nocturnal cold bias (−1 to −4 ˚C), which increases during hotter months in the desert and mountain regions. The marine region has the lowest T-2m biases (≤−0.75 ˚C). WRF performs well regarding TD-2m, with mean biases mostly ≤ 1 ˚C. TD-2m over the marine region is overestimated though (0.75–1 ˚C), and nocturnal mountain TD-2m is underestimated (~ −2 ˚C). UV-10m performance on land still needs improvement, and biases can occasionally be large (1–2 m s−1). This performance tends to worsen during the hot months, particularly inland with peak biases reaching ~ 3 m s−1. UV-10m are better simulated in the marine region (bias ≤ 1 m s−1). There is an apparent relationship between T-2m bias and UV-10m bias, which may indicate issues in simulation of the daytime sea breeze. TD-2m biases tend to be more independent. Studies such as these are vital for accurate assessment of WRF nowcasting performance and to identify model deficiencies. By combining sensitivity tests, process and observational studies with seasonal verification, we can further improve forecasting systems for the UAE.

scholarly journals Seasonal and diurnal performance of daily forecasts with WRF V3.8.1 over the United Arab Emirates

2021 ◽  
Vol 14 (3) ◽  
pp. 1615-1637
Author(s):  
Oliver Branch ◽  
Thomas Schwitalla ◽  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
...  
Keyword(s):  
United Arab Emirates ◽  
Weather Forecasting ◽  
Heat Waves ◽  
Sea Breeze ◽  
Dust Storms ◽  
Dew Point ◽  
Cold Bias ◽  
Mountain Regions ◽  
Numerical Weather Forecasting ◽  
Daily Forecast

Abstract. Effective numerical weather forecasting is vital in arid regions like the United Arab Emirates (UAE) where extreme events like heat waves, flash floods, and dust storms are severe. Hence, accurate forecasting of quantities like surface temperatures and humidity is very important. To date, there have been few seasonal-to-annual scale verification studies with WRF at high spatial and temporal resolution. This study employs a convection-permitting scale (2.7 km grid scale) simulation with WRF with Noah-MP, in daily forecast mode, from 1 January to 30 November 2015. WRF was verified using measurements of 2 m air temperature (T2 m), 2 m dew point (TD2 m), and 10 m wind speed (UV10 m) from 48 UAE WMO-compliant surface weather stations. Analysis was made of seasonal and diurnal performance within the desert, marine, and mountain regions of the UAE. Results show that WRF represents temperature (T2 m) quite adequately during the daytime with biases ≤+1 ∘C. There is, however, a nocturnal cold bias (−1 to −4 ∘C), which increases during hotter months in the desert and mountain regions. The marine region has the smallest T2 m biases (≤-0.75 ∘C). WRF performs well regarding TD2 m, with mean biases mostly ≤ 1 ∘C. TD2 m over the marine region is overestimated, though (0.75–1 ∘C), and nocturnal mountain TD2 m is underestimated (∼-2 ∘C). UV10 m performance on land still needs improvement, and biases can occasionally be large (1–2 m s−1). This performance tends to worsen during the hot months, particularly inland with peak biases reaching ∼ 3 m s−1. UV10 m is better simulated in the marine region (bias ≤ 1 m s−1). There is an apparent relationship between T2 m bias and UV10 m bias, which may indicate issues in simulation of the daytime sea breeze. TD2 m biases tend to be more independent. Studies such as these are vital for accurate assessment of WRF nowcasting performance and to identify model deficiencies. By combining sensitivity tests, process, and observational studies with seasonal verification, we can further improve forecasting systems for the UAE.

scholarly journals Estimating Water Vapor Using Signals from Microwave Links below 25 GHz

2021 ◽  
Vol 13 (8) ◽  
pp. 1409
Author(s):  
Kun Song ◽  
Xichuan Liu ◽  
Taichang Gao ◽  
Peng Zhang
Keyword(s):  
Water Vapor ◽  
Weather Forecasting ◽  
Water Cycle ◽  
Correlation Coefficients ◽  
Support Vector ◽  
Vapor Density ◽  
Measurement Resolution ◽  
Sensing Model ◽  
Numerical Weather Forecasting ◽  
Mean Square Errors

Water vapor is a key element in both the greenhouse effect and the water cycle. However, water vapor has not been well studied due to the limitations of conventional monitoring instruments. Recently, estimating rain rate by the rain-induced attenuation of commercial microwave links (MLs) has been proven to be a feasible method. Similar to rainfall, water vapor also attenuates the energy of MLs. Thus, MLs also have the potential of estimating water vapor. This study proposes a method to estimate water vapor density by using the received signal level (RSL) of MLs at 15, 18, and 23 GHz, which is the first attempt to estimate water vapor by MLs below 20 GHz. This method trains a sensing model with prior RSL data and water vapor density by the support vector machine, and the model can directly estimate the water vapor density from the RSLs without preprocessing. The results show that the measurement resolution of the proposed method is less than 1 g/m3. The correlation coefficients between automatic weather stations and MLs range from 0.72 to 0.81, and the root mean square errors range from 1.57 to 2.31 g/m3. With the large availability of signal measurements from communications operators, this method has the potential of providing refined data on water vapor density, which can contribute to research on the atmospheric boundary layer and numerical weather forecasting.

scholarly journals Coupling between the JULES land-surface scheme and the CCATT-BRAMS atmospheric chemistry model (JULES-CCATT-BRAMS1.0): applications to numerical weather forecasting and the CO<sub>2</sub> budget in South America

2013 ◽  
Vol 6 (1) ◽  
pp. 453-494 ◽  
Author(s):  
D. S. Moreira ◽  
S. R. Freitas ◽  
J. P. Bonatti ◽  
L. M. Mercado ◽  
N. M. É. Rosário ◽  
...  
Keyword(s):  
South America ◽  
Atmospheric Chemistry ◽  
Land Surface ◽  
Amazon Basin ◽  
Mean Squared Error ◽  
Weather Forecasting ◽  
Dew Point ◽  
Surface Model ◽  
Co2 Concentrations ◽  
Wide Range

Abstract. This article presents the development of a new numerical system denominated JULES-CCATT-BRAMS, which resulted from the coupling of the JULES surface model to the CCATT-BRAMS atmospheric chemistry model. The performance of this system in relation to several meteorological variables (wind speed at 10 m, air temperature at 2 m, dew point temperature at 2 m, pressure reduced to mean sea level and 6 h accumulated precipitation) and the CO2 concentration above an extensive area of South America is also presented, focusing on the Amazon basin. The evaluations were conducted for two periods, the wet (March) and dry (September) seasons of 2010. The statistics used to perform the evaluation included bias (BIAS) and root mean squared error (RMSE). The errors were calculated in relation to observations at conventional stations in airports and automatic stations. In addition, CO2 concentrations in the first model level were compared with meteorological tower measurements and vertical CO2 profiles were compared with aircraft data. The results of this study show that the JULES model coupled to CCATT-BRAMS provided a significant gain in performance in the evaluated atmospheric fields relative to those simulated by the LEAF (version 3) surface model originally utilized by CCATT-BRAMS. Simulations of CO2 concentrations in Amazonia and a comparison with observations are also discussed and show that the system presents a gain in performance relative to previous studies. Finally, we discuss a wide range of numerical studies integrating coupled atmospheric, land surface and chemistry processes that could be produced with the system described here. Therefore, this work presents to the scientific community a free tool, with good performance in relation to the observed data and re-analyses, able to produce atmospheric simulations/forecasts at different resolutions, for any period of time and in any region of the globe.

Current Threats to the Environmental Conditions in Cities of the Eastern Mediterranean

2021 ◽  
Author(s):  
Manfred A. Lange
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Environmental Conditions ◽  
Heat Waves ◽  
Eastern Mediterranean ◽  
Middle Eastern ◽  
Liquid Waste ◽  
Dust Storms ◽  
Urban Structures ◽  
Space Cooling

&lt;p&gt;The environmental conditions in urban settings are subject to processes and conditions within cities, on the one hand, and have a strong bearing on the overall conditions and the quality of life of the cities&amp;#8217; inhabitants, on the other. The built environment, in general, and buildings and infrastructure, in particular, play a major role in shaping the urban environment. At the same time, environmental conditions affect strongly the conditions within and outside of buildings.&lt;/p&gt;&lt;p&gt;The continued growth of cities in the Eastern Mediterranean and Middle Eastern (EMME) region, the demise of environmental quality adds to the challenges faced by their inhabitants. Of the many factors contributing to these threats, climate change and its amplification in urban structures, the increasing load of pollutants in air and water and the rising numbers of dust storms as well as the growing amount of solid and liquid waste stand out.&lt;/p&gt;&lt;p&gt;The significant increase in the number of cars and the rising quantity of energy production has contributed to ever-worsening air quality in EMME cities. More specifically, urban road transport represents one of the major sources of air-borne pollutants in many of these cities and causes substantial threats to the health of their inhabitants.&lt;/p&gt;&lt;p&gt;The Middle East and North Africa (MENA) and the EMME region are major sources of desert dust storms that travel north and east to Europe and Asia, thereby strongly affecting cities and their air quality in the EMME. Dust storms and suspended bacteria and viruses pose serious consequences to communities in the EMME region and are likely to worsen due to ongoing climate change.&lt;/p&gt;&lt;p&gt;Present and future changes in climate conditions will have numerous adverse effects on the EMME region, in general, and on EMME cities, in particular. This includes extended heat waves as well as enhanced water scarcity for inhabitants and green spaces. In combination with poor air quality, this will cause severe health risks for urban populations as well as the need for increased and extended periods of space cooling in private, commercial and municipal buildings. The greater needs for water and energy in urban structures are interrelated and have been described by the Water-Energy Nexus. The higher demand for water is increasingly satisfied through desalination, which is particularly energy-intensive. The need for additional space cooling during hot spells in cities will require more electricity.&lt;/p&gt;&lt;p&gt;The high rate of population growth, ever-increasing urbanization, changes in lifestyles and economic expansion in the EMME countries result in steadily increasing volumes of solid and liquid waste. The waste problems are exacerbated by the rising number of displaced persons and refugees in growing camps in some of the EMME countries, particularly, in Turkey, Jordan and Lebanon. The huge quantity of daily produced sewage sludge in Middle Eastern countries presents a serious challenge due to its high treatment costs and risks to the environment and human health.&lt;/p&gt;&lt;p&gt;This paper will address some of these challenges, which call for holistic and interdisciplinary efforts to design effective and sustainable adaptation strategies in EMME cities.&lt;/p&gt;

First Doppler lidar and cloud radar measurements of orographic convection initiation from a mountain observatory in the Al Hajar Mountains of the United Arab Emirates.

2021 ◽  
Author(s):  
Oliver Branch ◽  
Andreas Behrendt ◽  
Osama Alnayef ◽  
Florian Späth ◽  
Thomas Schwitalla ◽  
...  
Keyword(s):  
United Arab Emirates ◽  
Sea Breeze ◽  
Doppler Lidar ◽  
Cloud Seeding ◽  
Low Level ◽  
Cloud Radar ◽  
Orographic Convection ◽  
Radar Measurements ◽  
Convection Initiation ◽  
Convective Cells

&lt;p&gt;We present exciting Doppler lidar and cloud radar measurements from a high-vantage mountain observatory in the hyper-arid United Arab Emirates (UAE) - initiated as part of the UAE Research Program for Rain Enhancement Science (UAEREP). The observatory was designed to study the clear-air pre-convective environment and subsequent convective events in the arid Al Hajar Mountains, with the overarching goal of improving understanding and nowcasting of seedable orographic clouds. During summer in the Al Hajar Mountains (June to September), weather processes are often complex, with summer convection being initiated by several phenomena acting in concert, e.g., interaction between sea breeze and horizontal convective rolls. These interactions can combine to initiate sporadic convective storms and these can be intense enough to cause flash floods and erosion. Such events here are influenced by mesoscale phenomena like the low-level jet and local sea breeze, and are constrained by larger-scale synoptic conditions.&lt;/p&gt;&lt;p&gt;The Doppler lidar and cloud radar were employed for approximately two years at a high vantage-point to capture valley wind flows and observe convective cells. The instruments were configured to run synchronized polar (PPI) scans at 0&amp;#176;, 5&amp;#176;, and 45&amp;#176; elevation angles and vertical cross-section (RHI) scans at 0&amp;#176;, 30&amp;#176;, 60, 90&amp;#176;, 120&amp;#176;, and 150&amp;#176; azimuth angles. Using this imagery, along with local C-band radar and satellite data, we were able to identify and analyze several convective cases. To illustrate our results, we have selected two cases under unstable conditions - the 5 and 6 September 2018. In both cases, we observed areas of low-level convergence/divergence, particularly associated with wind flow around a peak 2 km to the south-west of the observatory. The extension of these deformations are visible in the atmosphere to a height of 3 km above sea level. Subsequently, we observed convective cells developing at those approximate locations &amp;#8211; apparently initiated because of these phenomena. The cloud radar images provided detailed observations of cloud structure, evolution, and precipitation. In both convective cases, pre-convective signatures were apparent before CI, in the form of convergence, wind shear structures, and updrafts.&lt;/p&gt;&lt;p&gt;These results have demonstrated the value of synergetic observations for understanding orographic convection initiation, improvement of forecast models, and cloud seeding guidance. The manuscript based on these results is now the subject of a peer review (Branch et al., 2021).&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Branch, O., Behrendt, Andreas Alnayef, O., Sp&amp;#228;th, F., Schwitalla, Thomas, Temimi, M., Weston, M., Farrah, S., Al Yazeedi, O., Tampi, S., Waal, K. de and Wulfmeyer, V.: The new Mountain Observatory of the Project &amp;#8220;Optimizing Cloud Seeding by Advanced Remote Sensing and Land Cover Modification (OCAL)&amp;#8221; in the United Arab Emirates: First results on Convection Initiation, J. Geophys. Res.&amp;#160; Atmos., 2021. In review (submitted 23.11.2020).&lt;/p&gt;

Mechanical stability indicators derived from detailed snow cover simulations

2021 ◽  
Author(s):  
Léo Viallon-Galinier ◽  
Pascal Hagenmuller ◽  
Nicolas Eckert ◽  
Benjamin Reuter
Keyword(s):  
Mechanical Properties ◽  
Snow Cover ◽  
Mechanical Stability ◽  
Weather Forecasting ◽  
Large Data ◽  
Failure Initiation ◽  
Avalanche Hazard ◽  
Snow Stratigraphy ◽  
Numerical Weather Forecasting ◽  
Numerical Tools

&lt;p&gt;The use of numerical modeling of the snow cover in support of avalanche hazard forecasting has been increasing in the last decade. Besides field observations and numerical weather forecasting, these numerical tools provide information otherwise unavailable on the present and future state of the snow cover. In order to provide useful input for avalanche hazard assessment, different mechanical stability indicators are typically computed from simulated snow stratigraphy. Such indicators condense the wealth of information produced by snow cover models, especially when dealing with large data (e.g., large domains, high spatial resolution, ensemble forecasting). Here, we provide an overview of such indicators. Mechanical stability indicators can be classified in two types i.e., whether they are solely based on mechanical rules or whether they include additional expert rules. These indicators span different mechanical processes involved in avalanche release: failure initiation and crack propagation, for instance. The indicators rely on mechanical properties of each layer. We discuss parameterizations of mechanical properties and the associated technical implementation details. We show simplified examples of snow stratigraphy to illustrate the benefit of different stability indicators in typical situations. There is no perfect indicator to describe the instability for any situation. All indicators are sensitive to the snow cover modeling assumptions and the computation of mechanical properties and hence, require some tuning before operational use. In practice, a combination of indicators should be considered to capture the variety of avalanche situations.&lt;/p&gt;

Verification and Case Studies for Urban Effects in HIRLAM Numerical Weather Forecasting

2009 ◽  
pp. 143-150 ◽  
Author(s):  
Alexander Mahura ◽  
Alexander Baklanov ◽  
Claus Petersen ◽  
Niels W. Nielsen ◽  
Bjarne Amstrup
Keyword(s):  
Case Studies ◽  
Weather Forecasting ◽  
Numerical Weather ◽  
Numerical Weather Forecasting ◽  
Urban Effects

scholarly journals Skill prediction of local weather forecasts based on the ECMWF ensemble

2001 ◽  
Vol 8 (6) ◽  
pp. 419-428 ◽  
Author(s):  
C. Ziehmann
Keyword(s):  
Weather Forecasting ◽  
A Priori ◽  
A Priori Estimate ◽  
Ensemble Prediction ◽  
Ensemble Forecasts ◽  
Data Set ◽  
Weather Forecasts ◽  
Numerical Weather Forecasting ◽  
Similar Good ◽  
Local Weather

Abstract. Ensemble Prediction has become an essential part of numerical weather forecasting. In this paper we investigate the ability of ensemble forecasts to provide an a priori estimate of the expected forecast skill. Several quantities derived from the local ensemble distribution are investigated for a two year data set of European Centre for Medium-Range Weather Forecasts (ECMWF) temperature and wind speed ensemble forecasts at 30 German stations. The results indicate that the population of the ensemble mode provides useful information for the uncertainty in temperature forecasts. The ensemble entropy is a similar good measure. This is not true for the spread if it is simply calculated as the variance of the ensemble members with respect to the ensemble mean. The number of clusters in the C regions is almost unrelated to the local skill. For wind forecasts, the results are less promising.

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