Port thermodynamics module to support both CPU and GPU execution

[Copilot]

This PR ports the thermodynamics module (modthermodynamics.f90) to run on both CPU and GPU, following the same pattern established for the advection modules. The implementation maintains full backward compatibility while adding GPU acceleration for computationally intensive thermodynamics calculations.

Changes Made

GPU Device Memory Management

• Added thermodynamics-specific device arrays to modcuda.f90:
  • Field arrays: ql0_d, ql0h_d, qt0h_d, thl0h_d, presf_d, presh_d, exnf_d, exnh_d, thv0_d, th0av_d, ql0av_d, thvf_d, rhof_d
  • Physical constants: rlv_d, cp_d, rd_d, rv_d, es0_d, at_d, bt_d, tmelt_d
• Updated allocation, deallocation, and device update routines

Conditional Compilation

• Added #if defined(_GPU) preprocessor directives throughout modthermodynamics.f90
• CPU code paths remain unchanged when GPU support is not compiled
• GPU kernels are only compiled when _GPU flag is defined

GPU Kernels Implemented

1. thermo_cuda: Calculates liquid water content using iterative saturation vapor pressure computation
2. calc_thv0_cuda: Computes virtual potential temperature at full levels
3. calc_thv0h_cuda: Computes virtual potential temperature at half levels
4. calc_thl0h_cuda/calc_qt0h_cuda: Half-level interpolation for temperature and moisture scalars
5. calc_dthvdz_cuda: Applies boundary conditions and numerical thresholds for virtual potential temperature gradients

Key Features

• Performance: GPU parallelization of nested i,j,k loops that dominate thermodynamics computation time
• Consistency: Follows identical patterns used in advection modules for GPU porting
• Compatibility: No changes to existing CPU-only builds or runtime behavior
• Memory Management: Automatic device memory synchronization through existing updateDevice/updateHost infrastructure

Testing

• Builds successfully with GNU Fortran compiler
• Maintains existing CPU functionality when _GPU flag is not defined
• GPU kernels compiled and linked successfully (ready for NVIDIA HPC compiler testing)

This implementation enables GPU acceleration of the thermodynamics calculations while preserving the existing CPU code paths, providing a foundation for significant performance improvements in moist thermodynamics simulations.

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