Control of radiation and evaporation on temperature variability in a WRF regional climate simulation: comparison with colocated long term ground based observations near Paris

Abstract

The objective of this paper is to understand how large-scale processes, cloud cover and surface fluxes affect the temperature variability over the SIRTA site, near Paris, and in a regional climate simulation performed in the frame of HyMeX/Med-CORDEX programs. This site is located in a climatic transitional area where models usually show strong dispersions despite the significant influence of large scale on interannual variability due to its western location. At seasonal time scale, the temperature is mainly controlled by surface fluxes. In the model, the transition from radiation to soil moisture limited regime occurs earlier than in observations leading to an overestimate of summertime temperature. An overestimate of shortwave radiation (SW), consistent with a lack of low clouds, enhances the soil dryness. A simulation with a wet soil is used to better analyse the relationship between dry soil and clouds but while the wetter soil leads to colder temperature, the cloud cover during daytime is not increased due to the atmospheric stability. At shorter time scales, the control of surface radiation becomes higher. In the simulation, higher temperatures are associated with higher SW. A wet soil mitigates the effect of radiation due to modulation by evaporation. In observations, the variability of clouds and their effect on SW is stronger leading to a nearly constant mean SW when sorted by temperature quantile but a stronger impact of cloud cover on day-to-day temperature variability. Impact of cloud albedo effect on precipitation is also compared.

Appendix: Lidar equations

ATB _tot and ATB _mol are respectively the attenuated backscattered signals for particles and molecules (ATB_tot) and for molecules only (ATB_mol) and are given by (1) and (2):

$$ATB_{mol} \left( z \right) = \beta_{sca,mol} \left( z \right) \cdot e^{{ - 2\eta \mathop \smallint \limits_{{z_{TOA} }}^{z} \alpha_{sca,mol} \left( z \right) \cdot dz}}$$

(1)

$$ATB_{tot} \left( z \right) = \left( {\beta_{sca,part} \left( z \right) + \beta_{sca,mol} \left( z \right)} \right) \cdot e^{{ - 2\eta \mathop \smallint \limits_{{z_{TOA} }}^{z} \left( {\alpha_{sca,part} \left( z \right) + \alpha_{sca,mol} \left( z \right)} \right) \cdot dz}}$$

(2)

where β_sca,part, β_sca,mol are lidar backscatter coefficients (m⁻¹ sr⁻¹) and α_sca,part and α_sca,mol attenuation coefficients (m⁻¹) for particles (clouds, aerosols) and molecules. η is a multiple scattering coefficient that depends both on lidar characteristics and size, shape and density of particles. It is about 0.7 for CALIPSO (Winker 2003; Chepfer et al. 2008). The ATB_mol and ATB_tot products are averaged vertically to obtain SR over 40 layers (Chepfer et al. 2008, 2010). SR is given by (3):

$$SR = \frac{{ATB_{tot} }}{{ATB_{mol} }}$$

(3)