Search

Potential for regional climate engineering is gaining interest as a means of solving regional environmental problems like water scarcity and high temperatures. In the hyper-arid United Arab Emirates (UAE), water scarcity is reaching a crisis point due to high consumption and over-extraction and is being exacerbated by climate change. To counteract this problem, the UAE has conducted cloud-seeding operations and intensive desalination for many years but is now considering other means of increasing water resources. Very large "artificial black surfaces" (ABSs), made of black mesh, black-painted, or solar photovoltaic (PV) panels have been proposed as a means of enhancing convective precipitation via surface heating and amplification of vertical motion. Under the influence of the daily UAE sea breeze, this can lead to convection initiation under the right conditions. Currently it is not known how strong this rainfall enhancement would be or what scale of black surface would need to be employed. This study simulates the impacts at different ABS scales using the WRF-Noah-MP model chain and investigates impacts on precipitation quantities and underlying convective processes. Simulations of five square ABSs of 10, 20, 30, 40, and 50 km sizes were made on four 1 d cases, each for a period of 24 h. These were compared with a Control model run, with no land use change, to quantify impacts. The ABSs themselves were simulated by altering land cover static data and prescribing a unique set of land surface parameters like albedo and roughness length. On all 4 d, rainfall is enhanced by low-albedo surfaces of 20 km or larger, primarily through a reduction of convection inhibition and production of convergence lines and buoyant updrafts. The 10 km square ABS had very little impact. From 20 km upwards there is a strong scale dependency, with ABS size influencing the strength of convective processes and volume of rainfall. In terms of rainfall increases, 20 km produces a mean rainfall increase over the Control simulation of 571 616 m 3 d -1 , with the other sizes as follows: 30 km (∼ 1 million m 3 d -1), 40 km (∼ 1.5 million m 3 d -1), and 50 km (∼ 2.3 million m 3 d -1). If we assume that such rainfall events happen only on 10 d in a year, this would equate to respective annual water supplies for > 31 000, > 50 000, > 79 000, and > 125 000 extra people yr -1 at UAE per capita consumption rates. Thus, artificial heat islands made from black panels or solar PV offer a means of enhancing rainfall in arid regions like the UAE and should be made a high priority for further research. [ABSTRACT FROM AUTHOR]

Potential for regional climate engineering is gaining interest as a means of solving regional environmental problems like water scarcity and high temperatures. In the hyper-arid United Arab Emirates (UAE), water scarcity is reaching crisis point due to high consumption and over-extraction, and is exacerbated further with climate change. To counteract this problem, the UAE has conducted cloud seeding operations and intensive desalination for many years, but is now considering other means of increasing water resources. Very large 'Artificial Black Surfaces' (ABS), made of black mesh/black painted/solar PV panels have been proposed as a means of enhancing convective precipitation, via surface heating and amplification of vertical motion. Under the influence of the daily UAE sea breeze, this can lead to convection initiation under the right conditions. Currently it is not known how strong this rainfall enhancement would be, nor what scale of black surface would need to be employed. This study simulates the impacts at different ABS scales using the WRF-NoahMP model chain and investigates impacts on precipitation quantities and underlying convective processes. Simulations of five square ABS of 10, 20, 30, 40, and 50 km sizes were made on four one-day cases over a 24-hour period. These were compared with a Control model run, with no land use change, to quantify impacts. The ABS themselves were simulated by altering land cover static data, and prescribing a unique set of land surface parameters like albedo and roughness length. On all four days, rainfall is enhanced by low-albedo surfaces of 20 km or larger, primarily through a reduction of convection inhibition and production of convergence lines and buoyant updrafts. The 10 km square ABS had very little impact. From 20 km upwards there is a strong scale-dependency, with ABS size influencing the strength of convective processes and volume of rainfall. In terms of rainfall increases, the 20 km produces a mean rainfall increase, over the Control simulation, of 571,616 m3 day-1, 30 km (~1 mil. m3 day-1), 40 km (~1.5 mil. m3 day-1), and 50 km (~ 2.3 mil. m3 day-1). If we assume that such rainfall events happen only in 10 days in a year, this would equate to respective annual water supplies for >31,000, >50,000, >79,000, and >125,000 extra people yr-1, at UAE per capita consumption rates. Thus, artificial heat islands made from black panels or solar PV offer a means of enhancing rainfall in arid regions like the UAE, and should be made a high priority for further research. [ABSTRACT FROM AUTHOR]

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 (TD 2 m), and 10 m wind speed (UV 10 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 TD 2 m , with mean biases mostly ≤ 1 ∘ C. TD 2 m over the marine region is overestimated, though (0.75–1 ∘ C), and nocturnal mountain TD 2 m is underestimated (∼-2 ∘ C). UV 10 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. UV 10 m is better simulated in the marine region (bias ≤ 1 m s -1). There is an apparent relationship between T2 m bias and UV 10 m bias, which may indicate issues in simulation of the daytime sea breeze. TD 2 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this study, we present a five‐member Weather Research and Forecasting (WRF) physics ensemble over the Arabian Peninsula on the convection‐permitting (CP) scale and investigate the ability to simulate convection and precipitation by varying the applied cloud microphysics and planetary boundary layer (PBL) parametrizations. The study covers a typical precipitation event ocurring during summertime over the eastern part of the United Arab Emirates (UAE). Our results show that the best results are obtained by using water‐ and ice‐friendly aerosols combined with aerosol‐aware Thompson cloud microphysics and the Mellor‐Yamada‐Nakanishi‐Niino (MYNN) PBL parametrization. The diurnal cycle of 2‐m temperature over the desert is well captured by all members, although a cold bias is present during the morning and evening transition. All members are capable of simulating the correct timing of the onset of convection. Simulations with the MYNN PBL and Thompson scheme produce the highest convective available potential energy (CAPE) and convective inhibition (CIN), associated with stronger mixing inside the PBL, leading to the formation of more dense liquid water clouds. The WDM6 microphysics scheme is not a suitable option, as there are hardly any liquid water clouds; mainly ice clouds are simulated. Precipitation is best captured by applying the MYNN and Thomspon scheme. Although the ensemble size is relatively small, this allows for the provision of cloud probability maps suitable for cloud‐seeding applications. [ABSTRACT FROM AUTHOR]

This study investigates an extreme weather event that impacted the United Arab Emirates (UAE) in March 2016, using the Weather Research and Forecasting (WRF) model version 3.7.1 coupled with its hydrological modeling extension package (WRF-Hydro). Six-hourly forecasted forcing records at 0.5 ∘ spatial resolution, obtained from the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS), are used to drive the three nested downscaling domains of both standalone WRF and coupled WRF–WRF-Hydro configurations for the recent flood-triggering storm. Ground and satellite observations over the UAE are employed to validate the model results. The model performance was assessed using precipitation from the Global Precipitation Measurement (GPM) mission (30 min, 0.1 ∘ product), soil moisture from the Advanced Microwave Scanning Radiometer 2 (AMSR2; daily, 0.1 ∘ product) and the NOAA Soil Moisture Operational Products System (SMOPS; 6-hourly, 0.25 ∘ product), and cloud fraction retrievals from the Moderate Resolution Imaging Spectroradiometer Atmosphere product (MODATM; daily, 5 km product). The Pearson correlation coefficient (PCC), relative bias (rBIAS), and root-mean-square error (RMSE) are used as performance measures. Results show reductions of 24 % and 13 % in RMSE and rBIAS measures, respectively, in precipitation forecasts from the coupled WRF–WRF-Hydro model configuration, when compared to standalone WRF. The coupled system also shows improvements in global radiation forecasts, with reductions of 45 % and 12 % for RMSE and rBIAS, respectively. Moreover, WRF-Hydro was able to simulate the spatial distribution of soil moisture reasonably well across the study domain when compared to AMSR2-derived soil moisture estimates, despite a noticeable dry and wet bias in areas where soil moisture is high and low. Temporal and spatial variabilities of simulated soil moisture compare well to estimates from the NOAA SMOPS product, which indicates the model's capability to simulate surface drainage. Finally, the coupled model showed a shallower planetary boundary layer (PBL) compared to the standalone WRF simulation, which is attributed to the effect of soil moisture feedback. The demonstrated improvement, at the local scale, implies that WRF-Hydro coupling may enhance hydrological and meteorological forecasts in hyper-arid environments. [ABSTRACT FROM AUTHOR]

This study investigates an extreme weather event that impacted the United Arab Emirates (UAE) in March 2016 using the Weather Research and Forecasting (WRF) model version 3.7.1 coupled with its hydrological modeling extension package (Hydro). Six-hourly forecasted forcing records at 0.5o spatial resolution, obtained from the NCEP Global Forecast System (GFS), are used to drive the three nested downscaling domains of both standalone WRF and coupled WRF/WRF-Hydro configurations for the recent flood-triggering storm. Ground and satellite observations over the UAE are employed to validate the model results. Precipitation, soil moisture, and cloud fraction retrievals from GPM (30-minute, 0.1o product), AMSR2 (daily, 0.1o product), and MODIS (daily, 5 km product), respectively, are used to assess the model output. The Pearson correlation coefficient (PCC), relative bias (rBIAS) and root-mean-square error (RMSE) are used as performance measures. Results show reductions of 24 % and 13 % in RMSE and rBIAS measures, respectively, in precipitation forecasts from the coupled WRF/WRF-Hydro model configuration, when compared to standalone WRF. The coupled system also shows improvements in global radiation forecasts, with reductions of 45 % and 12 % for RMSE and rBIAS, respectively. Moreover, WRF-Hydro was able to simulate the spatial distribution of soil moisture reasonably well across the study domain when compared to AMSR2 satellite soil moisture estimates, despite a noticeable dry/wet bias in areas where soil moisture is high/low. The demonstrated improvement, at the local scale, implies that WRF-Hydro coupling may enhance hydrologic forecasts and flash flood guidance systems in the region. [ABSTRACT FROM AUTHOR]