Abstract

Atmospheric downward longwave radiation flux (L↓) is a variable that directly influences the surface net radiation and consequently, weather and climatic conditions. Measurements of L↓ are scarce, and the use of classical models depending on some atmospheric variables may be an alternative. In this paper, we analyzed L↓ measured over the Brazilian Pampa biome. This region is located in a humid subtropical climate zone and characterized by well defined seasons and well distributed precipitation. Furthermore, we evaluated the performance of the eleven classical L↓ models for clear sky with one-year experimental data collected in the Santa Maria experimental site (SMA) over native vegetation and high relative humidity throughout the year. Most of the L↓ estimations, using the original coefficients, underestimated the experimental data. We performed the local calibration of the L↓ equations coefficients over an annual period and separated them into different sky cover classifications: clear sky, partly cloudy sky, and cloudy sky. The calibrations decreased the errors, especially in cloudy sky classification. We also proposed the joint calibration between the clear sky emissivity equations and cloud sky correction function to reduce errors and evaluate different sky classifications. The results found after these calibrations presented better statistical indexes. Additionally, we presented a new empirical model to estimate L↓ based on multiple regression analysis using water vapor pressure and air temperature. The new equation well represents partial and cloudy sky, even without including the cloud cover parameterization, and was validated with the following five years in SMA and two years in the Cachoeira do Sul experimental site (CAS). The new equation proposed herein presents a root mean square error ranging from 13 to 21 Wm−2 and correlation coefficient from 0.68 to 0.83 for different sky cover classifications. Therefore, we recommend using the novel equation to calculate L↓ over the Pampa biome under these specific climatic conditions.

Highlights

  • We propose a joint calibration between clear sky emissivity and cloud sky correction models to estimate L↓ using a basic structure based on the formulation proposed by Maykurt and Church [35], Jacobs [36], Iziomon et al [34], Sugita and Brutsaert [37], among others

  • 0.7 μm) represents the atmospheric transmissivity and is defined as the ratio between the daily integrated shortwave radiation received on surface-level and the daily shortwave radiation coming from the sun that is theoretically received at the top of the atmosphere (R0 ) [2]

  • L↓ estimations were compared with experimental data using the correlation coefficient (R2 ), the root mean square error (RMSE), and percentage bias (PBias)

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Summary

Location of of experiment areas in in thethe

L↓ L and global solar radiation (Rg) Andtemperature air temperature measured using thermo-hygrometer sensor a ) were (RH). Air (Ta) (T were measured using thethe thermo-hygrometer sensor (HMP155, Vaisala, Finland), all at the height of m. The data period used in this study (HMP155, Vaisala, Finland), all at the height of 3 m. The data period used in this study was from. More details on the CAS site are described in Diaz et al [44] and Souza et al [45]. More details on the CAS site are described in Diaz et al [44] and Souza et al. Measurements were processed in 30 min in both sites. Where: Ta is the air temperature (◦ C) and RH is the relative humidity (%)

Clearness Index
Evaluated Parameterizations
Proposed Model
Statistical Indexes and Analysis
Results and Discussion
Using Original Coefficients—Step 1
Calibrating the Coefficients—Step 2
Calibrating the Coefficients—Step 3
Validation of a New Proposed Downward Longwave Radiation—Step 4
Findings
Conclusions
Full Text
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