Ahmed B. Tawfik

The Heated Condensation Framework. Part I: Description and Southern Great Plains Case Study

AbstractThis study extends the heated condensation framework (HCF) presented in Tawfik and Dirmeyer to include variables for describing the convective background state of the atmosphere used to quantify the contribution of the atmosphere to convective initiation within the context of land–atmosphere coupling. In particular, the ability for the full suite of HCF variables to 1) quantify the amount of latent and sensible heat energy necessary for convective initiation, 2) identify the transition from moistening advantage to boundary layer growth advantage, 3) identify locally originating convection, and 4) compare models and observations, directly highlighting biases in the convective state, is demonstrated. These capabilities are illustrated for a clear-sky and convectively active day over the Atmospheric Radiation Measurement Program Southern Great Plains central station using observations, the Rapid Update Cycle (RUC) operational model, and the North American Regional Reanalysis (NARR). The clear-sky day...

Improvements in the representation of the Indian summer monsoon in the NCEP climate forecast system version 2

A new triggering mechanism for deep convection based on the heated condensation framework (HCF) is implemented into the National Centers for Environmental Prediction climate forecast system version 2 (CFSv2). The new trigger is added as an additional criterion in the simplified Arakawa–Schubert scheme for deep convection. Seasonal forecasts are performed to evaluate the influence of the new triggering mechanism in the representation of the Indian summer monsoon in the CFSv2. The HCF trigger improves the seasonal representation of precipitation over the Indian subcontinent. The new triggering mechanism leads to a significant, albeit relatively small, improvement in the bias of seasonal precipitation totals. In addition, the new trigger improves the representation of the seasonal precipitation cycle including the monsoon onset, and the probability distribution of precipitation intensities. The mechanism whereby the HCF improves convection over India seems to be related not only to a better representation of the background state of atmospheric convection but also to an increase in the frequency in which SAS is triggered. As a result, there was an increase in convective precipitation over India favored by the availability of moist convective instability. The increase in precipitation intensity leads to a reduction in the dry bias.

The Heated Condensation Framework. Part II: Climatological Behavior of Convective Initiation and Land–Atmosphere Coupling over the Conterminous United States

AbstractThis is Part II of a two-part study introducing the heated condensation framework (HCF), which quantifies the potential convective state of the atmosphere in terms of land–atmosphere interactions. Part I introduced the full suite of HCF variables and applied them to case studies with observations and models over a single location in the southern Great Plains. It was shown in Part I that the HCF was capable of identifying locally initiated convection and quantifying energetically favorable pathways for initiation. Here, the HCF is applied to the entire conterminous United States and the climatology of convective initiation (CI) in relation to local land–atmosphere coupling (LoCo) is explored for 34 summers (June–August) using the North American Regional Reanalysis (NARR) and observations. NARR is found to be capable of capturing the convective threshold (buoyant mixing potential temperature θBM) and energy advantage transition (energy advantage potential temperature θadv) for most of the United Sta...

Observational study of land-surface-cloud-atmosphere coupling on daily timescales

Our aim is to provide an observational reference for the evaluation of the surface and boundary layer parameterizations used in large-scale models using the remarkable long-term Canadian Prairie hourly dataset. First we use shortwave and longwave data from the Baseline Surface Radiation Network (BSRN) station at Bratt’s Lake, Saskatchewan, and clear sky radiative fluxes from ERA-Interim, to show the coupling between the diurnal cycle of temperature and relative humidity and effective cloud albedo and net longwave flux. Then we calibrate the nearby opaque cloud observations at Regina, Saskatchewan in terms of the BSRN radiation fluxes. We find that in the warm season, we can determine effective cloud albedo to ±0.08 from daytime opaque cloud, and net long-wave radiation to ±8 W/m2 from daily mean opaque cloud and relative humidity. This enables us to extend our analysis to the 55 years of hourly observations of opaque cloud cover, temperature, relative humidity, and daily precipitation from 11 climate stations across the Canadian Prairies. We show the land-surface-atmosphere coupling on daily timescales in summer by stratifying the Prairie data by opaque cloud, relative humidity, surface wind, day-night cloud asymmetry and monthly weighted precipitation anomalies. The multiple linear regression fits relating key diurnal climate variables, the diurnal temperature range, afternoon relative humidity and lifting condensation level, to daily mean net longwave flux, wind-speed and precipitation anomalies have R2 values between 0.61 and 0.69. These fits will be a useful guide for evaluating the fully coupled system in models.

The heated condensation framework as a convective trigger in the NCEP Climate Forecast System version 2

An updated version of the Heated Condensation Framework (HCF) is implemented as a convective triggering criterion into the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). The new trigger replaces the original criteria in both the deep (Simplified Arakawa-Schubert – SAS) and shallow (SAS based) convective schemes. The performance of the original and new triggering criteria is first compared against radiosonde observations. Then, a series of hindcasts are performed to evaluate the influence of the triggering criterion in the CFSv2 representation of summer precipitation, the diurnal cycle of precipitation, and hurricanes that made landfall. The observational analysis shows that the HCF trigger better captures the frequency of convection, where the original SAS trigger initiates convection too often. When implemented in CFSv2, the HCF trigger improves the seasonal forecast of the Indian summer monsoon rainfall, including the representation of the onset dates of the rainy season over India. On the other hand, the HCF trigger increases error in the seasonal forecast of precipitation over the eastern United States. The HCF trigger also improves the representation of the intensity of hurricanes. Moreover, the simulation of hurricanes provides insights on the mechanism whereby the HCF trigger impacts the representation of convection.

Annual Climatology of the Diurnal Cycle on the Canadian Prairies

We show the annual climatology of the diurnal cycle, stratified by opaque cloud, using the full hourly resolution of the Canadian Prairie data. The opaque cloud field itself has distinct cold and warm season diurnal climatologies; with a near-sunrise peak of cloud in the cold season and an early afternoon peak in the warm season. There are two primary climate states on the Canadian Prairies, separated by the freezing point of water, because a reflective surface snow cover acts as a climate switch. Both cold and warm season climatologies can be seen in the transition months of November, March and April with a large difference in mean temperature. In the cold season with snow, the diurnal ranges of temperature and relative humidity increase quasi-linearly with decreasing cloud, and increase from December to March with increased solar forcing. The warm season months, April to September, show a homogeneous coupling to the cloud cover, and a diurnal cycle of temperature and humidity that depends only on net longwave. Our improved representation of the diurnal cycle shows that the warm season coupling between diurnal temperature range and net longwave is weakly quadratic through the origin, rather than the linear coupling shown in earlier papers. We calculate the conceptually important 24-h imbalances of temperature and relative humidity (and other thermodynamic variables) as a function of opaque cloud cover. In the warm season under nearly clear skies, there is a warming of +2oC and a drying of -6% over the 24-h cycle, which is about 12% of their diurnal ranges. We summarize results on conserved variable diagrams and explore the impact of surface windspeed on the diurnal cycle in the cold and warm seasons. In all months, the fall in minimum temperature is reduced with increasing windspeed, which reduces the diurnal temperature range. In July and August, there is an increase of afternoon maximum temperature and humidity at low windspeeds, and a corresponding rise in equivalent potential temperature of 4.4K that appears coupled to increased precipitation. However overcast skies are associated with the major rain events and higher windspeeds.

Revisiting Hydrometeorology Using Cloud and Climate Observations

AbstractThis paper uses 620 station years of hourly Canadian Prairie climate data to analyze the coupling of monthly near-surface climate with opaque cloud, a surrogate for radiation, and precipitation anomalies. While the cloud–climate coupling is strong, precipitation anomalies impact monthly climate for as long as 5 months. The April climate has memory of precipitation anomalies back to freeze-up in November, mostly stored in the snowpack. The summer climate has memory of precipitation anomalies back to the beginning of snowmelt in March. In the warm season, mean temperature is strongly correlated to opaque cloud anomalies, but only weakly to precipitation anomalies. Mixing ratio anomalies are correlated to precipitation, but only weakly to cloud. The diurnal cycle of mixing ratio shifts upward with increasing precipitation anomalies. Positive precipitation anomalies are coupled to a lower afternoon lifting condensation level and a higher afternoon equivalent potential temperature; both favor increased...

Land-atmosphere interactions the LoCo perspective

AbstractLand–atmosphere (L-A) interactions are a main driver of Earth’s surface water and energy budgets; as such, they modulate near-surface climate, including clouds and precipitation, and can in...

On the Sensitivity of the Diurnal Cycle in the Amazon to Convective Intensity

Abstract Climate and reanalysis models contain large water and energy budget errors over tropical land related to the misrepresentation of diurnally forced moist convection. Motivated by recent work suggesting that the water and energy budget is influenced by the sensitivity of the convective diurnal cycle to atmospheric state, this study investigates the relationship between convective intensity, the convective diurnal cycle, and atmospheric state in a region of frequent convection—the Amazon. Daily, 3‐hourly satellite observations of top of atmosphere (TOA) fluxes from Clouds and the Earths Radiant Energy System Ed3a SYN1DEG and precipitation from Tropical Rainfall Measuring Mission 3B42 data sets are collocated with twice daily Integrated Global Radiosonde Archive observations from 2002 to 2012 and hourly flux tower observations. Percentiles of daily minimum outgoing longwave radiation are used to define convective intensity regimes. The results indicate a significant increase in the convective diurnal cycle amplitude with increased convective intensity. The TOA flux diurnal phase exhibits 1–3 h shifts with convective intensity, and precipitation phase is less sensitive. However, the timing of precipitation onset occurs 2–3 h earlier and the duration lasts 3–5 h longer on very convective compared to stable days. While statistically significant changes are found between morning atmospheric state and convective intensity, variations in upper and lower tropospheric humidity exhibit the strongest relationships with convective intensity and diurnal cycle characteristics. Lastly, convective available potential energy (CAPE) is found to vary with convective intensity but does not explain the variations in Amazonian convection, suggesting that a CAPE‐based convective parameterization will not capture the observed behavior without incorporating the sensitivity of convection to column humidity.

Biophysical consequences of photosynthetic temperature acclimation for climate

Photosynthetic temperature acclimation is a commonly observed process that is increasingly being incorporated into Earth System Models (ESMs). While short-term acclimation has been shown to increase carbon storage in the future, it is uncertain whether acclimation will directly influence simulated future climate through biophysical mechanisms. Here, we used coupled atmosphere-biosphere simulations using the Community Earth System Model (CESM) to assess how acclimation-induced changes in photosynthesis influence global climate under present-day and future (RCP 8.5) conditions. We ran four 30 year simulations that differed only in sea surface temperatures and atmospheric CO2 (present or future) and whether a mechanism for photosynthetic temperature acclimation was included (yes or no). Acclimation increased future photosynthesis and, consequently, the proportion of energy returned to the atmosphere as latent heat, resulting in reduced surface air temperatures in areas and seasons where acclimation caused the biggest increase in photosynthesis. However, this was partially offset by temperature increases elsewhere, resulting in a small, but significant, global cooling of 0.05°C in the future, similar to that expected from acclimation-induced increases in future land carbon storage found in previous studies. In the present-day simulations, the photosynthetic response was not as strong and cooling in highly vegetated regions was less than warming elsewhere, leading to a net global increase in temperatures of 0.04°C. Precipitation responses were variable and rates did not change globally in either time period. These results, combined with carbon-cycle effects, suggest that models without acclimation may be overestimating positive feedbacks between climate and the land surface in the future.