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previous MIPs: albedo is still a major source of uncertainty, surface exchange parameterizations are still problematic, and individual model performance is inconsistent. In fact, models are less classifiable with results from more sites, years and evaluation variables. Our initial, or false, hypothesis had to be killed off. Developments have been made, particularly in terms of the complexity of snow process representations, and conclusions from PILPS2(d) and snow MIPs have undoubtedly driven model
previous MIPs: albedo is still a major source of uncertainty, surface exchange parameterizations are still problematic, and individual model performance is inconsistent. In fact, models are less classifiable with results from more sites, years and evaluation variables. Our initial, or false, hypothesis had to be killed off. Developments have been made, particularly in terms of the complexity of snow process representations, and conclusions from PILPS2(d) and snow MIPs have undoubtedly driven model
, and (iii) provide summary statistics for forecast comparisons. The MET-TC summary tools produce a variety of statistics, including frequency of superior performance (e.g., to meet one of HFIP’s goals to compare the performance of different TC modeling systems), time series independence calculations, and confidence intervals (CIs) on mean differences. In addition, MET-TC includes tools to evaluate rapid intensification/weakening (RI/RW) events, with flexible options for selecting thresholds to
, and (iii) provide summary statistics for forecast comparisons. The MET-TC summary tools produce a variety of statistics, including frequency of superior performance (e.g., to meet one of HFIP’s goals to compare the performance of different TC modeling systems), time series independence calculations, and confidence intervals (CIs) on mean differences. In addition, MET-TC includes tools to evaluate rapid intensification/weakening (RI/RW) events, with flexible options for selecting thresholds to
model performance for the August–September period in 2018 and 2019 in comparison to satellite observations; and (iii) to investigate how extreme Amazonian wildfire events can affect the atmospheric composition over the São Paulo metropolitan area (SPMA). The Amazon fire season and the new system, hereafter referred to as CPTEC WRF-Chem, are described in the second and third sections, respectively. The model evaluation and the unusual event over the SPMA are presented in the fourth section, and the
model performance for the August–September period in 2018 and 2019 in comparison to satellite observations; and (iii) to investigate how extreme Amazonian wildfire events can affect the atmospheric composition over the São Paulo metropolitan area (SPMA). The Amazon fire season and the new system, hereafter referred to as CPTEC WRF-Chem, are described in the second and third sections, respectively. The model evaluation and the unusual event over the SPMA are presented in the fourth section, and the
-Africa model improvement and evaluation ( James et al. 2018 ). The remaining four were transdisciplinary, delivering climate change research and bringing innovative co-production of climate information and services in East, West, Central, and southern Africa through pilot studies. The IMPALA project has targeted effort on some of the important challenges to improved model performance. A major focus has been on understanding the sensitivity of model climate predictions to the representation of mesoscale
-Africa model improvement and evaluation ( James et al. 2018 ). The remaining four were transdisciplinary, delivering climate change research and bringing innovative co-production of climate information and services in East, West, Central, and southern Africa through pilot studies. The IMPALA project has targeted effort on some of the important challenges to improved model performance. A major focus has been on understanding the sensitivity of model climate predictions to the representation of mesoscale
(i) analysis of physical processes and (ii) quantification of performance. On a global scale, important work has been done to investigate model representation of clouds and water vapor (e.g., Jiang et al. 2012 ; Klein et al. 2013 ), tropical circulation (e.g., Niznik and Lintner 2013 ; Oueslati and Bellon 2015 ), and modes of variability (e.g., Guilyardi et al. 2009 ; Kim et al. 2009 ). This process-oriented evaluation is fundamental to inform model development. On a regional scale
(i) analysis of physical processes and (ii) quantification of performance. On a global scale, important work has been done to investigate model representation of clouds and water vapor (e.g., Jiang et al. 2012 ; Klein et al. 2013 ), tropical circulation (e.g., Niznik and Lintner 2013 ; Oueslati and Bellon 2015 ), and modes of variability (e.g., Guilyardi et al. 2009 ; Kim et al. 2009 ). This process-oriented evaluation is fundamental to inform model development. On a regional scale
scorecard indicates better performance by one modeling system, and displaying a square for each unique combination of domain, time period, metric, and threshold can reveal systemic differences. These systemic differences could then be examined in depth, in order to diagnose model deficiencies. For instance, if a new system has difficulty with nocturnal temperatures, that would become evident from the columns of the scorecard rather than potentially obscured by a summary metric evaluated over the entire
scorecard indicates better performance by one modeling system, and displaying a square for each unique combination of domain, time period, metric, and threshold can reveal systemic differences. These systemic differences could then be examined in depth, in order to diagnose model deficiencies. For instance, if a new system has difficulty with nocturnal temperatures, that would become evident from the columns of the scorecard rather than potentially obscured by a summary metric evaluated over the entire
multiple regional and global climate models, impacts researchers will have the ingredients to produce impacts assessments that characterize multiple uncertainties. Additional goals of the program include the following: to evaluate regional model performance over North America by nesting the RCMs in National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) Reanalysis; to explore some remaining uncertainties in regional climate modeling (e.g., importance of compatibility of physics in
multiple regional and global climate models, impacts researchers will have the ingredients to produce impacts assessments that characterize multiple uncertainties. Additional goals of the program include the following: to evaluate regional model performance over North America by nesting the RCMs in National Centers for Environmental Prediction–Department of Energy (NCEP–DOE) Reanalysis; to explore some remaining uncertainties in regional climate modeling (e.g., importance of compatibility of physics in
and are initialized with an aerosol data assimilation process (i.e., GEOS5) appear the most useful for clear-sky solar irradiance. In particular, imposing the temporal variability of the AOD produces large improvements in DNI and DIF with respect to the more extended use of aerosol climatologies. Current developments focus on comparing forecasts and actual solar power production to precisely evaluate the model performance under all-sky conditions (including cloudy periods). Further modeling
and are initialized with an aerosol data assimilation process (i.e., GEOS5) appear the most useful for clear-sky solar irradiance. In particular, imposing the temporal variability of the AOD produces large improvements in DNI and DIF with respect to the more extended use of aerosol climatologies. Current developments focus on comparing forecasts and actual solar power production to precisely evaluate the model performance under all-sky conditions (including cloudy periods). Further modeling
to date include plots of vertical cross sections, integrated water vapor transport, and radiation fields. While objective verification statistics are a vital component of the evaluation, the graphics are also an excellent diagnostic tool to monitor model performance throughout an event and subjectively compare DTC baselines to an experimental run that includes an innovation. The research community is strongly encouraged to use MET ( Fowler et al. 2010 ; code and documentation are available online
to date include plots of vertical cross sections, integrated water vapor transport, and radiation fields. While objective verification statistics are a vital component of the evaluation, the graphics are also an excellent diagnostic tool to monitor model performance throughout an event and subjectively compare DTC baselines to an experimental run that includes an innovation. The research community is strongly encouraged to use MET ( Fowler et al. 2010 ; code and documentation are available online
FFG issuance. Ratios greater than 1.0 (or 100%) suggest that rainfall amounts have exceeded the threshold amount to cause bank-full conditions on small streams. In recent years, advances in high-performance massively parallel computing and remote sensing of the Earth’s atmosphere, surface, and subsurface have led to the advent of regional, continental, and even global models that forecast Earth’s water and energy cycles ( Wood et al. 2011 ). The resolution of the forcing datasets and digital
FFG issuance. Ratios greater than 1.0 (or 100%) suggest that rainfall amounts have exceeded the threshold amount to cause bank-full conditions on small streams. In recent years, advances in high-performance massively parallel computing and remote sensing of the Earth’s atmosphere, surface, and subsurface have led to the advent of regional, continental, and even global models that forecast Earth’s water and energy cycles ( Wood et al. 2011 ). The resolution of the forcing datasets and digital
