scholarly journals The Use of Weather Research and Forecasting Model to Predict Rainfall in Tropical Peatland: 1. Model Parameterization

Agromet ◽  
2021 ◽  
Vol 35 (1) ◽  
pp. 49-59
Author(s):  
Alfi Rizky Sanusi ◽  
Muh Taufik ◽  
I Putu Santikayasa
Keyword(s):  
Wrf Model ◽  
Longwave Radiation ◽  
Vital Role ◽  
Rainfall Data ◽  
Shortwave Radiation ◽  
Weather Data ◽  
Rainfall Forecasting ◽  
Maritime Continent ◽  
Tropical Peatland ◽  
Cloud Parameters

Rainfall dynamics play a vital role in tropical peatland by providing sufficient water to keep peat moist throughout the year. Therefore, information of rainfall data either historical or forecasting data has risen in recent decades especially for an alert system of fire. Here the Weather and Research Forecasting (WRF) model may act as a tool to provide forecasting weather data. This study aims to do parameterization on WRF parameters for peatland in Sumatra, and to perform bias correction on the WRF’s rainfall output with observed data. We performed stepwise calibration to choose the best five physical schemes of WRF for use in the study area. The output WRF’s rainfall was bias corrected by spatially observed rainfall data for 2019 at day resolution. Our results showed the following schemes namely (i) Eta scheme for cloud microphysical parameters; (ii) GD scheme for cumulus cloud parameters, (iii) MYJ scheme for planetary boundary layer parameters; (iv) RRTM for longwave radiation; and (v) New Goddard schemes for shortwave radiation are best combination for being used to predict rainfall in maritime continent. The spatially interpolated observed rainfall with the Inverse Distance Weighting (IDW) was outperformed for calibration process of WRF’s rainfall as shown by statistical indicators used in this study. Further, the findings have contributed to advance knowledge of rainfall forecasting in maritime continent, particularly in providing data to support the development of fire danger rating system for Indonesian peatland.

scholarly journals Optimization of Noah and Noah_MP WRF Land Surface Schemes in Snow-Melting Conditions over Complex Terrain

2017 ◽  
Vol 145 (12) ◽  
pp. 4727-4745 ◽  
Author(s):  
Elena Tomasi ◽  
Lorenzo Giovannini ◽  
Dino Zardi ◽  
Massimiliano de Franceschi
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Winter Season ◽  
Wrf Model ◽  
Longwave Radiation ◽  
Shortwave Radiation ◽  
Land Use Classification ◽  
Near Surface ◽  
Thermal Inversion ◽  
Alpine Valley

The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions in a typical Alpine valley. Accordingly, model results are compared against data collected during an intensive field campaign performed in the Adige Valley, in the eastern Italian Alps. In particular, the ability of the model in reproducing the time evolution of 2-m temperature and of incoming and outgoing shortwave and longwave radiation is examined. The validation of model results highlights that, in this context, WRF reproduces rather poorly near-surface temperature over snow-covered terrain, with an evident underestimation, during both daytime and nighttime. Furthermore it fails to capture specific atmospheric processes, such as the temporal evolution of the ground-based thermal inversion. The main cause of these errors lies in the miscalculation of the mean gridcell albedo, resulting in an inaccurate estimate of the reflected solar radiation calculated by both Noah and Noah_MP. Therefore, modifications to the initialization, to the land-use classification, and to both land surface models are performed to improve model results, by intervening in the calculation of the albedo, of the snow cover, and of the surface temperature. Qualitative and quantitative analyses show that, after these changes, a significant improvement in the comparability between model results and observations is achieved. In particular, outgoing shortwave radiation is lowered, 2-m temperature maxima increased accordingly, and ground-based thermal inversions are better captured.

scholarly journals Association Rule Mining For South West Monsoon Rainfall Prediction and Estimation over Mumbai Station

2019 ◽  
Vol 8 (3) ◽  
pp. 4490-4493
Keyword(s):  
Weather Prediction ◽  
Heavy Rain ◽  
Vital Role ◽  
Weather Data ◽  
Rainfall Forecasting ◽  
Rainfall Prediction ◽  
South West ◽  
South West Monsoon ◽  
Agricultural Yield ◽  
West Monsoon

Rainfall is important for agricultural yield and hence early prediction is required. It has a vital role in the improving the economy of a country. Accurate and timely weather prediction for rainfall forecasting has been one of the most challenging problems around the world as it changes the physical characteristics of the hydrologic system. Rainfall prediction model involves observation of weather data, deriving knowledge from it and implementing using computer models. The proposed work observed rainfall during south-west monsoon months of Mumbai (Latitude 19.0760°N / Longitude 72.8777°E) city. Predictive Apriori Algorithm was used to derive association rules for spot prediction, 24 hours ahead prediction and 48 hours ahead prediction, also to estimate a no rain day, moderate rain day and heavy rain day.

scholarly journals An Evaluation of Surface Atmospheric Changes over the Arctic Ocean for 2000–09 Using Recent Reanalyses

2015 ◽  
Vol 19 (2) ◽  
pp. 1-18 ◽  
Author(s):  
Ayan H. Chaudhuri ◽  
Rui M. Ponte
Keyword(s):  
Arctic Ocean ◽  
Extreme Event ◽  
Longwave Radiation ◽  
Remotely Sensed ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Near Surface ◽  
The Arctic Ocean ◽  
Ice Retreat

Abstract The authors examine five recent reanalysis products [NCEP Climate Forecast System Reanalysis (CFSR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), Japanese 25-year Reanalysis Project (JRA-25), Interim ECMWF Re-Analysis (ERA-Interim), and Arctic System Reanalysis (ASR)] for 1) trends in near-surface radiation fluxes, air temperature, and humidity, which are important indicators of changes within the Arctic Ocean and also influence sea ice and ocean conditions, and 2) fidelity of these atmospheric fields and effects for an extreme event: namely, the 2007 ice retreat. An analysis of trends over the Arctic for the past decade (2000–09) shows that reanalysis solutions have large spreads, particularly for downwelling shortwave radiation. In many cases, the differences in significant trends between the five reanalysis products are comparable to the estimated trend within a particular product. These discrepancies make it difficult to establish a consensus on likely changes occurring in the Arctic solely based on results from reanalyses fields. Regarding the 2007 ice retreat event, comparisons with remotely sensed estimates of downwelling radiation observations against these reanalysis products present an ambiguity. Remotely sensed observations from a study cited herewith suggest a large increase in downwelling summertime shortwave radiation and decrease in downwelling summertime longwave radiation from 2006 and 2007. On the contrary, the reanalysis products show only small gains in summertime shortwave radiation, if any; however, all the products show increases in downwelling longwave radiation. Thus, agreement within reanalysis fields needs to be further checked against observations to assess possible biases common to all products.

scholarly journals Simulation of Thermodynamic Features of a Thunderstorm Event over Dhaka using WRF-ARW Model

2018 ◽  
Vol 37 ◽  
pp. 131-145
Author(s):  
Md Mijanur Rahman ◽  
Md Abdus Samad ◽  
SM Quamrul Hassan
Keyword(s):  
Convective Available Potential Energy ◽  
Model Performance ◽  
Vertical Wind Shear ◽  
Longwave Radiation ◽  
Final Analysis ◽  
Horizontal Resolution ◽  
Cumulus Parameterization ◽  
Shortwave Radiation ◽  
Radiative Transfer Model ◽  
Transfer Model

An attempt has been made to simulate the thermodynamic features of the thunderstorm (TS) event over Dhaka (23.81°N, 90.41°E) occurred from 1300 UTC to 1320 UTC of 4 April 2015 using Advanced Research dynamics solver of Weather Research and Forecasting model (WRF-ARW). The model was run to conduct a simulation for 48 hours on a single domain of 5 km horizontal resolution utilizing six hourly Global Final Analysis (FNL) datasets from 0600 UTC of 3 April 2015 to 0600 UTC of 5 April 2015 as initial and lateral boundary conditions. Kessler schemes for microphysics, Yonsei University (YSU) scheme for planetary boundary layer (PBL) parametrization, Revised MM5 scheme for surface layer physics, Rapid Radiative Transfer Model (RRTM) for longwave radiation, Dudhia scheme for shortwave radiation and Kain–Fritsch (KF) scheme for cumulus parameterization were used. Hourly outputs produced by the model have been analyzed numerically and graphically using Grid Analysis and Display System (GrADS). Deep analyses were carried out by examining several thermodynamic parameters such as mean sea level pressure (MSLP), wind pattern, vertical wind shear, vorticity, temperature, convective available potential energy (CAPE), relative humidity (RH) and rainfall. To validate the model performance, simulated values of MSLP, maximum and minimum temperature and RH were compared with observational data obtained from Bangladesh Meteorological Department (BMD). Rainfall values were compared with that of BMD and Tropical Rainfall Measuring Mission (TRMM) of National Aeronautics and Space Administration (NASA). Based on the comparisons and validations, the present study advocates that the model captured the TS event reasonably well.GANIT J. Bangladesh Math. Soc.Vol. 37 (2017) 131-145

scholarly journals Combinational Optimization of the WRF Physical Parameterization Schemes to Improve Numerical Sea Breeze Prediction Using Micro-Genetic Algorithm

2021 ◽  
Vol 11 (23) ◽  
pp. 11221
Author(s):  
Ji Won Yoon ◽  
Sujeong Lim ◽  
Seon Ki Park
Keyword(s):  
Genetic Algorithm ◽  
Wind Speed ◽  
Land Surface ◽  
Wrf Model ◽  
Longwave Radiation ◽  
Sea Breeze ◽  
Meteorological Variables ◽  
Parameterization Schemes ◽  
Micro Genetic Algorithm ◽  
Physical Parameterization

This study aims to improve the performance of the Weather Research and Forecasting (WRF) model in the sea breeze circulation using the micro-Genetic Algorithm (micro-GA). We found the optimal combination of four physical parameterization schemes related to the sea breeze system, including planetary boundary layer (PBL), land surface, shortwave radiation, and longwave radiation, in the WRF model coupled with the micro-GA (WRF-μGA system). The optimization was performed with respect to surface meteorological variables (2 m temperature, 2 m relative humidity, 10 m wind speed and direction) and a vertical wind profile (wind speed and direction), simultaneously for three sea breeze cases over the northeastern coast of South Korea. The optimized set of parameterization schemes out of the WRF-μGA system includes the Mellor–Yamada–Nakanishi–Niino level-2.5 (MYNN2) for PBL, the Noah land surface model with multiple parameterization options (Noah-MP) for land surface, and the Rapid Radiative Transfer Model for GCMs (RRTMG) for both shortwave and longwave radiation. The optimized set compared with the various other sets of parameterization schemes for the sea breeze circulations showed up to 29 % for the improvement ratio in terms of the normalized RMSE considering all meteorological variables.

scholarly journals Estimation of Net Radiation using satellite based data inputs

2014 ◽  
Vol XL-8 ◽  
pp. 307-313 ◽  
Author(s):  
S. V. S. Sai Krishna ◽  
P. Manavalan ◽  
P. V. N. Rao
Keyword(s):  
Outgoing Longwave Radiation ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Shortwave Radiation ◽  
Net Radiation ◽  
Clear Sky ◽  
Statistical Measures ◽  
Indian Land ◽  
Radiation Fluxes

Daily net surface radiation fluxes are estimated for Indian land mass at spatial grid intervals of 0.1 degree. Two approaches are employed to obtain daily net radiation for four sample days viz., November 19, 2013, December 16, 2013, January 8, 2014 and March 20, 2014. Both the approaches compute net shortwave and net longwave fluxes, separately and sum them up to obtain net radiation. The first approach computes net shortwave radiation using daily insolation product of Kalpana VHRR and 15 days time composited broadband albedo product of Oceansat OCM2. The net outgoing longwave radiation is computed using Stefan Boltzmann equation corrected for humidity and cloudiness. In the second approach, instantaneous clear-sky net-shortwave radiation is estimated using computed clear-sky incoming shortwave radiation and the gridded MODIS 16-day time composited albedo product. The net longwave radiation is obtained by estimating outgoing and incoming longwave radiation fluxes, independently. In this, MODIS derived surface emissivity and skin temperature parameters are used for estimating outgoing longwave radiation component. In both the approaches, surface air temperature data required for estimation of net longwave radiation fluxes are extracted from India Meteorological Department’s (IMD) Automatic Weather Station (AWS) records. Estimates by the two different approaches are evaluated by comparing daily net radiation fluxes with CERES based estimates corresponding to the sample days, through statistical measures. The estimated all sky daily net radiation using the first approach compared well with CERES SYN1deg daily average net radiation with r<sup>2</sup> values of the order of 0.7 and RMS errors of the order of 8&ndash;16 w/m<sup>2</sup>.

scholarly journals Effects of clouds on surface melting of Laohugou glacier No. 12, western Qilian Mountains, China

2018 ◽  
Vol 64 (243) ◽  
pp. 89-99 ◽  
Author(s):  
JIZU CHEN ◽  
XIANG QIN ◽  
SHICHANG KANG ◽  
WENTAO DU ◽  
WEIJUN SUN ◽  
...  
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Meteorological Data ◽  
Water Vapor Pressure ◽  
Longwave Radiation ◽  
Turbulent Heat Flux ◽  
Qilian Mountains ◽  
Shortwave Radiation ◽  
Turbulent Heat ◽  
Glacier Melt

ABSTRACTWe analyzed a 2-year time series of meteorological data (January 2011–December 2012) from three automatic weather stations on Laohugou glacier No. 12, western Qilian Mountains, China. Air temperature, humidity and incoming radiation were significantly correlated between the three sites, while wind speed and direction were not. In this work, we focus on the effects of clouds on other meteorological parameters and on glacier melt. On an average, ~18% of top-of-atmosphere shortwave radiation was attenuated by the clear-sky atmosphere, and clouds attenuated a further 12%. Most of the time the monthly average increases in net longwave radiation caused by clouds were larger than decreases in net shortwave radiation but there was a tendency to lose energy during the daytime when melting was most intense. Air temperature and wind speed related to turbulent heat flux were found to suppress glacier melt during cloudy periods, while increased water vapor pressure during cloudy days could enhance glacier melt by reducing energy loss by latent heat. From these results, we have increased the physical understanding of the significance of cloud effects on continental glaciers.

scholarly journals Evaluation of Upper Indus Near-Surface Climate Representation by WRF in the High Asia Refined Analysis

2019 ◽  
Vol 20 (3) ◽  
pp. 467-487 ◽  
Author(s):  
David M. W. Pritchard ◽  
Nathan Forsythe ◽  
Hayley J. Fowler ◽  
Greg M. O’Donnell ◽  
Xiao-Feng Li
Keyword(s):  
Regional Climate ◽  
Critical Role ◽  
Critical Evaluation ◽  
Longwave Radiation ◽  
Indus Basin ◽  
Shortwave Radiation ◽  
Cold Bias ◽  
Near Surface ◽  
High Asia ◽  
High Bias

Abstract Data paucity is a severe barrier to the characterization of Himalayan near-surface climates. Regional climate modeling can help to fill this gap, but the resulting data products need critical evaluation before use. This study aims to extend the appraisal of one such dataset, the High Asia Refined Analysis (HAR). Focusing on the upper Indus basin (UIB), the climatologies of variables needed for process-based hydrological and cryospheric modeling are evaluated, leading to three main conclusions. First, precipitation in the 10-km HAR product shows reasonable correspondence with most in situ measurements. It is also generally consistent with observed runoff, while additionally reproducing the UIB’s strong vertical precipitation gradients. Second, the HAR shows seasonally varying bias patterns. A cold bias in temperature peaks in spring but reduces in summer, at which time the high bias in relative humidity diminishes. These patterns are concurrent with summer overestimation (underestimation) of incoming shortwave (longwave) radiation. Finally, these seasonally varying biases are partly related to deficiencies in cloud, snow, and albedo representations. In particular, insufficient cloud cover in summer leads to the overestimation of incoming shortwave radiation. This contributes to the reduced cold bias in summer by enhancing surface warming. A persistent high bias in albedo also plays a critical role, particularly by suppressing surface heating in spring. Improving representations of cloud, snow cover, and albedo, and thus their coupling with seasonal climate transitions, would therefore help build upon the considerable potential shown by the HAR to fill a vital data gap in this immensely important basin.

scholarly journals Reconnaissance Study of glacier energy balance in North Greenland, 1993–94

1998 ◽  
Vol 44 (147) ◽  
pp. 239-247 ◽  
Author(s):  
Roger J. Braithwaite ◽  
Thomas Konzelmann ◽  
Christoph Marty ◽  
Ole B. Olesen
Keyword(s):  
Energy Balance ◽  
Field Experiments ◽  
Longwave Radiation ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Balance Model ◽  
Conductive Heat ◽  
Glacier Surface ◽  
West Greenland ◽  
North Greenland

AbstractReconnaissance energy-balance studies were made for the first time at two sites in North Greenland to compare with conditions in West Greenland. The field experiments were planned to save weight because it is expensive to operate in North Greenland. The larger energy components (incoming radiation and ablation) were measured for 55 days altogether, and the smaller components were evaluated by indirect methods, e.g. turbulent fluxes are calculated from air temperature, humidity and wind speed, to save the weight of instruments. The energy-balance model is “tuned" by choosing surface roughness and albedo to reduce the mean error between measured ablation and modelled daily melting. The error standard deviation for ablation is only ± 5 kg m−2d−1’, which is much lower than found in West Greenland, due to better instruments and modelling in the present study. Net radiation is the main energy source for melting in North Greenland but ablation is relatively low because sublimation and conductive-heat fluxes use energy that would otherwise be available for melting. There is a strong diurnal variation in ablation, mainly forced by variations in shortwave radiation and reinforced by nocturnal cooling of the ice surface by outgoing longwave radiation and sublimation. The model frequently predicts a frozen glacier surface at night even when air temperatures are positive.

Spring Arctic Atmospheric Preconditioning: Do Not Rule Out Shortwave Radiation Just Yet

2018 ◽  
Vol 31 (11) ◽  
pp. 4225-4240 ◽  
Author(s):  
Joseph Sedlar
Keyword(s):  
Sea Ice ◽  
Surface Albedo ◽  
Atmospheric Transport ◽  
High Surface ◽  
Longwave Radiation ◽  
Absolute Magnitude ◽  
Arctic Sea Ice ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Ice Melt

Abstract Springtime atmospheric preconditioning of Arctic sea ice for enhanced or buffered sea ice melt during the subsequent melt year has received considerable research focus. Studies have identified enhanced poleward atmospheric transport of moisture and heat during spring, leading to increased emission of longwave radiation to the surface. Simultaneously, these studies ruled out the role of shortwave radiation as an effective preconditioning mechanism because of relatively weak incident solar radiation, high surface albedo from sea ice and snow, and increased clouds during spring. These conclusions are derived primarily from atmospheric reanalysis, which may not always accurately represent the Arctic climate system. Here, top-of-atmosphere shortwave radiation observations from a state-of-the-art satellite sensor are compared with ERA-Interim reanalysis to examine similarities and differences in the springtime absorbed shortwave radiation (ASR) over the Arctic Ocean. Distinct biases in regional location and absolute magnitude of ASR anomalies are found between satellite-based measurements and reanalysis. Observations indicate separability between ASR anomalies in spring corresponding to anomalously low and high ice extents in September; the reanalysis fails to capture the full extent of this separability. The causes for the difference in ASR anomalies between observations and reanalysis are considered in terms of the variability in surface albedo and cloud presence. Additionally, biases in reanalysis cloud water during spring are presented and are considered for their impact on overestimating spring downwelling longwave anomalies. Taken together, shortwave radiation should not be overlooked as a contributing mechanism to springtime Arctic atmospheric preconditioning.

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