Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction

2020 ◽  
Author(s):  
Diarra Dieng ◽  
Cornelius Hald ◽  
Patrick Laux ◽  
Christof Lorenz ◽  
Harald Kunstmann
Keyword(s):  
High Resolution ◽  
West Africa ◽  
Water Availability ◽  
Bias Correction ◽  
Wrf Model ◽  
Correction Method ◽  
Dew Point ◽  
Limited Area ◽  
Wide Range ◽  
Institute Of Technology

<p><strong>Future water availability in West Africa: Estimates from high-resolution RCM modeling and multivariate bias correction </strong></p><p>Diarra Dieng<sup>1</sup>, Cornelius Hald<sup>1</sup>, Patrick Laux<sup>1,2</sup>, Christof Lorenz<sup>1</sup>, Harald Kunstmann<sup>1,2</sup></p><p><sup>1</sup>Institute of Meteorology and Climate Research (IMK-IFU), Campus Alpine, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany,</p><p><sup>2</sup>Institute of Geography, University of Augsburg, Augsburg, Germany,</p><p> </p><p>With a wide range of ecological, climatic, and cultural diversities, West Africa is a rapidly developing region whose agricultural systems remain largely rain-fed and underdeveloped. In this study we examine the potential impacts of climate variability and climate change on the water availability in the mid-21st century in West 
Africa by using high resolution simulations (12km) from the Weather and Research Forecasting (WRF) model and the COSMO-Climate Limited area Modelling (CCLM) for the RCP 4.5 scenario. Our approach is based on the simplified Penman-Monteith (PM) equation for daily ET, which requires the joint information on relative humidity, maximum and minimum daily temperatures, dew point temperature, solar radiation and wind speed. It is not only crucial that the statistical behavior of these modelled variables is close to observations, but also that the interplay between these variables is realistic. We therefore further adapted, applied and analyzed a subsequent bias-correction method for the WRF and CCLM simulations using a nonparametric, trend-preserving quantile mapping approach and a multivariate bias correction approach (MBCn). We present the details of the method and the derived implications for expected water availability in West Africa.</p>

Non-reasonable but efficient use of schemes in current model to improve realistic explicit convection modelling

2020 ◽  
Author(s):  
christophe messager ◽  
marc honnorat
Keyword(s):  
High Resolution ◽  
Current Model ◽  
Wrf Model ◽  
Region Of Interest ◽  
Limited Area ◽  
Operational Mode ◽  
Model Framework ◽  
Large Eddy Simulation Model ◽  
Weather Model ◽  
Daily Forecast

<p>There is actually no limitation of current high-resolution weather model for producing simulation and forecast of convection at kilometer and infra-kilometer horizontal resolutions. However, the disappointing results as well as the associated huge amount of computer resources required may lead to focus on Large Eddy Simulation model instead. However, the use of LES is not trivial and required a long and non-portable adjustment over the region of interest. Also, it is difficult to use in operational mode for daily forecast since they require specific inputs.</p><p>In the other side, pushing the current regional or Limited Area Model towards very high resolution is a convenient way to reach explicit resolution of convective process for instance. However, an explicit simulation is not a guarantee of a realistic result mainly due to the fact that initial condition is crucial as well as all other descriptions of the environment (soil, vegetation, sst, etc) and use of correct parameterization schemes.</p><p>For instance, within the WRF model framework, one can identify more than 4000 set of parameterizations plus all the scheme adjustments and threshold associated to.</p><p>However, a physically based analyze of what it is necessary for a realistic and explicit convection simulation may conduct a physicist user to define its “ideal” physics with what it already exists in the model. It may conduct to so-called unrealistic model requests in term of computation requirement regarding the radiative, the turbulence and the microphysics schemes but it does works with HPC systems. This kind of parameterization will be presented here and used with a very realistic vertical circulation into convective systems with convective updraft and downdraft modelling, from few meters up to several kilometers height.</p>

scholarly journals Precipitation bias correction of very high resolution regional climate models

2013 ◽  
Vol 10 (6) ◽  
pp. 8145-8165 ◽  
Author(s):  
D. Argüeso ◽  
J. P. Evans ◽  
L. Fita
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Correction Method ◽  
Accurate Information ◽  
Recent Climate ◽  
Resolution Model ◽  
High Resolution Model

Abstract. Regional climate models are prone to biases in precipitation that are problematic for use in impact models such as hydrology models. A large number of methods have already been proposed aimed at correcting various moments of the rainfall distribution. They all require that the model produce the same or a higher number of rain days than the observational datasets, which are usually gridded datasets. Models have traditionally met this condition because their spatial resolution was coarser than the observational grids. But recent climate simulations use higher resolution than the gridded observational products and the models are likely to produce fewer rain days than the gridded observations. In this study, model output from a simulation at 2 km resolution are compared with gridded and in-situ observational datasets to determine whether the new scenario calls for revised methodologies. The gridded observations are found to be inadequate to correct the high-resolution model at daily timescales. A histogram equalisation bias correction method is selected and adapted to the use of stations, alleviating the problems associated with relatively low-resolution observational grids. The method is efficient at bias correcting both seasonal and daily characteristics of precipitation, providing more accurate information that is crucial for impact assessment studies.

scholarly journals High-Resolution Regional Climate Modeling and Projection over Western Canada using a Weather Research Forecasting Model with a Pseudo-Global Warming Approach

2019 ◽  
Author(s):  
Yanping Li ◽  
Zhenhua Li ◽  
Zhe Zhang ◽  
Liang Chen ◽  
Sopan Kurkute ◽  
...  
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
Water Availability ◽  
Bias Correction ◽  
Summer Precipitation ◽  
Precipitation Intensity ◽  
Western Canada ◽  
Canadian Rockies ◽  
Canadian Prairies ◽  
Precipitation Events

Abstract. To assess the hydroclimatic risks posed by climate change in western Canada, this study conducted a retrospective simulation (CTL) and a pseudo-global warming (PGW) dynamical downscaling of future warming projection under RCP8.5 from an ensemble of CMIP5 climate model projections using a convection-permitting 4-km Weather Research Forecasting (WRF) model. The convection-permitting resolution of the model avoids the error-prone convection parameterization by explicitly resolving cumulus plumes. The evaluation of surface air temperature by the retrospective simulation WRF-CTL against a gridded observation ANUSPLIN shows that WRF simulation of daily mean temperature agrees well with ANUSPLIN temperature in terms of the geographical distribution of cold biases east of the Canadian Rockies, especially in spring. Compared with the observed precipitation from ANUSPLIN and CaPA, the WRF-CTL simulation captures the main pattern of distribution, but with a wet bias seen in higher precipitation near the British Columbia coast in winter and over the immediate region on the lee side of the Canadian Rockies. The PGW simulation shows more warming than CTL, especially over the polar region in the northeast, during the cold season, and in daily minimum temperature. Precipitation changes in PGW over CTL vary with the seasons: In spring and late fall for both basins, precipitation is shown to increase, whereas in summer in the Saskatchewan River Basin, it either shows no increase or decreases, with less summer precipitation shown in PGW than in CTL for some parts of the Prairies. This seasonal difference in precipitation change suggests that in summer the Canadian Prairies and the southern Boreal Forest biomes will likely see a slight decline in precipitation minus evapotranspiration, which might impact soil moisture for farming and forest fires. With almost no increase in summer precipitation and much more evapotranspiration in PGW than in CTL, the water availability during the growing season will be challenging for the Canadian Prairies. WRF-PGW shows an increase of high-intensity precipitation events and shifts the distribution of precipitation events toward more extremely intensive events in all seasons, as current moderate events become extreme events with more vapor loading, especially in summer. Due to this shift in precipitation intensity to the higher end in the PGW simulation, the seemingly moderate increase in the total amount of precipitation in summer for both the Mackenzie and Saskatchewan river basins may not reflect the real change in flooding risk and water availability for agriculture. The high-resolution downscaled climate simulations provide abundant opportunities both for investigating local-scale atmospheric dynamics and for studying climate impacts in hydrology, agriculture, and ecosystems. The change in the probability distribution of precipitation intensity also calls for innovative bias-correction methods to be developed for the application of the dataset when bias-correction is required.

Mitigating geolocation errors in nighttime light satellite data and global CO2 emission gridded data

2021 ◽  
Vol 8 (2) ◽  
pp. 304-316
Author(s):  
V. Kinakh ◽  
◽  
T. Oda ◽  
R. Bun ◽  
O. Novitska ◽  
...  
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Urban Areas ◽  
Co2 Emission ◽  
Ghg Emissions ◽  
Correction Method ◽  
Emission Data ◽  
Nighttime Lights ◽  
Open Source Data ◽  
Carbon Dioxide Co2

Accurate geospatial modeling of greenhouse gas (GHG) emissions is an essential part of the future of global GHG monitoring systems. Our previous work found a systematic displacement in the high-resolution carbon dioxide (CO2) emission raster data of the Open-source Data Inventory for Anthropogenic CO2 (ODIAC) emission product. It turns out this displacement is due to geolocation bias in the Defense Meteorological Satellite Program (DMSP) nighttime lights (NTL) data products, which are used as a spatial emission proxy for estimating non-point source emissions distributions in ODIAC. Mitigating such geolocation error (~1.7 km), which is on the same order of the size of the carbon observing satellites field of view, is especially critical for the spatial analysis of emissions from cities. In this paper, there is proposed a method to mitigate the geolocation bias in DMSP NTL data that can be applied to DMSP NTL-based geospatial products, such as ODIAC. To identify and characterize the geolocation bias, we used the OpenStreetMap repository to define city boundaries for a large number of global cities. Assumption is that the total emissions within the city boundaries are at the maximum if there is no displacement (geolocation bias) in NTL data. Therefore, it is necessary to find an optimal vector (distance and angle) that maximizes the ODIAC total emissions within cities by shifting the emission fields. In the process of preparing annual composites of the nighttime stable lights data, some pixels of the DMSP data corresponding to water bodies were zeroed, which due to the geolocation bias unreasonably distorted the ODIAC emission fields. Hence, an original approach for restoring data in such pixels is considered using elimination of the factor that distorted the ODIAC emission fields. It is also proposed a bias correction method for shifted high-resolution emission fields in ODIAC. The bias correction was applied to multiple cities from the different continents. It is shown that the bias correction to the emission data (elimination of geolocation error in non-point emission source fields) increases the total CO2 emissions within city boundaries by 4.76% on average, due to reduced emissions from non-urban areas to which these emissions were likely to be erroneously attributed.

Comparison of the Impacts of Momentum Control Variables on High-Resolution Variational Data Assimilation and Precipitation Forecasting

2015 ◽  
Vol 144 (1) ◽  
pp. 149-169 ◽  
Author(s):  
Juanzhen Sun ◽  
Hongli Wang ◽  
Wenxue Tong ◽  
Ying Zhang ◽  
Chung-Yi Lin ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Control Variable ◽  
Wrf Model ◽  
Variational Data Assimilation ◽  
Error Modeling ◽  
Limited Area ◽  
Control Variables ◽  
Background Error ◽  
Precipitation Prediction

Abstract The momentum variables of streamfunction and velocity potential are used as control variables in a number of operational variational data assimilation systems. However, in this study it is shown that, for limited-area high-resolution data assimilation, the momentum control variables ψ and χ (ψχ) pose potential difficulties in background error modeling and, hence, may result in degraded analysis and forecast when compared with the direct use of x and y components of wind (UV). In this study, the characteristics of the modeled background error statistics, derived from an ensemble generated from Weather Research and Forecasting (WRF) Model real-time forecasts of two summer months, are first compared between the two control variable options. Assimilation and forecast experiments are then conducted with both options for seven convective events in a domain that encompasses the Rocky Mountain Front Range using the three-dimensional variational data assimilation (3DVar) system of the WRF Model. The impacts of the two control variable options are compared in terms of their skills in short-term qualitative precipitation forecasts. Further analysis is performed for one case to examine the impacts when radar observations are included in the 3DVar assimilation. The main findings are as follows: 1) the background error modeling used in WRF 3DVar with the control variables ψχ increases the length scale and decreases the variance for u and υ, which causes negative impact on the analysis of the velocity field and on precipitation prediction; 2) the UV-based 3DVar allows closer fits to radar wind observations; and 3) the use of UV control variables improves the 0–12-h precipitation prediction.

scholarly journals Variational Bias Correction of GNSS ZTD in the HARMONIE Modeling System

2016 ◽  
Vol 55 (5) ◽  
pp. 1259-1276 ◽  
Author(s):  
Jana Sánchez Arriola ◽  
Magnus Lindskog ◽  
Sigurdur Thorsteinsson ◽  
Jelena Bojarova
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Case Studies ◽  
Bias Correction ◽  
Processing System ◽  
Individual Case ◽  
Scale Model ◽  
Observation System ◽  
Limited Area ◽  
The Impact

AbstractTo fill the gap in the observation system for humidity, the HIRLAM–ALADIN Research on Mesoscale Operational NWP in Euromed (HARMONIE) limited-area high-resolution kilometer-scale model has been prepared for assimilation of Global Navigation Satellite System (GNSS) zenith total delay (ZTD) observations. The observation-processing system includes data selection, bias correction, quality control, and a GNSS observation operator for data assimilation. A large part of the bias between observations and model equivalents comes from the relatively low model top used in the HARMONIE experiments. The functionality of the different observation-processing components was investigated in detail as was the overall performance of the GNSS ZTD data assimilation. This paper contains an extensive description of the GNSS ZTD observation-processing system and a comparison of a newly introduced variational bias correction for GNSS ZTD data with an alternative static bias correction, as well as a detailed analysis of the impact of GNSS ZTD data, both in terms of statistical evaluations over a longer period and in terms of individual case studies. Assimilation of the GNSS ZTD observations with a variational bias correction has improved the quality of short-range weather forecasts for the moisture-related parameters in particular, both in a statistical sense and in individual case studies. The paper also discusses further improvements in the HARMONIE variational data-assimilation system that are needed to fully utilize the potential of high-resolution GNSS ZTD observations.

scholarly journals The Sensitivity of WRF Daily Summertime Simulations over West Africa to Alternative Parameterizations. Part II: Precipitation

2016 ◽  
Vol 145 (1) ◽  
pp. 215-233 ◽  
Author(s):  
Erik Noble ◽  
Leonard M. Druyan ◽  
Matthew Fulakeza
Keyword(s):  
West Africa ◽  
Daily Precipitation ◽  
Wrf Model ◽  
Tropical Rainfall Measuring Mission ◽  
Atmospheric Model ◽  
Global Precipitation Climatology Project ◽  
Spatiotemporal Variability ◽  
Convective Precipitation ◽  
Convection Scheme ◽  
Wide Range

Abstract This paper evaluates the performance of the Weather Research and Forecasting (WRF) Model as a regional atmospheric model over West Africa. It tests WRF’s sensitivity to 64 configurations of alternative parameterizations in a series of 104 twelve-day September simulations during 11 consecutive years, 2000–10. The 64 configurations combine WRF parameterizations of cumulus convection, radiation, surface hydrology, and the PBL. Simulated daily and total precipitation results are validated against Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) data. Particular attention is given to westward-propagating precipitation maxima associated with African easterly waves (AEWs). A wide range of daily precipitation validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve time–longitude correlations (against GPCP) of between 0.35 and 0.42 and spatiotemporal variability amplitudes only slightly higher than observed estimates. A parallel simulation by the benchmark Regional Model version 3 achieves a higher correlation (0.52) and realistic spatiotemporal variability amplitudes. The largest favorable impact on WRF precipitation validation is achieved by selecting the Grell–Devenyi convection scheme, resulting in higher correlations against observations than using the Kain–Fritch convection scheme. Other parameterizations have less obvious impacts. Validation statistics for optimized WRF configurations simulating the parallel period during 2000–10 are more favorable for 2005, 2006, and 2008 than for other years. The selection of some of the same WRF configurations as high scorers in both circulation and precipitation validations supports the notion that simulations of West African daily precipitation benefit from skillful simulations of associated AEW vorticity centers and that simulations of AEWs would benefit from skillful simulations of convective precipitation.

scholarly journals Integrated water vapour from GPS

MAUSAM ◽  
2021 ◽  
Vol 58 (1) ◽  
pp. 101-106
Author(s):  
R. K. GIRI ◽  
L. R. MEENA ◽  
S. S. BHANDARI ◽  
R. C. BHATIA
Keyword(s):  
Water Vapour ◽  
Global Climate ◽  
Spatial Scales ◽  
Limited Area ◽  
Gps Data ◽  
Massachusetts Institute Of Technology ◽  
Stochastic Filtering ◽  
Wide Range ◽  
Integrated Water Vapour ◽  
Institute Of Technology

Water vapour is highly variable in space and time, and plays a large role in atmospheric processes that act over a wide range of temporal and spatial scales on global climate to micrometeorology. This paper deals with a new approach to remotely sense the water vapour based on the Global Position System (GPS). The signal propagating from GPS satellites to ground based receivers is delayed by atmospheric water vapour. The delay is parameterized in terms of time varying Zenith-Wet Delay (ZWD), which is retrieved by stochastic filtering of GPS data. With the help of surface pressure and temperature readings at the GPS receiver, the retrieved ZWD can be transformed into Integrated Water Vapour (IWV) overlying at the receiver with little additional uncertainties. In this study the Zenith Total time Delay (ZTD) data without met package is retrieved using the GAMIT (King and Bock, 1997) GPS data processing software developed by Massachusetts Institute of Technology (MIT) for the period of January 2003 to February 2003 for two stations New Delhi and Bangalore .The IWV retrieved from GPS and its comparison with Limited Area Model (LAM) retrieved IWV shows fairly good agreement.

Diagnosing Model Errors from Time-Averaged Tendencies in the Weather Research and Forecasting (WRF) Model

2016 ◽  
Vol 144 (2) ◽  
pp. 759-779 ◽  
Author(s):  
Steven M. Cavallo ◽  
Judith Berner ◽  
Chris Snyder
Keyword(s):  
Global Analysis ◽  
Wrf Model ◽  
Ensemble Member ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Limited Area ◽  
Model Errors ◽  
Short Term ◽  
Wide Range ◽  
Weather Research

Abstract Accurate predictions in numerical weather models depend on the ability to accurately represent physical processes across a wide range of scales. This paper evaluates the utility of model time tendencies, averaged over many forecasts at a given lead time, to diagnose systematic forecast biases in the Advanced Research version of the Weather Research and Forecasting (WRF) Model during the 2010 North Atlantic hurricane season using continuously cycled ensemble data assimilation (DA). Erroneously strong low-level heating originates from the planetary boundary layer parameterization as a consequence of using fixed sea surface temperatures, impacting the upward surface sensible heat fluxes. Warm temperature bias is observed with a magnitude 0.5 K in a deep tropospheric layer centered 700 hPa, originating primarily from the Kain–Fritsch convective parameterization. This study is the first to diagnose systematic forecast bias in a limited-area mesoscale model using its forecast tendencies. Unlike global models where relatively fewer time steps typically encompass a DA cycling period, averaging all short-term forecast tendencies can require potentially large data. It is shown that 30-min averaging intervals can sufficiently represent the systematic model bias in this modeling configuration when initializing forecasts from an ensemble member that is generated using a DA system with an identical model configuration. However, the number of time steps before model error begins to dominate initial condition (IC) errors may vary between modeling configurations. Model and IC error are indistinguishable in short-term forecasts when initialized from the ensemble mean, a global analysis from a different model, and an ensemble member using a different parameterization.

scholarly journals A new high-resolution BOLAM-MOLOCH suite for the SIMM forecasting system: assessment over two HyMeX intense observation periods

2015 ◽  
Vol 15 (1) ◽  
pp. 1-24 ◽  
Author(s):  
S. Mariani ◽  
M. Casaioli ◽  
E. Coraci ◽  
P. Malguzzi
Keyword(s):  
High Resolution ◽  
Storm Surge ◽  
Numerical Models ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Forecast Performance ◽  
Northern Adriatic ◽  
Wide Range ◽  
Forecasting System ◽  
The Impact

Abstract. High-resolution numerical models can be effective in monitoring and predicting natural hazards, especially when dealing with Mediterranean atmospheric and marine intense/severe events characterised by a wide range of interacting scales. The understanding of the key factors associated to these Mediterranean phenomena, and the usefulness of adopting high-resolution numerical models in their simulation, are among the aims of the international initiative HyMeX – HYdrological cycle in Mediterranean EXperiment. At the turn of 2013, two monitoring campaigns (SOPs – Special Observation Periods) were devoted to these issues. For this purpose, a new high-resolution BOlogna Limited Area Model-MOdello LOCale (BOLAM-MOLOCH) suite was implemented in the Institute for Environmental Protection and Research (ISPRA) hydro–meteo–marine forecasting system (SIMM – Sistema Idro-Meteo-Mare) as a possible alternative to the operational meteorological component based on the BOLAM model self-nested over two lower-resolution domains. The present paper provides an assessment of this new configuration of SIMM with respect to the operational one that was also used during the two SOPs. More in details, it investigates the forecast performance of these SIMM configurations during two of the Intense Observation Periods (IOPs) declared in the first SOP campaign. These IOPs were characterised by high precipitations and very intense and exceptional high waters over the northern Adriatic Sea (acqua alta). Concerning the meteorological component, the high-resolution BOLAM-MOLOCH forecasts are compared against the lower-resolution BOLAM forecasts over three areas – mostly corresponding to the Italian HyMeX hydrometeorological sites – using the rainfall observations collected in the HyMeX database. Three-month categorical scores are also calculated for the MOLOCH model. Despite the presence of a slight positive bias of the MOLOCH model, the results show that the precipitation forecast turns out to improve with increasing resolution. In both SIMM configurations, the sea storm surge component is based on the same version of the Shallow water HYdrodynamic Finite Element Model (SHYFEM). Hence, it is evaluated the impact of the meteorological forcing provided by the two adopted BOLAM configurations on the SHYFEM forecasts for six tide-gauge stations. A benchmark for this part of the study is given by the performance of the SHYFEM model forced by the ECMWF IFS forecast fields. For this component, both BOLAM-SHYFEM configurations clearly outperform the benchmark. The results are, however, strongly affected by the predictability of the weather systems associated to the IOPs, thus suggesting the opportunity to develop and test a time-lagged multi-model ensemble for the prediction of high storm surge events.

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